Tandem-L Interferometric Radar Mission
Tandem-L is a DLR proposal for a highly innovative radar satellite mission to monitor dynamic processes on the Earth's surface with hitherto unknown quality and resolution. Important mission goals are the global measurement of forest biomass and its temporal variation for a better understanding of the carbon cycle, the systematic monitoring of deformations of the Earth's surface on a millimeter scale for the investigation of earthquakes and risk analysis, the quantification of glacier motion and melting processes in the polar regions, the fine scale measurement of variations in the near-surface soil moisture as well as observations of the dynamics of ocean surfaces and ice drift.
The Tandem-L mission concept builds upon the success of TanDEM-X and utilizes two formation-flying radar satellites operating in L-band (Figure 1). The use of the SAR (Synthitic Aperture Radar) technique enables the systematic acquisition of high-resolution radar images independent of weather and daylight and constitutes therefore an ideal basis for the continuous monitoring of dynamic processes on Earth's surface. Furthermore, the wavelength of Tandem-L (23.6 cm) optimally fulfils the requirements for a tomographic imaging of the three-dimensional structure of vegetation and ice bodies, as well as for a systematic measurement of wide-area deformations with millimeter precision. To ensure regular observations with short repeat intervals, Tandem-L will employ cutting-edge radar technology based on the latest digital beamforming techniques which allow for the mapping of ultra-wide image swaths with high azimuth resolution. The goal of Tandem-L is to interferometrically map large parts of the Earth's landmass up to two times per week. Beyond the primary mission objectives, the data set recorded with Tandem-L represents a tremendous opportunity for the development of novel scientific applications and commercial services. 1) 2) 3)
Figure 1: Artist's rendition of the Tandem-L satellites (image credit: DLR)
The feasibility of Tandem-L has been analyzed and confirmed in the scope of a phase A study, which has been conducted in close cooperation between the DLR (German Aerospace Center) and the German space industry.
User and mission requirements: The Tandem-L user requirements have been defined and elaborated in close cooperation with a large international science community. Important mission objectives are:
- Global measurement and monitoring of 3-D forest structure and biomass for a better understanding of ecosystem dynamics and the carbon cycle.
- Systematic recording of small and large scale deformations of the Earth's surface with millimeter accuracy for earthquake, volcano and landslides research as well as risk analysis and mitigation.
- Quantification of glacier movements, 3-D ice structure and melting processes in the polar regions for improved predictions of future sea level rise.
- Fine scale measurements of soil moisture and its variations close to the surface for a better understanding of the water cycle and its dynamics.
- Systematic observation of coastal zones and sea ice for environmental monitoring and ship routing.
- Monitoring of agricultural fields for crop yield forecasts, as well as the generation of highly accurate global digital terrain and surface models which form the basis for a wide range of further remote sensing applications.
These objectives address subjects of great societal importance and encompass a broad science and application spectrum that ranges from basic Earth system research to environmental monitoring and disaster mitigation. Tandem-L will moreover contribute to the measurement of 7 essential climate variables (Figure 2). The unique Tandem-L observations will therefore provide also important and currently missing information about the extent and influence of climate change, based on which improved scientific forecasts and socio-political decisions can be made.
Figure 2: Examples of dynamic processes within the bio-, geo-, cryo- and hydrosphere and the observation intervals required for their systematic monitoring. The processes denoted by a star represent essential climate variables (image credit: DLR)
Based on the user requirements, a set of 26 preliminary geophysical products have been defined during Phase A and summarized within the Mission Requirements Document. Table 1 provides an excerpt of the most important products and their main parameters. Most of the products are unique in terms of their quality, quantity, resolution and coverage and rely on special data acquisition modes such as single-pass polarimetric SAR interferometry (PolInSAR) and multi-baseline coherence tomography. Implicit to most products is moreover the demand for high-resolution SAR acquisitions with short repeat intervals. Due to the limitations of current spaceborne SAR systems, such radar data can only be provided by a new generation of multi-channel SAR instruments.
Table 1: Main geophysical products of Tandem-L
To satisfy the challenging user and mission requirements, a dedicated data acquisition concept has been developed which consists of two basic measurement modes:
1) The 3-D structure mode employs fully-polarimetric single-pass SAR interferometry to acquire structural parameters of semitransparent volume scatterers. By combining multiple interferometric acquisitions with varying cross-track baselines ( Figure 3), it becomes moreover possible to derive tomographic images with fine vertical and horizontal resolutions as required for the accurate measurement of 3-D forest and ice structure as well as for the generation of digital terrain and surface models.
2) The deformation mode employs repeat-pass interferometry to measure small displacements on the Earth surface with accuracies down to centimeters or even millimeters. To minimize errors from atmospheric disturbances and temporal decorrelation, special attention has been paid to maximize the number of image acquisitions. For this, a special SAR imaging mode has been developed which allows for the systematic mapping of 350 km wide swaths with an azimuth resolution of 7 m.
