SMAP (Soil Moisture Active/Passive) Mission
SMAP is a NASA mission under development within the ESSP (Earth System Science Pathfinder) program. In January 2007, the Panel on Water Resources and the Global Hydrologic Cycle of NRC (National Research Council) released a report “Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond” in which the SMAP mission was ranked with the highest priority among all proposed missions, and the report recommended it for implementation in the first phase of new missions (2010-2013).
The overall objective of SMAP is to monitor global soil moisture mapping with unprecedented resolution, sensitivity, area coverage, and revisit times. The SMAP instrument concept draws heavily upon the heritage of the Hydros (Hydrosphere State) project which was cancelled by NASA due to budget constraints in late 2005. - As a consequence of the NRC report, NASA/HQ held a two-day workshop on July 9-10, 2007 to evaluate the SMAP mission as defined in the report and to identify the ancillary measurements (if any) required to accomplish mission goals. 1) 2) 3) 4) 5) 6) 7) 8) 9) 10) 11) 12) 13) 14)
Science goals: The SMAP data will help characterize the relationship between soil moisture, its freeze/thaw state, and the associated environmental constraints to ecosystem processes including land-atmosphere carbon, water and energy exchange, and vegetation productivity. Soil moisture is a key control on evaporation and transpiration at the land-atmosphere boundary. Since large amounts of energy are required to vaporize water, soil control on evaporation and transpiration also has a significant impact on the surface energy fluxes. Therefore, soil moisture variations affect the evolution of weather and climate over continental regions. Initialization of numerical weather prediction (NWP) models and seasonal climate models with correct soil moisture information enhances their prediction skill and extends their skillful lead-times.
Equally important are the likely societal benefits to be derived from SMAP measurements. Many of these application areas and the approach to their improvement and modernization are also present in GEOSS (Global Earth Observation System of Systems). The application areas directly addressed by SMAP measurements of soil moisture and freeze/thaw state, acquired globally and at high spatial and temporal resolutions, are as follows (Ref. 2):
1) Weather and Climate Forecasting. Soil moisture variations affect the evolution of weather and climate over continental regions. Initialization of numerical weather prediction and seasonal climate models with accurate soil moisture information enhances their prediction skills and extends their skillful lead times. Improved seasonal climate predictions will benefit climate-sensitive socioeconomic activities, including water management, agriculture, fire, flood, and drought hazards monitoring.
2) Droughts. Soil moisture strongly affects plant growth and hence agricultural productivity, especially during conditions of water shortage and drought. Currently, there is no global in situ network for soil moisture monitoring. Global estimates of soil moisture and plant water stress must be derived from models. These model predictions (and hence drought monitoring) can be greatly enhanced through assimilation of space-based soil moisture observations.
3) Floods. Soil moisture is a key variable in water-related natural hazards including floods and landslides. High-resolution observations of soil moisture and landscape freeze/thaw status will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. The surface soil moisture state is key to the partitioning of precipitation into infiltration and runoff, and thus is one of the major pieces of information which drives flood prediction modeling. Similarly, soil moisture in mountainous areas is one of the most important determinants of landslides. In cold land regions, the timing of thawing (which can be derived from satellite radar measurements) is coincident with the onset of seasonal snowmelt, soil thaw, and ice breakup on large rivers and lakes. Hydrologic forecast systems initialized with mapped high-resolution soil moisture and freeze/thaw fields will therefore open up new capabilities in operational flood forecasting.
4) Agricultural Productivity. SMAP will provide information on water availability and environmental stress for estimating plant productivity and potential yield. The availability of direct observations of soil moisture status and the timing and extent of potential frost damage from SMAP will enable significant improvements in operational crop productivity and water stress information systems, by providing realistic soil moisture and freeze/thaw observations as inputs for agricultural prediction models.
5) Human Health. Improved seasonal soil moisture forecasts using SMAP data will directly benefit famine early warning systems particularly in sub-Saharan Africa and South Asia, where hunger remains a major human health factor and the population harvests its food from rain-fed agriculture in highly monsoonal (seasonal) conditions. In the temperate and extra-tropical latitudes, freeze/thaw measurements from SMAP will benefit environmental risk models and early warning systems related to the potential expansion of many disease vectors that are constrained by the timing and duration of seasonal frozen temperatures. SMAP will also benefit the emerging field of landscape epidemiology (aimed at identifying and mapping vector habitats for human diseases such as malaria) where direct observations of soil moisture and freeze/thaw status can provide valuable information on vector population dynamics. Indirect benefits will also be realized as SMAP data will enable better weather forecasts that lead to improved predictions of heat stress and virus spreading rates. Better flood forecasts will also lead to improved disaster preparation and response.
6) National Security. Information on surface soil moisture and freeze/thaw is critical to ground trafficability and mobility. Weather models also need maps of the soil moisture and freeze/thaw variables to initialize forecasts for low-level fog, aviation density altitude, and dust generation. SMAP soil moisture and freeze/thaw information exceed current capability in terms of resolution, sensitivity, coverage, and sensing depth. Furthermore, radar observations over oceans and water bodies yield information on ice cover at high resolution and regardless of illumination.
The SMAP mission concept includes an L-band radiometer and an L-band high-resolution radar that share a single feedhorn and parabolic mesh reflector. The radar operates with VV, HH, and HV/VH transmit-receive polarizations, and uses separate transmit frequencies for the H (1.26 GHz) and V (1.29 GHz) polarizations. The radiometer operates with V, H and U (third Stokes parameter) polarizations at 1.41 GHz. The reflector is offset from nadir and rotates about the nadir axis at 13.0 rpm, providing a conically scanning antenna beam with a surface incidence angle of approximately 40º. The reflector diameter is approximately 6 m, providing a radiometer footprint of about 40 km defined by the one-way 3 dB beamwidth.
The SMAP project is managed for NASA by the Jet Propulsion Laboratory (JPL), with participation by the Goddard Space Flight Center (GSFC). SMAP builds on the heritage and risk-reduction activities of the NASA ESSP Hydros mission.
- The SMAP Mission Concept Review was conducted on June 24, 2008. On Sept. 24, 2008, SMAP was formally approved to initiate Phase A.
- The Phase-B of SMAP started in January 2010.
- In 2011, the instrument system has completed the preliminary design review (PDR) stage, and detailed instrument design has begun.
- In May 2012, SMAP successfully passed the Key Decision Point-C (KDP-C) review and is now in Phase C of the mission.
- SMAP succesfully completed its CDR (Critical Design Review) in July, 2012.
- In May 2013, a NASA team at GSFC delivered the SMAP radiometer to JPL where it will be integrated into the SMAP spacecraft along with the L-band radar (SAR) instrument developed by JPL. 15)
Table 1: Preliminary mission requirements of SMAP
Figure 1: Artist's view of the SMAP mission observation scheme (image credit: NASA)
The radar and spacecraft are being developed in-house at JPL, leveraging previous Earth mission radar experience and adapting power and avionics elements from a recent JPL planetary mission. The radiometer is being developed at GSFC leveraging previous Earth mission radiometer experience. Mission operations and science data processing will be conducted by JPL with GSFC support.
The spacecraft design was developed concurrently and synergistically with the instrument to reduce overall observatory complexity and therefore, development effort. The spacecraft development addressed the unique challenges associated with instrument accommodation and implementation approach. Planetary avionics from a previous JPL mission were adapted to support SMAP’s high data volume and data rates, and also to support the high degree of functional integration between the instrument and spacecraft.
In addition, the spacecraft was required to maintain compatibility with several launch vehicles including the Minotaur -4+, Atlas V, Falcon 9, and most recently the Delta-2 until relatively late in the design lifecycle without slowing the development or delaying the launch ready date (the Delta-2 was selected by NASA for SMAP at CDR-time). From the spacecraft and observatory packaging and volume standpoint, a key challenge was packaging the RBA (Reflector Boom Assembly) within the most constraining vehicle: Minotaur IV+ with the 2.34 m fairing. Designing for electromagnetic compatibility was also a challenge given the sensitivity of the instruments (and especially the radiometer) to L-band emissions. The RBA and SIA (Spun Instrument Assembly) also posed a challenge to the spacecraft’s pointing control design. This also posed a challenge for the fault protection design, primarily to ensure that minor faults do not result in a spin down of the observatory with the additional loss of science observation time that would impose (Ref. 27).
The key challenge for the Observatory configuration is in meeting the needs of the science and the supporting subsystems (many of which have stringent demands as well) and ensuring that the spacecraft could meet all operational, pointing, environmental, and launch vehicle requirements. A major trade for the mission design is deciding “what spins”. One approach is to spin the entire Observatory, while another approach is to spin just the instrument (Ref. 12). 16) 17) 18)
The spacecraft is three axis–stabilized and employs momentum compensation via reaction wheels to accommodate the angular momentum of the spinning instrument. The spacecraft has an aluminum primary structure with a zenith deck provided for mounting the SIA and an anti-sun facing panel for mounting the radar electronics. The structure of the spacecraft bus employs a pentagonal box shape with internal components, including a semi-permanent frame structure with removable panels. Removable panels are organized by subsystem and serve as thermal radiators. The structure uses aluminum and aluminum honeycomb construction.
A modular design for accommodating subsystems, each on a panel, provides for ease of integration (Figure 2). A deployable, fixed solar array with three panels is utilized as the primary power source and provides about 1400 W for the observatory. Spacecraft batteries have a total 74 Ah capacity using Li-ion small cell chemistry based on NASA Aquarius/Argentina’s/CONAE Satélite de Aplicaciones Científicas-D (Satellite for Scientific Applications or SAC-D) and Kepler spacecraft heritage.
SMAP spacecraft avionics and power electronics leverage a JPL planetary heritage design based on the commercial RAD750 flight computer and PCI (Peripheral Component Interconnect) bus architecture for the C&DH (Command and Data Handling) subsystem , 1553 data bus as the observatory command and telemetry backbone, built-to-print design for telecommunication and instrument interfaces, power bus architecture (including power converters, switches, and pyro-firing circuits) for the Power and Pyrotechnic subsystem, as well as the control electronics for the Reaction Control System (thrusters and latch valves). A small number of new capabilities were added, including a 128 GB NVM (Non-Volatile Memory) capable of accommodating much larger science data storage volumes and transmission rates (130 Mbit/s downlink rate vs. 6 Mbit/s typical for planetary missions’ maximum X-band downlink rate), new engineering interface control, a high-capacity solar array interface, and a new power bus controller.
Figure 2: SMAP employs a modular packaging approach (image credit: NASA)
The ACS (Attitude Control Subsystem) employs high-heritage, flight-proven attitude sensors and control mechanisms. Attitude knowledge is provided by a star tracker and 12 sun sensors, which also support safing and attitude reinitialization. Redundant inertial measurement units propagate attitude knowledge between stellar attitude updates. Three large reaction wheels, with a 4th wheel used for momentum compensation, maintain momentum balance between the spacecraft and the SIA and counteract any disturbance torques. Three magnetic torque assemblies are used to manage the reaction wheel momentum and are controlled based on on-orbit magnetic field information from a single 3-axis magnetometer. Orbit position is determined via two-way Doppler tracking and propagated on-board the spacecraft.
