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Fast Direction-Finding Algorithm by Partial Spatial Smoothing in Sparse MIMO Radar

By Sheng Liu, Feng Qin, Jing Zhao, Weizhi Xiong, and Ziqing Yuan
Progress In Electromagnetics Research M, Vol. 93, 127-136, 2020


For reducing the computational complexity of direction-finding algorithm in sparse multiple-input multiple-output (MIMO) radar, a low-complexity partial spatial smoothing (PSS) algorithm is presented to estimate the directions of multiple targets. Firstly, by dealing with a partly continuous sampling covariance vector in PSS technology, an incomplete signal subspace can be obtained. Then, a special matrix can be obtained by using this incomplete signal subspace. Meanwhile the incomplete signal subspace can also be repaired by the special matrix. At last, the multiple signal classification (MUSIC) algorithm is used to obtain direction estimations. In the process of obtaining signal subspace, no eigenvalue decomposition (EVD) needs to be performed. Compared with the traditional spatial smoothing (SS) technology, the proposed algorithm has lower computational complexity and higher estimation precision. Many simulation results are provided to support the proposed scheme.


Sheng Liu, Feng Qin, Jing Zhao, Weizhi Xiong, and Ziqing Yuan, "Fast Direction-Finding Algorithm by Partial Spatial Smoothing in Sparse MIMO Radar," Progress In Electromagnetics Research M, Vol. 93, 127-136, 2020.


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