非高斯杂波中机载多进多出雷达动目标检测

Detection of the airborne MIMO radar moving target in the non-Gaussian clutter

由于多进多出雷达的机载平台运动,导致机载多进多出雷达的杂波是非高斯的并且是非均匀的,无法获得独立同分布的训练数据来估计杂波的协方差矩阵。为解决这一问题,提出把非高斯杂波的协方差建模为未知随机的且服从逆复威沙特分布的随机过程,其均值建模为杂波协方差矩阵的锐化因子和杂波多普勒谱的阿达马乘积。在此基础上采用贝叶斯方法和广义似然比检验准则,设计了一种新型的自适应检测器。数值仿真结果表明:所设计的检测器的性能要好于目前常用的两种非贝叶斯类检测器。

Due to the moving platforms,the clutters in distributed airborne MIMO radar are non-Gaussian and non-homogeneous,which leads to having no independent and identically distributed training data to estimate the clutter covariance matrix.To solve the problem,we propose that the covariance of the clutter should be modeled as an inverse complex Wishart distribution whose average value is a Hadamard product of the covariance matrix taper(CMT)and the clutter Doppler spectrum component.Based on this clutter model,a novel detector combing the Bayesian approach and the generalized likelihood ratio test(GLRT)is proposed.Numerical simulation results show that the proposed detector has a better detection performance compared with two current commonly used non-Bayesian detectors.