An Improved Azimuth Signal Reconstruction Algorithm for Wide-Beam Distributed SAR

IF 4 3区 地球科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Geoscience and Remote Sensing Letters Pub Date : 2022-01-01 DOI:10.1109/lgrs.2022.3194702
Chi Zhang, Zegang Ding, Han Li, Tianyi Zhang
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Abstract

Distributed multichannel synthetic aperture radar (MC-SAR) is a system in which transmitting or receiving arrays are distributed on multiple platforms or at different locations on one platform. The along-track component of the baseline makes distributed SAR promising in high-resolution wide-swath (HRWS) imaging such as azimuth MC-SAR. However, the additional channel mismatch introduced by the cross-track baseline (CTB) is considered for the distributed SAR. When the azimuth beam is wide, the azimuth-variant channel mismatch caused by the CTB must be compensated before SAR imaging. First, an improved azimuth signal reconstruction algorithm for distributed wide-beam SAR is proposed in this article. The azimuth variance of the channel mismatch is considered in a reconstruction filter to further suppress the ambiguity, and the computational consumption is decreased by approximately decomposing the mismatch matrix. Second, the ambiguity suppression performance of the proposed method is analyzed quantitatively. Finally, a simulation and real data processing are provided to demonstrate the effectiveness of the proposed method.
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一种改进的宽波束分布式SAR方位信号重构算法
分布式多通道合成孔径雷达(MC-SAR)是一种发射或接收阵列分布在多个平台上或在一个平台上的不同位置的系统。基线的沿航迹分量使得分布式SAR在高分辨率宽幅(HRWS)成像(如方位MC-SAR)中很有前景。然而,分布式合成孔径雷达考虑了交叉航迹基线(CTB)带来的额外信道失配,当方位角波束较宽时,必须在成像前补偿由CTB引起的方位角变信道失配。首先,本文提出了一种改进的分布式宽波束SAR方位信号重构算法。在重构滤波器中考虑了信道失配的方位角方差,进一步抑制了模糊性,并通过对失配矩阵的近似分解降低了计算量。其次,对该方法的模糊抑制性能进行了定量分析。最后,通过仿真和实际数据处理验证了该方法的有效性。
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来源期刊
IEEE Geoscience and Remote Sensing Letters
IEEE Geoscience and Remote Sensing Letters 工程技术-地球化学与地球物理
CiteScore
7.60
自引率
12.50%
发文量
1113
审稿时长
3.4 months
期刊介绍: IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts. Papers should relate to the theory, concepts and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space, and the processing, interpretation, and dissemination of this information. The technical content of papers must be both new and significant. Experimental data must be complete and include sufficient description of experimental apparatus, methods, and relevant experimental conditions. GRSL encourages the incorporation of "extended objects" or "multimedia" such as animations to enhance the shorter papers.
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