SAR Muti-Channel Adaptive Equalization Method Based On Particle Swarm Optimization

Qing Yang, Zhuo Zhou, K. Du, Nianzhu Wen, Zhongyu Li, Junjie Wu
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Abstract

Multi-channel SAR system improves the suppression performance of the main lobe clutter by increasing the degree of spatial freedom. In actual project, channel mismatch will greatly reduce the performance of clutter suppression. How to eliminate the amplitude and phase errors between channels has become an important engineering problem. Aiming at the problem of inconsistent amplitude and phase between the receiving channels of bistatic multi-channel SAR systems, this paper proposes an adaptive channel equalization method with faster convergence speed and lower computational complexity. Firstly, analyze and model the channel mismatch by constructing the echo model of the bistatic multi-channel SAR. Then use the adaptive algorithm to complete the equalization processing of multi-channel echo signal, and propose a method of combining the particle swarm algorithm and the adaptive algorithms. Through simulation and experimental data verification, the adaptive channel equalization technology combined with particle swarm algorithm can compensate the relative error between channels more accurately and efficiently.
基于粒子群优化的SAR多通道自适应均衡方法
多通道SAR系统通过增加空间自由度来提高对主瓣杂波的抑制性能。在实际工程中,信道失配会大大降低杂波抑制性能。如何消除信道间的幅度和相位误差已成为一个重要的工程问题。针对双基地多通道SAR系统接收信道间幅度相位不一致的问题,提出了一种收敛速度快、计算复杂度低的自适应信道均衡方法。首先,通过构建双基地多通道SAR回波模型,对信道失配进行分析和建模,然后利用自适应算法完成多通道回波信号的均衡处理,提出了粒子群算法与自适应算法相结合的方法。通过仿真和实验数据验证,结合粒子群算法的自适应信道均衡技术能够更准确、高效地补偿信道间的相对误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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