One-Bit DOA Estimation for Partially Calibrated Arrays with Unknown Uncertainties

Combining multiple distributed sub-arrays can create an array with a much larger aperture, achieving significant improvement in direction-of-arrival (DOA) estimation performance. In this paper, one-bit DOA estimation for partially calibrated arrays (PCAs) is investigated, in the presence of imperfections with unknown inter-subarray displacements and amplitude-phase uncertainty. Toward this end, the DOAs are decoupled with these imperfections, forming a decoupled array signal model after one-bit quantization. Then, based on the group-sparsity (GS) concept, a one-bit sparse representation of array covariance vectors (SRACV) framework is formulated, exploiting information from all sub-arrays jointly. Besides, the pessimistic Cramér-Rao Bound (CRB) for one-bit measurements is derived to provide a benchmark for evaluating the performance. Simulation results are provided to demonstrate the effectiveness and improved performance of the proposed method.