Adaptive Beamforming for Cascaded Sparse Diversely Polarized Planar Array

Abstract

Adaptive beamforming plays an increasingly vital role in various applications, including radar, sonar, telecommunications, and many other related fields. In this paper, we present an adaptive beamformer (called polarimetric Sparse-Reconstruction beamformer) based on cascaded sparse diversely polarized planar array. The cascaded sparse array consists of multiple parallel sparse linear subarrays, whose difference co-array has no holes. The beamformer is operated in the joint spatial and polarization domain; thus, can potentially suppress the interferences that are close to the desired signal with different polarization states. Two key building blocks of our proposed beamformer are polynomial rooting-based closed-form two-dimensional direction-of-arrival and polarization joint estimation procedures, where the involved polynomial coefficients are also derived. Then, the closed-form power distribution estimation is presented to reconstruct the interference-plus-noise covariance matrix by leveraging the sparsity of the desired signal and interferences in the joint spatial and polarization domain. Thus, the proposed adaptive beamformer is computationally efficient, since all the procedures involved are formatted by closed-form expressions. Finally, a set of simulation examples are given to evaluate the characteristics of the proposed cascaded sparse array as well as the performance and robustness of the proposed beamformer in different scenarios, and compared against several existing approaches.