One-Bit Doa Estimation Via Sparse Linear Arrays

Parameter estimation from noisy and quantized received signals has become an important topic in signal processing, as it offers low cost and low complexity in the implementation. Techniques to achieve high estimation performance in spite of the coarse quantizers have recently been advanced. On the other hand, Direction-of-Arrival (DoA) estimation using Sparse Linear Arrays (SLAs), such as nested and co-prime arrays, has recently gained considerable interest in array processing due to their attractive capability of providing enhanced degrees of freedom. In this paper, we propose a novel algorithm to estimate DoAs from one-bit samples received by a SLA. The proposed approach first provides an estimate of the received signal covariance matrix through minimization of a constrained weighted least-squares criterion. Then, the DoA are estimated by applying MUSIC on the estimated covariance matrix. Several numerical results are provided to demonstrate the performance of the proposed approach compared to the existing algorithms.