姚伟伟1,
杨超1,
仇洪冰1
1.桂林电子科技大学无线宽带通信与信号处理广西重点实验室 ??桂林 ??541004
2.通信网信息传输与分发技术重点实验室 ??石家庄 ??050081
基金项目:国家自然科学基金(61571143, 61371107)；广西无线宽带通信与信号处理重点实验室基金(GXKL061501)；通信网信息传输与分发技术重点实验室开发课题(KX172600033)
详细信息
作者简介:郑霖：男，1973年生，教授，主要研究方向为无线宽带通信与定位、自适应信号处理、无线传感网络
姚伟伟：男，1992年生，硕士生，研究方向为通信雷达一体化
杨超：男，1988年生，博士生，研究方向为无线通信、通信雷达一体化
仇洪冰：男，1963年生，教授，主要研究方向为无线通信、超宽带通信、无线传感网络
通讯作者:郑霖 gwzheng@gmail.com
中图分类号:TN953计量
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被引次数:0
出版历程
收稿日期:2018-01-09
修回日期:2018-05-02
网络出版日期:2018-07-30
刊出日期:2018-10-01
Clutter Suppression Method for Short Range Slow Moving Target Detection
Lin ZHENG1, 2,,,Weiwei YAO1,
Chao YANG1,
Hongbing QIU1
1. Guangxi Key Laboratory of Wireless Communication & Signal Processing, Guilin University of Electronic Technology, Guilin 541004, China
2. Science & Technology on Information Transmission & Dissemination in Communication Networks Laboratory, Shijiazhuang 050081, China
Funds:The National Natural Science Foundations of China (61571143, 61371107), The Wideband Wireless Communications & Signal Processing Key Lab oratory. Foundation of Guangxi (GXKL061501), The Science and Technology on Communication Networks Laboratory Foundation (KX172600033)
摘要
摘要:针对强杂波环境下近距慢速运动目标检测问题，该文提出一种基于相位编码及子空间投影的杂波抑制方法。主要对周期探测信号调制Chirp相位编码，通过回波慢时间维解码使杂波近似白化，降低杂波与目标回波相关性，再依据白化后杂波及有用信号成分自相关性差异分离出信号和杂波干扰子空间；最后将接收信号投影至正交于杂波子空间的信号子空间来抑制杂波。由于该方法中杂波空间的构建不需要假设杂波模型，避免了模型假设与实际环境不匹配的问题。仿真结果和实测数据处理结果证明该方法在低信杂比条件下性能明显优于传统方法。
关键词:杂波抑制/
慢速运动目标/
相位编码/
子空间投影
Abstract:This paper proposes a method of clutter suppression based on phase encoding and subspace projection for close slow-moving target detection in strong clutter environment. In the framework, the periodic detection signal is modulated with phase encoding, and the clutter is whitened through echo decoding of the slow-time dimension to reduce the correlation between clutter and target echo. Furthermore interference subspace is constructed on the basis of the autocorrelation differences between whitened clutter and useful signal components. The receiving signal is projected to the signal subspace orthogonal to the clutter subspace for clutter suppression. Since the construction of clutter space does not need to assume the clutter model, it avoids the problem of mismatch between the model hypothesis and the actual environment. Simulation results and real data processing results show that this method has better performance than conventional methods under low signal-to-clutter ratio.
Key words:Clutter suppression/
Slow-moving target/
Phase encoding/
Subspace projection
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