Figure 3: Left: The formation flight of the two Tandem-L satellites exploits the naturally occurring differential secular variations of the right ascension of the ascending nodes in response to slightly different inclinations. Right: Evolution of the equatorial baseline over the course of one year (image credit: DLR)
The Tandem-L satellites will fly on a sun-synchronous dawn-dusk orbit with a repeat cycle of 16 days (Table 2). During each repeat cycle, up to four global data acquisitions can be performed from different viewing directions in single- and dual-pol mode. Deformation measurements are further supported by flying the master satellite in a closely controlled orbital tube with a radius of 250 m (3σ). To obtain the required cross-track baselines for single-pass interferometry and tomography, the inclination of the slave satellite will be periodically adjusted. This results in a natural drift of the ascending node and allows for large periodic baseline variations with a minimum amount of fuel. 4)
A challenge in Tandem-L is the large amount of data that has to be transferred to the ground. For this, a high- performance Ka-band downlink with a net data rate of up to 2.6 Gbit/s will be employed. Together with an appropriate ground station network, 8 Terabyte can be downlinked every day. To show the mission feasibility, a first data acquisition plan has been developed and Figure 4 shows how the available data volume is distributed among the different applications. 5)
The systematic observation of dynamic processes will be further supported by the long mission lifetime of 10 years, which may even be extended as all consumables are planned for 12 years. At the end of the mission, the satellites will be deorbited via dedicated thrusters.
Table 2: Key parameters and performance figures of the Tandem-L satellites
Figure 4: Daily data volume acquired for the different application areas over one year. Note that most data acquisitions serve not only one but multiple applications (image credit: DLR)
The phase A study of Tandem-L has confirmed both the feasibility and the unique opportunities of this highly innovative SAR mission. In the summer of 2016, Tandem-L is proceeding to Phase B1 which will last until the mid of 2017.
Greater insight into climate research with the Tandem-L satellite mission 6)
The Earth system is multifaceted, complex and in constant motion. Our home planet is ever changing – the ground rises and falls, glaciers calve into the ocean, and fires destroy forest areas. "But alterations to the environment are not only natural – today, human intrusion is playing a major role too – from deforestation and construction activities through to the impact we have on the climate," says Alberto Moreira, Director of the Microwaves and Radar Institute of the German Aerospace Center (DLR) and Principal Investigator of the Helmholtz Alliance ‘Remote Sensing and Earth System Dynamics'. Understanding these changes is an essential part of climate research and is important for enabling sustainable, positive development in the long term. Since the 1990s, Moreira has been working on radar technologies that enable Earth's dynamics to be recorded and depicted globally. The Tandem-L mission will bring science one step closer to achieving this goal.
Earth observation using radar satellites offers unique insights into our planet's dynamic processes. Radar satellites deliver reliable data regardless of weather and time of day, and enable the use of highly precise interferometric and even tomographic measurement techniques. A recent example is the interferometric imaging of Earth provided by the twin satellites TerraSAR-X and TanDEM-X, which since 2010 have been measuring the Earth's surface in close formation flight at a few hundred meters apart. Numerous fields within climate and environmental research are benefiting from the highly precise, three-dimensional images of our planet. Although more than 1000 scientists across the globe are working with the elevation model of Earth, it quickly became clear that TanDEM-X is merely scratching the surface – quite literally – of what such a satellite mission is capable of.
Numerous processes important to environmental research are occurring within the three-dimensional structure of forest ecosystems. In addition, many of the changes take place within a relatively short period of time, which is why it is necessary to continuously monitor their status. Consequently, a solution was needed that could not only penetrate deeper into the vegetation layer but also enable regular imaging at short time intervals. "We carried out the first experiments in X-band and L-band using our airborne radar system in the early 1990s, and realized how accurately we could determine the Earth's topography with radar. And so, the idea of TerraSAR-X and TanDEM-X was conceived. When TanDEM-X was officially approved in 2006, the question of how it could be developed further immediately arose at the Institute. My answer to this – even back then – was very clear: the next project will be Tandem-L," recalls Moreira.
Table 3: Listening to Earth's Heartbeat — Greater insight into climate research with the Tandem-L satellite mission (Ref. 6)
Figure 5: Overview of DLR SAR mission scenario (image credit: DLR)
Figure 6: City forest in Traunstein in Upper Bavaria: The forest is thoroughly mapped and has been used as a stable reference area for the development of radar remote sensing technology for more than 10 years. At the time of the flight in late June 2016, a large part of the fields was overgrown. The various crops and stages of growth result in differently colored polarimetric signatures (image credit: DLR)
A spacecraft description will be provided when available.
