基于不确定集的稳健MIMO雷达波形设计算法

针对雷达目标回波信号存在不确定性导致MIMO雷达波形优化设计性能下降问题，该文提出一种扁平椭球不确定集约束下的稳健自适应发射-接收波形联合优化设计方法。首先将目标脉冲响应的误差推广到更为一般的扁平椭球不确定集约束条件，并利用Lagrange乘子法对优化过程进行推导，得出扁平椭球不确定集约束下的闭式表达式。其次为了提高目标脉冲响应不确定集范围较大时的优化性能，采用了迭代鲁棒最小方差法进行求解(IRMVB)，求得更为精确的目标脉冲响应，提高了SINR改善性能。然后进一步分析了基于扁平椭球不确定集约束条件与球体约束条件优化问题的内在联系，推导得出该文求解过程为广义对角加载方法。最后通过仿真实验表明所提算法对于目标回波信号不确定性具有更高的稳健性。

Robust MIMO Radar Waveform Design Algorithm Based on Uncertainty Set

In order to solve the problem of performance losses in the MIMO radar waveform design when target signal is uncertainty, a novel joint optimization of transmitting waveforms and receiving filters in the MIMO radar for the case of target in flat ellipsoid uncertainty set is proposed. Firstly, constraint of impulse response of target is extended to flat ellipsoid uncertainty set, Lagrange multiplier is used to solve the optimization problem, and the closed form solution is got under the constrain. Secondly, in order to improve SINR output of waveform design when the uncertainty set is large, Iterative Robust Minimum Variance Beamforming (IRMVB) is used to get more precise target impulse response. Thirdly, the relationship between flat ellipsoid uncertainty set and sphere uncertainty set is analyzed, and a solution which has the form of diagonal loading is derived. Finally, simulation results show that the proposed algorithm has excellent performance and it is robust for the uncertainty of impulse response of the target.