Wideband source localization using sparse learning via iterative minimization

•Two direction-of-arrival estimation algorithms for wideband sources are proposed.•The algorithms are extensions of the SLIM algorithm designed for narrowband sources.•The algorithms are extended to the localization scenario with vector-sensor arrays.•The classical RELAX algorithm is incorporated to further refine the localization results.•The wideband deterministic Cramer–Rao bound is derived.

In this paper, two extensions of the Sparse Learning via Iterative Minimization (SLIM) algorithm are presented for wideband source localization using a sensor array. The proposed methods exploit the joint sparse structure across all frequency bins, and estimate the spatial pseudo-spectra at various frequency bins jointly and iteratively. Via several numerical examples, we show that the proposed methods can provide high-resolution angle estimates and excellent source localization performance, and are able to resolve the left–right ambiguity problem, when used together with the vector sensor array technology.