Launch: According to current planning, and subject to timely financial approval, the Tandem-L satellites could be launched at the end of 2022.
Orbit: Sun-synchronous dawn/dusk orbit, altitude = 745 km, inclination = 98.4º, revisit time = 16 days.
Sensor complement (L-SAR)
A particular challenge of the Tandem-L mission is the development of two extremely capable but at the same time also cost-efficient SAR instruments that shall map a 350 km wide swath in single/dual pol mode and a 175 km wide swath in quad-pol mode, both with an azimuth resolution of 7 m and a range bandwidth of up to 84 MHz (Table 4). Moreover, the noise equivalent sigma zero (NESZ) shall be better than -25 dB and the ASR (Ambiguity-to-Signal-Ratio) shall be better than -25 dB in single/dual pol mode (-22 dB in quad-pol mode). These requirements exceed by far the capabilities of current spaceborne SAR systems. Therefore, a new instrument concept has been developed that combines a large unfurlable mesh reflector with a digital feed that is composed of 32 patch elements in elevation and 6 patch elements in azimuth. The 6 azimuth patches are connected to a single T/R module via fixed power dividers to obtain, for each elevation direction, an optimized azimuth antenna pattern. The outputs of the T/R modules are then individually digitized and combined in real-time to form multiple elevation beams that follow the simultaneously arriving radar echoes from subsequent transmit pulses. By this, it becomes possible to map a very wide swath with high azimuth resolution.
The emergence of blind ranges is moreover avoided by a systematic variation of the pulse repetition interval . 7) Figure 7 demonstrates that such a staggered SAR mode provides an excellent performance that can meet the demanding science requirements for both the fully polarimetric 3-D structure mode and the ultra-wide swath deformation mode. 8)
Table 4: Key parameters of the L-SAR instrument
Figure 7: Top row left:AASR (Azimuth Ambiguity-to-Signal Ratio) for single-pol; right: quad-pol mode. Middle row left: RASR (Range Ambiguity-to-Signal Ratio) for single-pol; right: quad-pol mode. Bottom row left: NESZ (Noise Equivalent Sigma Zero) for single-pol; right: quad-pol mode (image credit: DLR)
Some background on SAR technology:
As the staggered SAR mode is associated with a notable oversampling of the SAR signal, a new onboard data reduction technique will be employed to keep the data rate even below that of a conventional SAR system. This will maximize the science output for a given downlink budget. 9)
Conventional SAR systems are limited, in that a wide swath can only be achieved at the expense of a degraded azimuth resolution. This limitation can be overcome by using systems with multiple receive apertures, displaced in along-track, but a very long antenna is required to map a wide swath. If a relatively short antenna with a single aperture in along-track is available, it is still possible to map a wide area: Multiple swaths can be, in fact, simultaneously imaged using digital beamforming in elevation, but "blind ranges" are present between adjacent swaths, as the radar cannot receive while it is transmitting. Staggered SAR overcomes the problem of blind ranges by continuously varying the PRI (Pulse Repetition Interval). If the sequence of PRIs is properly chosen, the samples, missing because the radar is transmitting, are distributed across the swath and along azimuth, such that they can be then recovered by interpolation of neighboring azimuth samples. This concept therefore allows high-resolution imaging of a wide continuous swath without the need for a long antenna with multiple apertures. In order to provide satisfactory suppression of azimuth ambiguities, some azimuth oversampling is required. This may cause (1) increased range ambiguities, which can be suppressed by jointly processing the data acquired by the available multiple elevation beams, and (2) an increased data volume, which can be reduced by on-board Doppler filtering and decimation.
In conventional stripmap SAR, the swath width constrains the PRI (Pulse Repetition Interval): To control range ambiguities, the PRI must be larger than the time it takes to collect returns from the entire illuminated swath. On the other hand, to avoid significant azimuth ambiguity levels, a large PRI, or equivalently a low PRF (Pulse Repetition Frequency), implies the adoption of a small Doppler bandwidth and limits the achievable azimuth resolution. A wide swath can be also mapped using ScanSAR or TOPS (Terrain Observation with Progressive Scan), but the azimuth resolution is still impaired.