The SMAP mission is composed of three elements – the instrument system, the spacecraft bus system, and the ground system. Together, the instrument and the spacecraft bus form the observatory, which collects information and relays it to the ground. The observatory has one portion that is 3-axis stabilized and one portion that will spin at 13 revolutions per minute. 19)
The spacecraft is responsible for avionics [including C&DH (Command and Data Handling) as well as FSW (Flight Software )], GNC (Guidance Navigation and Control), propulsion, communication to the ground and to the instruments, thermal maintenance of the de-spun portion, propulsive maneuvers, and power.
The thermal subsystem is based on a passive design. MLI coverage is optimized for survival heater power and ability to reject electronic heat. Heaters may be added as needed. The battery is thermally isolated from the supporting radiator panel, externally mounted, with dedicated radiator/MLI/heaters.
Figure 3: Illustration of the spacecraft bus configuration (image credit: NASA)
Figure 4: Basic block diagram of the SMAP observatory (image credit: NASA/JPL)
Propulsion subsystem: The monopropellant (hydrazine) propulsion subsystem employs a blow-down design. All components and processes have flight heritage, and include single titanium, diaphragm propellant tank (ROCSAT design made by ATK), eight 4.5 N monopropellant thrusters identical to MER & MSL cruise stage, redundant latch valves and pressure transducers. One of the key requirements for the thermal aspects of propulsion is to meet all range safety requirements.
Figure 5: Illustration of the propulsion subsystem (image credit: NASA)
RF communications: The subsystem is composed of redundant S-band transponders for uplink/downlink command and telemetry functions to the NASA Earth Network and Space Network (single access mode). The transponder provides for coherent Doppler tracking to support orbit determination. The high rate X-band data downlink is provided by redundant X-band transmitters. The telecommunication antennas are mounted on a fixed (nondeployable) outrigger at the nadir end of the spacecraft. The payload downlink is in X-band at 80 Mbit/s, the TT&C data link is in S-band at 2.5 Mbit/s.
SMAP uses a single-string architecture with selective redundancy. Graceful degradation features have also been designed into the observatory where practical. The transponders, transmitters, and IRUs (Inertial Reference Units) are redundant. Propulsion latch valves are mounted in parallel for redundancy and all the thrusters are placed on a single branch. The reactions wheels are oriented and sized so that a failure in an individual wheel can be tolerated. Each magnetic torque assembly is internally redundant (via redundant windings) and magnetic field information can be provided via a ground-based model in the case of a magnetometer failure. Survival heaters and many instrument slip rings are redundantly wired. All actuators include redundant windings.
Particular attention has been paid to fault protection design to reduce the likelihood and mission impact of specific faults and also to minimize the number of fault events that cause the instrument to despin. The observatory is designed to robustly and autonomously recover attitude following the momentum change associated with a despin, but the return to science operations is a longer process resulting in undesirable science data loss. For this reason, the instrument remains spinning for all but the most severe faults (Figure 6).
Figure 6: SMAP observatory fault protection is designed to reduce faults that spin down the instrument (image credit: NASA)
Table 2: Observatory mass and power breakdown
Launch: A launch of the SMAP spacecraft is scheduled for the fall of 2014 on a Delta-2 vehicle from VAFB, CA. NASA contracted ULA (United Launch Services LLC) in July 2012. 20)
Orbit: Sun-synchronous dawn/dusk orbit, altitude = 685 km, inclination = 98º, LTAN (Local Time of Ascending Node) = 18:00 hours, repeat cycle = 8 days.
Figure 7: Data availability after launch (image credit: NASA, Ref. 24)
Sensor complement: (SMAP)
The instrument name is the same as the mission name. As with most microwave instruments, the antenna is the dominant instrument subsystem that both determines the ultimate measurement performance and governs spacecraft accommodation.
The key instrument requirements were determined by the SMAP science working group to be:
1) dual-polarization (linear H and V) L-band passive radiometer measurements
2) linear HH, VV and HV L-band radar (SAR) measurements
3) a wide swath to ensure global three-day refresh time for these measurements (1000 km swath at the selected orbit altitude of 680 km).
The radiometer and radar resolution requirements at L-band dictate that a relatively large antenna aperture must be employed. A shared antenna/feed approach is utilized for accomplishing the required simultaneous radiometer and radar requirements. The overall SMAP architecture is shown in Figure 10, which includes the rotating RBA (Reflector Boom Assembly), feed assembly, radiometer electronics subsystem, and radar electronics subsystem. 21) 22) 23) 24) 25)
A deployable conically-scanning antenna structure of 6 m diameter is selected for the instrument design. In 2009, Astro Aerospace (Carpinteria, CA, a business unit of Northrop Grumman) received a contract from JPL for the design and development of RBA. The antenna consists of an AstroMeshTM reflector and a single feed horn shared by an L-band radar and an L-band radiometer. Whereas the radiometer resolution is defined in the standard manner as the real-aperture antenna footprint, the higher resolution radar measurements are obtained by utilizing SAR (Synthetic Aperture Radar) processing (Figure 17).
Two design modifications were introduced in 2011 (Ref. 21):
• The addition of active thermal control to the instrument spun side to provide a more stable, settable thermal environment for the radiometer electronics
• A “sequential transmit” strategy for the two radar polarization channels which allows a single high-power amplifier to be used.
Because the rotating RBA is shared by the radiometer and radar, the RF signals from the Earth must be separated by diplexers into the active and passive bands, respectively. These diplexers are located on the spun side and are shown as part of the radiometer subsystem. All of the radiometer electronics are located on the spun side of the interface to minimize front-end losses, with slip rings providing a telemetry, signal, and power interface to the spacecraft. The more massive and more thermally dissipative radar electronics are on the fixed side, with the transmit/receive pulses routed to the spun side via a two channel RF rotary joint.
A major milestone in the development of the RBA CDR (Critical Design Review) was completed on December 13-14, 2011 for the SMAP payload. The spun portion of the RBA has a nominal mass of 49 kg; the entire RBA, including launch restraint equipment, has a mass of 65 kg. The launch restraint equipment attaches the compact, stowed reflector to the side of the spacecraft for launch. 26)
The radiometer measures microwave emissions for H and V polarization brightness temperatures, and provides 3rd and 4th stokes parameters that are used for RFI mitigation. The radiometer digital electronics includes digital spectral filtering for RFI mitigation. The key to high radiometric measurement accuracy is achieving repeatable, characterizable, and monotonic responses over temperature and time. Therefore, the thermal design employs passive design features for short-term stability, such as the use of a titanium thermal isolator and radome for the feed. In addition, active thermal control is used for additional seasonal stability, as well as for temperature set-point adjustment, which enables the operational temperature to be changed on-orbit to avoid gain non-linearities. This set-point feature was added to the design as a result of lessons learned from other microwave radiometer missions that exhibited this undesirable behavior. Radiometer performance requirements are summarized in Table 3. 27)
A frequency diplexer allows the radar and radiometer to share a common instrument antenna. The diplexer simultaneously provides high RF isolation between the radar and radiometer frequencies and pre-select filtering for RFI (Radio Frequency Interference) rejection in a compact and low-RF-loss package. It also accommodates high-power handling capability for the radar.
Table 3: SMAP radar and radiometer requirements
Table 4: SMAP instrument key antenna requirements
The instrument antenna design is an offset-fed reflector arrangement (0.7 f/D) with a 6 m projected aperture and vertical and horizontal linear polarizations selectable through an orthomode transducer (OMT). Zenith deck mounting offered a number of system design and performance advantages including (1) lowest overall spun mass/inertia; (2) lowest RF transmission line losses to the radiometer and radar; and (3) lowest overall system noise temperature for radiometer measurements because most feed spillover ‘sees’ cold space. The zenith mounting location and conical scanning requirement, however, posed a significant constraint on the flight system design to avoid intrusions into the instrument antenna FOV (Field of View), the solar array design was a particular challenge (Figure 8). The zenith location also partially but significantly blocks visibility to the GPS (Global Positioning System)—this contributed to a decision in Formulation to forego on-board GPS capability for orbit position and ephemeris and to instead use Doppler tracking and ground-based time synchronization. The most significant design drivers on the antenna came from the radiometer: beam efficiency, reflector surface emissivity, and temperature knowledge to achieve the antenna noise temperature requirements. Radar drivers on the antenna performance were gain stability, sidelobes, and cross polarization levels. Key instrument antenna performance requirements are summarized in Table 4.
Figure 8: Final solar array simplified to reduce panels and deployments; allowed slight penetration into instrument antenna FOVs (image credit: NASA)
Legend to Figure 8: As power requirements matured in the design, the solar array was simplified to a three-panel configuration (with only two deployments) that protruded slightly into the instrument antenna FOV. The resulting RF pattern and performance perturbations from the intrusion can be removed in ground science data processing; however, high-fidelity RF analysis (confirmed by scale model testing) showed that perturbations are very minor and may be negligible. The stowed configuration was also significantly driven by launch vehicle fairing packaging and resulted in having no exposed cells when stowed. This iterative design example is representative of the close interaction between science, instrument, and spacecraft design teams to arrive at the least complex design to satisfy mission requirements.
Mechanically, the spin subsystem and spun platform assembly provide the spin function; launch lock and release; mechanical support for the radiometer, feed and RBA (Reflector Boom Assembly); and spun-side electrical control functions (RBA deployment motors control, thermal control, telemetry, etc.). The heart of the spin subsystem is a Boeing-provided BAPTA (Bearing and Power Transfer Assembly) that includes the spin motor, bearings, 65 slip rings for power and digital telemetry transfer across the spinning interface, and the RF rotary joint used by the radar. The BAPTA is enclosed within the cylindrical instrument core structure that also provides the mounting platform for all spun-side assemblies. ICE (Integrated Control Electronics) control the RBA deployment motors, spun-side thermal control, and radiometer command and telemetry. The Radiometer Front-End Electronics and passive RF components such as the diplexer are mounted to the feed horn. The Radiometer Electronics and Spin Control Electronics are mounted to separate structures to optimize spun mass properties. A CCA (Cone-Clutch Assembly) is the structural interface between the spun platform assembly and the spacecraft, and also locks the spun platform and offloads the BAPTA bearings during launch. Design features are incorporated to attenuate pyroshock levels for the spun electronics and bearings.
