DOA Estimation for Switch-Element Arrays Based on Sparse Representation
Liang Liu, Zhouchen Li, Jiancheng An, Lu Gan, Hongbin Li
Abstract
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.
BibTeX
@inproceedings{icassp2024_doaestimationfor,
title = {DOA Estimation for Switch-Element Arrays Based on Sparse Representation},
author = {Liang Liu and Zhouchen Li and Jiancheng An and Lu Gan and Hongbin Li},
booktitle = {ICASSP 2024},
year = {2024}
}