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Synthetic aperture sonar and synthetic aperture radar involve the creation of high-resolution images of a scene via scattered signals recorded at different locations. Each pixel of the reconstructed image includes information obtained from multiple aspects due to the changing position of the sources/receivers. In this paper, the aspect-dependent scattering at each pixel is exploited to provide additional information about the scene; this paper presents a framework for converting and utilizing multiaspect data, as well as several examples. For sonar data, as is presented here, the aspect dependence may be leveraged to separate objects of interest from the background, to understand the local bathymetry, or for visualizing acoustic shadowing in full circular synthetic aperture sonar images. Several examples of images of the seafloor containing objects of interest are presented for both circular and linear apertures. In addition, the aspect dependence of low-frequency elastic scattering from objects may be used to understand the underlying scattering physics, which is of potential use in fields such as target recognition and nondestructive testing; a laboratory example is presented. [ABSTRACT FROM AUTHOR]

Tandem-L is proposed as a spaceborne synthetic aperture radar (SAR) mission developed and operated by the German Aerospace Center in cooperation with several Helmholtz research centers and the German space industries. The mission concept comprises two fully polarimetric radar satellites providing monostatic and bistatic SAR imagery. A key feature of these SAR sensors is the employment of large lightweight unfurlable mesh reflectors fed by digital feed arrays. The main advantage of this new SAR system concept is the provision of large antenna apertures in space and flexible operation via reconfigurable feed electronics. By this, it becomes possible to map, for the first time, a continuous 350-km wide swath with a 7-m azimuth resolution with excellent noise equivalent sigma zero and ambiguity suppression. This paper shall give an overview on the technical aspects of the Tandem-L SAR instrument and antenna design. In particular, after a short review of the SAR system requirements, the concept of reflector SAR systems is outlined and the operation principle is presented. General guidelines for the design of array-fed reflector antennas with application to SAR imaging are given. Then, the optimization approach of the feed array design is detailed with a specific emphasis on a fixed beamforming concept in azimuth. In this context, also the problem of cross-pol pattern mitigation is addressed. These optimization steps are shown to be crucial for achieving the performance requirements in quad-pol acquisitions. Beamforming in elevation is performed onboard the spacecraft via digital hardware. This paper presents the beamforming architecture on receive for Tandem-L, which would apply in general for instance also to planar multielevation beam SAR antennas with Scan-On-Receive capabilities. Tandem-L is operated as a staggered SAR, which means varying the pulse repetition interval from pulse to pulse. In this context, the major design challenges are presented. Moreover, the impact of pulse staggering on the imaging performance is discussed. Tandem-L’s SAR performance is presented by means of numerical simulations showing that the performance requirements imposed by the scientific user community could be met. The final part of this paper addresses options for high azimuth resolution imaging as well as a beamforming method for enhanced range ambiguity suppression. [ABSTRACT FROM AUTHOR]

This paper addresses the performance in the retrieval of 3-D mean deformation maps by exploiting simultaneous or quasi-simultaneous squinted synthetic aperture radar (SAR) interferometric acquisitions in a repeat-pass scenario. In multisatellite or multibeam low earth observation missions, the availability of two (or more) lines of sight (LOSs) allows the simultaneous acquisition of SAR images with different squint angles, hence improving the sensitivity to the north–south component of the deformation. Due to the simultaneity of the acquisitions, the troposphere will be highly correlated and, therefore, will tend to cancel out when performing the differential measurement between the interferograms obtained with the different LOSs, hence resulting in a practically troposphere-free estimation of the along-track deformation measurement. In practice, however, the atmospheric noise in the differential measurement will increase for increasing angular separations. This paper expounds the mathematical framework to derive the performance by properly considering the correlation of the atmospheric delays between the simultaneous acquisitions. To that aim, the hybrid Cramér–Rao bound is exploited making use of the autocorrelation function of the troposphere. Some performance examples are presented in the frame of future spaceborne SAR missions at C and L band. [ABSTRACT FROM AUTHOR]

In recent years, synthetic aperture radar interferometry has become a recognized geodetic tool for observing ground motion. For monitoring areas with low density of coherent targets, artificial corner reflectors (CRs) are usually introduced. The required size of a reflector depends on radar wavelength and resolution and on the required deformation accuracy. CRs have been traditionally used to provide a high signal-to-clutter ratio (SCR). However, large dimensions can make the reflector bulky, difficult to install and maintain. Furthermore, if a large number of reflectors are needed for long infrastructure, such as vegetation-covered dikes, the total price of the reflectors can become unaffordable. On the other hand, small reflectors have the advantage of easy installation and low cost. In this paper, we design and study the use of small reflectors with low SCR for ground motion monitoring. In addition, we propose a new closed-form expression to estimate the interferometric phase precision of resolution cells containing a (strong or weak) point target and a clutter. Through experiments, we demonstrate that the small reflectors can also deliver displacement estimates with an accuracy of a few millimeters. To achieve this, we apply a filtering method for reducing clutter noise. [ABSTRACT FROM PUBLISHER]

This paper presents a whole new method for simulating a raw signal of synthetic aperture radar (SAR) with trajectory deviation. In this paper, a SAR raw signal is viewed as a spatial function in terms of radar location, at a fixed range frequency component of the radar signal. It is disclosed and verified that the SAR raw signals is band limited from the perspective of spatial spectrum analysis. Based on this finding, SAR raw signals under condition of trajectory deviation are obtained by interpolating the SAR raw signal along a set of ideally linear trajectories. The unprecedent performance achieved by the new method mainly includes the following. First, it provides a way to update existing simulators designed for ideally linear trajectory, giving them the capability to take trajectory deviation into consideration. Second, it is an efficient SAR raw signal simulator whose validity limit is greatly expanded compared with existing efficient simulators, as many constraints are eliminated without sacrificing computational efficiency or phase accuracy. Third, it is a uniform framework applicable for multiple SAR acquisition modes. Finally, the computational complexity of Monte Carlo experiment under various trajectory deviations is dramatically reduced, at the expense of storage memory requirement. Theoretical analyses are demonstrated by experimental results. [ABSTRACT FROM PUBLISHER]

This paper focuses on the detection, from a stack of repeated-pass interferometric synthetic aperture radar (SAR) images, of such changes causing a target to completely lose the correlation between one epoch and another. This can be the consequence of human activities, such as construction, destruction, and agricultural activities, and also be the consequence of hazards, such as earthquake, landslides, or flooding, to buildings or terrains. The millimetric sensitivity of SAR makes it valuable for detecting such changes. This paper approaches two coherent change detection methods: a space coherent, time incoherent one and a full space and time coherent one, both based on the generalized likelihood ratiob (LR) test. A preliminary validation of the method is provided by processing two Sentinel-1 data stacks of 2016 Central Italy earthquake and by comparing the results with the map of damaged buildings in Amatrice and Accumoli made by Copernicus Emergency Management Service. [ABSTRACT FROM AUTHOR]