Table 5: Instrument mass and power breakdown (reflects CDR estimates with growth contingency applied)
Collectively, the instrument spinning elements form the SIA (Spun Instrument Assembly). The SIA is largely balanced, by design, by adjusting the antenna optical prescription, by appropriately offsetting the feed and spun electronics assemblies from the spin axis using varying strut lengths, and by including small pre-launch adjustable ballast/balance masses at key locations (mostly on the RBA) in the design. An aggressive mass properties management program insures that as-built spun-side mass properties are tracked; the prelaunch adjustable ballast/balance masses allow correction for as-built mass characteristics to ensure proper on-orbit balance is achieved. Extensive analysis and modeling of the system dynamics and control behavior demonstrated that robust and stable balance is achieved by the fixed instrument balance design approach coupled with the spacecraft pointing control authority. Practical SIA on-orbit adjustable balance mechanisms could only provide a small fraction of total available pointing margin and were therefore not included in the design. The spun momentum of the SIA is compensated by the spacecraft’s reaction wheels and ACS (Attitude Control System ). This arrangement simplified the instrument design as well as overall control and fault protection design for the observatory; however, it places a constraint on the maximum spun momentum of the SIA of 364 Nms (at CDR the estimated spun momentum was 326 Nms). Another instrument configuration benefit is that most of the spun mass is concentrated near the rotation axis, which greatly reduces the sensitivity of spun momentum to mass growth.
Instrument RBA (Reflector Boom Assembly):
The 6 m shared reflector posed a number of unique challenges for SMAP:
• Packaging and deployment to accommodate fairing volume and spacecraft constraints
• Spinning and pointing control of such a structure
• Use of a mesh deployable for radiometric measurements
• Accurate pre-launch RF pattern characterization, accounting for spacecraft interaction effects.
The NGAS (Northrop Grumman Aerospace System's) deployable AstromeshTM (AM) reflector was selected and its mass properties are ideally suited for SMAP’s application. These reflector designs have been used in geosynchronous communications satellite applications including MBSAT (Mobile Broadcasting Satellite) of Thuraya, Inmarsat-4, and Alphasat. SMAP uses a derivative of Astro’s heritage antenna design, AM-Lite (Figure 9), which accommodates smaller aperture sizes and fits within a smaller stowed volume.
Figure 9: The 6.5 m AstroMeshTM Lite engineering model reflector (image credit: NGAS - Astro Aerospace)
This is the first known application of this kind of deployable reflector design within a high-performance microwave radar and radiometer antenna system, operating in LEO and also in a spinning configuration. Each of these ‘firsts’ poses unique challenges for SMAP that have been addressed within the mission and system design, and in the verification and validation (V&V) approach. The overall configuration and basic components of the stowed and deployed reflector are shown in Figure 10.
The reflector uses a perimeter truss consisting of composite tubes to support front and rear webs of fiber-reinforced tape. The reflector surface is a 20 OPI, gold-plated molybdenum wire mesh held in place with a net that attaches to a front web to provide the proper spacing to form the mesh’s parabolic shape. The perimeter truss is attached to a prime batten, which in turn attaches to the two-segment boom. The boom is made of two graphite/epoxy tubes connected by hinges that allow the furled reflector to be stowed for launch to fit within the launch vehicle fairing. Pyro-initiated releases are required to open launch restraints before the boom can be deployed.
The RBA deployment is a significant driver to the mission and observatory design. The boom and reflector are deployed separately (boom first, followed nominally by the reflector two days later). The LEO orbit drove the thermal designs to ensure there were no “hot spots” that could either overheat or introduce large thermal gradients, which could add deployment risk. An operational constraint is imposed to idle spacecraft guidance and attitude control during deployment to eliminate ACS reaction loads on the RBA. This, in turn, places requirements and constraints on the deployment duration to be completed within 40 minutes (a spacecraft power constraint). Heritage reflectors have been deployed over long periods (hours) to prevent motor overheating, so new motor and thermal designs were required for SMAP to accommodate the short deployment time and thermal loading.
Figure 10: SMAP’s reflector-boom assembly stowed and deployed configurations (image credit: NASA)
The <0.5 K radiometer antenna temperature calibration requirement places challenges on the mesh and web RF emissivity and mesh temperature knowledge (mesh emissivity < 0.0035, mesh emissivity knowledge to 0.001, mesh temperature known to 60ºC). Early measurements of mesh materials were completed to confirm it was acceptable for soil-moisture applications (Figure 11). The mesh density (OPI) was assessed to meet the L-band emissivity requirements. 20 OPI was selected as the best trade between mass properties and RF performance (lower mass and easier to stow and manage than 40 OPI density, and although the 10 OPI mesh has lower mass it was found to be too lossy for L-band radiometer measurements). The mesh temperature knowledge is another key parameter required for antenna pattern correction. The mesh temperature cannot be measured directly on-obit, so it will be determined by ground test-verified models to provide on-orbit temperature estimates.
Heritage reflectors have been flown in geosynchronous orbits. The LEO environmental effects on the mesh had to be considered during the mesh qualification, including effects of the extensive thermal cycling on-orbit, effects of atomic oxygen, solar ultraviolet (UV) radiation, ESD (Electrostatic Discharge) charging, solid particles, and PIM (Passive Intermodulation) concerns. The mesh qualification program determined that “cold welding” from thermal cycling or gold flaking due to CTE mismatch were not credible failure modes. The mesh is not susceptible to oxidizing from the atomic oxygen. The RF performance would be negligibly impacted if there were a small hole or tear in the mesh from a solid particle micrometeroids. PIM was determined not to cause an interference concern for science or telecom functions. In communication applications of the mesh reflector, the webs are typically painted with a conductive paint for ESD considerations. However, for SMAP, this type of paint contributed too much radiometric loss and had a significant impact in the overall antenna error budget, so an effort was made to eliminate the use of the paint. However, it was determined that the un-painted webs would degrade unacceptably in the vacuum UV environment, so a paint was ultimately selected that was both low loss and tolerant to atomic oxygen and UV. This is an example of how critical RF performance had to be carefully balanced with other design considerations such as operating in LEO.
Figure 11: Mesh emissivity test setup and sample (image credit: NASA)
Another challenge related to the RBA has been the extensive modeling and component level testing for a piecewise verification of the antenna RF performance. Radar and radiometer performance are highly dependent on antenna pattern characteristics such as gain, half-power beamwidth, sidelobe and cross-polarization levels, and electrical pointing. SMAP’s large antenna size and gravity effects make it impractical and high risk to conduct an end-to-end antenna test on the ground in a flight-like configuration and environment (to “test as you fly”). The antenna pattern RF performance is being verified by a combination of test and analysis. Scattering from the boom, solar panels, and other parts of the observatory structure affect the antenna pattern. Moreover, the radar and radiometer have stability requirements for pattern characteristics. GRASPTM (Geodetic Reference Antenna in Space) is used to model the antenna in the presence of the observatory to determine the effects that could change the antenna pattern, such the FOV changes as the antenna rotates, reflector and boom thermal distortions, and dynamic distortions from spacecraft. As an independent verification, a high-fidelity 1/10th scale model of the observatory was tested to confirm the GRASPTM model (Figure 12). The flight feedhorn pattern characteristics will be measured and applied to the GRASPTM RF model to form the final-prelaunch antenna performance. The performance will be verified and uncertainties will be refined during post-launch commissioning and during the science calibration and validation campaign.
Figure 12: 1/10th scale model undergoing antenna range measurements (image credit: NASA)
RFI (Radio Frequency Interference) mitigation:
The L-band spectrum region (Figure 13) is heavily used and SMAP’s measurements are made over land areas, where most potential interferers are located. This contrasts with the similar L-band Aquarius mission, where the primary target is the relatively RFI-quiet ocean. It’s also worth noting here that RFI is evolving and generally increasing over time and that trend is expected continue into the future; SMAP must therefore be prepared to operate not only in the RFI environment as it exists today, but also in the RFI environment that may exist later in this decade. To meet radiometric accuracy requirements, SMAP has adopted aggressive measures to identify and mitigate the effects of RFI. Because SMAP is a global mapping mission with continuous, near-real-time generation of data products, any RFI mitigation techniques must lend themselves to reliable automation in ground processing software. The nature of the RFI threat differs somewhat for the radiometer and radar channels, which are treated in turn (Ref. 27).
Figure 13: SMAP radar and radiometer operate within congested spectrum allocations that require RFI mitigation strategies to be applied (image credit: NASA)
Radiometer: The RFI power in the radiometer’s 24 MHz bandwidth will positively bias the observed brightness temperature, resulting in an erroneous dry bias in soil moisture estimates if uncorrected. While large RFI impacts (> ~40–50 K) can be detected and discarded, causing data loss, smaller RFI contributions are more difficult to detect and more likely to impact science product accuracy. Errors resulting from RFI corruption of even ~0.5 K are significant, therefore the radiometer includes a digital receiver to enable RFI detection and mitigation.
An extensive effort has been conducted to characterize the RFI environment expected for the radiometer. Two primary sources of RFI information have been utilized: a set of airborne observations in the United States and observations from the SMOS (Soil Moisture and Ocean Salinity) L-band radiometer mission of ESA (European Space Agency). The results show a variety of sources are present, including pulsed and narrowband, with some limited evidence of “broadband” continuous sources. SMOS data do not provide detailed RFI source information, but do provide a global characterization of observed RFI power levels. In particular, SMOS data show increased RFI levels in global regions outside the Americas.
Available characterization data shows RFI sources are either pulsed or narrow-band [i.e., continuous wave (CW)–like] in nature. Pulsed sources can be detected in the time-domain, if the radiometer detector is sampled at a sufficiently high temporal resolution. The radiometer has a fundamental sampling frequency at the radar PRF of 3.2 kHz, which allows ground-based sub-millisecond RFI detection and mitigation using simple time-domain pulse thresholding strategies. To detect and mitigate CW sources, the radiometer’s 24 MHz bandwidth is digitally filtered into 16 x 1.5 MHz subbands (Figure 14). Detected powers in these subbands will be telemetered to the ground at ~ 1 ms temporal resolution. The resulting ~ 1.5 MHz x 1 ms spectrogram dataset can be utilized in a variety of RFI detection methods, including channelized pulse detection, cross-frequency algorithms, or “peak-picking” methods.
Figure 14: Radiometer band divided into 16 x 1.5 MHz spectral subbands for RFI detection (image credit: NASA)
In addition to time/frequency discrimination, the radiometer digital subsystem will also compute the first through fourth moments of observed fields both in the 24 MHz “full-band” (i.e., 3.2 kHz) and 1.5 MHz “subband” (16 channel x 1 ms) datasets. The availability of these moments will
Radar: In contrast to the radiometer, the SMAP radar operates in a “shared” band between 1215 and 1300 MHz with other services including FAA and DOD aircraft navigation systems. Very strong interference from these systems is expected, and indeed has been observed by previous L-band radar missions. Most potential interfering emissions at L-band are relatively narrow band. Because the SMAP radar itself is a narrow band system (1 MHz linear chirp), a key RFI avoidance strategy for SMAP is to make the center transmit frequency adjustable. If persistent RFI is encountered in a given band over a given region, the center frequency is simply commanded to a different location in the spectrum. Despite best efforts to operate the SMAP radar in a “clear” band, however, it is inevitable that some RFI contamination will be observed. Therefore, RFI detection and removal will be performed as part of the ground data processing.
