Abstract
In this paper, a partitioned matrices products approach based on Gerschgorin disk estimation (PM-GDE) method is proposed in order to solve the problem of correlated source number estimation under spatially correlated noise background. This method is based on a uniform linear array. The improved partitioned matrices products of the array receiving data are computed by weighted summation of the rows and adjustment of the element sequence from partitioned matrices products matrix. The auto correlation matrix of the partitioned matrices products and its Gerschgorin radii are computed. A source number estimation criterion based on Gerschgorin radii is deduced by considering the second-order statistical property of the partitioned matrices products auto correlation matrix. Simulations results validate the efficiency and robustness of PM-GDE with correlated signals and spatially correlated noise background. PM-GDE performs better than its counterpart especially for close incident azimuth correlated sources.
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This work was supported by the National Nature Science Foundation of China (NSFC) under Grants 61431005, 61671211.
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Wang, J., Ji, F., Chen, F. et al. Correlated Source Number Estimation with Gerschgorin Radii of Partitioned Matrices Products. Wireless Pers Commun 107, 1077–1091 (2019). https://doi.org/10.1007/s11277-019-06318-w
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DOI: https://doi.org/10.1007/s11277-019-06318-w