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线性正则域抑制频谱弥散干扰方法
引用本文:张亮,王国宏,李思文. 线性正则域抑制频谱弥散干扰方法[J]. 信号处理, 2020, 36(3): 328-336. DOI: 10.16798/j.issn.1003-0530.2020.03.002
作者姓名:张亮  王国宏  李思文
作者单位:海军航空大学
基金项目:国家自然科学基金(61731023,61701519,61671462);“泰山学者”攀登计划专项经费资助项目。
摘    要:频谱弥散干扰(SMSP)是一种对抗线性调频脉冲压缩雷达的新型干扰样式。自卫式干扰条件下,目标回波与干扰信号时频域重叠,传统抗干扰手段难以有效抑制。针对该问题,分析了目标回波和干扰信号线性正则域(LCT域)特征,依据特征差异提出了两种LCT域干扰抑制方法,分别为窄带滤波法和稀疏重构法,其中窄带滤波方法通过LCT域遮盖处理,滤除干扰分量,而稀疏重构方法首先利用Pei型DLCT核矩阵构造正交字典,然后基于压缩感知理论重构真实回波。仿真表明,所提两种方法均具有一定的干扰抑制效能,恢复信号与真实回波高度相似,且幅度高于真实回波,使干扰信号成为标的。

关 键 词:频谱弥散干扰  线性正则变换  干扰抑制
收稿时间:2019-09-11

SMSP Jamming Suppression Methods in Linear Canonical Domain
Zhang Liang,Wang Guohong,Li Siwen. SMSP Jamming Suppression Methods in Linear Canonical Domain[J]. Signal Processing(China), 2020, 36(3): 328-336. DOI: 10.16798/j.issn.1003-0530.2020.03.002
Authors:Zhang Liang  Wang Guohong  Li Siwen
Affiliation:Naval Aviation UniversityUnit 94326 of the PLA
Abstract:The smeared spectrum jamming(SMSP)is a new type jamming used to counter LFM pulse compression radar.Under the condition of self screening jamming,the target echo and jamming signal overlap in time and frequency domain,and the traditional anti-jamming means are difficult to suppress the SMSP jamming effectively.In order to solve this problem,the LCT domain characteristics of the real target echo and SMSP jamming were analyzed.Two methods of jamming suppression in LCT domain were proposed,which were narrowband-filtering and sparse reconstruction.Narrow-filtering method filtered out jamming components by covering in LCT domain.As for the sparse reconstruction method,LCT orthogonal dictionary depend on Pei type DLCT kernel matrix was designed,and then the real target echo was reconstructed based on compressed sensing theory.The simulation results show that the proposed methods have certain jamming suppression efficiency.The recovered signal is highly similar to the real target echo,and the amplitude of the recovered signal is larger than the real target echo,making the jamming signal become the target.
Keywords:smeared spectrum jamming  linear canonical transformation  jamming suppression
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