Moreover, the performance of conventional soil moisture inversion algorithms is strongly compromised by the presence of vegetation. Therefore, the fact that agriculture fields are most of the year covered by vege- tation makes the development of a distinct approach essential. A promising solution is the use of fully pola- rimetric SAR at lower frequencies providing an appropri- ate penetration as well as an observation space that allows the interpretation and decomposition of different scatter- ing contributions. Indeed, polarimetric decomposition techniques have been successfully developed and used to filter the disturbing vegetation contribution, allowing the estimation of moisture content on the isolated surface components , . Fig. 21 shows the high-resolution soil moisture maps for different moisture levels, which were obtained from airborne fully polarimetric L-band data acquired by the E-SAR sensor at three different dates. This analysis was conducted within the framework of the agricultural bio/geophysical retrieval from frequent repeat- pass SAR and optical imaging (AGRISAR) experiment in 2006. At the time of the first acquisition, the crop layer was still short and sparse. Crop height and density increased with time to the next acquisitions performed almost one and two months later. However, the comparison with the ground measurements indicated that despite the growth of the vegetation cover, soil moisture was estimated with an impressive root mean square error (RMSE) between 4 vol% and 11 vol%. (The detailed validation is provided in , while only the measured moisture trend is shown on the bottom of Fig. 21.)
Since 1998, he has been with the Microwaves andRadar Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany, where he is working on syntheticapertureradar (SAR) calibration methods and performance analysis tools. Since 2000, he has been the Head of the Radar Calibration Group, per- forming various radar calibration activities for differ- ent SAR missions like X-band SyntheticApertureRadar on the Shuttle Radar Topography Mission or the ScanSAR mode of Advanced SyntheticApertureRadar (ASAR)/Envisat. He was responsible for the successful calibration of the German TerraSAR-X and TanDEM-X satellites, launched in 2007 and 2010, respectively. Furthermore, as part of the Global Monitoring Environment and Security Program, he is responsible for developing the overall SAR system calibration and validation plan for European Space Agency’s Sentinel- 1 mission. Under his leadership, the DLR’s comprehensive radar calibration facilities, including novel tools for product quality control and performance analysis, have been maintained and extended. His major research interest includes the development of innovative and efficient calibration methods. Dr. Schwerdt was a recipient of the Der Deutsche Gr¨underfonds award in 1997 for establishing an enterprise of manufacturing electrooptical field sensors under the patronage of the German Federal Minister for Science and Research.
displacement, a parametric model like a linear rate of change or a seasonal oscillation is assumed. Preliminary estimation of displacement parameters has the clear disadvantage that a functional model has to be postulated, chosen either from a priori knowledge or by statistically testing the performance of different models (van Leijen and Hanssen, 2007). Whereas preliminary displacement estimation is included in most PS processing chains, it is disapproved by Hooper et al. (2004, 2007) who only estimate per PS an absolute height error δh (or look angle error, respectively) and a spatially uncorrelated contribution of the master image. Assuming the relative displacement of nearby PS to be small, their approach does not rely on the preliminary choice of a specific functional model. However, in contrast to other approaches, large spatial displacement gradients may be critical for successful unwrapping. The most critical issue inherent to all unwrapping approaches is the validity of the assumption that phase differences of PS adjacent in time or space are smaller than π. Taking into account the unseizable noise contribution, it is rather desirable that systematic signal components differ by distinctly less than π. Preliminary mitigation of atmospheric and orbital signals is usually neither performed nor required, because their local gradients are mostly sufficiently small. However, even though this assumption applies to the great majority of applications, it might prove invalid in some cases with very large orbit errors, where only a preliminary estimation enables successful unwrapping.
A syntheticapertureradar (SAR) is an active microwave instrument capable of imag- ing the surface of the earth at specific wavelengths and polarizations in day/night and all-weather conditions. In its basic configuration, a small airborne/spaceborne antenna traveling along a straight-line trajectory is pointed perpendicular to the flight track in a side-looking fashion. This results in the synthesis of a virtual along-track antenna aperture that enables the formation of a high-resolution 2-D image of the illuminated area. Moreover, when multiple parallel trajectories—with cross-track and/or elevation displacements—are considered, the resulting sensing geometry enables the synthesis of two virtual antenna apertures that allow for 3-D backscatter profiling. This imaging modality is known as SAR tomography and is commonly approached by first obtain- ing multiple 2-D coregistered SAR images—such that each image corresponds with a parallel pass—followed by 1-D standard spectral estimation techniques. A typical ap- plication is the 3-D imaging of vegetated areas which, due to the high-penetration ca- pabilities of radiation at long wavelengths, has proven to be of great value for the esti- mation of forest structure and, in turn, for the quantification of above ground biomass. In addition, with the anticipated advent of long-wavelength spaceborne radars, tomo- graphic SAR techniques will become of considerable interest, as tomographic data sets will be available on a large scale. However, ideal sampling conditions are known to require a large number of dense regular acquisitions, which are not only limited and expensive but can also lead to temporal decorrelation.
