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• W2109452261 abstract "In this paper, we address the problem of estimating the number of sources impinging on an array of sensors in the presence of unknown non-uniform noise. In such a situation, sensor noise levels across the array are spatially inhomogeneous. We first consider the eigenvalues of the array correlation matrix as a set of measured data, and then we treat the eigenvalues corresponding to the sources as outliers. Thus, the robust source detection in array processing is viewed as a problem of outlier detection in the eigenvalue domain. Then, we propose a new source detection method based on multiple test procedures that considers ordered differences of the robust distance estimates. The proposed approach can be used in uniform/non-uniform noise, non-Gaussian noise, and colored noise. Unlike the information theoretic criteria, which depend on the selected model, our technique can be applied for many array processing models , and is therefore favourable in real world applications." @default.
• W2109452261 created "2016-06-24" @default.
• W2109452261 creator A5021397477 @default.
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• W2109452261 date "2009-08-01" @default.
• W2109452261 modified "2023-09-22" @default.
• W2109452261 title "Source number estimation for unbalanced arrays using robust outlier detection in the eigenvalue domain" @default.
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• W2109452261 doi "https://doi.org/10.1109/ssp.2009.5278543" @default.
• W2109452261 hasPublicationYear "2009" @default.
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