As with the radiometer, an extensive effort has been made to characterize the RFI environment expected for the radar. An examination of currently operating L-band systems indicates that 87% of RFI is from “pulsed” sources, and 13% is from “other” sources such as CW emitters. A simulation, developed to model RFI and the effectiveness of mitigation algorithms, uses the database of known emitters over North America. RFI emitter characteristics are varied in different runs of the simulation to assess sensitivities. To validate the RFI simulation, it was run assuming the Aquarius instrument parameters and orbit. When compared against the actual Aquarius data, the agreement was found to be excellent (Figure 15). In order to estimate the impact of other regions of the world where the RFI is observed to be somewhat worse (e.g., Europe and East Asia), the simulation can be run with an increased number of emitters, with higher duty cycles, higher powers, etc.
Figure 15: Aquarius noise only data vs. Simulation, multiple ascending nodes (image credit: NASA)
Legend to Figure 15: Complementary cumulative distribution functions of real and simulated Aquarius radar noise-only data for sets of passes over different geographical regions. Power levels above the radar noise floor are due to RFI.
The primary detection/correction algorithm for pulsed interferers is STT (Slow-Time Thresholding). Here, SMAP leverages the fact that RFI signal pulse rates are usually slower than SMAP’s radar pulse rate. The STT technique looks at the slow-time series associated with a given range bin, sets an appropriate threshold, and flags any azimuth samples that exceed this threshold as RFI events. When the STT is applied to the results of the North American simulation described above, it is observed that the overall measurement errors due to RFI will be well within the budgeted allocation of 0.4 dB RMS. Further, this mitigation technique appears robust to artificially intensifying the RFI environment in the simulation to approximate regions other than North America (Ref. 27). 28) 29)
The unique aspect of the SMAP application is the necessity for rotating the large antenna. At the nominal SMAP altitude of 685 km, the reflector must be rotated at a rate of 13.0 rpm to maintain contiguity (i.e., minimum overlap, SMAP is designed for 14.6 rpm) of the measurements in the along-track direction. Key requirements that must be met by the reflector assembly include:
1) All RF performance requirements (gain, beam efficiency, etc.) must be met under the spinning conditions
2) The total momentum generated must be within the amount the spacecraft is capable of compensating
3) The disturbances resulting from residual imbalances must be sufficiently small as to not affect overall pointing or impart excessive loads to the spin motor bearings.
The deployable antenna is attached to the structure of the SPA (Spun Platform Assembly). The SPA includes the primary and secondary structures. The former provides the backbone of the SMAP instrument, while the radiometer electronics and IFA (Integrated Feed Assembly) are supported by the secondary structure. The feed assembly design employs a single horn, capable of dual-polarization and dual frequency (the radiometer frequency at 1.41 GHz, and the radar frequencies between 1.22 and 1.30 GHz). In order to minimize the moment of inertia, the horn is designed to be as small, compact, and lightweight as possible. To meet measurement performance requirements, the antenna beamwidth of the radiometer frequency band is between 2.3º to 2.5º, and the antenna gain at the radar band is better than 35.5 dBi.
Figure 16: Spun platform assembly and electronics on the spun portion of the SMAP instrumentation (image credit: NASA)
Table 6: SMAP instrument parameters
Figure 17: SMAP measurement geometry showing radiometer swath, and high- and low-resolution radar swaths (image credit: NASA)
Radiometer parameters: Measurement precision for a radiometer is principally affected by NEDT. NEDT (0.65 K) is set by the system noise temperature (777 K), bandwidth (22 MHz), and net integration time (65 ms for a 30 km x 30 km grid cell, including both fore and aft looking radiometer samples). Many other factors contribute to the measurement imprecision, including antenna pattern instability. Altogether, measurement precision is 0.95 K. The radiometer calibration stability is 0.62 K. Calibration stability is achieved by frequent observation of internal calibration sources, observation of stable earth and space targets, and stable thermal design. The root-sum-square of the 0.62 K stability and the 0.95 K precision estimates yields a total error of 1.1 K, satisfying the 1.3 K requirement of the soil moisture science objective. 30)
Initially the radiometer was designed with passive thermal control, and analysis demonstrated that the required thermal stability could be met. Achieving anomaly free performance over a large thermal range, however, carries a development risk due to potential for thermo-mechanically induced calibration shifts associated with internally calibrated radiometers; these have been observed in the prelaunch testing of SAC-D/Aquarius, Jason-2/AMR, and Juno/MWR. It was therefore decided to implement an active thermal control augmentation to the existing passive thermal design. The temperature of the RAD front end (Figure 16) is settable to within ±2ºC over a 15ºC range within the acceptable flight temperature range.
Radar parameters: To obtain the required 3 km and 10 km resolution for the freeze/thaw and soil moisture products, the radar will employ pulse compression in range and Doppler discrimination in azimuth to sub-divide the antenna footprint. This is equivalent to the application of SAR (Synthetic Aperture Radar) techniques to the conically scanning radar case.
Due to squint angle effects, the high-resolution products will be somewhat degraded within the 300 km band of the swath centered on the nadir track (Figure 17 and Figure 18), with azimuth resolution capability decreasing over this region as the target area approaches the nadir track. The baseline system has both V- and H-pol channels. An additional channel measures the HV (or VH)cross-pol return.
Figure 18: Radar measurement geometry as a function of scan angle (image credit: NASA)
Legend to Figure 18: The spacecraft velocity vector is shown as vg. Also shown are the iso-range and iso-Doppler contours that govern the radar pixel formation.
There are two requirements placed on the radar relative error. The soil moisture measurement requirement places a 0.5 dB relative error on both the vertical and horizontal copolarized backscattering coefficient measurements at 10 km resolution. The freeze/thaw state measurement places a 1 dB requirement on the relative error of each vertical and horizontal co-polarized backscatter measurement at 3 km resolution.
The radar relative error depends on the signal-to-noise ratio (SNR) and the number of independent samples, or “looks”, averaged in each measurement, as well as the relative calibration error. Looks will be obtained by averaging in both range and azimuth. The 1 MHz bandwidth will yield a ground range resolution of approximately 250 m and will result in a minimum of 12 looks in range for 3 km cells and 40 looks for 10 km cells.
The Doppler diversity (Figure 18) will be maximized at a scan angle perpendicular to the platform velocity, leading to a single-look azimuth resolution of approximately 400 m. The single-look resolution will degrade as the scan angle approaches the platform velocity vector (θaz = 0 in Figure 18), reaching 1500 m at the inner swath edge (150 km cross-track).
To ease volume and mass issues encountered in the spacecraft design, a decision was made to generate both linearly polarized transmit signals sequentially by switching a single high-power amplifier. The current sequential transmit scheme is shown in Figure 19. In this timing configuration, the duration of the total transmit event has been extended, and the nominal PRF (Pulse Repetition Frequency) is lowered to approximately 2.9 kHz in order to accommodate the temporal width of both echo returns. As was the case in the previous design, the two polarized returns are isolated by transmitting signals at offset frequencies (f1 and f2) as shown in Figure 20. This scheme maintains the same science performance.
Figure 19: Instrument timing in sequential transmit configuration (image credit: NASA)
Figure 20: Signals from V- and H-pol channels are isolated in frequency domain (image credit: NASA)
The active radar will utilize onboard SAR processing in order to obtain the sub-footprint resolution necessary for the geophysical retrievals. The OBP (Onboard Processor) software package receives the capability to turn raw data into low-resolution and high-resolution data ready to be downlinked for further ground processing into low-resolution and high-resolution radar products. 31)
Figure 21: Swath size of radar and radiometer instruments on SMAP (image credit: Northrop Grumman/Astro Aerospace)
The SMAP RDE (Radiometer Digital Electronics):
The SMAP radiometer has an entirely digital back-end processor for its DSP (Digital Signal Processing) and RFI (Radio Frequency Interference) mitigation. The mission of SMAP is to provide global high-resolution mapping of soil moisture and its freeze/thaw state to link terrestrial water, energy, and carbon cycle processes. Fusion of SMAP’s L-band SAR data and L-band microwave radiometer data will enable this mission. In addition, both of SMAP instruments include new technology that enables mitigation of RFI via ground processing. In particular, the SMAP radiometer employs the first spaceborne digital back-end processor subsystem called the RDE (Radiometer Digital Electronics). The RDE is a FPGA-based digital signal processing system that uses time, frequency, statistical and polarization diversity to detect and flag RFI during its mission lifetime 32)
The SMAP radiometer can be thought of as three major subsystems: the RFE (Radiometer Front End ), RBE (Radiometer Back End), and RDE (Radiometer Digital Electronics). 33)
The RFE includes a calibrated noise source and interfaces to a 6 m conical-scanning deployable mesh antenna that is shared with the radar. The RFE and RBE subsystems together form a polarimetric heterodyne radiometer that downconverts predetected horizontal and vertical polarization component signals to an IF (Intermediate Frequency) of 120 MHz using highside local oscillator injection at 1533.5 MHz. Both channels are subsequently digitized and processed by the RDE at 96 MHz with 14 bit resolution.
Figure 22: Exploded view of the RDE assembly (image credit: NASA/GSFC)
In addition, the RDE interfaces with the spacecraft for commanding/telemetry and science data pipeline, provides the instrument power conditioning and distribution, command/control, housekeeping and overall timing and synchronization. The RDE consists of five CCAs (Circuit Card Assemblies), an enclosure, a baseplate, a connector panel and cover shown in Figure 3. Two identical CCAs, APU-H (Analog Processing Unit-Horizontal) and APU-V, perform quadrature down-conversion, subbanding and generation of the first 4 raw sample moments for fullband and 16 adjacent frequency channels of subband data for each polarization.
The DPU (Data Processing Unit) orchestrates control of the radiometer, processing, timing and packetization of data within the RDE. The DPU also digitizes analog telemetry from the RFE, RBE, and platinum resistance thermometers throughout the radiometer. Furthermore, the DPU correlates fullband and subband signals, producing complex-valued counts for generating the third and fourth Stokes parameters (C3 and C4).
The PDU (Power Distribution Unit) accepts primary power from the spacecraft in the range of 22 to 36 volts. The PDU produces the secondary voltages for the RDE as well as voltages for powering the RBE and RFE subsystems. The last CCA is the high-speed digital backplane that connects the two APU cards to the DPU (Ref. 33).
SMAP instrument antenna control:
SMAP’s attitude control and pointing system performs the key on-orbit operations needed to implement the conical scanning scheme employed for data acquisition by the radar and radiometer. The observatory uses a zero momentum bias, dual-spin architecture to rotate its large antenna at a spin rate of 13–14.5 rpm, while the spacecraft bus provides a three-axis controlled platform that maintains both itself and the instrument section’s spin axis in a nadir-pointed orientation. The major pointing and control functional aspects and design characteristics are illustrated in Figure 23. A key challenge with the spinning antenna stems from its large spin axis moment of inertia, which at almost 240 kgm2 is larger than that of the spacecraft bus at about 190 kgm2(Ref. 27).
