Scanning Synthetic Aperture Radar Research Articles

System Design and Echo Preprocessing of Spaceborne Squinted Two-Dimensional Beam Scanning Synthetic Aperture Radar.

Conventional squinted sliding spotlight synthetic aperture radar (SAR) imaging suffers from substantial swath width reduction and complex processing requirements due to the continuous variation in the squint angle and the large range cell migration (RCM) throughout the data acquisition interval. A novel two-dimensional (2D) beam scanning mode for high-resolution wide swath (HRWS) imaging is proposed. The key to the novel imaging mode lies in the synchronous scanning of azimuth and range beams, allowing for a broader and more flexible imaging swath with a high geometric resolution. Azimuth beam scanning from fore to aft was used to improve the azimuth resolution, while range beam scanning was adopted to illuminate the oblique wide swath to avoid the large RCM and the serious swath width reduction. Compared with the conventional sliding spotlight mode, both the swath width and swath length could be extended. According to the echo model of this imaging mode, an echo signal preprocessing approach is proposed. The key points of this approach are range data extension and azimuth data upsampling. A designed system example with a resolution of 0.5 m, swath width of 60 km, and azimuth coverage length of 134 km is presented. Furthermore, a simulation experiment on point targets was carried out. Both the presented system example and imaging results of point targets validated the proposed imaging mode.

Sea ice classification of TerraSAR-X ScanSAR images for the MOSAiC expedition incorporating per-class incidence angle dependency of image texture

Abstract. We provide sea ice classification maps of a sub-weekly time series of single (horizontal–horizontal, HH) polarization X-band TerraSAR-X scanning synthetic aperture radar (TSX SC) images from November 2019 to March 2020, covering the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This classified time series benefits from the wide spatial coverage and relatively high spatial resolution of TSX SC data and is a useful basic dataset for future MOSAiC studies on physical sea ice processes and ocean and climate modeling. Sea ice is classified into leads, young ice with different backscatter intensities, and first-year ice (FYI) or multiyear ice (MYI) with different degrees of deformation. We establish the per-class incidence angle (IA) dependencies of TSX SC intensities and gray-level co-occurrence matrix (GLCM) textures and use a classifier that corrects for the class-specific decreasing backscatter with increasing IAs, with both HH intensities and textures as input features. Optimal parameters for texture calculation are derived to achieve good class separation while maintaining maximum spatial detail and minimizing textural collinearity. Class probabilities yielded by the classifier are adjusted by Markov random field contextual smoothing to produce classification results. The texture-based classification process yields an average overall accuracy of 83.70 % and good correspondence to geometric ice surface roughness derived from in situ ice thickness measurements (correspondence consistently close to or higher than 80 %). A positive logarithmic relationship is found between geometric ice surface roughness and TSX SC HH backscatter intensity, similar to previous C- and L-band studies. Areal fractions of classes representing ice openings (leads and young ice) show prominent increases in middle to late November 2019 and March 2020, corresponding well to ice-opening time series derived from in situ data in this study and those derived from satellite synthetic aperture radar (SAR) and optical data in other MOSAiC studies.

A Joint Parameters Estimation Method for Azimuth Multichannel TOPS SAR

Multi-channel parameter estimation is a key technology for azimuth multi-channel terrain observation by progressive scans synthetic aperture radar (MC TOPS SAR) systems. Normally, for the traditional multichannel parameter estimation algorithms, the mismatch parameters are concluded as phase error, baseline error, and Doppler centroid. The beam rotation speed error is ignored. However, for MC TOPS SAR, beam rotation speed error will degrade the reconstruction performance of the Doppler spectrum. Moreover, only part of the mismatch parameters can be estimated for the traditional algorithms. To address those problems, a joint parameters estimation algorithm for TOPS SAR based on spatial time cross-correlation coefficient (STCCC) is proposed. Combined with phase wrapping and the least-squares method (LSM), the algorithm is capable of realizing a joint parameters estimation of channel consistency error, azimuth baseline error, Doppler centroid frequency, and beam rotation speed estimation without iteration. The real data processing result shows that the method can effectively realize MC TOPS SAR data error estimation.