To overcome these limitations, new radar techniques have been developed, which allow for the acquisition of spaceborne high-resolution SAR images without the classical swath limitation imposed by range and azimuth ambiguities .10) These techniques are mainly based on DBF (Digital Beamforming) and multiple aperture signal recording. DBF on receive is used to steer in real-time a narrow beam towards the direction of arrival of the radar echo from the ground, exploiting the one-to-one relationship between the radar pulse travel time and its direction of arrival, this is also referred to as SCORE (Scan-On-Receive) or Sweep-SAR. A large receiving antenna can hence be used to improve the sensitivity without narrowing the swath width. As the unambiguous swath width is limited by the antenna length, a long antenna is deployed to map a wide swath. Moreover, to improve the azimuth resolution, the receive antenna is divided into multiple sub-apertures, mutually displaced in the along-track direction and connected to individual receive channels. By this, multiple samples of the synthetic aperture can be acquired for each transmitted pulse. The coherent combination of all signals in a dedicated multichannel processor enables the generation of a high-resolution wide-swath SAR image. The need for a very long antenna represents the main limitation of the mentioned system: A 40 m antenna is, in fact, required to map a 350 km swath width on ground in stripmap imaging mode.
In order to keep the antenna length down, several new instrument architectures and modes have been proposed. 11) One example is the combination of displaced phase centers in azimuth with ScanSAR or TOPS mode (Figure 8 (a)). As in classical ScanSAR, azimuth bursts are used to map several swaths. The associated resolution loss from sharing the synthetic aperture among different swaths is compensated by illuminating a wider Doppler spectrum and reducing the PRF by collecting radar echoes with multiple displaced azimuth apertures. A possible drawback of multichannel ScanSAR or TOPS approaches is the rather high Doppler centroid for some of the imaged targets, in case high resolution is desired. Moreover, high squint angles may also challenge co-registration in interferometric applications. Besides multichannel ScanSAR, of great interest are concepts based on simultaneous recording of echoes of different pulses, transmitted by a wide beam illuminator and coming from different elevation directions. This enables an increase of the coverage area without the necessity to either lengthen the antenna or to employ burst modes.
Figure 8 (b) provides an illustration, where three narrow receive beams follow the echoes from three simultaneously mapped image swaths that are illuminated by a broad transmit beam. A sufficiently high antenna is needed to separate the echoes from the different swaths by digital beamforming on receive, while a wide beam can either be accomplished by a separate small transmit antenna or a combined transmit-receive antenna together with tapering, spectral diversity on transmission or sequences of subpulses. An interesting alternative to a planar antenna is a reflector, fed by a multichannel array, as illustrated in Figure 8 (c). A parabolic reflector focuses an arriving plane wave on one or a small subset of feed elements. As the swath echoes arrive as plane waves from increasing look angles, one needs hence to only read out one feed element after the other to steer a high-gain beam in concert with the arriving echoes.
A drawback of the multi-beam mode is the presence of blind ranges across the swath, as the radar cannot receive while it is transmitting. The Staggered SAR concept (Figure 8 (d)) overcomes this drawback by continuously varying the PRI in a cyclic manner, so allowing the imaging of a wide continuous swath without the need for a long antenna with multiple apertures (Ref. 7). 12)
Figure 8: Advanced concepts for high-resolution wide-swath (HRWS) imaging. (a) ScanSAR with multiple azimuth channels. (b) Single-channel SAR with multiple elevation beams. (c) Digital beamforming with reflector antenna. (d) Staggered-SAR (image credit: DLR)
The system architecture is based on a large parabolic reflector antenna that is illuminated by a digital feed with multiple elevation channels (Figure 9). As each feed element is associated with a different secondary beam, it becomes possible to image a wide swath with high Rx gain by a time-variant combination of the feed signals in synchrony with the expected direction of arrival of the desired radar echo. The imaging capacity is further increased by using not only one but multiple elevation beams that map multiple swaths at the same time. As these swaths are separated by blind ranges, several strategies and modes have been proposed to avoid such gaps in the SAR image. Out of these modes, Tandem-L will employ a technique where the pulse repetition interval is rapidly changed from pulse to pulse. This technique, now denoted as staggered SAR, has been further analyzed and elaborated in detail in Ref. 12). In combination with an optimized Tandem-L reflector and feed system it becomes then possible to map a 350 km wide swath with an azimuth resolution of 7 m, thereby significantly improving the imaging capacity if compared to state-of-the-art L-band SAR systems like ALOS-2 or even the C-band satellite constellation Sentinel-1A and 1B. 13)
While staggered SAR enables the acquisition of an ultra-wide image swath with high resolution, it requires also a notable oversampling in azimuth. Such an increase of the average PRF (Pulse Repetition Frequency) is mandatory to avoid a rise of azimuth ambiguities caused by missing samples along the synthetic aperture. 14) The high PRF will, however, also increase the susceptibility to range ambiguities. Range ambiguity suppression is further challenged by the required wide swath illumination, which causes multiple mutually ambiguous radar echoes to arrive at the same time from different elevation angles but with comparable magnitudes. This poses high demands on the multichannel receiver system which has to steer multiple elevation beams in real time towards the radar echoes' expected directions of arrival. The shape of each of these receiver beams must be adjusted to maximize for each instant of time the antenna gain in the direction of the desired radar echo, while minimizing the gain towards the arrival angles of the interfering range ambiguous radar echoes.
