石星宇,
水鹏朗
西安电子科技大学雷达信号处理国家重点实验室 西安 710071
西安电子科技大学信息感知技术协同创新中心 西安 710071
基金项目:国家自然科学基金(61871303)，电波环境特性及模化技术重点实验室基金(6142403180204)，陕西省自然科学基础研究计划(2017JM6031)，陕西省科协青年人才托举计划(20160205)，高等学校学科创新引智计划(111计划)(B18039)
详细信息
作者简介:许述文(1985–)，男，安徽黄山人，博士，副教授。2011年在西安电子科技大学获得博士学位，现担任西安电子科技大学电子工程学院雷达信号处理国家重点实验室副教授、硕导、博导。主要研究方向为雷达目标检测、机器学习、时频分析和SAR图像处理。E-mail: swxu@mail.xidian.edu.cn
石星宇(1994–)，男，甘肃民乐人，2016年在西安电子科技大学获得学士学位，现在西安电子科技大学雷达信号处理国家重点实验室攻读硕士学位，研究方向为信号检测与参数估计、海杂波信号处理。E-mail: xyshi@stu.xidian.edu.cn
水鹏朗(1967–)，男，陕西西安人，博士，教授。1999年在西安电子科技大学获得博士学位，现担任西安电子科技大学电子工程学院雷达信号处理国家重点实验室教授、硕导、博导。主要研究方向为海杂波建模、雷达目标检测和图像处理。E-mail: plshui@xidian.edu.cn
通讯作者:许述文 swxu@mail.xidian.edu.cn
中图分类号:TN957.51计量
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出版历程
收稿日期:2019-02-25
修回日期:2019-05-05
网络出版日期:2019-05-20
An Adaptive Detector with Mismatched Signals Rejection in Compound Gaussian Clutter
XU Shuwen,,SHI Xingyu,
SHUI Penglang
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Collaborative Innovation Center of Information Sensing and Understanding, Xi’an 710071, China
Funds:The National Natural Science Foundation of China (61871303), The Foundation of National Key Laboratory of Electromagnetic Environment (6142403180204), The Natural Science Basic Research Plan in Shaanxi Province of China (2017JM6031), Young Talent Fund of University Association for Science and Technology in Shaanxi (20160205), Foreign Scholars in University Research and Teaching Programs (the 111 Project) (B18039)
More Information
Corresponding author:XU Shuwen, swxu@mail.xidian.edu.cn
摘要
摘要:随着雷达分辨率的提高及擦地角的减小，海杂波幅度分布明显偏离瑞利分布，表现出很强的非高斯特性，复合高斯模型得到广泛应用。因此该文以复合高斯杂波为背景，研究当信号发生失配时的雷达目标检测问题。该文基于两步广义似然比(GLRT)检验，设计了复合高斯杂波下对失配信号具有选择性的自适应检测器。为了设计选择性检测器，在零假设下引入虚假干扰以修正原始二元假设，并假设该虚假干扰与实际目标信号在白化空间正交。该文提出的检测器对海杂波纹理分量及协方差矩阵恒虚警(CFAR)。最后利用仿真及实测海杂波数据，通过蒙特卡洛实验验证该检测器的有效性。实验表明，该文所提检测器有效提高了对失配信号的选择性，同时对距离扩展目标匹配信号的检测性能也有1～3 dB的提升。
关键词:复合高斯杂波/
信号失配/
恒虚警/
广义似然比/
选择性检测器
Abstract:Because of the improvement in radar resolution and decrease in grazing angle, the amplitude distribution of sea clutter obviously deviates from the Rayleigh distribution and presents a significant non-Gaussian feature. In this case, the compound Gaussian model is widely used. This study investigates the problem of detecting a target when signal mismatches occur in compound Gaussian clutter and proposes a selective detector to reject mismatched signals embedded in compound Gaussian clutter based on the so-called two-step Generalized Likelihood Ratio Test (GLRT). To design the selective detector, we modified the original hypothesis test by injecting a fictitious interference under the null hypothesis. These unwanted signals are assumed to be orthogonal to the nominal steering vector in the whitened subspace. The proposed detector has a Constant False Alarm Rate (CFAR) with respect to the statistics of the texture and covariance matrix. Finally, to demonstrate the effectiveness of the proposed detector, a Monte Carlo simulation is conducted to assess its performance based on the simulated and measured sea clutter data. The experimental results show that the proposed detector effectively improves the selectivity of the mismatched signals together with the detection of matched signals in a range spread target of 1～3 dB.
Key words:Compound Gaussian clutter/
Signal mismatch/
Constant False Alarm Rate (CFAR)/
Generalized Likelihood Ratio Test (GLRT)/
Selective detector
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