An adaptive scalloping suppression method for spaceborne ScanSAR images based on pre-estimation and weighted filtering

Spaceborne scanning synthetic aperture radar (ScanSAR) is widely used in global observations due to its ability to perform wide-swath mapping in the range direction. However, its special working mode causes scalloping, which reduces the quality of images and affects subsequent applications. According to its characteristics, an adaptive method based on pre-estimation and weighted filtering is proposed in this paper to suppress scalloping in the image domain. First, the azimuth intensity distribution of the image after scalloping suppression is estimated, which is used for scene stationarity test. Then, the images that cannot meet the stationary standard are segmented into subimages using maximum entropy principle and mathematical morphology. Finally, an algorithm based on adaptive weighted filtering is introduced to suppress scalloping, and the suppressed subimages are fused to obtain final results. The performance of the proposed method is tested with real ScanSAR data from the Gaofen-3 (GF-3) satellite. The experimental results indicate that the effect of scalloping suppression is excellent, since the depth of scalloping can be suppressed to approximately 0.3 dB. Notably, the proposed system is efficient in processing large-area images, such as GF-3 ScanSAR images whose actual width is more than 300 km. The entire process requires no parameter adjustment, and the proposed method is suitable for various complex scenes. The effectiveness, high efficiency, adaptability and robustness of the proposed system are verified.

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

In recent years, the number of geological disasters in Sichuan Province has significantly increased due to the influence of earthquakes and extreme climate, as well as the disturbance to the geological environment by human activities. Thus, geological disaster monitoring is particularly important, which can provide some scientific basis for disaster prevention and reduction. In this paper, the interferometric synthetic aperture radar (InSAR) technology was introduced to monitor potential geological hazards, taking parts of Dujiangyan City, Wenchuan County, and Mao County in Sichuan Province, China as examples. Firstly, the data such as Sentinel-1A Terrain Observation with Progressive Scans (TOPS) Synthetic Aperture Radar (SAR) images and Precision Orbit Determination (POD) precise orbit ephemerides from 2018 to 2020, high-resolution optical satellite images and Digital Elevation Model (DEM) were collected. Secondly, the Differential InSAR (D-InSAR), Persistent Scatterer InSAR (PS-InSAR), Small Baseline Subset InSAR (SBAS-InSAR), Offset-Tracking, and Distributed Scatterer InSAR (DS-InSAR) algorithms were used to invert the surface deformation of the study area. Thirdly, according to the deformation results obtained by experiments, we used GF-1 and GF-2 optical images as a reference and combine the experimental results of InSAR algorithms to delineate the areas affected by geological disasters. A total of 49 geological disaster areas were obtained, mainly including landslides, collapses, and debris flow. Through field verification, the overall accuracy rate of InSAR deformation monitoring achieved 69.23%, and the accuracy rate of new potential hazards monitoring reached 63.64%. Among all InSAR methods, the DS-InSAR method outperformed and monitored the geological disaster areas well. Finally, the study area was divided into three elevation intervals and the applicability of different InSAR algorithms in different elevation intervals was discussed.

Study on Airborne Near-Nadir TOPS SAR Imaging With Attitude Angle Error

Combined with terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), near-nadir SAR (N-SAR) system has great potential for the surface water and ocean topography (SWOT) observation. However, one practical problem of the airborne N-SAR is the non-ideal attitude angle caused by the environment. Normally, the influence of attitude angle error can be considered as a constant squint angle of the system. However, in fact, for the near-nadir SAR system with TOPS SAR mode, the attitude angle error will cause a non-ideal 2-dimensional space-variant Doppler centroid for the receiving data and cause the traditional imaging algorithm failure. To deal with such problems, an imaging algorithm with attitude angle estimation for the near-nadir TOPS SAR system is proposed in this paper. Firstly, the influence of attitude angle error and the signal properties are analyzed. Secondly, based on the analysis, an attitude angle estimate algorithm (AAE), utilizing the nonlinear least square method (NLSM) and minimum entropy criterion, is proposed. Then, based on the estimated altitude angle, without data blocking, a full data imaging algorithm (FDA) is proposed. Its main idea is to obtain an un-ambiguous azimuth spectrum and design an appropriate range-variant azimuth filter through frequency chirp scaling (FCS). The numerical simulations and real data processing demonstrate that the proposed algorithm has good performance on attitude angle error estimation and well-focused image obtaining.

