基于随机矩阵理论和最小描述长度的机载前视阵雷达杂波自由度估计  

Estimation of Clutter Degrees of Freedom in Airborne Forward-looking Radar via Random Matrix Theory and Minimum Description Length Criteria

作　　者：李海[1] 刘新龙[1] 蒋婷[1] 吴仁彪[1] LI Hai LIU Xinlong JIANG Ting WU Renbiao(Tianjin Key Lab oratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, Chin)

机构地区：[1]中国民航大学天津市智能信号与图像处理重点实验室,天津300300

出　　处：《电子与信息学报》2016年第12期3224-3229,共6页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(61471365;61571442;61231017);中央高校基本科研业务费项目(3122015B002);中国民航大学蓝天青年学者培养经费~~

摘　　要：有限训练样本时,总体协方差矩阵特征谱的严重扩展使得机载前视阵雷达杂波自由度估计困难。该文提出一种前视阵杂波自由度估计方法,该方法利用随机矩阵理论(Random Matrix Theory,RMT)中特征值统计分布特性建立参数化的概率模型,结合最小描述长度(Minimum Description Length,MDL)准则关于信源检测的思想估计杂波自由度。该方法能够在有限训练样下实现杂波自由度的有效估计,仿真结果验证了方法的有效性。Owing to the heavy spread of eigenspectrum of the population covariance matrix under finite training samples condition, it is a challenge to estimate the clutter Degrees of Freedom （DoF） in airborne forward-looking radar. In this work, a method for estimation the clutter’s DoF is proposed. In order to estimate the clutter’s DoF, an idea from sources detection by Minimum Description Length （MDL） criterion is borrowed, and the parametric probability model is formed based on the eigenvalue’s statistical distribution properties from Random Matrix Theory （RMT）. The proposed method is effective to estimate the clutter’s DoF under finite training samples condition, and the simulation results verify the efficiency of the proposed method.

关 键 词：前视阵雷达 杂波自由度 随机矩阵理论 最小描述长度 协方差矩阵 

分 类 号：TN958[电子电信—信号与信息处理]