This paper deals with the compensation of phase miscalibration in the general context of tomographic synthetic aperture radar image focusing. Phase errors are typically independent of one acquisition to the other, thus leading to a spreading and defocusing in the multidimensional (3-D, 4-D, and 5-D) imaging space. Coping with this problem in presence of volumetric scattering is generally a complex issue. In this paper, we consider the approach for phase calibration characterized by the advantage, with respect to classical phase calibration algorithms, of not requiring either the identification of a reference target or specific assumptions about the unknown phase function, or a priori information about the terrain topography. The novelty of the proposed phase miscalibration estimation and compensation method is related to its ability to avoid unwanted and uncontrollable vertical shifts in the focused image. The estimation of the calibration phase is performed by optimizing the contrast or the entropy of the vertical profile with the constraint of a zero phase derivative. Such a constraint preserves the output height distribution. Experimental results of simulated and real data are included to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Sea ice concentration (SIC) is an important sea ice parameter for sea ice navigation, environmental research, and weather and ice forecasting. We have developed and tested a method for estimation of the Baltic Sea SIC using SENTINEL-1 synthetic aperture radar (SAR) and Advanced Microwave Scanning Radiometer 2 passive microwave radiometer (MWR) data. Here, we present the method and results for January 2016. Ice concentration grids of Finnish Meteorological Institute daily ice charts have been used as reference data in this paper. We present a comparison of four SIC estimation methods with our reference data. In addition to the combined SAR/MWR SIC estimation method, we also compare SIC estimates produced using SAR alone and two MWR-based methods. The main target of this paper was to develop and test a high-resolution SIC estimation method suitable for operational use. [ABSTRACT FROM PUBLISHER]

The availability of accurate trajectory information is paramount for the processing and exploitation of synthetic aperture radar (SAR) data. Considering the particular case of spaceborne SARs designed for repeat-pass interferometric applications, errors in the trajectory translate into phase artifacts that affect the interferometric performance. In this paper, we propose a model-based procedure to calibrate the trajectories of spaceborne SAR systems by the multisquint (MS) phase. The technique allows to estimate the along and the derivative of across track geometric errors. The geometric model of the InSAR phase is derived as a function of positioning errors and the MS phase model as derivative of the InSAR phase geometric model, with respect to the squint angle. We perform a sensitivity analysis of the model in order to define which geometric errors can be estimated by the MS phase, justifying the assumption that the MS phase is very poorly affected by the atmospheric phase screen. We particularly concentrate on the TOPSAR acquisition mode, where the phase is very sensitive to geometric errors. We start from the classical two-image case and then consider the extension to the multibaseline case. Experimental results obtained by processing of interferometric pairs acquired by the Sentinel-1A sensor are reported. [ABSTRACT FROM PUBLISHER]

This paper describes the Naval Research Laboratory Multichannel Synthetic Aperture Radar (NRL MSAR) and presents initial results from the first field deployment of this system. The NRL MSAR is an airborne test bed designed to investigate remote sensing and surveillance applications that exploit multiple along-track phase centers, particularly applications that require measurement of scene motion. The system operates at X-band and supports 32 along-track phase centers through the use of two transmit horns and 16 receive antennas. As illustrated in this paper, SAR images generated with these phase centers can be coherently combined to directly measure scene motion using the velocity SAR algorithm, and these measurements can then be used to correct the image distortion that the motion causes. In September 2014, this unique radar was deployed for the first time on an airborne platform. This paper presents a description of the system and results from its inaugural deployment, including the correction of distorted maritime signatures. These data were collected over an ocean inlet and contain a variety of moving backscatter sources, including automobiles, ships, shoaling ocean waves, and tidal currents. [ABSTRACT FROM PUBLISHER]

Similar to the conventional squint mode synthetic aperture radar (SAR) imaging processing, the estimation of Doppler centroid is one key problem for the low-squint-mode (within the range of [−5°, 5°]) multichannel in an azimuth high-resolution and wide-swath (HRWS) SAR system. In this paper, based on the electromagnetic scattering model, a novel weighted Doppler centroid estimation approach is proposed for the multichannel in the azimuth HRWS (MC-HRWS) SAR system. First, Maxwell’s equations are employed to derive the echo model for the multichannel SAR system. Then, an improved backscattering model is presented based on the small perturbation method and the available echo model, which is adopted to produce the weights for Doppler centroid estimation. More importantly, in order to improve the precision of Doppler centroid estimation, a weighted ambiguity-free Doppler centroid estimation approach is proposed, where the range-variant characteristic of Doppler centroid is employed to resolve the ambiguity number of Doppler centroid, and the echoes from different range bins with different signal-to-noise ratios are considered. In addition, the Cramer–Rao low bound of the estimated Doppler centroid is also discussed in this paper. The effectiveness of the proposed Doppler centroid estimation approach is verified via simulated and real measured low-squint-mode MC-HRWS SAR data. [ABSTRACT FROM AUTHOR]

The field of wireless communications has benefited from multiple-input and multiple-output (MIMO) techniques. As researchers seek to apply MIMO (multistatic) techniques to radar and specifically to synthetic aperture radar (SAR), a key factor in determining MIMO application and performance is the level of correlation of signals from different receiver/transmitter pairs. The level of correlation determines whether a MIMO array falls into the category of a collocated array or a distributed array. The type of array dramatically affects which MIMO techniques may be performed and what advantages MIMO offers from conventional techniques. This paper presents models for calculating geometric correlation of multistatic SAR pixels using a ground-plane image formation. The models' results are compared to previous correlation models found in literature. A key result is that correlation depends on pixel resolution and not the number of individual scatterers. This paper concludes that most MIMO arrays operating on a single platform operate in the collocated regime. [ABSTRACT FROM PUBLISHER]

This paper presents a methodology to design a spaceborne dual-beam along-track synthetic aperture radar interferometer to retrieve ocean surface velocity vectors. All related aspects and necessary tradeoffs are identified and discussed or reviewed, respectively. This includes a review of the measurement principle and the relation between baseline and sensitivity, the relation between wind and radar backscatter, a discussion of the observation geometry, including the antenna concept, polarization diversity, and all main error contributions. The design methodology consists of a sensitivity-based derivation of explicit instrument requirements from scientific requirements. In turn, this derivation is based on a statistical model for the interferometric phase error. This allows a quantitative, well-grounded instrument design offering an additional degree of freedom to the approach, which we call “noise-equivalent-sigma-zero requirement space.” Crucial tradeoffs for the system design, such as the resolution, the number of independent looks, the minimum wind speed, and the coherence and ambiguities, are pointed out and discussed. Finally, this paper concludes with a single platform system concept operating in Ku-band, which provides the measurement quality needed to achieve a surface velocity estimation accuracy of 5 cm/s, 200-km swath coverage, for 4 $\times$ 4 km2 L2-product resolution and winds starting at 3 m/s. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce the concept, develop the theory, and demonstrate the advantages of fully focused coherent processing of pulse echoes from a nadir-looking pulse-limited radar altimeter. This process, similar to synthetic aperture radar (SAR) imaging systems, reduces the along-track resolution down to the theoretical limit equal to half the antenna length. We call this the fully focused SAR (FF-SAR) altimetry processing. The technique is directly applicable to SAR altimetry missions such as CryoSat-2, Sentinel-3, or Sentinel-6/Jason-CS. The footprint of an FF-SAR altimeter measurement is a narrow strip on the surface, which is pulse limited across track and SAR focused along track. Despite the asymmetry of the altimeter footprint, the fully focused technique may be useful for applications in which one needs to separate specific targets within highly heterogeneous scenes, such as in the case of sea ice lead detection, hydrology, and coastal altimetry applications. In addition, over rough homogeneous surfaces, such as the ocean or ice sheets, the improved multilooking capability of FF-SAR leads to a significant increase in the effective number of looks with respect to the delay/Doppler processing, resulting in better geophysical parameter estimation. The proposed processing technique was verified by processing full bit rate CryoSat-2 SAR mode data over the Svalbard transponder. Hydrology, sea ice, and open ocean applications are also demonstrated in this paper, showing the improvement of this technique with respect to conventional and delay/Doppler altimetry. [ABSTRACT FROM PUBLISHER]

