基于知识辅助的MIMO雷达波形设计方法

Knowledge-aided MIMO Radar Waveform Design Method

该文针对雷达系统受到天线主瓣和副瓣杂波以及强干扰影响时性能下降问题,提出基于距离扩展目标和杂波先验信息的MIMO雷达波形设计方法。首先建立了目标函数,综合考虑了波束主瓣增益、旁瓣杂波抑制能力以及目标输出SCNR的改善性能;然后在优化问题求解中对约束条件进行松弛,使得波形矩阵空域和时域2维解耦合,从而实现空域波束形成和时域波形设计独立优化求解;其次利用L-BFGS算法设计恒模的发射波形矩阵,形成低副瓣的波束方向图和较深的强杂波抑制凹口,并基于目标输出SCNR最大化准则,利用迭代算法分步求解优化的主瓣发射波形和接收滤波器;最后通过电磁仿真的距离扩展目标数据验证所提算法的有效性。

In order to solve the problem of performance degradation when radar system is influenced by clutter from mainlobe and sidelobe, MIMO radar waveform design algorithm based on knowledge of range-spread target and clutter is investigated. Firstly, an optimization cost function is established, which includes mainlobe gain, sidelobe clutter suppression capability and Signal to Clutter plus Noise Ratio （SCNR） improvement. Secondly, to tackle the optimization problem, a relaxation is made to decouple spatial and temporal domain of the waveform matrix, beamforming and waveform design can be solved independently. Thirdly, L-BFGS algorithm is used to design the unimodular waveform matrix, beampattern with lower sidelobe and deep null is got. Based on maximization of SCNR, transmitted waveform and receiving filter are designed by iterative algorithm. Finally, the effectiveness of the proposed algorithm is verified by electromagnetic simulation of range-spread target.