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作 者:夏朝禹 高瑜翔[1,2] 黄坤超 余杰[1] 谢建峰 闫鸿 XIA Chaoyu;GAO Yuxiang;HUANG Kunchao;YU Jie;XIE Jianfeng;YAN Hong(College of Communication Engineering,Chengdu University of Information Technology,Chengdu 610225,China;Meteorological Information and Signal Processing Key Laboratory of Sichuan Education Institutes,Chengdu 610225,China;Southwest China Institute of Electronic Technology,Chengdu 610036,China)
机构地区:[1]成都信息工程大学通信工程学院,成都610225 [2]气象信息与信号处理四川省高校重点实验室,成都610225 [3]中国西南电子技术研究所,成都610036
出 处:《电讯技术》2019年第10期1186-1190,共5页Telecommunication Engineering
摘 要:针对压缩感知穿墙雷达成像过程中受壁杂波污染严重等问题,提出了一种组合滤波的杂波抑制算法。该算法利用小波预处理、统计信号滤波法相结合的方式对回波信号进行处理,通过动态阈值分段弱正交匹配追踪进行稀疏迭代求解。在强壁杂波存在的情况下,组合滤波法能够有效地消除杂波检测出墙后目标。实验结果表明,该算法与传统单一主成分分析、奇异值分解和经验模态分解滤波相比,所成雷达像的子杂波比分别提高了1.57、1.52、1.26倍。For the problem that the compressed sensing through-wall radar(CS-TWR)imaging process is seriously polluted by wall clutter,a combined filtering clutter suppression algorithm(CF)is proposed.The algorithm combines wavelet pre-filtering with statistical signal filtering to process the echo signal.The sparse iterative solution is performed by dynamic threshold segmentation weak orthogonal matching pursuit.In the presence of strong wall clutter,the CF can effectively eliminate clutter and detect the target behind the wall.The experiment results show that the CF algorithm improves the target clutter ratio(TCR)of radar image by 1.57,1.52 and 1.26 times,respectively,compared with the traditional principal component analysis(PCA),singular value decomposition(SVD)and empirical mode decomposition(EMD)filtering.
分 类 号:TN957.5[电子电信—信号与信息处理]
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