Differential Interferometry over Sentinel-1 TopSAR Images as a Tool for Water and Tillage Soil Erosion Analysis

Erosion is a major problem on agricultural lands in Europe. Erosion measurement tools have traditionally been focused on delocalized quantification but without mapping the real places inside the basin where the erosion took effect. In this article, we use new space missions, such as Sentinel-1, and the opportunity they offer to obtain SAR (Synthetic Aperture Radar) images with high frequency, resolution, range, and, above all, availability to enable the application of techniques, like differential interferometry, in new fields. We propose to measure ground deformation caused by water and tillage erosion in small agricultural basins using TopSAR (Terrain Observation with Progressive Scans SAR, Synthetic Aperture Radar) images acquired by the Sentinel-1 mission, after previously verifying the accuracy of these measurements through comparison with measurements from a LIDAR (Light Detection and Ranging) system. The results of this work confirm the potential of monitoring erosion in agricultural basins with differential interferometry over Sentinel-1 TopSAR images. Its capabilities have been successfully tested in different conditions related to agricultural tasks without precipitation or storm events. This technique makes it possible to study both water and tillage erosion and sedimentation processes and even to test the efficiency of anti-erosion measures in the field or to verify the results of different management practices over time.

A Novel Mosaic Method for Spaceborne ScanSAR Images Based on Homography Matrix Compensation

Accurate and efficient image mosaicking is essential for generating wide-range swath images of spaceborne scanning synthetic aperture radar (ScanSAR). However, the existing methods cannot guarantee the accuracy and efficiency of stitching simultaneously, especially when mosaicking multiple large-area images. In this paper, we propose a novel image mosaic method based on homography matrix compensation to solve the mentioned problem. A set of spaceborne ScanSAR images from the Gaofen-3 (GF-3) satellite were selected to test the performance of the new method. First, images are preprocessed by an improved Wallis filter to eliminate intensity inconsistencies. Then, to reduce the enormous computational redundancy of registration, the overlapping areas of adjacent images are coarsely extracted using geolocation technologies. Furthermore, to improve the efficiency of stitching and maintain the original information and resolution of images, we deduce a compensation of homography matrix to implement downsampled images registration and original-size images projection. After stitching, the transitions at the edges of the images were smooth and seamless, the information and resolution of the original images were preserved successfully, and the efficiency of the mosaic was improved by approximately one thousand-fold. The validity, high efficiency and reliability of the method are verified.

Stable Scatterer Detection in Multi-Aperture Spaceborne-TX / Ground based-RX Bistatic SAR

Abstract This paper presents a detection method for stable scatterers (SS) used for single-pass resolution enhancement in spaceborne transmitter (TX) – ground based receiver (RX) bistatic Synthetic Aperture Radar (SAR). Resolution is improved by coherently focusing multiple sub-apertures, each sub-aperture being represented by the data received from a different sub-swath. This requires that the transmitting satellite operate in Terrain Observation with Progressive Scans SAR (TOPSAR) mode. Detecting which zones in the image are common and coherent among the sub-apertures is paramount to image quality and Signal to Noise Ratio (SNR).

Scalloping Suppression for ScanSAR Images Based on Modified Kalman Filter With Preprocessing

Scanning synthetic aperture radar (ScanSAR) mode is widely used in Earth observation because of its capability of acquiring wide-swath images with moderate resolution. However, due to the operation mechanism of ScanSAR mode, the acquired images often suffer from the scalloping problem, resulting in significant deterioration of image quality. In this article, a novel scalloping suppression method is proposed for ScanSAR images based on the modified Kalman filter with preprocessing. First, an image model is built to analyze the effect caused by scalloping. Then, a modified Kalman filter is proposed to estimate the intensity of scalloping. However, if the scene is complicated or the scalloping effect is strong, the Kalman filter works with poor performance. Therefore, an innovative preprocessing operation is introduced, involving image segmentation and pixel value filling. Finally, the proposed method is verified by the GaoFen-3 (GF-3) and TerraSAR-X satellite images with different scenes. The results demonstrate that the proposed method can accommodate the complex scene well and achieve effective scalloping suppression.

Ground Cartesian Back-Projection Algorithm for High Squint Diving TOPS SAR Imaging

This article presents a fast back-projection (BP) algorithm based on subaperture (SA) image coherent combination in a downsampled Cartesian coordinate grid for high squint diving terrain observation by progressive scans (HSD-TOPS) synthetic aperture radar (SAR) ground plane imaging. A two-step spectrum compression (SC) method is proposed to coherently combine the aliasing SA images by exploiting the relationship between the wavenumber and the image frequency. The first-step SC is introduced to align the spectrum support region centers. The second-step SC effectively corrects the space-variant spectrum inclination. The proposed algorithm does not need interpolation in the process of image combination, which ensures the accuracy and the efficiency of the algorithm. Furthermore, the SC method is well-modified to suppress the sidelobes of the focused image. Simulation and measured data processing verify the effectiveness of the proposed method.

