Classification and Localization of Mixed Sources after Blind Calibration of Unknown Mutual Coupling
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 ar...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2019/5943956 |
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| Summary: | 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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| ISSN: | 1687-5869 1687-5877 |