DOA Estimation for Switch-Element Arrays Based on Sparse Representation

In the context of perceiving spatial information, researchers extensively investigate the use of large-scale arrays due to their numerous advantages such as high precision and resolution, as well as increased degrees of freedom. However, large-scale arrays may be impractical in certain applications due to the prohibitive hardware cost. To address this bottleneck, a switch-element array structure composed of a switch network offers an appealing low-cost alternative by multiplexing the Radio Frequency (RF) chains. With this novel array architecture, we explore the direction-of-arrival (DOA) estimation problem and examine the inherent signal structures. Subsequently, two DOA estimation algorithms based on a dynamic-dictionary sparse representation are developed, namely the Jointly-Selected Orthogonal Matching Pursuit (JSOMP) algorithm and the Auxiliary Variable Joint Alternating Optimization (AVJAO) algorithm. The performance of the proposed algorithms is demonstrated through simulation results.