An Improved Full-Aperture ScanSAR Imaging Method Integrating the MIAA Based Aperture Interpolation

In the scanning synthetic aperture radar (ScanSAR) mode, the radar antenna sweeps through different range subswaths to image a wide swath. The full-aperture imaging algorithm for ScanSAR data has been widely used because it can be realized by exploiting the existing standard high-precision Stripmap SAR processor and does not require stitch processing in the azimuth. However, both the focused image and the interferogram achieved by full-aperture processing suffer from spikes. The spikes adversely affect the ScanSAR-related applications, such as target detection and interferometry. To effectively suppress the spikes, an improved algorithm based on the missing-data iterative adaptive approach (MIAA) is proposed in this manuscript. Besides, the proposed method can also improve the azimuth resolution of ScanSAR images. Simulation and experimental results demonstrate that this algorithm has better performance when processing ScanSAR data compared with existing methods.

Optimal Design of the Reflector Antenna to Improve Performance of C-Band Quad-Pol ScanSAR Systems

The performance of synthetic aperture radar (SAR) antenna determines the quality of images obtained from the spaceborne SAR system, and thus, SAR antenna should be designed to satisfy the target performance of SAR system. The performance indicators of a SAR system, such as ambiguity-to-signal ratio and resolution, also depend on the SAR operation mode. Therefore, it is important to consider the operation mode when designing an SAR antenna. In this paper, we analyzed the SAR antenna’s effect on ScanSAR (scanning synthetic aperture radar) which is a representative wide-swath mode and its quadrature-polarimetric (quad-pol) mode. In addition, we confirmed that the optimal reflector antenna for the C-band quad-pol ScanSAR system can be designed by analyzing the relation between the antenna size and the system performance.

An Automatic Method for Black Margin Elimination of Sentinel-1A Images over Antarctica

The Sentinel-1A satellite was launched in April 2014 with a primary C-Band terrain observation with progressive scans synthetic aperture radar (TOPSAR) onboard and has collected plenty of high-quality images for global change studies. However, low magnitude signals around image margins (black margins) does not preserve the normal standard level, influencing the potential usage with these data. Through image analysis, we find that the signal from black margin (BM) is highly dominated by the closest effective signals and the signal in BM shows an increasing trend along the direction from image boundary to image center. An edge detector is developed based on the signal characteristics of BM. Furthermore, an automatic method to discriminate and eliminate BM is designed. Images from both extra wide (EW) and interferometric wide (IW) swath observation modes, covering the land, ocean, and coast of the Antarctic, are taken to verify the robustness of our method. Through comparison with BM edges extracted by human interpretation, our method has the maximum BM edge extraction error of 1.9 ± 3.2 pixels. When considering perimeter (or area) difference along radial direction of BM edge, our method has an averaging extraction accuracy of −0.35 ± 0.11 (or 0.14 ± 1.38) pixels, which suggests that our method is effective and can be potentially used to eliminate BM for multidisciplinary applications of Sentinel-1 data.

Signal Modeling and Analysis for Elevation Frequency Scanning HRWS SAR

Elevation frequency scanning synthetic aperture radar (EF-SCAN SAR) can isolate range ambiguities in the range-frequency domain. Therefore, range ambiguity suppression can be accomplished through range-frequency bandpass filtering, which can outperform spatial filtering-based ambiguity suppression. In this article, the analytic space–time signal model of an intrapulse frequency scanning array is derived. Based on the analysis of the characteristics of this signal model, waveform design criteria for EF-SCAN SAR are developed to effectively separate the range ambiguities in the range frequency domain. The ground echo model of EF-SCAN SAR is also developed based on this space–time signal model. The impact of intrapulse frequency scanning on the performance of high-resolution and wide-swath (HRWS) imaging is analyzed based on the derivation and analysis of the echo spectrum. Finally, an imaging algorithm for EF-SCAN SAR is developed based on this analysis. Numerical simulations verify the effectiveness of the proposed waveform design criteria and imaging algorithm.

A High-Squint TOPS SAR Imaging Algorithm for Maneuvering Platforms Based on Joint Time-Doppler Deramp Without Subaperture

The beam steering of high-squint terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR) mounted on maneuvering platforms causes azimuth spectrum aliasing and nonlinear variation of the Doppler center with target azimuth position. A joint time-Doppler deramp (JTDD) based method is proposed and mainly contains two parts. First, for the azimuth spectrum aliasing, the unfolded 2-D spectrum is obtained by a modified linear deramp function in the azimuth time domain constructed from the 3-D motion parameters. After range cell migration correction (RCMC), the data supporting area in the azimuth time domain is expanded, and thus, aliased because of the nonlinear variation of Doppler center. Then, a nonlinear deramp operation in the Doppler domain is further proposed to obtain a nonaliasing signal. The proposed algorithm is efficient with less zero-padding due to the consideration of nonlinear components of Doppler center variation. Simulation and real SAR data processing are presented to validate the proposed algorithm.