Although the first filtering algorithms have been proposed more than 30 years ago, despeckling of synthetic aperture radar images is still an open issue. A new boost has been provided by nonlocal (NL) means filters. The idea of NL filters is to move from the exploitation of spatial neighboring pixels to the exploitation of similar pixels found across the image. The difference between the NL algorithms is mainly related to the definition of the similarity between pixels and how similar pixels are exploited in the restoration process. Generally, to define the similarity, the patches are adopted. In this paper, a new similarity criterion for selecting similar pixels is presented. It is based on the definition of the ratio patch between the patch containing the pixel to be restored and the patch containing a candidate similar pixel. If the two pixels are similar, it is expected that the corresponding ratio patch will follow a specific statistical distribution. A modified version of the Kolmogorov–Smirnov distance is introduced to decide whether the statistical distribution of the ratio patch follows the expected one. To reduce the possible artifacts, anisotropy is exploited. Considering the proposed approach, the designed algorithm turns to be unbiased, able to provide the restored solution without any thresholding procedure, in which the tuning is substantially unsupervised and able to work with both single-look and multilook images. The algorithm has been tested on different simulated and real data. Qualitative and quantitative analyses validate the proposed approach, showing very good despeckling capabilities. [ABSTRACT FROM AUTHOR]

This paper deals with precise absolute geolocation of point targets by means of a pair of high-resolution synthetic aperture radar (SAR) acquisitions, acquired from a satellite. Even though a single SAR image is a 2-D projection of the backscatter, some 3-D information can be extracted from a defocussing analysis, depending on the resolution, thanks to orbital curvature. A second acquisition, observing the same scene under a different look angle, adds stereogrammetric capability and can achieve geolocation accuracy at decimeter level. However, for the stereogrammetric analysis to work, it is necessary to match targets correctly in the two images. This task is particularly difficult if it has to be automatic and targets are dense. Unfortunately, the defocussing-based geolocation is not sufficient for reliable target matching: the limiting factor is the unknown tropospheric delay that can cause geolocation errors of several meters in the elevation direction. However, observing that the tropospheric phase screen displays a low-pass character, this paper shows how to identify statistically the local atmospheric disturbances, therefore dramatically improving the score of successful matching. All steps involved exploit peculiar radar image characteristics and, thanks to this, avoid generic point cloud matching algorithms. The proposed algorithm is shown at work on a pair of TerraSAR-X staring spotlight images. [ABSTRACT FROM AUTHOR]

Space–time adaptive processing (STAP) of multichannel radar data is an established and powerful method for detecting ground moving targets, as well as for estimating their geographical positions and line-of-sight velocities. Crucial steps for practical applications are: 1) the appropriate and automatic selection of the training data and 2) the periodic update of these data to take into account the change of the clutter statistics over space and time. Improper training data and contamination by moving target signals may result in a decreased clutter suppression performance, an incorrect constant false alarm rate threshold, and target cancelation by self-whitening. In this paper, two conventional and two novel methods for training data selection are evaluated and compared using real four-channel X-band radar data acquired with DLR’s airborne sensor F-SAR. In addition, a module for rejecting potential moving target signals and strong scatterers from the training data is proposed and discussed. All methods are evaluated for a conventional post-Doppler (PD) STAP processor and for a particular PD STAP that uses an a priori known road map. [ABSTRACT FROM AUTHOR]

Frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) is now a commonly adopted solution for producing high-resolution electromagnetic images of the earth surface. However, many SAR applications, such as detection or imaging of moving targets, have not yet been thoroughly researched for FMCW scenarios. This paper presents a refocusing technique that works in the wavenumber domain and is based on the reference spectrum of a point-like moving target. The method is illustrated using simulated experiments, and is further tested by processing real data collected by the Ka-band MIRANDA-35 sensor. The obtained results are validated and compared with independent ground measurements, thus demonstrating the accuracy of the presented method. [ABSTRACT FROM AUTHOR]

This paper examines the attainable performance of various Doppler sublook or subband cross correlation techniques for vessel detection in synthetic aperture radar images. Research from the past two decades claims that these techniques were capable of improving the detection of small ships in challenging maritime environments. Despite many published experimental examples, a thorough analytical investigation corroborating this claim is noticeably absent. This paper is based on a rigorous theoretical analysis founded on the statistical properties of a textured sea surface model in thermal noise with simultaneous consideration of a constant false alarm rate. Emphasis has been placed on the correct accounting for detrimental physical effects caused by the Doppler spectrum being split into nonoverlapping parts, which have not been sufficiently considered in the literature to date. The theoretical results are confirmed via simulations and are substantiated with real RADARSAT-2 data. The analysis in this paper has neither found theoretical nor empirical evidence that sublook correlation techniques outperform the classical detector based on the image magnitude. [ABSTRACT FROM AUTHOR]

This paper evaluates the capability of Sentinel-1 VH-polarized synthetic aperture radar signals, involving 738 scenes in the interferometric wide swath (IW) mode, for ocean surface wind speed retrieval using a novel subswath-based C-band cross-polarized ocean model. When compared with in situ measurements, it is observed that wind speed retrieval accuracy varies progressively along swath, with the most accurate wind speed retrievals being derived from subswath 3 [root-mean-square error (RMSE) of $1.82\,\,\text {m}\cdot \mathrm {s}^{-1}$ ], followed by subswath 2 (RMSE of $1.92\,\,\text {m}\cdot \mathrm {s}^{-1}$), while subswath 1 showed the lowest retrieval accuracy (RMSE of $2.37\,\,\text {m}\,\cdot \,\mathrm {s}^{-1}$). The average RMSE of wind speeds retrieved from all the three subswaths is $2.08\,\,\text {m}\,\cdot \,\mathrm {s}^{-1}$ under low-to-high wind speed regimes (wind speeds $< 25\,\,\text {m}\,\cdot \,\mathrm {s}^{-1}$). We further observed that the dependence of VH-polarized normalized radar cross section (NRCS) on incidence angle is attributable to the high and changing noise equivalent sigma zero (NESZ) with incidence angle under low-to-moderate wind speed regimes. And that strong VH-polarized radar signals could overcome the NESZ effect, thereby eliminating the dependence of VH-polarized NRCS on incidence angle under strong wind conditions. For Sentinel-1 IW mode VH-polarized data, the effect of NESZ could be ignored when wind speeds are greater than $15\,\,\text {m}\cdot \mathrm {s}^{-1}$ , as a better wind speed retrieval performance of these data has been recorded in this paper at wind speeds greater than $10\,\,\text {m}\cdot \mathrm {s}^{-1}$ , owing to an RMSE below $1.6\,\,\text {m}\cdot \mathrm {s}^{-1}$ and biases ranging from −0.5 to $0.5\,\,\text {m}\cdot \mathrm {s}^{-1}$. [ABSTRACT FROM AUTHOR]

