Moving Target Indication for Dual-Channel Circular SAR/GMTI Systems

Liu

et al. 2022

Multichannel SAR systems have grown rapidly over the past decade due to their powerful high-resolution and wide-swath (HRWS) capabilities. Because spatially separated channels also have the potential to suppress jamming, dual-channel cancellation is a general method that is effective regardless of the type of jamming signal. In this paper, the principle of dual-channel cancellation (DCC) is introduced, and several practical problems using DCC are also discussed. Moreover, this paper emphasizes interferometric phase estimation, which is the key to DCC. If the jamming-to-signal ratio (JSR) is high, the interferometric phase can be estimated accurately from the interferometry of two channel signals, but estimation becomes rather difficult when the JSR decreases. To solve the problem of interferometric phase estimation under a low JSR, a novel interferometric phase estimation method using cosine similarity is proposed in this paper. L-band airborne dual-channel SAR is performed to investigate the applicability of the method. The results not only prove that cosine similarity is an effective method for interferometric phase estimation, but also demonstrate the potential of DCC in the SAR anti-jamming processing.

Section: Introductionmentioning

confidence: 99%

A Novel Method for Interferometric Phase Estimation in Dual-Channel Cancellation

Liu

et al. 2022

“…Synthetic aperture radar (SAR) is widely used in military and civil fields due to its high-resolution imaging of ground scenes, large coverage area, and all-weather capability [ 1 , 2 , 3 ]. The ground-moving-target detection mode of SAR is playing an increasingly important role for battlefield surveillance, traffic monitoring, and other applications [ 4 , 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…Different from the single-channel system, the multichannel system has more spatial degrees-of-freedom in azimuth and can realize clutter suppression, thus improving SCR, which effectively enhances detection and parameter estimation performance for slowly moving targets [ 17 ]. To detect slowly moving targets submerged in the main-lobe clutter spectrum, multichannel methods such as displaced phase center antenna (DPCA) [ 11 , 18 , 19 ], ATI [ 7 , 20 , 21 ], space–time adaptive processing (STAP) [ 12 , 22 ], and robust principal component analysis (RPCA) [ 23 , 24 , 25 ] have been widely developed. DPCA and ATI are sensitive to the inevitable noise and are suboptimal for systems with more than two channels.…”

Section: Introductionmentioning

confidence: 99%

A Novel Detection Scheme in Image Domain for Multichannel Circular SAR Ground-Moving-Target Indication

Dong

Wang

Xiang

et al. 2022

Circular synthetic aperture radar (CSAR), which can observe the region of interest for a long time and from multiple angles, offers the opportunity for moving-target detection (MTD). However, traditional MTD methods cannot effectively solve the problem of high probability of false alarm (PFA) caused by strong clutter. To mitigate this, a novel, three-step scheme combining clutter background extraction, multichannel clutter suppression, and the degree of linear consistency of radial velocity interferometric phase (DLRVP) test is proposed. In the first step, the spatial similarity of the scatterers and the correlation between sub-aperture images are fused to extract the strong clutter mask prior to clutter suppression. In the second step, using the data remaining after elimination of the background clutter in Step 1, an amplitude-based detector with higher processing gain is utilized to detect potential moving targets. In the third step, a novel test model based on DLRVP is proposed to further reduce the PFA caused by isolated strong scatterers. After the above processing, almost all false alarms are excluded. Measured data verified that the PFA of the proposed method is only 20% that of the comparison method, with improved detection of slow and weakly moving targets and with better robustness.

“…Synthetic aperture radar (SAR) is different from optical sensors, and is capable of penetrating rain, snow, cloud, and fog, providing high-resolution images under severe weather conditions [ 1 , 2 , 3 ]. As a result, SAR has been widely exploited in various application fields [ 4 , 5 , 6 ]. Thanks to a large number of collected SAR images, automatic target recognition (ATR) of SAR images have attracted increasing popularity in recent years.…”

Section: Introductionmentioning

confidence: 99%

Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Liu

Chen

et al. 2021

For target detection in complex scenes of synthetic aperture radar (SAR) images, the false alarms in the land areas are hard to eliminate, especially for the ones near the coastline. Focusing on the problem, an algorithm based on the fusion of multiscale superpixel segmentations is proposed in this paper. Firstly, the SAR images are partitioned by using different scales of superpixel segmentation. For the superpixels in each scale, the land-sea segmentation is achieved by judging their statistical properties. Then, the land-sea segmentation results obtained in each scale are combined with the result of the constant false alarm rate (CFAR) detector to eliminate the false alarms located on the land areas of the SAR image. In the end, to enhance the robustness of the proposed algorithm, the detection results obtained in different scales are fused together to realize the final target detection. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.