Figure 23: SMAP pointing and control system functional aspects and design characteristics (image credit: NASA)
Figure 24 shows the sensor and actuator suite and locations. This control system configuration was informed by a prior design concept for the NROSS (Navy Remote Ocean Sensing System) satellite, which would have employed a similar sized-rotating antenna and nadir-pointing scheme (NROSS development was halted after Preliminary Design Review in the 1980s). From a control standpoint, SMAP took an integrated approach to momentum management, with momentum compensation for the spun side and three-axis control accomplished with a single set of four RWAs (Reaction Wheel Assemblies), rather than using a dedicated momentum wheel for spun-side momentum compensation. In a recent operational example of a nadir-pointing observatory employing a momentum-compensated rotating antenna, WindSat/Coriolis, a dedicated momentum wheel was also used to counteract the antenna’s angular momentum, in a manner similar to that planned for NROSS. SMAP’s approach provides a degree of functional redundancy for wheel failure and reduces control complexity.
Figure 24: Observatory sensor and actuator description (image credit: NASA)
The system architecture is illustrated in Figure 25, encompassing the attitude and spin rate determination functions, attitude control modes for both RWA and RCS (Reaction Control System) based three-axis control, spun-side momentum compensation, and the torque rod-based scheme employed for RWA momentum management. For translational maneuvers (needed for orbit altitude maintenance) and select contingency scenarios, the RCS is used due to the much larger control authority offered by the thrusters. For nominal mapping operations, this system can control nadir pointing errors due to precession and nutation to within 0.5º, with a stability tolerance of ±0.3º (3σ).
From a design and verification standpoint, the key challenge for pointing and control is accommodating the flexible modes, especially for the large antenna and its supporting boom, while simultaneously controlling the antenna spin rate and nadir orientation to within the required tolerances. This has been accomplished via careful engineering of the primary frequencies associated with these various elements, to ensure adequate separation and avoid the potential for interference or undesired resonance effects. Frequency distribution of these system components is shown in Figure 26 to illustrate this aspect of the design. The minimum 1st flexible mode frequencies of the solar array, as well as the antenna and boom, became key design requirements on the structure to ensure adequate separation from the spin control system and the observatory’s attitude control bandwidth.
Figure 25: Pointing and control system architecture (image credit: NASA)
GDS (Ground Data System):
The ground data system being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. The SMAP mission shares in common many characteristics as those of Jason-1 and WISE. One of the mission objectives is to achieve similar cost savings as done by Jason-1 and WISE, through automation of real-time operations. However, the SMAP mission has selected a different GDS subsystem element in place of the one that provides the automation services for Jason-1 and WISE [Note: The GDS subsystem that provides automation of engineering operations for Jason-1 and WISE missions is the JPL ESMC (Earth Science Mission Center)]. The SMAP GDS will use NASA’s AMPCS [AMMOS (Advanced Multi-Mission Operations System) Mission Data Processing and Control System] to provide telemetry processing, storage, reporting, display, and a subset of automation capabilities for real-time operations. 34)
The SMAP GDS consists of numerous subsystems that provide specific and necessary services. Although many GDS functional elements will automate routine operations activities, the AOE (Automated Operations Element) will not directly control all of them.
Figure 27: Functional block diagram of the SMAP GDS architecture (image credit: NASA)
NowCast: Product development:
The SMAP Applications program is designed to first increase and then sustain the interaction between application users and scientists involved in mission development. The SMAP project has sponsored several applications meetings and workshops. To better reach the applications users, some of these have been held at user locations such as the USDA (U.S. Department of Agriculture), USGS (U.S. Geological Survey), and NOAA headquarters, among others. Feedback from user communities is formally and actively reported to mission scientists to broaden and facilitate eventual SMAP data access and enhance opportunities to use mission data to address societal needs. For example, collaboration between the SMAP mission and the USDA’s FAS (Foreign Agriculture Service) has elicited the requirements of yield forecasting and familiarized analysts with soil moisture data. Another example pertains to the Emergency Response and Operational users, who have worked with the SMAP mission to plan for providing data in friendly formats (KMZ and GeoTIFF) for a more rapid ingestion of soil moisture data into decision-making environments. 35)
The SMAP Applications program is groundbreaking and serves as an example for other NASA missions to expand their focus to include user communities’ needs in the early phases of mission development. Through a team that includes an applications lead on the SDT (Science Definition Team), leadership from the mission, and an applications coordinator, the applications program works to characterize the community of mission data users through workshops and applied research. The project has also initiated a program of Early Adopters to promote application research in the prelaunch stages of the mission, in order to provide a better understanding of how SMAP data products can be scaled and integrated onto organizations’ policy, business, and management activities. These efforts will expand the use of the data after launch, and increase the societal benefit of the mission.
Table 7: Anticipated SMAP mission products
Legend to Table 7: * Mean latency under normal operating conditions. Latency is defined as the time from data acquisition by the instrument to its availability in a designated data archive. The SMAP project will make a best effort to reduce these latencies.
The overall strategy for the SMAP applications program is to develop a community of end users and decision makers who are interested in using SMAP products in their applications by providing opportunities to learn about SMAP’s unique capabilities and scientific objectives. The SMAP science objectives are to acquire spaceborne hydrosphere state measurements to 1) understand processes that link the terrestrial water, energy, and carbon cycles; 2) estimate global water and energy fluxes at the land surface; 3) quantify net carbon flux in boreal landscapes; 4) enhance weather and climate forecast abilities; and 5) develop improved flood prediction and drought-monitoring capabilities. To meet its scientific goals, SMAP will fly a dedicated satellite in a near-polar, sun synchronous orbit, crossing the equator at 6:00 a.m. and 6:00 p.m. local time. The satellite will carry an L-band (1.26 GHz) radar and an L-band (1.4 GHz) radiometer that share a deployable lightweight mesh parabolic reflector, which provides a conically scanning antenna beam with a constant surface incidence angle of approximately 40º and will measure a swath approximately 1000 km wide. The combined observations from the two sensors will allow accurate estimation of soil moisture and freeze/thaw states at spatial scales valuable for both hydrometeorological (10 km) and hydroclimatological (40 km) studies.
After launch, the satellite’s instruments will be calibrated (an expected time period of three months). Once calibrated, the SMAP mission will deliver estimates of soil moisture in the top 5 cm of soil with an accuracy of 0.04 cm3/cm3 volumetric soil moisture, at 10-km resolution, with 3 day average intervals (Table 7). Global maps will also be available of landscape freeze/thaw state derived from L-band radar at 3 km spatial resolution with a 2 day refresh rate for the high northern latitudes (i.e., latitudes above 45ºN). Measurements will be made over the global land area, excluding regions of snow and ice, mountainous topography, open water, and areas of extremely dense vegetation such as tropical forests.
In addition to the instrument measurements and derived products for the surface layer, SMAP will also provide Level 4 data assimilation products by ingesting active and passive observations into land surface models to provide root-zone soil moisture (to a depth of 100 cm). A net ecosystem exchange product will also be developed that integrates freeze/thaw measurements into a carbon model to provide ecosystem exchange at 9 km resolution. As these two products are intended to serve a broad community, there is an opportunity for user engagement now to optimize the design of these products so that they can ultimately satisfy user requirements (Ref. 35).
Background: The SMOS interferometric radiometer of ESA observes L-band passive microwave emission at a range of incidence angles at a resolution of about 40 km (varying with incidence angle) and with a measurement error standard deviation of approximately 4 K. The SMAP mission will make simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band). Similar to SMOS, the SMAP radiometer measurements will be at about 40 km resolution. Unlike SMOS, SMAP will observe brightness temperature at a constant incidence angle of 40º and with a design accuracy of 1.3 K. 36)
SMAP and SMOS observations are directly connected to surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (~top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP brightness temperature observations with estimates from a land surface model in a soil moisture data assimilation system (Figure 28). The land surface model component of the assimilation system, the NASA Catchment land surface model, is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. A radiative transfer model is added to the land surface model to simulate microwave radiances. The horizontally distributed ensemble Kalman filter (“3d EnKF”) update step considers the respective uncertainties of the model estimates and the observations, resulting in a soil moisture and soil temperature analysis at 9 km resolution that is, in theory, superior to satellite or model estimates alone. Moreover, error estimates for the L4_SM product are generated as a by-product of the data assimilation system.
Figure 28: The SMAP L4_SM soil moisture product merges land model estimates of L-band brightness temperature with SMAP observations in a soil moisture and soil temperature analysis. SMOS observations are used to calibrate and validate the SMAP L4_SM algorithm prior to the launch of SMAP (image credit: NASA)
SMOS has been providing multi-angular, global passive microwave observations at L-band since its launch in November 2009. These observations are highly valuable for the science development of the SMAP L4_SM algorithm. In a first step, the multi-angular SMOS observations were used to calibrate the L4_SM microwave radiative transfer model. In a second step, multi-angular SMOS observations were assimilated into the prototype L4_SM algorithm. The results show that the assimilation estimates of surface and root zone soil moisture are superior to estimates derived from the model alone. The assimilation of SMOS observations represents an important step in the prelaunch calibration of the SMAP L4_SM algorithm.
Development of a ground network of sensors for product validation:
NASA is developing a wireless sensor network, control system, and data analysis technologies for dynamic and near-real-time validation of the spaceborne soil moisture measurements of the SWAP mission. Soil moisture fields are functions of variables that change over time across the range of scales from a few meters to several kilometers. Sensor placement rules are being developed based on spatial statistics of soil moisture. For each location, dynamic scheduling policies are being defined based on physical models of soil moisture temporal dynamics and microwave sensor models for heterogeneous landscapes. Furthermore, the ground-based estimates of the true mean to the spaceborne estimates are being related through a physics-based landscape simulator and statistical aggregation procedure.
An energy-efficient integrated communication and actuation platform was developed and used to command the sensors and transmit their data to a base station in near-real time. Full-scale field experiments were initiated in August 2010 with the deployment of the first full-scale wireless sensor network in Canton, Oklahoma, using the custom-built Ripple-1 architecture. 37) 38)
This project introduces a new concept for a smart wireless sensor web technology for optimal measurements of surface-to-depth profiles of soil moisture using in-situ sensors. The objective is to enable a guided and adaptive sampling strategy for the in-situ sensor network to meet the measurement validation objectives of spaceborne soil moisture sensors. The validation of SWAP mission data products is only one potential application of this technology. The project is being carried out at the University of Michigan (Umich) and at MIT (Massachusetts Institute of Technology) through a grant from the NASA/ESTO (Earth Science Technology Office).
Figure 29: Global architecture of the Ripple wireless sensor network system (Umich, MIT)
The wireless sensor network will communicate with a coordinator, and actuate measurements only when their measurement significantly adds value to the across-network computation of the field mean. The principal technology innovations that make this possible are:
• Optimal design of sensor node placement and scheduling based on modeled soil moisture spatial statistics, and joint placement, scheduling and mean estimation
• Strategies for deriving large-scale spaceborne estimates of heterogeneous soil moisture that are compatible with ground-based estimates of true mean of soil moisture fields
• Wireless communication protocols and actuation systems that configure the sampling within the network to yield large-scale field mean conditions.
