In order to deal with the problem of passive mixed source localization under unknown mutual coupling, the authors propose an effective algorithm. This algorithm provides array blind calibration as well as classification and localization of mixed sources in this paper. In practice, an ideal sensor array without the effects of unknown mutual coupling is rarely satisfied, which degrades the performance of most high-resolution algorithms. Firstly, the directions of arrival of far-field sources and the number of nonzero mutual coupling coefficients are estimated directly through the rank-reduction type method. Then, these estimates are adopted to reconstruct the mutual coupling matrix. In addition, the fourth-order cumulant technique is required to eliminate the Gauss colored noise effects caused by mutual coupling calibration of the raw received data vector. Finally, in an algebraic way, the results of rapid classification and localization of near-field sources are obtained without any spectral search. The proposed algorithm is described in detail, and its behavior is illustrated by numerical examples.

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farfield sources rankreduction type method then fourthorder cumulant technique algorithm spectral search highresolution algorithms raw received data rapid classification and localization of nearfield sources array blind calibration nonzero mutual coupling coefficients gauss colored noise effects

Kai Wang,Ling Wang,Jian Xie,Yuexian Wang,.Classification and Localization of Mixed Sources after Blind Calibration of Unknown Mutual Coupling. 2019 (),.

Kai Wang,Ling Wang,Jian Xie,Yuexian Wang,"Classification and Localization of Mixed Sources after Blind Calibration of Unknown Mutual Coupling" 2019

Kai Wang,Ling Wang,Jian Xie,Yuexian Wang,"Classification and Localization of Mixed Sources after Blind Calibration of Unknown Mutual Coupling"