This paper addresses the highly challenging problem of automatically detecting man-made structures especially buildings in very high-resolution (VHR) synthetic aperture radar (SAR) images. In this context, this paper has two major contributions. First, it presents a novel and generic workflow that initially classifies the spaceborne SAR tomography (TomoSAR) point clouds—generated by processing VHR SAR image stacks using advanced interferometric techniques known as TomoSAR—into buildings and nonbuildings with the aid of auxiliary information (i.e., either using openly available 2-D building footprints or adopting an optical image classification scheme) and later back project the extracted building points onto the SAR imaging coordinates to produce automatic large-scale benchmark labeled (buildings/nonbuildings) SAR data sets. Second, these labeled data sets (i.e., building masks) have been utilized to construct and train the state-of-the-art deep fully convolution neural networks with an additional conditional random field represented as a recurrent neural network to detect building regions in a single VHR SAR image. Such a cascaded formation has been successfully employed in computer vision and remote sensing fields for optical image classification but, to our knowledge, has not been applied to SAR images. The results of the building detection are illustrated and validated over a TerraSAR-X VHR spotlight SAR image covering approximately 39 km 2—almost the whole city of Berlin— with the mean pixel accuracies of around 93.84%. [ABSTRACT FROM AUTHOR]

This paper leads a discussion on how to form a Synthetic Aperture Radar (SAR) image without knowing the relative track. That is, within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection (FFBP) formulation with six free geometry parameters (per subaperture pair). These are tuned step by step until a sharp image is obtained. This innovative autofocus concept can compensate completely for an erroneous geometry. The FGA algorithm has been applied successfully on two ultrawideband (UWB) data sets, acquired by the CARABAS II system at very high frequency (VHF)-band. The relative tracks are known (measured accurately). We, however, adopt and modify a basic geometry model. A linear equidistant track at fixed altitude is initially assumed. Apart from deviations due to linearization, a ~2.5-m/s along-track velocity error is also introduced. Resulting FGA images are compared to reference images and verified to be focused. This indicates that it is feasible to form a wavelength-resolution SAR image at VHF-band without support from a motion measurement system. The execution time for the examples in this paper is about five times longer with autofocus than without. Hence, the FGA algorithm is now fit for use on a regular basis. [ABSTRACT FROM AUTHOR]

A generalized continuous wave synthetic aperture radar (GCW-SAR) concept is proposed in this paper. By using full-duplex radio frontend and continuous wave signaling, the GCW-SAR system can overcome a number of limitations inherent within the existing SAR systems and achieve high-resolution and wide-swath remote sensing with low-power signal transmission. Unlike the conventional pulsed SAR and the frequency-modulated continuous-wave SAR, the GCW-SAR reconstructs a radar image by directly correlating the received 1-D raw data after self-interference cancellation with predetermined location-dependent reference signals. A fast imaging algorithm, called the piecewise constant Doppler (PCD) algorithm, is also proposed, which produces the radar image recursively in the azimuth direction without any intermediate step, such as range compression and migration compensation, as required by conventional algorithms. By removing the stop-and-go assumption or slow-time sampling in azimuth, the PCD algorithm not only achieves better imaging quality but also allows for more flexible waveform and system designs. Analyses and simulations show that the GCW-SAR tolerates significant self-interference and works well with a large selection of various system parameters. The work presented in this paper establishes a solid theoretical foundation for next-generation imaging radars. [ABSTRACT FROM AUTHOR]

This paper deals with the assignment of persistent scatterers (PSs) to buildings represented by a 3-D city model. Affiliating PSs to real-world structures is highly relevant for two reasons. First, it facilitates interpretation of PS deformation estimates and can be even used to improve those estimates using advanced deformation models for complete structures. Second, such an assignment enables the compilation of a PS density map for the structures under investigation. This helps to mitigate the problem of opportunistic sampling, which is one of the major drawbacks of PS interferometry (PSI). Specifically, a framework in which the PSs are geometrically aligned with the city model and assigned to the bounding surfaces of the single models is outlined. Cases where such an assignment cannot be established are attributed to generalization of the city model or to locations where the reflection mechanism inducing the PS does not correspond to a real-world structure. From the assignments, a density map is compiled, and the main factors driving the PS density are identified and discussed: surface structure, shadowing, aspect dependency, and quasi-random effects (e.g., temporary changes due to building renovation activities). The test site for this paper is located in the inner city area of Berlin. PS results of two high-resolution spotlight TerraSAR-X data stacks of different pass directions are used. The buildings are represented by a level-of-detail 2 city model and an airborne light detection and ranging data set. [ABSTRACT FROM AUTHOR]

This paper introduces a bistatic fast backprojection synthetic aperture radar (SAR) algorithm that is available for different bistatic geometries. The proposed algorithm is tested with the bistatic CARABAS-like data, and the results indicate that the algorithm is a good candidate for bistatic SAR data processing. The image quality measurements are quite similar to the referenced values obtained with the bistatic global backprojection algorithm. That is, the peak sidelobe ratio (PSLR) is −13.7 dB in comparison to the referenced PSLR of −13.8 dB. The half-power beamwidths (HPBWs) measured on the cuts in $x$ and $y$ and the direction where the peak sidelobes locate are 2.8, 3.7, and 3.5 m, respectively, which are approximate to the referenced HPBWs. The small differences in the measured results mainly come from the interpolation step of the algorithm. [ABSTRACT FROM AUTHOR]

