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基于截断修正平滑l0范数的MIMO雷达目标参数估计
陈金立a,b,c,李伟b,唐彬彬b,李家强a,b,c
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(南京信息工程大学 a.气象灾害预报预警与评估协同创新中心;b.电子与信息工程学院;c.江苏省气象探测与信息处理重点实验室，南京210044)

摘要:

在多输入多输出(MIMO)雷达中，针对平滑l0范数(SL0)因感知矩阵的病态性而导致其失效的问题，提出了一种基于截断修正SL0的MIMO雷达目标参数估计方法。该方法在对MIMO雷达感知矩阵进行截断奇异值分解(TSVD)处理的基础上，将保留的奇异值以均值为截断门限，分成较大和较小的两部分，分别采用不同的修正准则进行修正；然后经奇异值分解(SVD)反变换获得非病态感知矩阵，利用该非病态感知矩阵通过SL0算法对MIMO雷达目标参数进行估计，从而显著提高了MIMO雷达目标参数估计的精度和速度。仿真结果验证了该方法的有效性。

关键词: MIMO雷达目标参数估计平滑l0范数算法病态矩阵截断修正奇异值分解

DOI：10.3969/j.issn.1001-893x.2017.09.004

基金项目:国家自然科学基金资助项目（61302188，61372066）；江苏省自然科学基金资助项目（BK20131005）；江苏高校优势学科Ⅱ期建设工程资助项目

Target parameter estimation for MIMO radars based on truncated modified smoothed l0 norm

CHEN Jinlia,b,c,LI Weib,TANG Binbinb,LI Jiaqianga,b,c

(a. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters;b.School of Electronic and Information Engineering;c.Jiangsu Key Laboratory of Meteorological Observation and Information Processing,Nanjing University of Information Science and Technology,Nanjing 210044,China)

Abstract:

Because of the ill-posed sensing matrix,the smoothed l0 norm(SL0) algorithm fails to estimate target parameter in multiple input multiple output(MIMO) radars. To solve this problem,the truncated modified smoothed l0 norm algorithm for MIMO radars is proposed. Based on the truncated singular value decomposition algorithm(TSVD),the retained singular values of sensing matrix are divided into the larger and smaller by the mean value of singular values. Then,the two groups of the singular values are modified by using different modified criterion. From the modified singular values,the SVD inverse transform is utilized to obtain a non ill-posed sensing matrix. Finally,the SL0 algorithm can be used to reconstruct the target signals in the MIMO radar by taking advantage of the obtained non ill-posed sensing matrix. Therefore,the target parameters can be fast estimated with high accuracy for MIMO radar. The validity of the proposed method is demonstrated with the numerical simulations.

Key words: target parameter estimation smoothed l0 norm(SL0) algorithm ill-posed matrix truncated modified singular value decomposition