文件名称:MP_DOA
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针对多径效应的影响,提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号,采用单样本数信号矢量构造了一个前后向矩阵束,并利用两个酉矩阵对该矩阵束进行降维处理,最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵,可在低
信噪比和单样本数情况下,有效地克服多径效应,实现同时多目标低仰角估计,相比最大似然算法,避免了谱峰搜索,计算量小。仿真结果验证了该算法的有效性。-To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method
信噪比和单样本数情况下,有效地克服多径效应,实现同时多目标低仰角估计,相比最大似然算法,避免了谱峰搜索,计算量小。仿真结果验证了该算法的有效性。-To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method
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基于矩阵束的MIMO雷达低仰角快速估计方法.pdf