Recently, we have proposed a retrieval technique based on an original polarimetric two-scale model (PTSM), which is able to estimate the volumetric water content of bare soils from polarimetric synthetic aperture radar (SAR) data. In this paper, to extend the field of application of our retrieval technique to moderately vegetated soils, we combine the PTSM with a randomly oriented dipole-cloud volumetric scattering model, thus obtaining a polarimetric two-scale two-component model (PTSTCM). By using this model we show that, in principle, suitable combinations of the polarimetric SAR channels, i.e., “modified copolarized ratio” and “modified copolarized correlation coefficient,” are related only to the surface parameters because the dependence on the unknown volumetric contribution intensity cancels out. This allows us to retrieve soil moisture from L-band SAR data not only for bare soils but also in moderately vegetated areas, interested by a nonnegligible volumetric scattering contribution, provided that the double-bounce scattering component is negligible. In addition, describing the surface component by using the PTSM allows us to mitigate the well-known problem of overestimating the volume component, which affects most model-based target decompositions and that may lead to the so-called “negative power problem.” Both the performance and validity limits of the estimation method are assessed by comparing the obtained soil-moisture retrieval results to “in situ” measurements. To this aim, data from SMEX'03 and AGRISAR'06 campaigns available in literature are considered. They refer to sites with a flat topography. In particular, we employ the AGRISAR database, which includes data from several fields covering a period that spans all the phases of vegetation growth, to explore the validity range of the method in terms of vegetation height. Results of PTSTCM are also compared with those of available three-component methods (3CMs) employing more simplified surface scattering models. It has turned out that the use of the PTSTCM provides more accurate results for low vegetation (average modulus of soil moisture relative error for vegetation height smaller than 50 cm: 18.5% for the PTSTCM and 34% for the 3CM). Conversely, for higher vegetation, 3CMs should be more conveniently employed (average modulus of relative error for vegetation height greater than 50 cm: 17.5% for the 3CM and about 100% for the PTSTCM). A simple method to adaptively and automatically (i.e., based on measured data) select between PTSTCM and 3CM on a pixel-by-pixel basis is finally suggested, leading to a less than 20% average modulus of relative error on the retrieved soil moisture for the considered fields over the entire vegetation growth cycle. [ABSTRACT FROM PUBLISHER]

In spaceborne synthetic aperture radar, the sliding spotlight mode can acquire high resolution and large azimuth scene size simultaneously. However, when the resolution is very high and the azimuth scene size is large, the traditional hyperbolic range model (HRM) is inaccurate and the variation of the equivalent velocity in azimuth dimension cannot be ignored. Thus, the traditional imaging algorithms based on HRM are no longer available. For this problem, this paper proposes an equivalent acceleration range model, which can precisely take into account the spaceborne curved orbit. Then, velocity scaling algorithm based on this new range model is proposed to meet the needs of very high resolution and large azimuth scene size. The results of the simulation validate the effectiveness of the new range model and the imaging algorithm. [ABSTRACT FROM PUBLISHER]

This paper deals with signal reconstruction for multichannel high-resolution wide-swath synthetic aperture radar (HRWS-SAR) systems. One of the commonly used algorithms for processing HRWS-SAR data is Krieger's digital beamforming (DBF) algorithm. This algorithm works quite well for cases with uniform space–time sampling as well as moderately nonuniform sampling. However, for cases with highly nonuniform sampling, Krieger's DBF algorithm in its original form suffers from a severe degradation in the signal-to-noise ratio, and for cases with coinciding sampling, this algorithm even fails to function. In this paper, we will solve these problems such that an improved DBF (IDBF) algorithm is developed. The key of the IDBF algorithm consists of two procedures: The first one implements an operation called ambiguity-index screening, which is based on two novel quantities, termed the equivalent sampling spacing and the effective reconstructed Doppler bandwidth; and the other key procedure implements a Doppler-spectrum weighting based on a newly defined parameter that is termed the maximum-to-minimum ratio of the noise spectrum. Simulation results show that the newly proposed IDBF algorithm shares a pronounced improvement in the imaging performance over Krieger's DBF algorithm. Moreover, simulation results also demonstrate that the IDBF algorithm exhibits a more robust and consistent overall performance than several other existing reconstruction algorithms. [ABSTRACT FROM PUBLISHER]

This paper presents a detailed characterization of sea/ocean clutter returns at X-band, imaged by TerraSAR-X (TSX) mission from the radiometric, statistical, and polarimetric standpoints. Different TSX data takes, covering the typical spaceborne incidence angle region (20°–45°), are analyzed: dual-polarized (dual-pol) and experimental quad-polarized (quad-pol) data have been used. The thermal noise of the receiver for quad-pol data turns out to be an important limitation in the sea characterization from TSX, particularly at high incidence angles (above 36°), where low signal-to-noise ratios (SNRs) can impair the proper data distribution fitting and the polarimetric backscattering description. Statistical analysis shows large deviation from Gaussianity, indicating presence of texture, mainly in the small incidence region (20°–36°), with favorable SNR conditions. The different polarimetric features revealed contribution of nonpolarized scattering, related to the presence of breaking waves. This paper also proposes and evaluates an extension of the well-known X-Bragg model, named X2-Bragg (extended-extended Bragg), which properly accounts for the impact of thermal noise and sea clutter temporal decorrelation, due to the dual receive antenna (DRA) acquisition mode. Such additional decorrelation sources, if not properly analyzed and accounted for in the physical-based model description, could lead to an incorrect interpretation of the polarimetric properties and the related erroneous geophysical parametric inversion from the real data. In this sense, the X2-Bragg proves its fitting to the experimental data, quantifying accordingly the presence of nonpolarized scattering in terms of the roughness parameter \beta1. [ABSTRACT FROM AUTHOR]

Since the SEASAT mission in 1978, satellite-based synthetic aperture radar (SAR) images have been used to study oceanic internal waves. Internal waves become visible in SAR images because their orbital currents modulate the surface roughness. While this leads to an accurate spatial representation of internal wave patterns, the complexity of the imaging mechanism makes it difficult to derive actual currents and internal wave amplitudes from SAR signatures. We demonstrate in this paper how a more robust parameter retrieval is possible with along-track interferometric SAR (InSAR) data that resolve amplitudes and temporal phase changes of the backscattered signal together, the latter of which are directly related to the scatterers' line-of-sight velocities. Our example data set, which was acquired by TerraSAR-X in Dual Receive Antenna mode at Dongsha (South China Sea), exhibits strong signatures of internal waves in the interferogram amplitude and phase. We use a simple internal soliton parameterization and a numerical radar imaging model to find a plausible combination of internal wave parameters, which leads to good agreement between simulated and observed signatures. Testing the sensitivity of radar amplitude and phase signatures to various parameters, we show that along-track InSAR data should generally permit more accurate and less ambiguous internal wave parameter retrievals than conventional SAR images. [ABSTRACT FROM PUBLISHER]

In this paper, the motion parameters’ estimation problem in synthetic aperture radar (SAR) imaging is extended to the multidimensional case, and the azimuth signal of a moving target with velocities and accelerations in three directions is modeled as a polynomial-phase signal (PPS). To estimate the multidimensional motion parameters of the moving target from the azimuth PPS, a multi-SAR system is required. On this basis, a new method based on the cubic phase function (CPF) is proposed to estimate the Doppler phase coefficients (DPCs) of the PPS. And, all the first- and second-order motion terms can be derived from the DPC. Experimental results have shown that, using the proposed scheme, the motion parameters can be accurately estimated in high signal-to-noise ratio scenarios. [ABSTRACT FROM AUTHOR]

