Sparse Array Placement for Bayesian Compressive Sensing Based Direction of Arrival Estimation

• Published in: Proceedings of the IEEE National Radar Conference (1996) pp. 1 - 6
• Main Authors: Lamberti, Lucas L., Roldan, Ignacio, Yarovoy, Alexander, Fioranelli, Francesco
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06.05.2024
• Subjects: antenna placement; Bayes methods; Bayesian Compressive Sensing; Direction-of-arrival estimation; Directive antennas; DoA estimation; Entropy; Estimation; MIMO radar; Radar antennas; Uncertainty
• ISSN: 2375-5318
• DOI: 10.1109/RadarConf2458775.2024.10548658

In this paper, an algorithm to generate a sparse linear antenna array for Direction of Arrival (DoA) estimation that works well in combination with Bayesian Compressive Sensing (BCS) is proposed. The proposed algorithms rely on the provided information inherent to BCS, i.e., the entropy of the recovered estimation vector, to place new sensor antenna elements in an initially empty array, so that the most additional information is gathered about the observed scene. It is shown by means of simulation and radar measurements that BCS methods for DoA estimation using sparse sensor arrays provide promising results in terms of detection probability and estimation accuracy. Furthermore, the proposed algorithms are able to generate sparse sensor arrangements which provide an improved performance when compared against randomly generated sparse arrays.