电子学报 ›› 2016, Vol. 44 ›› Issue (4): 860-867.DOI: 10.3969/j.issn.0372-2112.2016.04.015

• 学术论文 • 上一篇    下一篇

稀疏域海杂波抑制与微动目标检测方法

陈小龙1, 关键1, 董云龙2, 赵志坚3   

  1. 1. 海军航空工程学院电子信息工程系, 山东烟台 264001;
    2. 海军航空工程学院信息融合研究所, 山东烟台 264001;
    3. 海军航空工程学院接改装训练大队, 山东烟台 264001
  • 收稿日期:2014-08-04 修回日期:2015-01-23 出版日期:2016-04-25 发布日期:2016-04-25
  • 作者简介:陈小龙 1985年生于山东烟台.海军航空工程学院电子信息工程系讲师,博士.获全军优秀硕士论文奖.研究方向包括微多普勒分析,时频信号分析和海杂波中微弱目标检测. E-mail:cxlcxl1209@163.com;关 键 男,1968年生于辽宁锦州.海军航空工程学院电子信息工程系教授,博士生导师.获全国优秀博士学位论文奖,新世纪百千万人才工程国家级人选,"泰山学者"特聘教授.研究方向包括雷达目标检测与跟踪、侦察图像处理和信息融合. E-mail: guanjian96@tsinghua.org.cn
  • 基金资助:

    国家自然科学基金(No.61501487, No.61471382, No. 61401495, No. 61201445, No. 61179017); 山东省自然科学基金(No.2015ZRA06052);飞行器海上测量与控制联合实验室开放基金

Sea Clutter Suppression and Micromotion Target Detection in Sparse Domain

CHEN Xiao-long1, GUAN Jian1, DONG Yun-long2, ZHAO Zhi-jian3   

  1. 1. Department of Electronic and Information Engineering, Naval Aeronautical and Astronautical University, Yantai, Shandong 264001, China;
    2. Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai Shandong 264001, China;
    3. Training Brigade of the Received and Reformed Equipment, Naval Aeronautical and Astronautical University, Yantai, Shandong 264001, China
  • Received:2014-08-04 Revised:2015-01-23 Online:2016-04-25 Published:2016-04-25

摘要:

针对海上微动目标回波信号具有稀疏性的特点,该文研究了稀疏域微动特征提取和检测方法,提出一种基于形态成分分析(MCA)的海杂波抑制与微动目标检测方法.该方法充分利用海杂波和微多普勒信号组成成分的形态差异性,对不同源信号采用不同的字典进行稀疏表示,区分海杂波与微动目标.此外,提出的稀疏域海杂波抑制方法,能够在抑制海杂波的同时积累更多的信号能量,改善信杂比.仿真和实测数据验证了算法的正确性.

关键词: 雷达目标检测, 海杂波, 微多普勒, 稀疏表示, 形态成分分析

Abstract:

Using the sparse property of the signal from a marine micromotion target,the extraction and detection of micromotion signatures in sparse domain are studied.An algorithm for sea clutter suppression and micromotion target detection is proposed based on the morphological component analysis (MCA).The algorithm takes full advantage of the morphological differences between sea clutter and micro-Doppler signal,and can separate them via sparse representation of different source signals using different dictionaries.Moreover,the proposed sea clutter suppression method in sparse domain can achieve both target's energy accumulation and sea clutter suppression with improved signal-to-clutter ratio (SCR).Simulated and real data all verify the effectiveness of the proposed method.

Key words: radar target detection, sea clutter, micro-Doppler, sparse representation, morphological component analysis (MCA)

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