Upon successful completion of the baseline project in 2012, the TRL (Technology Readiness Level) is expected to be at 6, on-track for integration into an operational scenario for SMAP by the time it launches in the 2015 timeframe.
Ripple-1 network deployment in Canton, Oklahoma:
A conceptual and architectural depiction of the Ripple data collection system is illustrated in the Figure 1. The system consists of a field element and a remote element. A wireless sensor network is deployed over a target field, along with a base station that performs data collection and sensing control, and a database collocated with the base station for local data storage. At each sensing site (where a sensor node is placed), 3 moisture sensors are deployed at different depths with wire connection to the sensor node on the ground. The base station receives sensing data from each sensor node, but can also control the sensor measurement schedules on demand. It also periodically (every half an hour) uploads the collected sensor data through a 3G connection to a database server. The database server and web server constitute the remote element of the architecture.
The Ripple-1 (Figure 30) system is built using the ZigBee (IEEE 802.15.4 plus higher layer specifications) standard. ZigBee allows the formation and self-configuration of a multi-hop network, which can potentially provide the required coverage. In addition, ZigBee is a relatively mature technology with many products on the market to choose from, which can significantly shorten the development and production cycle. - The disadvantage with this choice is that a router node under the ZigBee specification cannot be put to sleep mode, which means it will consume significantly more energy and will require larger batteries and larger solar panels. For the end device, the project selected to use the Xbee Pro SOC as both the MCU Microcontroller Unit) and radio.
Figure 30: Photo of the Ripple-1 end device (image credit: Umich, MIT)
Prelaunch SMAP campaigns:
SMAPVEX12 (SMAP Validation Experiment 2012) Field Campaign and Aircraft Observations
SMAPVEX12 is the primary prelaunch field campaign for SMAP established to provide data for algorithm evaluation and testing and applications development. Several agencies in the U.S. and Canada are cooperating in the SMAPVEX12 data acquisition, processing and analysis.
The SMAP Algorithm Development Teams were asked to provide an assessment of what outstanding issues could be addressed with a field campaign. All of the soil moisture algorithms had two common requirements for a field campaign; an extended time series and diverse vegetation conditions. Data sets that supported the combined active passive algorithm were considered the top priority, which necessitated an aircraft instrument suite that could provide data to simulate the SMAP sensor system. This evaluation also indicated that it was critical that any campaign be conducted as soon as possible in order for the algorithm teams to effectively utilize the results.
In response to the issues identified, a field campaign SMAP Validation Experiment 2012 (SMAPVEX12) was designed and executed. The primary objectives were as follows (Ref. 43):
• Collect an extended times series of concurrent active and passive microwave observations
- Capture a wide range of soil moisture conditions
- Observe a wide range of vegetation conditions including variable types and growth stages
- Multiple resolution observations for scaling.
• Find ways to better mitigate low-level RFI effects observed in North America
• Improve the parametrization of vegetation (and its water content) and soil roughness
• Contribute to establishing an in situ Cal/Val site for SMAP post-launch validation.
The ground and airborne data acquisition phase of SMAPVEX12 took place over a period of approximately six weeks from June 6 to July 19, 2012 in an agricultural region south of Winnipeg, Manitoba (Canada). The campaign was organized jointly with the Canadian SMAP Science Team who were responsible for coordinating the site logistics and ground data sampling.
The site in the Carmen-Elm Creek area of Manitoba was chosen due to the existing soil moisture monitoring stations that have been installed on private farms in the region over the past growing season, and is expected to serve as a long-term site for assessing the satellite data post-launch. During this campaign, NASA conducted flights carrying instruments similar to the SMAP satellite several times per week over the selected study area covering forested and agricultural land. The study area had a size of of ~13 km x 70 km. 39) 40) 41)
SMAPVEX12 was funded by several agencies in Canada (CSA, AAFC, EC, and NSERC) and US (NASA). It complements the Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) by providing extensive data sets for the development and validation of SMAP passive and active soil moisture retrieval algorithms. 42)
Figure 31: The SMAPVEX12 intensive sample site (image credit: NASA/JPL, CSA)
Aircraft observations: 43)
Two aircraft-based instruments were deployed for SMAPVEX12 on different aircraft; the PALS (Passive/Active L-band Sensor) and the UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar).
• PALS provides both radiometer (vertically and horizontally polarized brightness temperatures) and radar products (normalized radar backscatter cross-section for V-transmit/V-receive, V-transmit/H-receive, H-transmit/H-receive, and H-transmit/V-receive). In addition, it can also provide the polarimetric third Stokes parameter measurement for the radiometer and the complex correlation between any two of the polarized radar echoes (VV, HH, HV and VH).
PALS was mounted at a 40 º incidence angle looking to the rear of the aircraft, a Twin Otter. The lowest elevation that PALS can operate at is determined by the minimum distance for radar data acquisition (~1000 m), which results in a spatial resolution of ~350 m cross-track and 650 m along-track for the low altitude flights. The highest flight altitude for SMAPVEX12 was determined by the operational and available maximum altitude of ~2500 m, which corresponds to a spatial resolution of 900 m cross-track and 1500 m along-track.
The PALS flightlines were designed to satisfy the major objectives of SMAPVEX. Four low altitude lines were used to provide high spatial resolution data for fields with homogeneous vegetation conditions. An attempt was made to locate many of the sampled fields directly on these lines. High altitude lines mapped a larger region and provide data for simulating SMAP combined algorithms. A total of eight lines covered a domain ~12.8 by 70 km. Lines were spaced ~ 1.6 km apart.
• UAVSAR is an aircraft based fully polarimetric L-band radar that is also capable of interferometry. It is currently implemented on a NASA Gulfstream-III aircraft. For SMAPVEX12, the nominal flight altitude was 13 km. UAVSAR looks to the left of flight direction and collects data over a swath between 25 and 65º, which is a nominal swath of 21 km. The most relevant portion of the data swath for SMAP, which has an incidence angle of 40º, are data collected between ~35 and 45º, which is a narrower swath of ~3.8 km. In order to provide coverage of the study domain, four overlapping flight lines were used. Spatial resolution can be as high as 3 m.
Outcome and outlook:
Both the weather conditions and instrument performance exceeded expectations resulting in SMAPVEX12 being very successful. A total of seventeen days of flights were conducted with supporting ground observations over 42 days (June 7-July 19, 2012). This simulated the temporal frequency expected from SMAP at mid-latitudes.
Following the first flight, which had moderate soil moisture levels, there was a series of rain events that resulted in very wet conditions for several days. This wet period was followed by an extended drying of the soils that lasted over two weeks. The remainder of the campaign had mixed conditions. - Many of the crops were near bare soil conditions at the outset of SMAPVEX12 and reached peak biomass/vegetation water content by its end. Winter wheat reached its peak biomass early in the campaign and then entered senescence.
Both instruments/aircraft were able to collect data on every flight day; however,, there were a few dates that only one of the two aircraft flew.. Very little data was lost due to RFI or instrument failure. Based upon the wide range of soil moisture and vegetation conditions that existed and that we were able to sample with both the ground-based and aircraft instruments, SMAPVEX12 was highly successful in achieving its objectives. Data processing is currently underway. Following a data quality and team evaluation period, all data will be archived at a public website.
ComRAD ground-based SMAP simulator
The ComRAD (Combined Radar/Radiometer) microwave instrument system used in this investigation has been developed jointly by NASA/GSFC and George Washington University. ComRAD includes a dual-pol 1.4 GHz radiometer and a quad-pol 1.24-1.34 GHz radar sharing a new 1.22 m Cassegrain parabolic dish antenna and subreflector to achieve a very low loss system. The absolute accuracy and the sensitivity of the instrument are ±1 K and ±0.1 K, respectively. External calibration is achieved using cold sky and ambient microwave absorber targets for the radiometer, and flat plates and dihedral reflectors for the radar. 44)
When deployed in the field, ComRAD is mounted on a 19 m hydraulic boom truck (Figure 32 top) and can operate over a range of incidence angles from 0º to 175º and a 300º range in azimuth. The mounting platform can also accommodate additional small instruments such as a CropScan visible/infrared sensor for vegetation reflectance measurements and a thermal infrared sensor for scene physical temperature.
Figure 32: Top: ComRAD truck-mounted instrument system deployed at the USDA OPE3 test site during July, 2012. Bottom: Schematic of ComRAD data-taking positions over soybeans (sector #2) and corn (sector #1). Approximately 60 independent radar measurements were acquired during 120º azimuthal sweeps of the boom over each crop (blue A1 – A60), while passive data were collected at 7 discrete locations (orange P1 through P7) within the 120º sectors for each crop (image credit: NASA/GSFC, USDA)
An extensive field experiment from crop planting through senescence was conducted from June to October, 2012 at the heavily instrumented USDA/ARS (U.S. Department of Agriculture/Agricultural Research Service) OPE3 (Optimizing Production Inputs for Economic and Environmental Enhancement) test site in Beltsville, MD, to acquire data needed to address active/passive microwave algorithm needs for accurate soil moisture retrieval. Vegetation cover in the experiment consisted of two crops, corn and soybeans, planted on either side of the ComRAD truck staging area (Figure 32 top). Corn was planted at the site on May 16 and harvested on October 17-18; soybeans were planted approximately one month later on June 14 and harvested on October 26. In situ soil moisture, soil temperature, and leaf wetness sensors were installed by USDA to provide continuous ground truth data.
These data were supplemented by additional soil moisture data collected manually twice a week by USDA personnel, along with weekly plant architectural, water content, and density measurements. The OPE3 site also contains a SCAN meteorological station and a flux tower which record precipitation and other micrometeorological data. ComRAD microwave measurements at the SMAP incidence angle of 40° were made on 75 days between June 1 and October 24, 2012. Active and passive data were acquired autonomously every 90 minutes (weather permitting) accordingly to the schematic in Figure 32 bottom. Manual calibration of the radiometer was performed weekly.
Analysis: Time series data from the 2012 ComRAD field experiment will be used to refine soil moisture retrieval algorithms being developed for the SMAP mission. An example of a ComRAD time series over corn from a 5-day period in late summer is shown in Figure 33. Diurnal patterns as well as an overall drying trend can be seen in the plotted data. Similar data throughout the growing season should prove useful to improving the parametrizations (related to both changing vegetation conditions and to simultaneous active/passive responses) in many of the SMAP baseline algorithms.
