基于随机矩阵的非高斯噪声条件下大规模MIMO雷达DOD和DOA联合估计方法

Hong Jiang, Yiwei Lu, Shunyou Yao
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引用次数: 12

摘要

传统的MIMO雷达目标参数估计方法是在观测数远大于阵元数的前提下进行的。然而,对于阵列较大且观测量不足的MIMO雷达,其估计性能会下降。本文研究了双基地MIMO雷达中收发元数与观测数乘积以相同速率增长的情况。提出了一种非高斯噪声环境下出发方向和到达方向联合估计的鲁棒方法。该方法利用鲁棒m估计量形成协方差矩阵估计,然后利用随机矩阵理论(RMT)和多项式生根算法对大规模MIMO雷达进行精确的DOD和DOA估计。仿真结果证明了该方法的鲁棒性和精度的提高。
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Random matrix based method for joint DOD and DOA estimation for large scale MIMO radar in non-Gaussian noise
Traditional methods of target parameter estimation in MIMO radar are carried out under the assumption that the number of observations is much larger than the number of array elements. However, their estimation performance will decline for the MIMO radar with large arrays and insufficient observations. In this paper, we investigate the situation in bistatic MIMO radar that the product of the numbers of the transmit and receive elements and the number of observations grow at the same rate. We propose a robust method for joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in non-Gaussian noise environment. The method uses robust M-estimator to form an estimate of the covariance matrix, and then applies random matrix theory (RMT) and polynomial rooting algorithm to receive accurate DOD and DOA estimates for large scale MIMO radar. The simulation results demonstrate the robustness and improvement in accuracy.
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