Robust Detection of Sources based on Clustering in Spatially Correlated Noise Fields

Z. Bao, B. Han, and S. Wu (PRC)


Fuzzy clustering, Source number detection, and Array signal processing


The research of sources number detection is still open and challenging issue in array signal processing. The accurate estimation may be very essential to those high resolution direction finding algorithms. Three crucial issues are discussed for the application of cluster method to the source-number detection. A detection method based on Fuzzy-c-Means clustering algorithm has been proposed, which uses canonical correlation coefficients of the joint covariance matrix as the feature to be classified. Compared with the classical methods, our algorithm has better performance in low SNR and angular resolution. In the spatially correlated noise fields, the simulation results demonstrate the effectiveness and robustness of the proposed scheme.

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