Multi-Layer Filled Coprime Arrays for DOA Estimation With Extended Hole-Free Coarray

Coprime arrays have shown desirable properties in reducing mutual coupling and increasing degrees of freedom (DOF) compared to uniform linear arrays (ULAs), which helps improve the estimation performance. However, the holes in the difference coarray of coprime arrays cause estimation performance loss. In this article, we present a multi-layer holes filling strategy for coprime arrays to fill the holes, thus enhancing the uniform difference coarray. Specifically, we first construct a coprime array with multiple duplicated subarrays (CAMDS) and classify the holes in the difference coarray into multiple layers. Then we present a multi-layer filled coprime array (MLFCA) by introducing extra subarrays to fill the holes in different layers, which resultantly achieves significantly increased uniform DOFs (uDOFs). We then derive the optimal MLFCA in the scale of difference coarray and develop an optimized structure to extend the difference coarray. Finally, the proposed coprime arrays enjoy a hole-free difference coarray and achieve a larger uniform difference coarray than previous coprime arrays. Simulation results have verified the merits of the proposed coprime arrays through the subspace-based estimator.