基于去冗余的MIMO雷达多维角度分阶段估计

Multidimensional Angles Staged Estimation for MIMO Radar Based on Redundancy Removal

  • 摘要: 针对双基地MIMO雷达目标在色噪声环境下多维角度的联合估计以及多维角度估计算法复杂度高的问题,提出一种L型MIMO雷达阵列中基于分段部分去冗余的FOC-ESPRIT-MUSIC算法。首先,通过生成交换矩阵得到DOD估计对应的重构信号,然后,分别构造DOA、DOD估计对应信号的四阶累积量矩阵,并提出SEG_INC_RR方法,实现累积量矩阵降维,最后,为避免高维谱峰搜索,分别利用FOC-ESPRIT算法和FOC-MUSIC算法实现目标的二维DOA和二维DOD估计。所提算法有效抑制高斯噪声影响,计算复杂度低,实现目标的四维角度估计,且参数可自动配对。仿真结果证实了算法的有效性。

     

    Abstract:  For jointly estimating multidimensional angles of bistatic MIMO radar target in colored noise environment and improving computational complexity of multidimensional angles estimation algorithm, a FOC-ESPRIT-MUSIC algorithm based on segmented partial redundancy removal in L-shaped MIMO radar array is proposed. Firstly, the reconstructive signal corresponding to DOD estimation can be obtained by generating an exchange matrix. Secondly, the fourth-order cumulant matrices of the corresponding signals of DOA estimation and DOD estimation are computed respectively. The SEG_INC_RR(segmented incomplete redundancy removal) method is proposed, and the fourth-order cumulants are segmented according to some criteria. Then, according to the need of this algorithm, some redundancy items in each segment should be removed to reduce the dimension of the cumulant matrix. Finally, FOC-ESPRIT algorithm and FOC-MUSIC algorithm are used respectively to realize the targets of 2-D DOA and 2-D DOD estimation. This method can avoid high dimensional spectrum peak search. The proposed method, which has low computational complexity, can suppress the effect of Gaussian colored noise. It can estimate fourdimensional angles of the target with multidimensional parameters paired automatically. Results of simulation validate its effectiveness.

     

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