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吉林大学通信工程学院,吉林,长春,130022
Published Online:25 January 2021,
Published:2021
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QIN Yu-di, SUN Xiao-ying, LIU Guo-hong. Passive Localization for Near-Field Sources Based on Covariance Difference[J]. Acta Electronica Sinica, 2021, 49(1): 177-182.
QIN Yu-di, SUN Xiao-ying, LIU Guo-hong. Passive Localization for Near-Field Sources Based on Covariance Difference[J]. Acta Electronica Sinica, 2021, 49(1): 177-182. DOI: 10.12263/DZXB.20141438.
提出一种基于空间差分技术的近场源方位角和距离联合估计新算法.算法利用平稳噪声协方差矩阵关于主对角线对称的特点,构造近场源定位模型下的空间差分矩阵.推导并证明了该矩阵的谱分解特性,以此为基础确定噪声子空间,借助谱峰搜索实现定位参量估计.算法通过对消噪声分量有效降低了未知平稳噪声对定位精度的影响,同时避免了应用差分技术解决信源定位时出现的伪峰问题.均方根误差的仿真结果证明了算法的有效性.
An algorithm for estimation of direction of arrival (DOA) and range of near field source based on the spatial differential technique is proposed in this paper. The algorithm firstly utilizes the feature that the stationary noise covariance matrix is symmetrical about the main diagonal and constructs the spatial difference matrix only containing the target signal location information. Then
it proves the distribution characteristics of the matrix eigenvalues and selects the noise subspace reasonably. Finally
the DOA and range estimations for near-field sources can be obtained through the spectral searching. The algorithm can effectively suppresses the unknown stationary noise and avoid the pseudo peak problems for the application of the spatial differential method when used to solve the source localization. Computer simulations confirm the satisfactory performance of the proposed algorithm.
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