In order to reduce the computational complexity for MIMO radar, this paper studies an algorithm that is based on the dimensionality reduction process of echo signals and two kinds of DOA estimation methods that are based on signal sub-space reconstruction (SSR) with sub-space reconstruction. By contrastive and simulative analyses of five kinds of algorithms, it comes to a conclusion that the RD-ESPRIT algorithm is much sensitive to the selection of reduced-dimensional matrix than other algorithms with special spectrum search, and lays more stresses on the rotational invariance of array flow types after dimension reduced. The RD polynomial rooting algorithm, RD-MUSIC algorithm and RD-Capon algorithm have higher estimation accuracy of angles. In addition, the computational complexity of the RD-ESPRIT algorithm and RD polynomial rooting algorithm is lower than other three types of algorithms, and the computational complexity of the RD-ESPRIT is lowest among those five algorithms.% 为了降低MIMO雷达的运算复杂度，研究了基于对回波信号降维处理算法和基于子空间重构的信号子空间重构(SSR)算法的两类波达方向(DOA)估计方法。通过对5种算法的对比和仿真分析可知：RD-ESPRIT算法相比其他空间谱搜索算法，对降维矩阵的选择较敏感，更强调降维后阵列流型的旋转不变性；RD-求根算法、RD-MUSIC算法和RD-Capon算法则有更好的角度估计性能；RD-ESPRIT算法和RD-求根算法运算量相比其他三种算法低一到两个数量级；RD-ESPRIT算法运算复杂度最小。
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