Syntheticaperture sonar (SAS) provides high-resolution imagery of the seafloor which, in contrast to conventional side-looking sonar systems, achieves a range-invariant cross-range resolution [Hayes and Gough (2009), Hansen et al. (2011)], thereby maintaining a constant resolution of the SAS image for the entire seafloor scenery. This is highly desirable for any post-processing application, e.g., object detection [Midelfart et al. (2009), Williams and Groen (2011), Fandos and Zoubir (2011)], mine hunting [Groen et al. (2010), Fandos et al. (2013)], seafloor mapping, and hydrography [McRea et al. (1999)]. Further, phase difference extraction of high- quality SAS image pairs, reconstructed by an interferometric SAS configuration, yields an accurate estimate of the seafloor topography [Sæbø et al. (2007)]. This enables potential applications such as pipeline inspection [Hansen et al. (2010)] or reconnaissance for installations of pipelines and offshore platforms [Bjørnø (2013)]. Ultimately, all aforementioned application tasks are performed autonomously without the need for permanent operator control. In order to maintain resolution during imaging, a syntheticaperture of variable length is formed by coherently processing a varying number of backscattered echo signals. These signals are recorded over consecutive transmission times by a physical hydrophone array that is either mounted onto a moving autonomous underwater vehicle (AUV) or employed as a towed array [Hayes and Gough (2009)]. The challenge of syntheticaperture formation is its high sensitivity (up to a fraction of a wavelength) to unknown platform motion, which arises from an imprecise on-board inertial navigation system (INS) [Hansen et al. (2011)]. As a consequence, image defocusing may occur, which is in conflict with the aim of achieving high-quality SAS imagery. Thus, additional means are required to obtain precise estimates of the platform motion in order to enable the reconstruction of high-quality SAS images.
The relativistic phase and time offsets from this paper are not only of high importance for DEM generation with a formation flying SAR cross-track interferometer. Formations with multiple satellites have also been suggested for a wide range of further remote sensing applications, ranging from along-track interferometry for moving object and ocean current measurements over sparse aperture ambiguity suppression and super resolution for enhanced high-resolution wide-swath SAR imaging up to single-pass SAR tomography for vertical struc- ture measurements –. Due consideration of relativistic effects from varying along-track baselines is again of essential importance for these advanced bistatic and multistatic SAR systems to avoid mutual range and phase offsets between the received SAR signals. The phase accuracy requirements for the combination of the different receiver signals are typically in the order of 1° or a few degrees. For comparison, an along-track baseline of 100 m causes in an X-band system a relativistic phase shift in the order of several tens of degrees. Future multistatic SAR satellite missions should therefore take into account relativistic effects in the design of the radar synchronization system and/or the SAR processor to avoid a possible performance loss.
Several proposals resolve the azimuth resolution vs. coverage dilemma by combining a multi-channel radar receiver with a fixed small aperture transmitter illuminating a wide area on the ground. An early example is a multiple beam SAR operating in a squinted imaging geometry . The squinted geometry allows for the simultaneous imaging of multiple swaths at an almost constant incident angle and the combination of the sub-swaths yields a wide image swath without ambiguities (Figure 1, left). Major drawback of this system is the high squint angle that complicates the processingand impairs the performance. Another promising approach is the displaced phase centre antenna technique . The basic idea behind this system is to use multiple apertures in the along-track direction and to acquire for each transmitted pulse additional samples along the syntheticaperture (Figure 1, second column). As a result, the transmit PRF can be reduced which enables in turn the unambiguous mapping of a wider image swath. An extension of the DPCA technique is the Quad Array system  which employs additional apertures in elevation to suppress range ambiguous returns . By this, one may further increase the image swath, but the drawback is a range gap in the middle of the wide swath since it is impossible to simultaneously transmit and receive radar pulses (Figure 1, third column). A further extension of the DPCA technique is the High-Resolution Wide-Swath (HRWS) SAR system . This system combines a separate small transmit antenna with a large receiver array as illustrated in the fourth column of Figure 1. The small transmit antenna illuminates a wide swath on the ground and the large receiver array compensates the Tx gain loss by a real time digital beamforming process in elevation called scanning on receive (SCORE). Multiple azimuth channels allow furthermore for the imaging of a wide swath without rising azimuth ambiguities. The combination of the azimuth signals from multiple displaced apertures requires the application of dedicated multi-channel SAR signalprocessing algorithms as introduced in  and further elaborated in .