Detecting moving targets in synthetic aperture radar (SAR) imagery has recently gained a lot of interest as a way to augment optical moving target detection and classification in adverse (e.g., cloudy) weather conditions. In this paper, we primarily focus on the problem of detecting and imaging moving targets in single-channel (or summed multichannel) SAR data. Single-channel-based methods provide the ability to do detection well below the normal minimum detectable velocity (MDV) of multichannel-based GMTI. This can be particularly important for small radar antennas, which tend to have high conventional GMTI MDV. We also show results for multiple channel geolocation after single-channel detection and imaging. The algorithms consist of the following steps. We first suppress the stationary scene by comparing noncoherent time-subimages. We then detect the movers by applying a set of possible motion corrections to the image and use a novel matched filter to detect the movers in this space. We can then image the moving targets using standard SAR focusing techniques and geolocate the movers using multichannel (if available) along-track interferometry. We demonstrate and evaluate our algorithms using data collected from the Lincoln Multimission ISR Testbed airborne radar system. [ABSTRACT FROM AUTHOR]

It has been previously demonstrated that it is possible to perform remote vibrometry using synthetic aperture radar (SAR) in conjunction with the discrete fractional Fourier transform (DFrFT). Specifically, the DFrFT estimates the chirp parameters (related to the instantaneous acceleration of a vibrating object) of a slow-time signal associated with the SAR image. However, ground clutter surrounding a vibrating object introduces uncertainties in the estimate of the chirp parameter retrieved via the DFrFT method. To overcome this shortcoming, various techniques based on subspace decomposition of the SAR slow-time signal have been developed. Nonetheless, the effectiveness of these techniques is limited to values of signal-to-clutter ratio ≥5 dB. In this paper, a new vibrometry technique based on displaced-phase-center antenna (DPCA) SAR is proposed. The main characteristic of a DPCA-SAR is that the clutter signal can be canceled, ideally, while retaining information on the instantaneous position and velocity of a target. In this paper, a novel method based on the extended Kalman filter (EKF) is introduced for performing vibrometry using the slow-time signal of a DPCA-SAR. The DPCA-SAR signal model for a vibrating target, the mathematical characterization of the EKF technique, and vibration estimation results for various types of vibration dynamics are presented. [ABSTRACT FROM AUTHOR]

This paper presents the first experimental demonstration of the virtual bandwidth synthetic aperture radar (VB-SAR) imaging scheme. VB-SAR is a newly developed subsurface imaging technique which, in stark contrast to traditional close proximity ground penetrating radar schemes, promises imaging from remote standoff platforms such as aircraft and satellites. It specifically exploits the differential interferometric SAR (DInSAR) phase history of a radar wave within a drying soil volume to generate high-resolution vertical maps of the scattering through the soil volume. For this study, a stack of C-band vertically polarized DInSAR images of a sandy soil containing a buried target was collected in the laboratory while the soil moisture was varied--first during controlled water addition, and then during subsequent drying. The wetting image set established the moisture-phase relationship for the soil, which was then applied to the drying DInSAR image set using the VB-SAR scheme. This allowed retrieval of high-resolution VB-SAR imagery with a vertical discrimination of 0.04 m from a stack of 1-m vertical resolution DInSAR images. This paper unequivocally shows that the basic principles of the VB-SAR technique are valid and opens the door to further investigation of this promising technique. [ABSTRACT FROM AUTHOR]

Polarimetric coherence, which has the potential to reveal physical properties of scatterers, is an important source for polarimetric synthetic aperture radar (PolSAR) data investigation. Target structure and orientation relative to the PolSAR illumination direction are key factors affecting the polarimetric coherence degree. The relative orientation between a sensor and a target can be adjusted using the rotating processing along the radar's line of sight. The main idea of this paper is to extend the traditional polarimetric coherence at a given rotation state (θ = 0) to the rotation domain (θ ∈ [-π, π)) along the radar's line of sight for hidden information exploration. A visualization and characterization tool named as a polarimetric coherence pattern for two arbitrary polarization channels is proposed and developed. This interpretation tool is able to view the variation of polarimetric coherence in the rotation domain containing rich orientation diversity information which is seldom considered. A set of characterization features are derived to completely describe a polarimetric coherence pattern thereafter. Experimental studies with unmanned aerial vehicle SAR (UAVSAR) PolSAR data over crop areas have validated that polarimetric coherence patterns vary in terms of polarization combinations and crop types. The proposed characterization features show good potential to differentiate polarimetric responses from different land covers. Furthermore, a classification scheme combining the selected proposed features and the commonly used roll-invariant features is developed for quantitative and application investigation. Comparison studies with both UAVSAR and Airborne SAR (AIRSAR) data clearly demonstrate the superiority of the proposed classification to the conventional classification with only roll-invariant features. The overall classification accuracies for the seven and eleven land covers of UAVSAR and AIRSAR data are, respectively, increased from 90.21% and 93.87% to 95.12% and 94.63% by the proposed classification scheme. This paper also demonstrates the importance of and potential for utilizing the complementary advantages of roll-invariant features and the proposed roll-variant features. [ABSTRACT FROM AUTHOR]

Atmospheric refraction in the troposphere causes the propagation speed of electromagnetic signals to be less than the light speed. This creates a difference between the actual propagation path delay and the distance of the geometrical straight-line path, i.e., a quantity known as the tropospheric delay. As classical imaging algorithms for spaceborne synthetic aperture radar (SAR) do not take the tropospheric delay into account, imaging filters are designed based on the assumption of rectilinear propagation with the light speed. Therefore, a residual phase exists in imaging results, which affects focusing quality under the condition of high resolution. In order to compensate for the impact of tropospheric delay on focusing performance, this paper modifies the spaceborne SAR echo model and then proposes an imaging compensation algorithm. The key to this algorithm is to fit a range delay coefficient based on the European Geostationary Navigation Overlay Service model of zenith delay and Niell mapping function, which projects the zenith delay onto the looking direction. After range compensation, classical imaging, and azimuth compensation, which compose the proposed algorithm, the processed results are well focused. [ABSTRACT FROM PUBLISHER]

A new powerful constant false-alarm rate (CFAR) method is proposed for detecting moving ships in along-track interferometric synthetic aperture radar (ATI-SAR) images, based on the sea interferogram's magnitude and phase (SIMP) metric, presented in Part I of this paper. First, within the structure of the product model, a statistical model (hereafter simply termed \mathcalN_q) for the square root of SIMP metrics of sea clutter was developed by assuming the radar cross-sectional (RCS) components of the return follow a commonly used gamma distribution. Moreover, the parameter estimators of the presented model were analytically derived by applying the well-known “method of log cumulants” (MoLC). Finally, the CFAR threshold of moving ship detection, using the proposed model was given analytically. The experimental results of measured ATI-SAR data by NASA/JPL's AirSAR show that the proposed method gives good performance. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of focusing moving targets in synthetic aperture radar (SAR) images. This task is solved here by using an inverse SAR (ISAR) technique. The ISAR technique performs an autofocus procedure by implementing exhaustive search algorithms, which are improved by classical convex optimization, of functions based on image contrast or entropy. In this paper, we discuss the possibility to perform an autofocus ISAR technique by exploiting the estimation of the target Doppler parameters, namely the Doppler centroid and the Doppler rate, which are related to the target motion parameters. The present algorithm is based on the reuse of efficient autofocus approaches that are classically used in direct SAR imaging. The effectiveness of the proposed method is tested on COSMO-SkyMed Spotlight SAR data of maritime targets. Furthermore, the proposed Doppler parameter estimation algorithm is compared with a well-known ISAR technique, namely the image-contrast-based technique. [ABSTRACT FROM AUTHOR]

