Multi-source off-grid DOA estimation using iterative phase offset correction in coarray domain

Abstract

Direction-of-arrival (DOA) estimation performance degrades when arrival angles of incident signals do not locate exactly on the discretized grid points. Existing off-grid DOA estimation algorithms either suffer from high computational complexity or are restricted to uniform linear arrays (ULAs). In order to overcome these disadvantages, we propose a simple but effective off-grid DOA estimation method, referred to as iterative phase offset correction (IPOC), for non-uniform linear arrays (NLAs) in this work. The proposed IPOC first transforms the received signal into the coarray domain and then iteratively corrects the phase offset between the coarray data and presumed model caused by angle biases according to a closed-form formula. In the case of multiple sources, we separate these sources using generalized inner product and then utilize IPOC to sequentially estimate the off-grid angle of one source in each iteration. The spectral leakage between multiple sources is reduced as well by subtracting cross-correlation terms, thus overcoming the shortage of requiring a large number of training snapshots. We calculate the mean squared error (MSE) of the proposed method theoretically. Simulation results demonstrate the effectiveness and efficacy of the proposed method for off-grid DOA estimation using NLAs with very few snapshots.