The launch of the German TerraSAR-X remote sensing satellite in 2006 will open a new era in the application of radar remote sensing. For the ﬁrst time there is a change from data products to information products, aimed for the commercial and public markets. This mission marks a clear move from serving the military and scientiﬁc community to supplying the commercial market. It is anticipated that the versatility of needs for remote sensing information prod- ucts will provide a non-negligible funding for this and similar future missions. At the same time it is, however, this versatility of needs being the shortcom- ing of current radar remote sensing systems. Up-to-date satellite systems are strongly conﬁned towards a handful of possible applications. Technical solu- tions part with two clear trends: on one side there is a move towards systems dedicated to a single application; while on the other side, the solution is found by constructing very complex remote sensing systems providing a large num- ber of mutually exclusive operation modes, each of which is dedicated to a certain purpose. Although the second approach oﬀers a certain ﬂexibility, it is at the cost of extremely sophisticated, low eﬃciency, high weight andhigh cost vulnerable hardware realizations based to a large extend on analog RF technologies. One common handicap of both trends is that the systems are bound to contradicting requirements on resolutionand coverage.
The XWAVE_C algorithm to derive meteo-marine parameters from X-band SAR data was developed for coastal applications particularly by taking into account the short wave sea state with a non-conventional imaging mechanism. It was found that the parameters of short wave sea states with a hardly visible imaged wave pattern can be estimated based on a combination of local wind information and the properties of image spectrum noise. An NRT version of the Sea State Processor was made operational (Pleskachevsky et al., 2016, Schwarz et al., 2015) and processed data were provided in a test mode for the validation of forecast Wave Model CWAM of the German Weather Service in the German Bight in order to support and improve the predictions in coastal areas and at offshore constructions. The SSP processor is now extended for SENTINEL S-1 C-band data and has been tuned for the worldwide application to estimate sea state from VV S-1 IW-mode images.
to detect unexploded ordnances (UXO). However, magnetome- ters as well as metal detectors cannot detect modern minimum metal mines in a reliable way. A GPR is a measuring device, which is able to generate subsurface images of minimum metal mines. In recent years, much research has therefore been done in the field of UAS-based detection of mines using a down- looking radar , , , . However, a down-looking radar has the disadvantage that the potential minefield has to be scanned line by line, resulting in a low area throughput. In addition, due to the strong ground reflection it is very difficult to detect objects buried just below the surface. To overcome these issues, a side-looking radar can be employed. A long syntheticaperture enables the generation of high-resolution 2D-radar images. However, using a linear aperture, there is an ambiguity problem in range direction and depth. This can be solved by either a nonlinear motion trajectory of the UAS, e.g. a circular syntheticapertureradar (CSAR), or by cross- track interferometric SAR (InSAR), or repeat pass tomog- raphy , . Due to the flexibility and highly accurate absolute localization of the used measurement system, both procedures and the combination of them can be performed. The system, the radar, and the antennas have been published in , , and , respectively. The detection of tripwires using this system is investigated in . First subsurface linear SAR (LSAR) measurements of realistic landmine dummys are shown in .
