米波MIMO雷达波束空间精确最大似然算法

针对阵元空间多输入多输出(multiple input multiple output, MIMO)雷达低仰角估计方法运算量和数据传输量太大的问题, 提出了基于波束空间的MIMO雷达精确最大似然(refined maximum likelihood, RML)算法。该算法将阵元空间的数据转换到波束空间, 实现降维处理, 再利用最大似然的思想对波束空间的数据进行测角。计算机仿真结果表明, 相比于基于阵元空间的MIMO雷达RML算法, 所提算法有着良好的测角性能, 并大大降低了算法运算时间。同时, 通过计算机仿真分析了信噪比、仰角、波束指向与目标仰角之间的偏差、阵元数、反射系数误差和天线中心高度等因素对所提算法测角性能的影响。

Beam space refined maximum likelihood algorithm for VHF MIMO radar

Aiming at the problem that the low-angle estimation method of array element space multiple input multiple output (MIMO) radar has too much computation and data transmission, a refined maximum likelihood (RML) algorithm for MIMO radar based on beam space is proposed. The algorithm converts the data of array element space into beam space to reduce the dimension, and then uses the idea of maximum likelihood to measure the angle of beam space data. Computer simulation results show that compared with the RML algorithm of MIMO radar based on array element space, the proposed algorithm has good angle measurement performance and greatly reduces the operation time of the algorithm. At the same time, the effects of signal to noise ratio, low-angle, deviation between beam pointing and target low-angle, number of array elements, reflection coefficient error and antenna center height on the angle measurement performance of the proposed algorithm are analyzed by computer simulation.