The retrieval of flooding levels with high-resolution (HR) synthetic aperture radar (SAR) images is presented in this paper. A new framework is proposed. It is based on the inversion of theoretical scattering models initially developed for nonflooded urban areas and here adapted to the flooding case. Starting from the theory, two possible retrieval approaches have been developed and are the main topic of this paper: two possible retrieval approaches have been developed and are the main topic of this paper: the local Single Image Objects Aware (SIObA) and the global Two Image Area Aware (TIArA). These two approaches are conceived to be applicable under different working conditions and consequently holding different properties and reliability. For each of them, a different algorithm is derived and tested, and the retrieval results are validated on a meaningful data set of HR TerraSAR-X images relevant to the Gloucestershire (U.K.) flooding that occurred in year 2007. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) has received much attention due to its interesting application potentials, but effective waveform diversity design is still a technical challenge. In a MIMO SAR, each antenna should transmit a unique waveform, orthogonal to the waveforms transmitted by other antennas. The waveforms should have a large time-bandwidth product, low cross-correlation interferences, and a low peak-average ratio. To reach these aims, this paper proposes an orthogonal frequency division multiplexing (OFDM) chirp waveform with random matrix modulation. The designed waveforms are time-delay and frequency-shift decorrelated. Referring to MIMO SAR high-resolution imaging, the proposed OFDM chirp waveform parameters are optimally designed, and their performances are analyzed through the ambiguity function and range-Doppler-based MIMO SAR imaging algorithm. Extensive and comparative simulation results show that the waveforms have the superiorities of high range resolution, constant time domain and almost constant frequency-domain modulus, large time-bandwidth product, low peak-average ratio, and low time-delay and frequency-shift correlation peaks. More importantly, this scheme can easily generate over three orthogonal waveforms with a large time-bandwidth product. [ABSTRACT FROM PUBLISHER]

This paper describes the first application of the fully adaptive radar (FAR) framework for cognition to the process of radar imaging. A cognitive radar adapts to its surroundings based on its perceptions of the environment, offering improved performance for a multitude of radar applications. We implemented an autoregressive backprojection (ARBP) imaging technique for the circular synthetic aperture radar (SAR) video within the structure of the FAR framework, allowing the system to adapt its down-range and cross-range resolutions to keep the detected targets visually distinct. This simple demonstration paves the way for more advanced adaptive imaging scenarios in the future. Application of the technique to the GOTCHA volumetric SAR data set demonstrated its capability in a realistic scenario in the presence of clutter and limited target persistence. When applied to the GOTCHA data set, the adaptive imaging system’s cumulative executive optimization cost (CEOC), which is used to quantify the overall performance, was 41.3% smaller than the constant, fine resolution case. This significant improvement in CEOC comes at the expense of occasionally failing to meet imaging performance goals as the system adjusts to changes in the environment. [ABSTRACT FROM AUTHOR]

Although basic understanding of the synthetic aperture radar (SAR) imaging mechanism of ocean waves has been achieved, challenges still remain. In this paper, a large number of quad-polarized SAR images are analyzed to help assess how the standard SAR imaging transformation applies to all polarization channels. Foremost, the azimuth cutoff, a parameter essentially governed by the detected wave motions, is today solely related to radar configuration and the ocean wave spectrum but not to the polarization configuration. As obtained, the analyses based on quad-polarized Radarsat-2 and Gaofen-3 products document the distinct dependence of azimuth cutoff on polarization and incidence angle. Especially for cross-polarized VH measurements, azimuth cutoff estimates are generally larger than copolarized HH ones, the latter already being larger than values estimated under VV configuration. This trend increases with the incidence angle. The systematic comparisons between SAR measurements and simulations further demonstrate that the present SAR nonlinear transformation may not properly take into account the differing coherence time associated with the multi-polarized observation of ocean scenes. In particular, to reproduce the large azimuth cutoff parameters of cross-polarized images, a reduced coherence time shall be expected. This measurable sensitivity shall enhance the capabilities of polarized SAR systems to precisely derive more ocean surface properties, especially the influence of wave breakers, by combining both the copolarization and cross-polarization measurements. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) is an active microwave imaging sensor with the capability of working in all-weather, all-day to provide high-resolution SAR images. Recently, SAR images have been widely used in civilian and military fields, such as ship detection. The scales of different ships vary in SAR images, especially for small-scale ships, which only occupy few pixels and have lower contrast. Compared with large-scale ships, the current ship detection methods are insensitive to small-scale ships. Therefore, the ship detection methods are facing difficulties with multi-scale ship detection in SAR images. A novel multi-scale ship detection method based on a dense attention pyramid network (DAPN) in SAR images is proposed in this paper. The DAPN adopts a pyramid structure, which densely connects convolutional block attention module (CBAM) to each concatenated feature map from top to bottom of the pyramid network. In this way, abundant features containing resolution and semantic information are extracted for multi-scale ship detection while refining concatenated feature maps to highlight salient features for specific scales by CBAM. Then, the salient features are integrated with global unblurred features to improve accuracy effectively in SAR images. Finally, the fused feature maps are fed to the detection network to obtain the final detection results. Experiments on the data set of SAR ship detection data set (SSDD) including multi-scale ships in various SAR images show that the proposed method can detect multi-scale ships in different scenes of SAR images with extremely high accuracy and outperforms other ship detection methods implemented on SSDD. [ABSTRACT FROM AUTHOR]

Enhancing the contrast of target and clutter is a crucial issue in synthetic aperture radar (SAR) image target detection. In this paper, we define a novel subspace, called minimal clutter-to-signal ratio (MCSR) subspace, which can minimize the clutter-to-signal ratio (CSR) by projecting the feature vector to the subspace. Based on MCSR, a novel polarimetric contrast enhancement method is proposed. The MCSR subspace is learned based on the commonly used polarimetric feature vectors extracted from the labeled training SAR image pixels. The feature vectors extracted form candidate SAR image pixels are projected to the MCSR subspace. By calculating the square norm of each transformed feature vector, an enhanced image can be obtained. It is demonstrated that the existing optimization of polarimetric contrast enhancement (OPCE) is a special case of the proposed method to some extent. Experimental results show that our method outperforms the traditional OPCE method on the RadarSat-2 SAR data. [ABSTRACT FROM AUTHOR]

