Progressive Scans Synthetic Aperture Radar Research Articles

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.

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.

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).

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.

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.