Figure 9: Reflector SAR with multiple elevation beams. Digital beamforming on receive plays a crucial role for the reliable separation of the simultaneously arriving radar echoes from range-ambiguous positions (image credit: DLR)
Several beamforming algorithms have been developed to address this challenge, but their performance depends crucially on the accurate knowledge of the amplitude and phase of the secondary beam patterns associated with individual feed array elements. 15) 16) While this knowledge is less important for a planar array, where the element patterns are typically pretty similar and the overall radiation performance is primarily determined by the array's geometry and excitation, it becomes mandatory for reflector SAR systems, where each feed has its own element pattern that points its secondary beam to a different direction. As it is impossible to measure the antenna patterns for a SAR system like Tandem-L with sufficient accuracy before launch on the ground, one needs an alternative strategy to obtain the required far-field pattern information. One established approach is the use of dedicated calibration targets like corner reflectors or transponders. 17)
A very large number of calibration targets would, however, be required to meet the accuracy requirements as the antenna patterns associated with individual feed elements cover different areas and are moreover characterized by a high degree of spatial variation, which is further complicated by the fact that the patterns are typically non-separable in elevation and azimuth. Another approach, which was successfully applied for TerraSAR-X [18)], is based on the use of an appropriate antenna model, but the requirements regarding the precise knowledge of the deployed reflector's attitude and shape are rather high to meet the demanding performance requirements. 19)
In-Orbit Multichannel Antenna Pattern Calibration:
As a complement to the conventional antenna pattern estimation and modeling techniques discussed before, we propose here a new multichannel calibration approach that enables highly accurate in-orbit measurements of the amplitude and phase differences between the secondary far-field patterns of the feed elements/channels. The proposed technique is capable of providing this information in two dimensions without the need of dedicated calibration targets and/or a sophisticated antenna model. The core concept is to operate the SAR system over an appropriately chosen natural scene with known topography in a series of dedicated calibration modes, which are described in more detail in the following subsections. The basic idea of this technique has already been suggested in the context of the cross-elevation beam range ambiguity suppression technique CEBRAS, 20) and is here further elaborated in view of the demanding requirements for Tandem-L.
LPAC (Low PRF Antenna Calibration): As a first calibration mode, we consider an operation with a very low pulse repetition frequency (PRF), so that only a single radar echo arrives at the radar satellite at any time. A wide swath is illuminated, and all elevation channels simultaneously record and digitize their received signals independently from each other without applying any on-board beamforming. As the total data rate of this transparency mode is likely to exceed the capacity of the input channel to the on-board memory, it is suggested to reduce the RF bandwidth in this mode. Tandem-L is, for example, capable to handle in its nominal staggered SAR mode the radar signals from five elevation beams, each recording a radar echo with an RF bandwidth of 84 MHz. A reduction to, e.g., 10 MHz allows therefore the simultaneous recording of all 35 feed signals without increasing the internal data rate.
If necessary, the full bandwidth can then be covered by subsequent measurements where the range center frequency is appropriately varied from data take to data take. The multichannel radar data acquired in this dedicated antenna calibration mode are then transmitted to the ground, where they are further evaluated.
The evaluation starts with a range compression of the signals from the individual elevation channels. Assuming a calibration scene that is sufficiently flat and free of layover, there exists thereafter a one-to-one relation between the instant of time in the range-compressed data and the elevation angle from which the radar echoes are arriving. This relationship is easily derived from the imaging geometry and the known topography of the calibration scene. (Note: A coarse DEM with a resolution in the order of 100 m is considered as sufficient.)
However, as the low PRF of the LPAC mode does not allow for azimuth focusing, radar echoes arriving at the same time from multiple azimuth angles cannot be separated from each other. A comparison of the recorded feed signals in amplitude and phase yields therefore an estimate of the relative antenna patterns integrated over azimuth.
The performance simulations (below) reveal that this information is nevertheless well suited to derive beamforming coefficients for highly efficient range ambiguity suppression without detailed a priori pattern knowledge.
Figure 10: Illustration of the basic steps of the proposed multichannel antenna calibration. The recorded radar data of each feed are first individually range compressed (RC) and bandpass-filtered in the Doppler domain (DF). In a second step, the feed signals are mutually compared and relative amplitude and phase patterns are computed as a function of range and Doppler. In a third step, the relative amplitude and phase patterns are transformed from the range-Doppler coordinates to the corresponding elevation and azimuth angles. This transformation requires knowledge of the satellite's orbit and attitude in combination with an appropriate digital elevation model. Finally, the relative pattern information is used to calculate a calibrated and optimized set of digital beamforming coefficients that are uploaded to the satellite (image credit: DLR)
HPAC (High PRF Antenna Calibration): While the LPAC mode outlined in the previous section is well suited to derive appropriate weights for elevation beamforming, a more detailed knowledge of the relative azimuth antenna patterns may be of interest to further improve the SAR imaging performance and to support the end-to-end system calibration.
