非理想条件下分布式MIMO雷达目标检测

针对任意波形相关、任意阵列配置情况下分布式MIMO雷达目标检测问题,提出了一种基于Cholesky分解的MIMO雷达检测器;首先分析了分布式MIMO雷达回波的相关性,并给出了任意阵列配置时MIMO雷达检测算法;同时,为了解决发射波形相关矩阵出现奇异性导致无法获得检测统计量的问题,提出了基于Cholesky分解的分布式MIMO雷达检测方法,给出了统一框架下的检测统计量表达式,推导了虚警概率和检测概率的近似解析式;研究得出:在低信噪比情况下,相关性越大,检测性能越好;在高信噪比时,相关性越小,检测性能越优;最后数值仿真验证了理论分析的有效性和正确性.

New Detection Method for MIMO Radar Under Non-Ideal Conditions

This paper studied the problem of target detection for the distributed multiple-input multipleoutput (MIMO) radars under arbitrary waveform correlation and antenna spacing.Based on the Cholesky decomposition,a new detection method under the Neyman-Pearson criterion for distributed MIMO radar was proposed.Firstly,we analyzed the correlation between the distributed MIMO radar echo,and proposed maximum likelihood MIMO detection algorithm with arbitrary array configuration.Then,in order to solve the problem of the singular correlation matrix of the transmitted waveforms,Cholesky decomposition method was applied.The uniform model of sufficient statistics was presented for distributed MIMO radars under non-ideal conditions.An approximate closed form formula was derived to calculate the theoretical probability of detection with a given probability of false alarm for the distributed MIMO radar.Through simulation we can draw conclusions that the detection performance in high SNR deteriorates with the increased the correlation of spatial diversity channels and transmitted wave forms,but the detection performance in low SNR improves with the increased the correlation.Finally,the numerical simulation verifies the validity and correctness of the theoretical analysis.