Source number estimation for unbalanced arrays using robust outlier detection in the eigenvalue domain
Pawan Setlur, M. Sahmoudi, François Gagnon · 2009 IEEE/SP 15th Workshop on Statistical Signal Processing · 2009
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.