For this, we suggest to acquire SAR data over an appropriate scene in the high PRF antenna calibration (HPAC) mode. In contrast to the LPAC mode, only a narrow swath is illuminated by transmitting with one or a small subset of the available feed elements. The reduced swath illumination provides an efficient means to suppress range ambiguities as they are, in contrast to the nominal wide-swath staggered SAR mode, already suppressed by the Tx pattern.
The calibration data for the full swath extension can then be recovered by combining the data from a series of measurements where different subswaths are illuminated.
In comparison to the staggered SAR mode, the use of a constant PRF avoids, moreover, the loss of azimuth samples and enables therefore an excellent suppression of the azimuth ambiguities. Stated differently, a reduced PRF could be used to achieve the same azimuth ambiguity-to-signal ratio.
The HPAC data are then transmitted to the ground and further analyzed as illustrated in Figure 10. The evaluation starts again with a range compression of each individual feed signal. In contrast to the LPAC mode, the range-compressed data are then transformed to the range-Doppler domain (or decomposed into multiple azimuth looks) which provides the basis for a two-dimensional analysis of the antenna patterns (Ref. 20).
Performance Simulation: This section shows an example of how the multichannel radar data acquired in the LPAC mode can be used to improve the elevation beamforming in a reflector SAR system like Tandem-L. For this purpose, we simulate a time series of multichannel radar data, as they would be recorded by a dedicated LPAC data take. To simplify the calculations, we model the backscatter by independent and identically distributed complex Gaussian noise, but a more refined simulation could also use real radar data to better account for inhomogeneities in the backscatter statistics. After range compression and appropriate consideration of the radar imaging geometry [Note: This includes the incorporation of the known scene topography. The simulation in this paper assumes the same geometry and spherical Earth model with flat topography as in Ref. 20).], the simulated multichannel radar data are obtained for each radar channel and range line by projecting the antenna-weighted backscatter along iso-range contours (cf. green line in the upper plot of Figure 11, which shows the 2-D antenna pattern of an optimum MVDR beamformer steered towards this range). To provide a realistic weighting, we use here the results from GRASP computations that predict, for each feed element, the two-dimensional complex antenna pattern for the nominal Tandem-L antenna geometry.
Figure 11: Simulated Tandem-L pattern for an optimum MVDR (Minimum Variance Distortionless Response) beamformer that is steered in elevation to a ground range of 460 km assuming full knowledge of each complex feed pattern. The top figure shows the 2-D twoway pattern which is projected on a spherical Earth, while the bottom shows 1-D pattern cuts for fixed range bins corresponding to the swath echo and range ambiguities for PRIs of 130, 140 and 150 µs. The desired swath echo is shown in green, while the near and far range ambiguities are shown in orange and magenta, respectively (image credit: DLR) .
In summary, a set of new antenna calibration modes and techniques is introduced for multichannel reflector SAR systems. The proposed modes are well suited to acquire information about the relative amplitude and phase of the secondary far-field patterns associated with pairs of feed elements/channels. This mutual pattern information can then be used to improve the performance of advanced realtime beamformers that maximize their gain towards the direction of arrival of the desired radar echo and suppress, at the same time, range ambiguities arriving from different directions. Such beamformers are of great benefit for advanced SAR imaging modes like staggered SAR, which employs multiple elevation beams to map a wide image swath with high resolution.
As the proposed technique does not depend on dedicated calibration targets, it can be used anywhere in the orbit, provided the scene has a known and sufficiently flat topography. To simplify the derivation of optimized beams in the LPAC mode, it is moreover advisable to use a scene with homogeneous and sufficiently strong backscatter as, e.g., provided by rainforests. The 2-D calibration with the HPAC mode may, on the other hand, also benefit from inhomogeneous backscatter to obtain further information about low sidelobes. In this context, permanent scatterers may offer a promising potential for advanced multichannel SAR calibration.
The proposed LPAC mode can not only provide optimized beamforming weights to suppress range ambiguities, but also offers a new opportunity to improve nadir suppression. This prospect is of high interest for advanced imaging modes like staggered SAR, which is susceptible to nadir echoes. To this aim, the LPAC data recording must include the nadir return, which is treated as an additional directional interference. This interference is then added while deriving the beamforming weights, either for all elevation beams, or at least those which may be superimposed by nadir echoes, taking into account variations in satellite height and nadir topography. To improve the strength of the nadir signal, it may even be advantageous to use extra data takes over flat scenes like calm water. The width of the nadir notch can moreover be increased by combining data from multiple LPAC measurements, each acquired with a slightly different roll angle of the satellite.
