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Online Sparse DOA Estimation Based on Sub–Aperture Recursive LASSO for TDM–MIMO Radar.

Authors :
Luo, Jiawei
Zhang, Yongwei
Yang, Jianyu
Zhang, Donghui
Zhang, Yongchao
Zhang, Yin
Huang, Yulin
Jakobsson, Andreas
Source :
Remote Sensing. May2022, Vol. 14 Issue 9, p2133-2133. 19p.
Publication Year :
2022

Abstract

The least absolute shrinkage and selection operator (LASSO) algorithm is a promising method for sparse source location in time–division multiplexing (TDM) multiple–input, multiple–output (MIMO) radar systems, with notable performance gains in regard to resolution enhancement and side lobe suppression. However, the current batch LASSO algorithm suffers from high–computational complexity when dealing with massive TDM–MIMO observations, due to high–dimensional matrix operations and the large number of iterations. In this paper, an online LASSO method is proposed for efficient direction–of–arrival (DOA) estimation of the TDM–MIMO radar based on the receiving features of the sub–aperture data blocks. This method recursively refines the location parameters for each receive (RX) block observation that becomes available sequentially in time. Compared with the conventional batch LASSO method, the proposed online DOA method makes full use of the TDM–MIMO reception time to improve the real–time performance. Additionally, it allows for much less iterations, avoiding high–dimensional matrix operations, allowing the computational complexity to be reduced from O K 3 to O K 2 . Simulated and real–data results demonstrate the superiority and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
14
Issue :
9
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
156874471
Full Text :
https://doi.org/10.3390/rs14092133