非高斯杂波中的MIMO雷达信号分离

针对传统匹配滤波对非高斯杂波中的多输入多输出（multiple input multiple output, MIMO）雷达信号分离性能下降的问题，提出一种基于分数低阶统计量的匹配滤波算法。该方法将对称Alpha稳定分布(symmetric Alpha stable, SαS)作为MIMO雷达的非高斯杂波模型，以滤波器输出分数低阶信杂比最大为准则导出最优匹配滤波器系数。分别对相关SαS和非相关SαS杂波条件下的MIMO雷达信号分离进行了仿真。结果表明，该方法可有效实现非高斯杂波中的MIMO雷达信号分离，且在高斯杂波条件下与传统匹配滤波的性能是一致的。

MIMO radar signal separation in non-Gaussian clutter

To address the problem of multiple input multiple output (MIMO) radar signal separation with traditional matched filter (MF) in non Gaussian clutter, a new MF based on fractional lower order statistics (FLOS) is proposed. The proposed method assumes that the MIMO radar clutter satisfies symmetric alpha stable (SαS) distribution, and then with the rule of maximizing the output fractional lower order signal to clutter power ratio, the optimum filter coefficients are obtained. The MIMO radar signal separation in coherent SαS and non coherent SαS clutter are simulated respectively. Simulation results show that the proposed method is very efficient for MIMO radar signal separation in non Gaussian clutter, and it has the same good performance as traditional MF in Gaussian clutter.