While this paper focused on multichannel antenna pattern calibration in Tandem-L and its use for advanced range ambiguity suppression, the proposed technique is neither limited to reflector antennas nor to beamforming in elevation. For example, a dedicated data take with a narrow azimuth Tx beam is well suited to derive the relative antenna patterns for a planar HRWS system with multiple azimuth channels (Ref. 13).
Concepts for Tandem-L products
Tandem-L is a proposal for a SAR mission with two L-band satellites which aims to observe globally dynamic processes of the Earth's surface. The mission will provide, on the one hand, 12 higher-level products addressing the problematics of, for example 3D forest structure measurements or large scale deformation monitoring. On the other hand, it will deliver focused SAR data to generate other products, which will contribute to the understanding of e.g. ice or ocean dynamics. 21)
Some important mission goals are: The global measurement of forest biomass and its variation in order to understand the carbon cycle, the systematic recording of Earth's surface deformations for earthquake research and risk analysis, the large scale observation of ocean currents and sea ice drift or the quantification of glacier movements and melting processes in the Polar Regions. Inspired by the TanDEM-X mission, the Tandem-L mission concept uses two SAR satellites at L-band which fly in different formations to enable bistatic or (pursuit) monostatic acquisitions of the whole Earth's landmass up to four times per week.
A set of 24 so-called higher-level products have been defined based on user requirements. Among these, 12 products will be generated operationally during the mission. These cover the biosphere and geosphere topics but also DEMS (Digital Elevation Models). Besides that, various basic SAR and InSAR products will be delivered as a basis for higher-level products covering the hydrosphere and cryosphere matters. Table 5 summarizes all basic SAR products and Table 6 the deformation (geosphere) higher-level products.
Table 5: Summary of the basic SAR products
Table 6: List of the deformation higher-level products
These products enable to monitor large scale deformation, urban subsidences, landslides, volcanic activity and earthquakes. Forest (biosphere) products, on the other hand, will provide global measurements of 3D forest structure and biomass.
Each of these products is generated to support different application fields which require different kind of processing and consequently specific acquisitions conditions:
• acquisition mode (standard is Staggered StripMap)
• geometry (right/left looking, ascending/descending orbits)
• acquisition frequency (e.g. one acquisition per cycle)
• flight configuration (close formation for bistatic acquisitions or pursuit monostatic or constellation for monostatic acquisitions)
• polarization mode (single or quad pol) implying different swath width (respectively 350 km and 175 km)
• range bandwidth (20, 40 or 84 MHz).
In this way, forest observations require bistatic quad pol 84 MHz acquisitions whereas deformation products need single pol monostatic 20 MHz SAR data. Additionally, it is reasonable to monitor these applications only for specific regions of interest (Figure 12), which may of course overlap. As a consequence, an acquisition configuration has to be preferred when the ROIs overlap and some application may get some acquisitions with different data-taking configurations than the foreseen ones. For example, processors for deformation products will have to deal with data with forest acquisition parameters since they are more constraining as suggested in Figure 2. It also implies a seamless transition between acquisitions to avoid gaps within the regions of interests (the instrument must thus be able to switch the acquisition mode from one instrument source packet to the next).
Figure 12: Regions of interest for geosphere (top) and biosphere (bottom) higher-level products (image credit: DLR)
Altogether, an acquired (SAR raw) data volume of up to 8 TB per day have to be downlinked and processed to L1A and made available for external users or external processors but also for a good part of them systematically further processed to higher-level products.
Figure 13: Imaginary scenario and resulting acquisitions (image credit: DLR)
Basic SAR products processing
Combined Systematic L0 annotation and L1A processing: It is foreseen to logically assemble the SAR raw data during their ingestion together with a comprehensive SAR header analysis and quality assessment of the source packets. The more complex processing is performed at the same time than the systematic L1A (SSCs and CoBiSSCs) generation in order to avoid shuffling the data several times. In this way, further processing steps are performed once all auxiliary data (orbit, calibration information, attitude, etc) are available i.e. about 3 days after acquisition. The complex products are generated systematically and are provided at a data hub for user access for a given period of time. SSCs or CoBiSSCs needed for the operational higher-level products generation are archived for the needed duration. For example, the line-of-sight deformation rate maps shall be generated based on one year of acquisitions.
