Joint Angular-Frequency Distribution Estimation of Incoherently Distributed Wideband Sources via Low-Rank Matrix Recovery

Abstract

This article considers the problem of joint angular-frequency distribution (JAFD) estimation for incoherently distributed wideband (IDW) sources. It is observed that the angular spread and the frequency bandwidth of IDW signals degrade the sparsity in angle and frequency domains, however, give rise to a useful low-rank structure, which can be exploited to estimate the JAFD. By showing the low-rank property of the JAFD matrix for IDW sources, a rank minimization problem is formulated to directly estimate the JAFD matrix. Then, an efficient algorithm is developed by combining the alternating direction method of multipliers and the iteratively reweighted nuclear norm algorithm to approximate the nonconvex rank function. Finally, off-grid estimators are applied to estimate the key parameters of the JAFD. The Cramer–Rao bound of the key parameters are also deduced. Numerical simulations show that the proposed method enjoys better precision and faster computation than traditional methods.