A large sweep bandwidth of the network analyzer signals allows an adequate downrange resolution that facilitates time domain post-processing of the acquired antenna data. Positioner velocity shall allow a high number of frequency increments within the sweep time of the signal analyzer to avoid unwanted range aliasing effects. With this method, the investigated radiating surface is enlarged from the bare antenna to the complete antenna carrier structure. The electromagnetic vectors of all parasitic scatters are superimposed with that of the radiating antenna element. Measurements now include multi-pass effects on the structure and scattering on edges that influence the antenna patterns in amplitude and phase, see figures 3 and 4, with the spherical contour plots of the X-band antenna measurements in a elevation over azimuth coordinate system
First of all, a more sophisticated building model should be applied to be able to reconstruct more complex buildings. Here, a post-processing step, which makes use of the generated rectangular shaped buildings, could be a start. Furthermore, the pre-classification of the InSAR data in vege- tated and urban related areas could undergo a more intensive study including seasonal and configu- ration effects (e.g. length of temporal and spatial baseline). The processing step of calculating interferometric phases delivers only wrapped phases, thus only height differences in a range of 2π can be covered. Hence, the development of a strategy that enables the local unwrapping of the building phase signature is necessary to reconstruct buildings showing heights larger than the height of ambiguity. For that, relying mainly on the phase trend in the layover area should help to unwrap building roof phases in a proper way. The detection and segmentation of the building fea- tures (i.e. layover and corner lines) are efficiently realised. Only the extraction of the building pa- rameters necessary to model non-flat roofs should be improved to obtain more reliable results. The implemented generation of building footprints delivers very good results for orthogonal flight con- figurations. For the future, an enhancement by supporting all configurations in the same way would be preferable. In detail, the search of right-angled structures, currently limited to features spanning L-, T-, and X-shape, can be widened to H- and U-shapes. Additionally, the merging of overlapping hypotheses could be handled in a more sophisticated way, in combination with the stated en- hancement of the building model. The height estimation of buildings would benefit from fusing multi-aspect height information whereby different contributions (i.e. layover areas and roof areas) have to be combined in a suitable way. For that purpose, sizes of the areas, differences in the height of ambiguity, and neighbouring effects should be taken into account. Generally, the pre- sented approach has to be tested on more data sets covering different sensor configurations and different areas to give proof of a more general applicability.
According to the ADBF approach, the receive beam steering algorithm is cast into the frame of spatial spectral estimation and DOA estimation. This topic has been extensively studied in array signalprocessing theory [9, 10], and also with reference to the Interferometric SAR application . Nevertheless, the HRWS SAR spaceborne application shows specific challenges. First, the processing of the signals available from the vertical sub-apertures should be performed onboard, in order to reduce the downlink data volume. This requires to dealing with wideband signals and imposes additional constraints on the complexity of the processing method [10, 12]. Moreover, in case of wide illuminated swaths, the useful signal could be superimposed to range-ambiguous echoes having a power comparable with that of the signal of interest. Finally, instrument parameters, such as dimension of the antenna, number of elements, noise level (NESZ), whose values strongly affect the ultimate estimation performance, do not allow for many degrees of freedom, due to imaging requirements and physical/economical constraints.
A number of algorithms for focusing the raw SAR data have been developed since its debut in 1950s. Most of them were originally developed for remote sensing app- lications. Therefore some approximations and assumptions due to the restrictions of the hardware, e.g. antenna beamwidth, squint angle, the computation ability of signal processor, have been made when focusing the raw SAR data. The most accurate SAR algorithm is the time-domain correlation algorithm , which can be used to pro- cess the SAR data acquired with arbitrary beam-width and space sampling trajectory. Neither restriction on the antenna’s beamwidth nor motion compensation need to be applied. However, it requires a veryhigh computational effort, which makes it im- practical for any true real-time SAR application given the performance of a realistic hardware environment [43, 44]. By restricting the space sampling interval to uniform, frequency-domain algorithms, which perform the focusing in frequency domain with the power of FFT, can substantially reduce the computational burden.
coverage and weather conditions –. It is predestined to monitor dynamic processes on the Earth surface in a reliable, continuous and global way. SAR systems have a side-looking imaging geometry and are based on a pulsed radar installed on a platform with a forward movement. The radar system transmits electromagnetic pulses with high power and receives the echoes of the backscattered signal in a sequential way. Typical values for the pulse repetition frequency range from a few hundred to a few thousand Hertz for airborneand spaceborne systems, re- spectively. The swath width varies typically from a few kilometers to 20 km in the airborne case and from 30 to 500 km in the spaceborne case. The transmitted pulse interacts with the Earth surface and only a portion of it is backscattered to the receiving antenna which can be the same as the transmit antenna (for a monostatic ra- dar) or a different one (for a bi- or multi-static radar). The amplitude and phase of the backscattered signal depends on the physical (i.e., geometry, roughness) and electri- cal properties (i.e., permittivity) of the imaged object. Depending on the frequency band, considerable pen- etration can occur so that the imaged objects and media must be modeled as a volume (e.g., vegetation, ice and snow, dry soil). More penetration of the electromagnetic pulses in media will occur for radar systems using longer wavelengths which usually have an accentuated volume contribution in the backscattered signal. Commonly used frequency bands in SAR systems and the associated wave- length ranges are shown in Table 1.
Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolutionradar images are helpful in analyzing a possible damage. Furthermore investigations on unknown space objects or satellites can be performed. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi- purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a high-power traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1.8 m RX antenna mounted on a common steerable positioner. High-resolutionradar images are obtained by using Inverse SyntheticApertureRadar (ISAR) techniques. The guided tracking of known objects during orbit pass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system. It shows the main error sources and solutions as well as the calibration effort to generate the first centimeter-resolutionradar image observed with IoSIS.
SyntheticApertureRadar can be considered nowadays as an established and mature technology to obtain high-resolution two-dimensional reflectivity images of the Earth surface in nearly all weather conditions and independently of the day-night cycle. During a first period, ranging from their conception in the 1950s to the beginning of the 1990s, SAR systems were characterized by a single acquisition channel, and it was proven that this technology allows the observation and characterization of the Earth surface in the microwave region of the electromagnetic spectra. At the beginning of the 1990s, SAR technology started to show its important potential with the availability of multichannel or multidimensional SAR system configurations. Among them, it is worth to mention: interferometric techniques (InSAR), using single- or multiple baselines configurations, polarimetric diversity (PolSAR), or the combination of these approaches called polarimetric SAR interferometry (PolInSAR). It is also important to note that in the recent years, the use of time diversity, in combination with any of the previously introduced multidimensional configurations, has emerged as a new and promising research field to improve the analysis of the areas being imaged, but also the observation and characterization of dynamic processes. The importance and interest on the diﬀerent multidimensional SAR system configurations is partly due to the increase of the number of radar observables but primarily to the fact that the acquired multidimensional signals are sensitive to diﬀerent biophysical and geophysical properties of the Earth surface and may then be used for quantitative retrieval purposes.
Abstract—Layover is frequent in imagingand monitoring with syntheticapertureradar (SAR) areas characterized by a high density of scatterers with steep topography, e.g., in urban environ- ment. Using medium-resolution SAR data tomographic techniques has been proven to be capable of separating multiple scatterers interfering (in layover) in the same pixel. With the advent of the new generation of high-resolution sensors, the layover effect on buildings becomes more evident. In this letter, we exploit the po- tential of the 4-D imaging applied to a set of TerraSAR-X spotlight acquisitions. Results show that the combination of high-resolution data and advanced coherent processing techniques can lead to impressive reconstruction and monitoring capabilities of the whole 3-D structure of buildings.
space-borne radar sensors can be used to determine mesoscale high-resolution wind fields in synergy with cloud parameters from optical data and, thus, help in the task of maintenance and plan- ning offshore wind farms. The aim of this paper is to use syntheticapertureradar (SAR) and medium resolutionimaging spectrom- eter (MERIS) onboard the environmental satellite (ENVISAT) in synergy to analyze severe weather systems, in particular, to describe the spatial evolution of the atmospheric boundary layer processes involved in cold air outbreaks. We investigated the fine-scale structure of a severe weather case on November 1, 2006 over the North Sea using satellite data. The satellite data are compared with numerical model results of the German Weather Service “Lokal Modell” (LM) and the high-resolution limited area model (HIRLAM). LM and HIRLAM show differences in mesoscale turbulent behavior and coastal shadowing. Maximum wind speeds of up to 25 m/s are measured by SAR and are confirmed by the models. Significant differences are observed in the location of the maxima. High-resolution ENVISAT ASAR measurements provide very detailed information on small-scale atmospheric features, which seem to not be captured well by the analyzed numerical models, in particular, in coastal areas. Meteosat second generation (MSG) is used to determine the move- ment of cloud patterns. Cloud patterns seen in the optical data andradar cross-section modulation give a consistent dynamical picture of the atmospheric processes. The relevance for offshore wind farming is discussed.
Having defined the rationale and the objectives of the research, this chapter will present the background relevant to the project. Section 2.1 is dedicated to a brief introduction to SAR remote sensing. Subsequent sections are dedicated to monostatic SAR (Section 2.2) and bi-static SAR (section 2.3). The physics related to SAR imaging are presented in section 2.4 (SAR image interpretation). Section 2.5 presents SAR interferometry describing the basic principles and introducing all the key concepts that provide the essential background to the analysis carried out in the chapter dealing with possible fields of applications. The notion of signal coherence is analysed in section 2.6 while the following section is dedicated to the principle of SAR image processing. Multi- static SAR configurations are discussed in section 2.8 while section 2.9 and the remaining part of the chapter present a literature review on Earth tides, tropospheric and ionospheric effects on SAR imaging.