On the statistical performance of music for distributed sources
O. Najim, Pascal Vallet, Guillaume Ferré, Xavier Mestre · 2016
This paper addresses the statistical behaviour of the MUSIC method for DoA estimation, in a scenario where each source signal direct path is disturbed by a clutter spreading in an angular neighborhood around the source DoA. In this scenario, it is well-known that subspace methods performance suffers from an additional clutter subspace, which breaks the orthogonality between the source steering vectors and noise subspace. To perform a statistical analysis of the MUSIC DoA estimates, we consider an asymptotic regime in which both the number of sensors and the sample size tend to infinity at the same rate, and rely on classical random matrix theory results. We establish the consistency of the MUSIC estimates and provide numerical results illustrating their performance in this non standard scenario.