电子学报 ›› 2014, Vol. 42 ›› Issue (11): 2286-2290.DOI: 10.3969/j.issn.0372-2112.2014.11.024

• 科研通信 • 上一篇    下一篇

基于降维稀疏重构的高效数据域STAP算法研究

沈明威1, 王杰1, 吴迪2, 朱岱寅2   

  1. 1. 河海大学计算机与信息学院, 江苏南京 211100;
    2. 南京航空航天大学电子信息工程学院, 江苏南京 210016
  • 收稿日期:2013-06-07 修回日期:2014-01-20 出版日期:2014-11-25
    • 作者简介:
    • 沈明威 男,1981年7月出生,江苏省苏州市人.2003年和2008年分别在南京航空航天大学获工学学士和工学博士学位.现为河海大学副教授,主要从事空时自适应处理和SAR/GMTI的研究工作. E-mail:smw_nuaa@hotmail.com;王杰 男,1989年月出生,江苏省常熟市人.现为河海大学信号与信息处理硕士研究生.研究方向为空时自适应处理. E-mail:jiewanghhu@gmail.com
    • 基金资助:
    • 国家自然科学青年基金 (No.61201459,No.61301212); 江苏省自然科学青年基金 (No.BK2012408); 国防基础科研 (No.B2520110008); 江苏省六大人才高峰 (No.ZBZZ-009); 中央高校科研业务费 (No.2012B6014); 雷达成像与微波光子技术教育部重点实验室基金 (No.PIMP-2013002)

An Efficient Data Domain STAP Algorithm Based on Reduced-Dimension Sparse Reconstruction

SHEN Ming-wei1, WANG Jie1, WU Di2, ZHU Dai-yin2   

  1. 1. College of Computer & Information Engineering, Hohai University, Nanjing, Jiangsu 211100, China;
    2. College of Electronic & Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China
  • Received:2013-06-07 Revised:2014-01-20 Online:2014-11-25 Published:2014-11-25
    • Supported by:
    • Youth Fund of National Natural Science Foundation of China (No.61201459, No.61301212); Youth Fund of Natural Science Foundation of Jiangsu Province,  China (No.BK2012408); National Defense Basic Research Project (No.B2520110008); Six Talents Peaks in Jiangsu Province (No.ZBZZ-009); Science Research Funds for the Central Universities (No.2012B6014); Fund for Key Laboratory of Radar Imaging and Microwave Photonics of Ministry of Education of China (No.PIMP-2013002)

摘要:

本文基于信号稀疏重构技术,研究利用待检测样本直接进行动目标检测的高效空时自适应处理(STAP)方案.该方案对时域降维的阵元-多普勒域数据采用空域稀疏重构技术估计高分辨率角度-多普勒谱,进而基于稀疏空时谱研究知识辅助的动目标检测算法.理论分析和仿真实验结果表明:本文算法能有效抑制杂波实现慢动目标检测,且运算量小易于实时并行处理.

关键词: 空时自适应处理, 稀疏重构, 杂波抑制

Abstract:

An efficient direct data domain STAP scheme based on a sparse reconstruction of the primary data is presented to effectively detect ground moving targets.To reduce the computational complexity,the proposed method obtains the high resolution angle-Doppler spectrum by finding the sparsest coefficients using the reduced-dimension data in element-Doppler domain.Therefore,based on the distinct image features of clutter and targets signals,a knowledge-aided moving targets detection algorithm is also introduced.The effectiveness of the proposed approach is shown by both theoretical analysis and simulation results.This scheme is computationally efficient for real-time parallel processing.

Key words: space-time adaptive processing, sparse reconstruction, clutter suppression

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