一种快速的单比特压缩感知SAR成像算法  

A Fast One-bit Compressed Sensing SAR Imaging Algorithm

作　　者：王峥 余平 刘发林[2] WANG Zheng;YU Ping;LIU Fa-lin(School of Electrical and Photoelectric Engineering,West Anhui University,Lu an 237012,China;Key Laboratory of Electromagnetic Space Information,University of Science and Technology of China,Hefei 230027,China)

机构地区：[1]皖西学院电气与光电工程学院,安徽六安237012 [2]中国科学技术大学电磁空间信息重点实验室,安徽合肥230027

出　　处：《长春师范大学学报》2020年第12期35-40,共6页Journal of Changchun Normal University

基　　金：国家自然科学基金重点项目“大场景微波凝视关联成像中基于压缩感知的快速关联成像方法”(61771446)。

摘　　要：近年来,压缩感知(CS)理论应用在合成孔径雷达(SAR)成像领域取得了巨大的成功。最近的研究表明,利用单比特量化数据也可以成功地实现稀疏场景的SAR成像。相对于采用FFT技术的匹配滤波(MF)聚焦算法,现有的重建算法往往涉及大规模的矩阵-向量乘法,这大大提高了算法的时间和内存消耗。本文提出了一种用于单比特量化数据压缩感知SAR成像的新方法。该方法利用匹配滤波算法反演推导出近似SAR观测模型,并采用迭代阈值算法求解。该算法利用匹配滤波的逆算子来逼近大的矩阵-向量的乘法,因此可以处理大型数据,通过对实际数据的仿真验证了该算法的性能。实验结果表明,在实际大规模数据的应用场景中,该方法可以有效地对单比特量化数据进行稀疏SAR成像。In recent years,the application of CS theory in synthetic aperture radar(SAR)imaging has achieved great success.Recent studies have shown that the use of one-bit quantization data can also successfully achieve SAR imaging of sparse scenes.Compared with the matching filter(MF)focusing algorithm using FFT technology,the existing reconstruction algorithm often involves large-scale matrix-vector multiplication,which greatly increases the time and memory consumption of the algorithm.This paper presents a new method for single bit quantization data compression sensing SAR imaging.In this method,the approximate SAR observation model is derived by inverse matching filter(MF)algorithm and solved by iterative threshold algorithm.The algorithm uses the inverse operator of matching filter to approximate the multiplication of large matrix-vector,so it can deal with large data.The performance of the algorithm is verified by simulation of actual data.Experimental results show that this method can effectively perform sparse SAR imaging on one-bit quantized data in real large-scale data application scenarios.

关 键 词：电磁场与微波技术 合成孔径雷达 单比特量化 压缩感知 SAR成像 相似算子 

分 类 号：TN959.4[电子电信—信号与信息处理] TN928[电子电信—信息与通信工程]