目标先验知识未确知条件下MIMO雷达波形优化

Waveform optimization of MIMO radar with imperfect target prior knowledge

考虑杂波场景下改善MIMO雷达最差估计性能的稳健波形优化方法,根据最小最大方法,首先基于克拉美-罗界描述稳健波形优化问题。为求解所得复杂非线性问题,提出一种基于对角加载(DL)的迭代方法。此方法中,内层优化首先利用哈达玛不等式被分解为若干个子问题。基于DL方法将子问题可以转化为凸问题,外层优化同样也可转化为凸问题,因而此优化问题可获得高效求解。初始优化问题的最优解可通过对迭代优化结果的最小二乘拟合得到。数值仿真验证了所提方法的有效性。

In this paper,the robust waveform optimization method to improve the worst-case estimation performance of multipleinput multiple-output（MIMO）radar in the clutter environment is considered. According to the min-max approach,the robust waveform optimization is described on the basis of Cramér-Rao bound（CRB）. In order to solve the complicated nonlinear problem,an iterative method based on diagonal loading（DL） is proposed. With the method,the inlayer optimization problem can be decomposed into some sub-problems first by means of the Hadamard inequation,and then these sub-problems are converted into the convex problem on the basis of DL method;the outer layer optimization problem can be also converted into the convex problem to get the effective solution of these optimization problems. The optimal solution of the original optimization problem can be obtained by means of the least squares（LS）fitting of the iterative optimization results. The efficiency of the proposed method was verified with numerical simulation.