Figure 33: Top: Example of ComRAD time series microwave measurements over corn during August 27 – September 1, 2012 at the SMAP incidence angle of 40º. Bottom: L-band brightness temperatures at horizontal (red) and vertical (blue) polarizations along with the scene infrared temperature (green). L-band radar backscatter at HH, VV, HV, and VH polarizations acquired over the same time period as the passive data (image credit: NASA/GSFC, USDA)
SMAPEx (Soil Moisture Active Passive Experiments) campaign -Australia
The SMAPEx field campaigns utilized airborne and ground data to contribute to the development of radar-only and combined radar-radiometer soil moisture retrieval algorithms for SMAP. A key objective is calibration and scaling of an Australian cal/val site for post-launch validation of SMAP products over Australia. The Australian SMAPEx program is led by: Jeffrey Walker of Monash University and Rocco Panciera of the University of Melbourne. 45)
The study site is located in the semi-arid agricultural area near Yanco, in the Murrumbidgee Catchment, south-eastern Australia (Figure 34). This site has been extensively monitored for soil moisture with in-situ stations since 2003, and has been the focus of several airborne field experiments. It is also listed as an official SMAP core calibration/validation site. The SMAPEx campaign, held in this site consist of a series of three field campaigns specifically designed to contribute to the development of radar and radiometer soil moisture retrieval algorithms for the SMAP mission. 46) 47) 48) 49) 50)
The airborne data were collected using a SMAP simulator, which included the PLMR (Polarimetric L-band Multibeam Radiometer) and the PLIS (Polarimetric L-band Imaging Synthetic aperture radar) aboard the same aircraft. The system provided brightness temperature and backscatter coefficient at 1km and 10 m, respectively, from an altitude of 3,000 m. Such data can be used to replicate the SMAP data stream for validating algorithms applicable to the SMAP mission viewing configuration. The main SMAPEx flights included simulation of a time series of SMAP observations by coverage of a 36 km x38 km area (equivalent to a pixel of the SMAP AS grid at S latitude) with a 2-3 days revisit time. Ground sampling of soil moisture, vegetation and roughness data were conducted concurrently with the airborne flights, in order to provide ancillary and validation data. The radiometer and radar data used in this study were from the third SMAPEx campaign (SMAPEx-3, September 5-23, 2011).
Figure 34: Overview of the SMAPEx site and its focus areas, with a size of ~36km×38km, approximating one SMAP radiometer pixel. Inset shows the airborne sensors PLMR and PLIS (image credit: Monash University, University of Melbourne, NASA/JPL)
Methodology and results: Before testing the baseline downscaling algorithm with SMAPEx data, the airborne observations were processed to closely represent the SMAP data stream in terms of spatial resolution, incidence angle, and azimuth direction. Consequently, the PLMR brightness temperatures observed at ±7º, ±21.5º, and ±38.5º incidence angles, and the PLIS backscattering observed at incidence angles ranging from 15º to 45º, were both normalized to the 40º of SMAP. Subsequently, the 10 m resolution PLIS and 1km resolution PLMR were upscaled to 1km and 36 km, respectively, being the SMAP radar and radiometer L1 product resolution. The impact of changes in the azimuthal view angle was also assessed and found to be unimportant at these spatial resolutions.
An example of the resulting radar and radiometer observations is shown in Figure 35. These data were then used to test the baseline downscaling algorithm for SMAP, which is based on the hypothesis of a near linear relationship between radiometer brightness temperature and radar backscatter observations at the same resolution.
Figure 35: Example of the simulated SMAP prototype data from PLMR and PLIS observations, with the incidence angle normalized to 40°: (1) PLMR observed at 1km & at h-pol; (2) PLMR upscaled to 36km & at h-pol; (3) PLIS observed at 10 m & at vv-pol; and (4) PLIS upscaled to 1km & at vv-pol (image credit: Monash University, University of Melbourne, NASA/JPL)
Application of the algorithm involves three main steps:
1) estimation of a parameter β using a time-series of vv-pol radar and h-pol radiometer data at coarse scale
2) estimation of a parameter γ using the same time-series of radar data but at hv-pol and at vv-pol
3) estimation of vegetation conditions by the respective variation of radar backscatter at hv- and vv-pol across the entire area.
Figure 36 shows an example of the downscaling results at 1km resolution obtained from this downscaling algorithm. The RMSE (Root Mean Square Error) of the downscaled brightness temperatures with respect to the PLMR observed brightness temperatures is approximately 8-9 K at 1 km resolution and 2-4 K at 9 km resolution.
Figure 36: Example of the downscaling results at 1km resolution: (1) downscaled brightness temperature at h-pol; (2) PLMR brightness temperature observations at h-pol as the reference; (3) difference between downscaled result and PLMR observations in each pixel (image credit: Monash University, University of Melbourne, NASA/JPL)
This study has tested the baseline active passive downscaling algorithm that has thus far received quite limited evaluation using experimental data. Based on an airborne simulation of the SMAP data stream from the SMAPEx field campaigns, the downscaling algorithm was found to yield an accuracy of downscaled brightness temperature between 8 and 9 K at 1km for h-pol. The accuracy improved to between 2 and 4 K when applied at 9 km resolution. The performance of the algorithm was slightly better at v-pol (improvement of 0.7 K) than at h-pol at 9 km. The results also indicated that the error of downscaled brightness temperature is generally smaller in grassland than in crop areas by about 1 K at 9 km. The accuracy of the downscaled brightness temperature from this study also depends on the robustness of β and γ estimates derived from the SMAPEx data. Based on the downscaled brightness temperature results, it should be possible to achieve a soil moisture product at medium resolution within the specified accuracy requirement.
1) Dara Entekhabi, Eni Njoku, Peggy O’Neill, Kent Kellogg, Jared Entin, “The NASA soil Moisture Active Passive (SMAP) Mission Formulation,” Proceedings of IGARSS (International Geoscience and Remote Sensing Symposium), Vancouver, Canada, July 24-29, 2011
2) Dara Entekhabi, Eni G. Njoku, Peggy E. O’Neill, Kent H. Kellogg, Wade T. Crow, Wendy N. Edelstein, Jared K. Entin, Shawn D. Goodman, Thomas J. Jackson, Joel Johnson, John Kimball, Jeffrey R. Piepmeier, Randal D. Koster, Neil Martin, Kyle C. McDonald, Mahta Moghaddam, Susan Moran, Rolf Reichle, J. C. Shi, Michael W. Spencer, Samuel W. Thurman, Leung Tsang, Jakob Van Zyl, “The Soil Moisture Active Passive (SMAP) Mission,” Proceedings of the IEEE, Vol. 98, No. 5, May 2010, URL: http://secure.ntsg.umt.edu/publications/2010/ENOKCEEGJJKPKMMMMRSSTTV10/Entekha0.pdf
3) Soil Moisture Active/Passive (SMAP) Mission NASA Workshop Report,” URL: http://nasascience.nasa.gov/earth-science/decadal-surveys/Volz1_SMAP_11-20-07.pdf
5) Stephen Volz, “NASA Earth Science New Mission Concepts for the Future,” 5th SORCE Science Meeting, Santa Fee, NM, Feb. 7, 2008, URL: http://lasp.colorado.edu/sorce/news/2008ScienceMeeting/doc/Session4/S4_08_Volz.pdf
6) Dara Entekhabi, Eni Njoku, Peggy O’Neill, Michael Spencer, Tom Jackson, Jared Entin, Eastwood Im, Kent Kellogg, “The Soil Moisture Active/Passive Mission (SMAP),” Proceedings of IGARSS 2008 (IEEE International Geoscience & Remote Sensing Symposium), Boston, MA, USA, July 6-11, 2008
7) Dara Entekhabi, Eni Njoku, Peggy O’Neill, “The Soil Moisture Active and Passive Mission (SMAP): Science and Applications,” Proceedings of the 2009 IEEE Radar Conference, Pasadena, CA, USA, May 4-8, 2009, paper: 3172
8) Peggy O'Neill, “Soil Moisture Active and Passive (SMAP) Mission,” 4th NAFE (National Airborne Field Experiment) Workshop, Melbourne, Australia, Sept. 22-23, 2008, URL: http://www.civenv.unimelb.edu.au/~jwalker/data/nafe/4thWorkshop/Talks/Day1/PO.ppt
9) E. Njoku, P. O'Neill, D. Entekhabi, K. Kellogg, “The Soil Moisture Active and Passive Mission (SMAP),” Earth Observation and Water Cycle Science - Towards a Water Cycle Multi-mission Observation Strategy, ESA/ESRIN, Frascati, Italy, Nov. 18-20, 2009, (ESA SP-674, January 2010)
10) K. Kellogg, E. Njoku, P. O'Neill, D. Entekhabi, “The Soil Moisture Active and Passive Mission (SMAP),” Canadian SMAP Applications and Cal/Val Workshop, Montreal, Canada, October 6-7, 2009, URL: http://smap.jpl.nasa.gov/files/smap2/c1_Njoku_Entekhabi.pdf
11) Stephen Volz, “Soil Moisture Active/Passive (SMAP) Mission,” NASA Workshop Report, Arlington, VA, July 9-10,, 2007, URL: http://science.nasa.gov/media/medialibrary/2010/03/31/Volz1_SMAP_11-20-07.pdf
12) Alexander Eremenko, Jason Kastner, Pamela Hoffman, “SMAP Observatory Configuration, from Concept to Preliminary Design,” Proceedings of the 2010 IEEE Aerospace Conference, Big Sky, MT, USA, March 6-13, 2010
13) Peggy O’Neill, Dara Entekhabi, Eni Njoku, Kent Kellogg, “The NASA Soil Moisture Active Passive (SMAP) Mission: Overview,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium) 2010, Honolulu, HI, USA, July 25-30, 2010
14) J. Eric Belz, Bryan L. Huneycutt, Michael W. Spencer, “A Study of Radio Frequency Interference in the Space-to-Earth Exploration Allocation at L-Band,” 2011 IEEE Aerospace Conference, Big Sky, MT, USA, March 5-12, 2011
15) Lori Keesey, “NASA Builds Sophisticated Earth-Observing Microwave Radiometer,” Space Daily, June 10, 2013, URL: http://www.spacedaily.com/reports/NASA_Builds_Sophisticated_Earth_Observing_Micr_999.html
