航空学报 > 2012, Vol. 33 Issue (12): 2261-2267

非高斯杂波背景中距离扩展目标的盲积累检测器

顾新锋1, 简涛1, 何友1, 郝晓琳2   

  1. 1. 海军航空工程学院 信息融合技术研究所, 山东 烟台 264001;
    2. 烟台电力经济技术研究所, 山东 烟台 264001
  • 收稿日期:2011-11-17 修回日期:2012-04-16 出版日期:2012-12-25 发布日期:2012-12-24
  • 通讯作者: 何友 E-mail:ncif09@163.com
  • 作者简介:顾新锋 男, 博士研究生。主要研究方向: 信号处理, 高分辨率雷达目标检测。Tel: 0535-6635695 E-mail: gxf1983@126.com
  • 基金资助:

    国家自然科学基金(61032001, 61102166);新世纪优秀人才支持计划(NCET-11-0872)

Blind Integrator of Range-spread Target in Non-Gaussian Clutter

GU Xinfeng1, JIAN Tao1, HE You1, HAO Xiaolin2   

  1. 1. Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China;
    2. Yantai Electricity and Economy Technical Institute, Yantai 264001, China
  • Received:2011-11-17 Revised:2012-04-16 Online:2012-12-25 Published:2012-12-24
  • Supported by:

    National Natural Science Foundation of China (61032001, 61102166);Program for New Century Excellent Talents in University(NCET-11-0872)

摘要:

在采用球不变随机向量(SIRV)建模的非高斯杂波背景下,研究了导向矢量失配或未知时距离扩展目标的检测问题。先假设导向矢量已知,采用广义似然比检验(GLRT)得到每个距离单元的归一化匹配滤波器(NMF)统计量,再将多个距离单元的统计量进行非相干积累得到扩展目标的NMF积累检测器(NMFI),然后通过最大化检测统计量的方法,结合特征值分解技术,对导向矢量进行估计,提出了距离扩展目标的盲NMFI(B-NMFI)。仿真分析表明:当导向矢量失配时,NMFI的检测性能优于GLRT;当导向矢量未知时,B-NMFI能有效地检测目标,并且对不同方位的目标具有很好的鲁棒性。

关键词: 非高斯杂波, 距离扩展目标, 广义似然比检验, 检测, 最大似然估计

Abstract:

The problem of detecting a range-spread target in a non-Gaussian clutter modeled as a spherically invariant random vector (SIRV) is investigated when the steer vector is mismatched or unknown. First, the steer vector is assumed known, and the statistics of the normalized matched filter (NMF) of each range cell are obtained by utilizing the generalized likelihood ratio test (GLRT). The NMF integrator (NMFI) is obtained by integrating incoherently the NMF statistics of the range cells which the range-spread target occupies. Then, the steer vector is estimated using the eigenvalue decomposition and the average phase-angle difference by maximizing the detection statistics of the NMFI. Finally, a blind-NMFI (B-NMFI) is obtained using the estimated steer vector. Simulation results show that the detection performance of the NMFI is better than that of GLRT when the steer vector is mismatched, and the B-NMFI can detect a range-spread target effectively and is robust to detect the targets in diverse orientations when the steer vector is unknown.

Key words: non-Gaussian clutter, range-spread target, generalized likelihood ratio test, detection, maximum likelihood estimation

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