Paper accepted at ICASSP 2020

The paper "Source Enumeration via Toeplitz Matrix Completion" co-authored by V. Garg, P. Gimenez-Febrer, A. Pages-Zamora and I. Santamaria will be presented at the IEEE Int. Conference on Acoustics, Speech and Signal Processing to be held in Barcelona, Spain, May 4-9, 2020.

Abstract—This paper addresses the problem of source enumeration by an array of sensors in the presence of noise whose spatial covariance structure is a diagonal matrix with possibly different variances, referred to non-iid noise hereafter, when the sources are uncorrelated. The diagonal terms of the sample covariance matrix are removed and, after applying Toeplitz rectification as a denoising step, the signal covariance matrix is reconstructed by using a low-rank matrix completion method adapted to enforce the Toeplitz structure of the sought solution. The proposed source enumeration criterion is based on the Frobenius norm of the
reconstructed signal covariance matrix obtained for increasing rank values. As illustrated by simulation examples, the proposed method performs robustly for both small and large-scale arrays with few snapshots, i.e. small-sample regime.