16) Alexander Eremenko, Jason Kastner, “SMAP Observatory Concept – A Configuration of Compromises,” 2011 IEEE Aerospace Conference, Big Sky, MT, USA, March 5-12, 2011
17) Matthew D. Stegman, “SMAP Antenna Feed Radome: Design, Development, and Test,” 2011 IEEE Aerospace Conference, Big Sky, MT, USA, March 5-12, 2011
18) Dara Entekhabi, Eni Njoku, Peggy O’Neill, Kent Kellogg, Jared Entin, “The NASA Soil MOISTURE Active Passive (SMAP) Mission Formulation,” Proceedings of IGARSS (International Geoscience and Remote Sensing Symposium), Vancouver, Canada, July 24-29, 2011
19) Elizabeth Deems, Chris Swan, Barry Weiss, “End-to-End Data Flow on the Soil Moisture Active Passive (SMAP) mission,” Proceedings of the 2012 IEEE Aerospace Conference, Big Sky, Montana, USA, March 3-10, 2012, URL of presentation: http://trs-new.jpl.nasa.gov/dspace/handle/2014/42583
20) Joshua Buck, George H. Diller, “NASA Selects Launch Services Contract for Three Missions,” NASA, July 16, 2012, URL: http://www.nasa.gov/home/hqnews/2012/jul/HQ_C12-028_RSLP-19_Launch_Services.html
21) Michael Spencer, Kevin Wheeler, Samuel Chan, Jeffrey Piepmeier, Derek Hudson, James Medeiros, “The Planned Soi l Moisture Active Passive (SMAP) Mission L-Band Radar/Radiometer Instrument,” Proceedings of IGARSS (International Geoscience and Remote Sensing Symposium), Vancouver, Canada, July 24-29, 2011
22) Michael Spencer, Kevin Wheeler, Chris White, Richard West, Jeffrey Piepmeier, Derek Hudson, James Medeiros, “The Soil Moisture Active Passive (SMAP) Mission L-Band Radar/Radiometer Instrument,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium) 2010, Honolulu, HI, USA, July 25-30, 2010
23) Michael Spencer, Samuel Chan, Louise Veilleux, Kevin Wheeler, “The Soil Moisture Active/Passive (SMAP) Mission Radar: a Novel Conically Scanning SAR,” Proceedings of the 2009 IEEE Radar Conference, Pasadena, CA, USA, May 4-8, 2009, paper: 3189
24) E. Njoku, K. Kellogg, D. Entekhabi, P. O’Neill, T. Jackson, J. Entin, “Soil Moisture Active Passive Mission SMAP - Algorithm & Cal/Val Activities and Synergies with SMOS and Other L-band Missions,” SMOS Science Workshop, September 27-29, 2011, Arles, France, URL: http://earth.eo.esa.int/workshops/smos_science_workshop/SESSION_5_C_Active_Passive.pdf
25) A. J. Mastropietro, Eug Kwack, Rebecca Mikhaylov, Michael Spencer, Pamela Hoffman, Douglas Dawson, Jeff Piepmeier, Derek Hudson, James Medeiros, “Preliminary Evaluation of Passive Thermal Control for the Soil Moisture Active and Passive (SMAP) Radiometer,” 41st ICES (International Conference on Environmental Systems), Portland, OR, USA, July 17-21, 2011, URL: http://smap.jpl.nasa.gov/files/publications/ICES_2011_Mastropietro.pdf
26) “Northrop Grumman's Astro Aerospace Unit Completes Critical Design Audit of Reflector Boom Assembly for SMAP Mission,” Astro Aerospace, January 9, 2012, URL: http://www.irconnect.com/noc/press/pages/news_releases.html?d=242340
27) Kent Kellogg, Sam Thurman, Wendy Edelstein, Michael Spencer, Gun-Shing Chen, Mark Underwood, Eni Njoku, Shawn Goodman, Benhan Jai, “NASA’s Soil Moisture Active Passive (SMAP) Observatory,” Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA, March 2-9, 2013
28) Samuel Chan, Mark Fischman, Michael Spencer, “RFI Mitigation and Detection for the SMAP Radar,” Proceedings of IGARSS (International Geoscience and Remote Sensing Symposium), Vancouver, Canada, July 24-29, 2011
29) Michael Spencer, Samuel Chan, Eric Belz, Jeffrey Piepmeier, Priscilla Mohammed, Edward Kim, “Radio Frequency Interference Mitigation for the Planned SMAP Radar and Radiometer,” Proceedings of IGARSS (International Geoscience and Remote Sensing Symposium), Vancouver, Canada, July 24-29, 2011
30) T. J. Jackson, M. Cosh, W. T. Crow, A. Colliander, J. P. Walker, “In Situ Validation of the Soil Moisture Active Passive (SMAP) Satellite Mission,” ISPRE-34 (International Symposium on Remote sensing of Environment), Sidney, Australia, April 10-15, 2011, URL: http://www.isprs.org/proceedings/2011/ISRSE-34/211104015Final00133.pdf
31) Charles Le, Michael W. Spencer, Louise Veilleux, Samuel Chan, Yutao He, Jason Zheng, Kayla Nguyen, “SMAP’s Radar OBP Algorithm Development,” Proceedings of the 2009 IEEE Radar Conference, Pasadena, CA, USA, May 4-8, 2009, paper: 3280
32) Sidharth Misra, Priscilla N. Mohammed, Baris Güner, Christopher S. Ruf, Jeffrey R. Piepmeier, Joel T. Johnson, “Microwave Radiometer Radio-Frequency Interference Detection Algorithms: A Comparative Study,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, No 11, Nov. 2009, pp.3742-3754, URL: http://ktb.engin.umich.edu/RSG/pubs_files/TGRS-2009-47-11_Misra_et_al_RFI_Algo_Comparison.pdf
33) Damon Bradley, Cliff Brambora, Ali Feizi, Rafael Garcia, Lynn Miles, Priscilla Mohammed, Jinzheng Peng, Jeff Piepmeier, Kamdin Shakoorzadeh, Mark Wong, “Preliminary results from the Soil Moisture Active/Passive (SMAP) Radiometer Digital Electronics Engineering Test Unit (ETU),” Proceedings of IGARSS (International Geoscience and Remote Sensing Symposium), Munich, Germany, July 22-27, 2012
34) Joshua S. Choi, Antonio L. Sanders, “Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission,” Proceedings of SpaceOps 2012, The 12th International Conference on Space Operations, Stockholm, Sweden, June 11-15, 2012, URL: http://www.google.de/url?sa=t&rct=j&q=end-to-end%20data%20flow%20on%20the%20soil%20moisture%20active%20sqi=2&ved=0CHQ8-Paper-004.pdf&ei=Y7idUZCBJcTOtQbF9IGICQ&usg=AFQjCNHsLiB1PONQQ7DN7_c12pW5a
35) Molly E. Brown, Vanessa Escobar, Susan Moran, Dara Entekhabi, Peggy E. O’Neill, Eni G. Njoku, Brad Doorn, Jared K. Entin, “NASA's Soil Moisture Active Passive (SMAP) Mission and Opportunities for Applications Users,” BAMS (Bulletin of the American Meteorological Society), Vol. 94, Issue 8, August 2013, pp. 1125-1128, URL: http://journals.ametsoc.org/doi/pdf/10.1175/BAMS-D-11-00049.1
36) Rolf Reichle, Gabrielle De Lannoy, Wade Crow, John Kimball, Randal Koster, Qing Liu, Clara Draper, “Using SMOS Observations for Science Development of the SMAP Level 4 Surface and Root Zone Soil Moisture Algorithm,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium), Melbourne, Australia, July 21-26, 2013
37) M. Moghaddam, M. Burgin, A. Castillo, D. Entekhabi, Y. Goykhman, A. Kakhbod, K. Li, M. Liu, A. Nayyar, A. Silva, D. Teneketzis, Q. Wang, X. Wu, “Soil Moisture Sensing Controller And optimal Estimator (SoilSCAPE): First Deployment of the Wireless Sensor Network and Latest Progress on Soil Moisture Satellite Retrieval Validation Strategies,” ESTF 2011 (Earth Science Technology Forum 2011), Pasadena, CA, USA, June 21-23, 2011, URL: http://esto.nasa.gov/conferences/estf2011/papers/Moghaddam_ESTF2011.pdf; URL of presentation: http://esto.nasa.gov/conferences/estf2011/presentations/Moghaddam_ESTF2011.pdf
39) “SMAP Validation Experiment 2012 (SMAPVEX12)June 6 - July 19, 2012,Winnipeg, Canada,” NASA/JPL, URL: http://smap.jpl.nasa.gov/science/Validation/Campaigns/SMAPVEX12/
41) “SMAPVEX12 -NASA & AAFC Validation Experiment of the Soil Moisture Active Passive (SMAP) Satellite,” Grant Wiseman, Sept. 24, 2012, URL: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=7&cad=rja&ved=0CF4QFjAG&url=http%386Up-7CcGK4AT-goH4CA&usg=AFQjCNEFmo7hQCs84oagTTZSD1zhw9XXYg
43) T. J. Jackson, H. McNairn, G. Wiseman, A. Colliander, A. Berg, P. Bullock, R. Magagi, M. Moghaddam, S. Kim, M. Cosh, E. Njoku, S. Belair, “SMAP Validation Experiment 2012 (SMAPVEX12): Overview and Outlook,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium), Melbourne, Australia, July 21-26, 2013
44) P. O’Neill, M. Kurum, A. Joseph, J. Fuchs, P. Young, M. Cosh, R. Lang, “L-band active/passive time series measurements over a growing season using the ComRAD ground-based SMAP simulator,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium), Melbourne, Australia, July 21-26, 2013
45) “Soil Moisture Active and Passive Experiments (SMAPEx), Australian Soil Moisture Field Campaigns,” URL: http://smap.jpl.nasa.gov/science/Validation/Campaigns/SMAPEx/
46) R. Panciera, J. P. Walker, T. J. Jackson, D. A. Gray, M.A. Tanase, D. Ryu, A. Monerris, H. Yardley, C. Rüdiger, N. Wu, Y. Gao, J. M. Hacker, “The Soil Moisture Active Passive Experiments (SMAPEx): Towards Soil Moisture Retrieval from the SMAP Mission,” IEEE Transaction on Geoscience and Remote Sensing, Vol. PP, Issue 99, 13 March 2013, DOI: 0.1109/TGRS.2013.2241774
47) J. P. Walker, R. Panciera, D. Ryu, “SMAPEx: Soilmoisture active passive remote sensing experiment for SMAP algorithm development,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium) 2010, Honolulu, HI, USA, July 25-30, 2010, URL: http://www.google.de/url?S10-2.pdf&ei=5AQ7Uo6XHcmrhQev-YHgCQ&usg=AFQjCNGRCH_SfAUnAz8VJ9XdKnUQMFh8Rg
48) X. Wu, J. P. Walker, N.N. Das, R. Panciera,C. Rüdiger, “Towards a medium resolution brightness temperature product from active and passive microwave observations,” Proceedings of IGARSS (IEEE International Geoscience and Remote Sensing Symposium), Melbourne, Australia, July 21-26, 2013
50) J. P. Walker, X. Wu, Y. Gao, A. Monerris, R. Panciera, T. Jackson, P. O’Neil, N. Das, D. Gray, D. Ryu, “The Soil Moisture Active Passive Experiments: SMAPEx,” Monash University, URL: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&cad=rja&ved=0CE4QFjAE&url=http%3A%2Q7Uev-YHgCQ&usg=AFQjCNGXTsmt8LLfaOmlAx51tAtEhghZPQ
The information compiled and edited in this article was provided by Herbert J. Kramer from his documentation of: ”Observation of the Earth and Its Environment: Survey of Missions and Sensors” (Springer Verlag) as well as many other sources after the publication of the 4th edition in 2002. - Comments and corrections to this article are always welcome for further updates.