Multi-target localization using frequency diverse coprime arrays with coprime frequency offsets

The performance of the frequency diverse array (FDA) radar is fundamentally limited by the geometry of the array and the frequency offset. In this paper, we overcome this limitation by introducing a novel sparsity-based multi-target localization approach incorporating both coprime array and coprime frequency offset. The covariance matrix of the received signals corresponding to all sensors and employed frequencies is formulated to generate a space-frequency virtual difference coarrays. The proposed approach enables the localization of up to O(M2 N2) targets using O(M + N) physical sensors with O(M + N) frequencies for a coprime pair of M and N. The joint DOA and range estimation is cast as a sparse reconstruction problem and solved using the complex multi-task Bayesian compressive sensing technique.