The main challenging problems in ocean current retrieval from along-track interferometric (ATI)-synthetic aperture radar (SAR) are phase calibration and wave bias removal. In this paper, a method based on differential InSAR (DInSAR) technique for correcting the phase offset and its variation is proposed. The wave bias removal is assessed using two different Doppler models and two different wind sources. In addition to the wind provided by an atmospheric model, the wind speed used for wave correction in this work is extracted from the calibrated SAR backscatter. This demonstrates that current retrieval from ATI-SAR can be completed independently of atmospheric models. The retrieved currents, from four TanDEM-X (TDX) acquisitions over the Öresund channel in the Baltic Sea, are compared to a regional ocean circulation model. It is shown that by applying the proposed phase correction and wave bias removal, a good agreement in spatial variation and current direction is achieved. The residual bias, between the ocean model and the current retrievals, varies between 0.013 and 0.3 m/s depending on the Doppler model and wind source used for wave correction. This paper shows that using SAR as a source of wind speed reduces the bias and root-mean-squared-error (RMSE) of the retrieved currents by 20% and 15%, respectively. Finally, the sensitivity of the sea current retrieval to Doppler model and wind errors are discussed. [ABSTRACT FROM AUTHOR]

In this paper, a feature extraction technique based on the electromagnetic (EM) representation of radar signals is presented. In particular, we focus on ground-penetrating radar (GPR) imaging, where we model the backscatter from varying 2-D geometric shapes with arbitrary local coordinate rotations. Due to the electrically small nature of buried targets and the bending of the radar signal at the air–soil interface, we focus on exact methods to model the surface current density induced on scattering surfaces. Overcomplete basis sets are derived from the EM descriptions to represent the scene sparsely. From this proposed modeling framework, we devise a novel methodology to exploit the prediction of scattering behavior to extract features for classification from radar scenes when multiple buried scattering surfaces are present. We see that our method can identify and reconstruct buried scattering geometries in the presence of false targets that are brought about by the nonlinear nature of the exact EM modeling methods. A noniterative algorithm based on the conjugate of Green’s function is developed to solve for the surface current in an unknown domain using multifrequency, multiaperture data. Our modeling and feature extraction algorithms are numerically validated for different target shapes buried in lossy soil profiles. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of retrieving soil moisture over a grassland alpine area from Synthetic Aperture Radar (SAR) data using a statistical algorithm trained by simulations of a physical model. A time series of C-band VV-polarized Wide Swath images acquired by Envisat Advanced SAR (ASAR) in the snow-free periods of 2010 and 2011 was simulated using a discrete radiative transfer model (RTM). The test area was located in the Mazia valley, South Tyrol (Italy), where the main land types are meadows and pastures. Soil moisture was collected from five meteorological stations, two of which situated in meadows and the rest in pastures. The smallest and the highest RMSEs of the RTM simulations were 0.78 dB and 1.91 dB, respectively. After backscattering simulation, the top soil moisture was estimated using Gaussian Process Regression (GPR). GPR was trained with the backscatter model simulations (including terrain features) for 2010, and then used to predict moisture from radar observations acquired in 2011. The relative importance of different input features was also assessed. The RMSE of the predicted soil moisture for the largest training data set (including aspect as a terrain feature) was 5.6% Vol. and the corresponding correlation coefficient was 0.84. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a feature-tracking algorithm for sea ice drift retrieval from a pair of sequential satellite synthetic aperture radar (SAR) images. The method is based on feature tracking comprising feature detection, description, and matching steps. The approach exploits the benefits of nonlinear multiscale image representations using accelerated-KAZE (A-KAZE) features, a method that detects and describes image features in an anisotropic scale space. We evaluated several state-of-the-art feature-based algorithms, including A-KAZE, Scale Invariant Feature Transform (SIFT), and a very fast feature extractor that computes binary descriptors known as Oriented FAST and Rotated BRIEF (ORB) on dual polarized Sentinel-1A C-SAR extra wide swath mode data over the Arctic. The A-KAZE approach outperforms both ORB and SIFT up to an order of magnitude in ice drift. The experimental results showed high relevance of the proposed algorithm for retrieval of ice drift at subkilometre resolution from a pair of SAR images with 100-m pixel size. From this paper, we found that feature tracking using nonlinear scale-spaces is preferable due to its high efficiency against noise with respect to image features compared with other existing feature tracking alternatives that make use of Gaussian or linear scale spaces. [ABSTRACT FROM PUBLISHER]

In high-resolution synthetic aperture radar (SAR) images, the spatial pattern of a homogenous region conveys rich information regarding the specific scatterers being imaged. Analytical modelings of both scattering and imaging processes are critical to better interpret a specific scatterer’s appearances in SAR imagery and thereafter quantitatively retrieve its physical parameters. Small-scale rough surface scattering represents one of the mostly common scattering mechanisms and yet its SAR image characteristics have not been well studied. This becomes more critical in millimeter-wave/terahertz regime as smooth surfaces would become slightly rough under millimeter/submillimeter wavelengths. In this paper, we recast the small perturbation method (SPM) approximation of rough surface scattering under the deterministic finite-length surface condition. By ignoring evanescent waves, a simplified SPM solution for rough facet is derived as well as the analytical form of its SAR image under the conventional setup. Then, we reformulate the scattering imaging process of rough facet as a signal processing chain that further reveals the underlying mechanism of rough surface as imaged by radar. The proposed method is extensively validated against the method of moments in terms of both scattering coefficients and imaging patterns. It is found that under the conventional SPM validity condition, the error of scattering coefficients is less than 1.5 dB, while the correlation between SPM-calculated and MoM-calcualted SAR images is larger than 0.9. The proposed model of rough facet SAR image could serve as the theoretical basis for parameter inversion and surface reconstruction. Preliminary cases of the inversion of rough surface spectrum using both simulated and real SAR image patches are presented. [ABSTRACT FROM PUBLISHER]

This paper evaluates the retrieval of soil moisture in the top 5-cm layer at 3-km spatial resolution using L-band dual-copolarized Soil Moisture Active-Passive (SMAP) synthetic aperture radar (SAR) data that mapped the globe every three days from mid-April to early July, 2015. Surface soil moisture retrievals using radar observations have been challenging in the past due to complicating factors of surface roughness and vegetation scattering. Here, physically based forward models of radar scattering for individual vegetation types are inverted using a time-series approach to retrieve soil moisture while correcting for the effects of static roughness and dynamic vegetation. Compared with the past studies in homogeneous field scales, this paper performs a stringent test with the satellite data in the presence of terrain slope, subpixel heterogeneity, and vegetation growth. The retrieval process also addresses any deficiencies in the forward model by removing any time-averaged bias between model and observations and by adjusting the strength of vegetation contributions. The retrievals are assessed at 14 core validation sites representing a wide range of global soil and vegetation conditions over grass, pasture, shrub, woody savanna, corn, wheat, and soybean fields. The predictions of the forward models used agree with SMAP measurements to within 0.5 dB unbiased-root-mean-square error (ubRMSE) and −0.05 dB (bias) for both copolarizations. Soil moisture retrievals have an accuracy of 0.052 m3/m3 ubRMSE, −0.015 m3/m3 bias, and a correlation of 0.50, compared to in situ measurements, thus meeting the accuracy target of 0.06 m3/m3 ubRMSE. The successful retrieval demonstrates the feasibility of a physically based time series retrieval with L-band SAR data for characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetation. [ABSTRACT FROM PUBLISHER]