The exemplary observation scenario as depicted Figure 13 could hint, that the individual acquisitions are processed according to the foreseen applications. This means a complete processing for the trigger application and possibly repeated processing for other applications and that the same raw data are possibly processed a times. To avoid it and the associated handling of L1A products specifically generated for a given application, the SAR processor should be able to focus the data datatake-wise "in one go" by taking into account which data is available with which configuration. At transition areas, it will process for the "lower performance" i.e. when a switch occurs between 84 MHz and a lower bandwidth, it extends the acquisition with the lowest bandwidth, or when a transition from quad to single pol (or inversely) happens, the length of the single polarization channel will be increased at the cost of a reduced swath width (single pol is 350 km wide whereas quad pol is only 175 km).
This SSC data stream is then cut into seamless and nonoverlapping SSC pieces, called SSC frames, following a global framing scheme. Each SSC frame is then treated as a stand-alone self-containing product with complete meta and annotation information, quicklooks, etc. Every further product (other L1 and higher-level product) are consistently generated based on these SSC frames.
Figure 14 depicts the resulting SSC frames for the forest and deformations applications for the acquisitions of cycle 9 in descending orbit of the current acquisition timeline of the close formation. In (a), acquisitions triggered for forest are in green and those for deformation in red. In (b), the resulting SSC frames for forest are plotted, since their required mode is the most constraining i.e. bistatic quad pol with 84 MHz bandwidth, no other triggered applications delivered usable data. In (c), on the opposite, it can be observed that deformation applications can accept data with almost any acquisition parameters and consequently exhibit all possible acquisition modes.
Figure 14: One cycle acquisitions (descending orbit) and resulting SSC framing (image credit: DLR)
A number of reasons favor the systematic processing scheme as presented:
• Focusing may be done in a straight-forward way on a data-driven basis without taking follow-on application products into consideration.
• Comprehensive annotation and quality information (about RFI, ionospheric perturbations, sync pulses, notch beam processings, etc.) is obtained as soon as needed input data are available.
• All acquired data are processed and the generated L1A products can be provided at a data hub for user download.
• All acquired data are processed and the generated L1A products can be provided at a data hub for user download.
• Different polarization channels may be assessed individually by different application processors on different time scales (weeks / months / years).
• The applied framing concept supports a systematic stack processing by allowing a consistent identification, processing and reuse of L1A products for the built-up of stacks and combined stacks as needed for higher-level product generation.
Systematic and on-demand L1B and L1C processings: A systematic generation of L1B and L1C products shall be also possible, but has to be based on more sophisticated production rules since this shall only be done on a restricted basis. The restrictions are coming from selected applications and geographical areas. An example might be the systematic generation of MGD products over given coastal areas to support ship detection.
Mostly, the L1B and L1C generations are done on-demand. The L1C products which are stacks of SSCs or CoBiSSCs are important inputs for a higher-level product generation. The activation of such higher-level products generation results then in a demand for the generation of the needed L1C inputs based on archived or reprocessed L1A. Furthermore, all level 1 products may be requested by users leading to an on-demand processing.
Higher-level products generation: example of the deformation products
Deformation products deal with Earth's surface large or small scale deformation monitoring. These products are listed in Table 5. LOS (Line-Of-Sight) displacement maps are designed for monitoring single events such as earthquakes, landslides or for supervising volcanic activities. The PSI (Persistent Scatterer Interferometry) deformation database is intended to study urban subsidence but also landslides. Finally, the LOS deformation rates maps and 3D deformation rates maps (based on the stacked interferometric phases) are targeting long-term monitoring of tectonic deformation in inter-seismic periods.
The deformation processor delivers most of its outputs systematically but some LOS displacement maps have to be provided on-demand. Indeed, in case of earthquakes or landslides, a displacement map has to be generated based on available acquisitions (one before and one after the event).
Figure 15 depicts the product dependencies together with the main algorithmic steps for their generation. The PSI analyses and the displacement maps generation lines are independent whereas the three last products are dependent from each other. The products generation of these higher-level products starts from the Stacked Single-look-Slant-range Complex (StaSSC). The first step is dedicated to the interferometric phase estimation. Atmospheric and ionospheric disturbances are compensated. No phase unwrapping or geocoding is therefore performed. In a second step the displacement rate maps w.r.t. the radar LOS are generated. These products present already a measurement (in mm/y) of the geophysical phenomena and they are already mapped in a geographical raster nevertheless such measurements still require some knowledge of the radar geometry as far as they represent only the part of the motion in the LOS direction. As a last step,the 3D displacement rate vectors are derived by combining data acquired from ascending and descending orbits with different incident angles as well as in right- and left-looking configurations providing a product completely independent from the radar geometry.
A general issue in the higher-level products generation framework is the update of the products from year to year. Intermediate products storage has to be considered in order to avoid huge memory consumption and data transfer. Concepts and algorithmic implementations are being studied.
Figure 15: Geosphere product dependencies graph and main algorithmic steps (image credit: DLR)
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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 (firstname.lastname@example.org).