摘要
该文考虑一种非均匀环境中,复合高斯杂波下的目标检测问题,即待检测单元杂波协方差矩阵与参考单元杂波协方差矩阵之间并不相等,且杂波数据满足复合高斯统计分布模型。利用已知的先验信息,选择合适的先验分布,基于贝叶斯方法,该文给出了杂波协方差矩阵的最小均方误差估计,并将其应用于正则化匹配滤波器检验。计算机仿真结果表明,采用该文提出的杂波协方差估计算法,能够在参考数据较少的情况下,获得较好的检测性能。
The adaptive detection of signal embedded in compound Gaussian clutter of nonhomogeneous environments, i.e., the training samples used for adaption do not share the same covariance matrix as the vector under test is considered in this paper, and the clutter can be modeled in terms of a compound Gaussian process. With known prior and some appropriate prior distribution, based on Bayesian framework, the minimum mean square error estimation of clutter covariance matrix is proposed, and the application to the adaptive normalized matched filter test is given. The results of computer simulation are presented to illustrate that the performance of the proposed detectors is better than conventional ones, especially in the present of a small number of training data.
出处
《电子与信息学报》
EI
CSCD
北大核心
2011年第10期2433-2437,共5页
Journal of Electronics & Information Technology
关键词
信号处理
自适应检测
复合高斯分布
非均匀场景
贝叶斯方法
协方差矩阵
Signal processing
Adaptive detection
Compound Gaussian distribution
Nonhomogeneous environments
Bayesian framework
Covariance matrix
作者简介
谢洪森：男，1966年生，副教授、博士生，从事军事通信、导航系统理论、信息处理理论的研究．
邹鲲：男，1976年生，讲师，从事雷达信号处理、统计信号检测及其在雷达、导航方面的应用研究．通讯作者： 邹鲲 Email： zoukun2003@yahoo.com.cn
