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首先将信号源的距离和到达角信息进行分离,构造出一个新的方向矩阵;利用此新的方向矩阵构造一个二阶协方差矩阵,并通过仅仅一维搜索获得了所有信号源的到达角.然后基于已得到的到达角信息,结合多重信号分类(MUSIC)算法,通过一维搜索将具有相同到达角的近场源和远场源进行了分离.最后,基于已获得的近场源的到达角信息,估计出了所有近场源的距离参数.此算法不需要构造高阶累计量、二维搜索和参数配对;所有的实现过程仅需一维搜索,计算量小,实现简便.数值实验证明了所提出算法的有效性.
Firstly, the signal source distance and angle of arrival information are separated to construct a new orientation matrix. A second-order covariance matrix is constructed by using this new orientation matrix, and the arrival angles of all signal sources are obtained by only one-dimension search. Then based on the obtained angle of arrival information, combined with multiple signal classification (MUSIC) algorithm, the near-field and far-field sources with the same angle of arrival are separated by one-dimensional search.Finally, based on the arrival of the near-field source Angle information, the distance parameters of all near-field sources are estimated.The algorithm does not need to construct high-order cumulant, two-dimensional search and parameter matching.All the realization process only needs one-dimensional search, the calculation is small and easy to implement.Numerical experiments The validity of the proposed algorithm is proved.