ScanSAR Interferometry of the Gaofen-3 Satellite with Unsynchronized Repeat-Pass Images.

Gaofen-3 is a Chinese remote sensing satellite with multiple working modes, among which the scanning synthetic aperture radar (ScanSAR) mode is used for wide-swath imaging. synthetic aperture radar (SAR) interferometry in the ScanSAR mode provides the most rapid way to obtain a global digital elevation model (DEM), which can also be realized by Gaofen-3. Gaofen-3 ScanSAR interferometry works in the repeat-pass mode, and image pair non-synchronizations can influence its performance. Non-synchronizations can include differences of burst central times, satellite velocities, and burst durations. Therefore, it is necessary to analyze their influences and improve the interferometric coherence. Meanwhile, interferometric phase compensation and rapid DEM geolocation also need to be considered in interferometric processing. In this paper, interferometric coherence was analyzed in detail, followed by an iterative filtering method, which helped to improve the interferometric performance. Further, a phase compensation method for Gaofen-3 was proposed to compensate for the phase error caused by the unsynchronized azimuth time offset of image pair, and a closed-form solution of DEM geolocation with ground control point (GCP) information was derived. Application of our methods to a pair of Gaofen-3 interferometric images showed that these methods were able to process the images with good accuracy and efficiency. Notably, these analysis and processing methods can also be applied to other SAR satellites in the ScanSAR mode to obtain DEMs with high quality.

JAXA Annual Forest Cover Maps for Vietnam during 2015–2018 Using ALOS-2/PALSAR-2 and Auxiliary Data

Monitoring the temporal changes of forests is important for sustainable forest management. In this study, we investigated the potential of using multi-temporal synthetic aperture radar (SAR) images for mapping annual change in forest cover at a national scale. We assessed the robustness of using multi-temporal Phased Array L-band Synthetic Aperture Radar-2/Scanning Synthetic Aperture Radar (PALSAR-2/ScanSAR) mosaic images for forest mapping by comparison with single-temporal PALSAR-2 mosaic images for three test sites in North, Central, and Southern Vietnam. We then used a combination of multi-temporal PALSAR-2/ScanSAR images, multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) images, and Shuttle Radar Topography Mission (SRTM) images to map annual forest cover for mainland Vietnam during 2015–2018. Average overall accuracies of our forest/non-forest (FNF) maps (86.6% ± 3.1%) were greater than recent maps of Japan Aerospace Exploration Agency (JAXA, (77.5% ± 3.2%)) and European Space Agency (ESA, (85.4% ± 1.6%)). Our estimates of mainland Vietnam’s forest area were close to that of the Vietnamese government. A comparison of the spatial distribution of forest estimated from JAXA and ESA FNF maps showed that our FNF map in 2015 agreed relatively well with the ESA map, with 77% of pixels being consistent. This study demonstrates the merit of using multi-temporal PALSAR-2/ScanSAR images for annual forest mapping at a national scale.

A Partitioned Deceptive Jamming Method Against TOPSAR

A deceptive jamming method against terrain observation by progressive scans synthetic aperture radar (TOPSAR) that considers the effect of the changing relative position between a jammer and a TOPSAR platform is presented. The method can generate flexible false targets with varying Doppler centroids. The jamming problem is decomposed into simpler subproblems of the same type, according to the relative position between the jammer and the satellite. The partial deceptive jamming modulation function can be pregenerated before the radar parameter reconnaissance. The partitioned scheme produces multiple deceptive jamming batches in parallel on the TOPSAR image to protect large regions of interest.

Imaging algorithm for multi‐channel scan synthetic aperture radar with channel error estimation and compensation

The wide swath synthetic aperture radar (SAR) imaging with a fine resolution is fundamentally a contradiction in conventional SAR imaging. To meet the demand of high-resolution width swath (HRWS) imaging, multi-channel scan mode has received a great deal of attention as a promising concept to realise HRWS observation. In this article, based on extended Chirp Scaling algorithm, an imaging algorithm for multi-channel scan SAR is proposed. Furthermore, channel error estimation and compensation are the key point in multi-channel scan imaging and are integrated into the proposed imaging algorithm. The computer simulation is shown to verify the presented imaging algorithm.