{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T18:44:34Z","timestamp":1761677074784,"version":"build-2065373602"},"reference-count":57,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T00:00:00Z","timestamp":1651190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China and Special Science Foundation of Quzhou","doi-asserted-by":"publisher","award":["61901092","61901090"],"award-info":[{"award-number":["61901092","61901090"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The least absolute shrinkage and selection operator (LASSO) algorithm is a promising method for sparse source location in time\u2013division multiplexing (TDM) multiple\u2013input, multiple\u2013output (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\u2013computational complexity when dealing with massive TDM\u2013MIMO observations, due to high\u2013dimensional matrix operations and the large number of iterations. In this paper, an online LASSO method is proposed for efficient direction\u2013of\u2013arrival (DOA) estimation of the TDM\u2013MIMO radar based on the receiving features of the sub\u2013aperture 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\u2013MIMO reception time to improve the real\u2013time performance. Additionally, it allows for much less iterations, avoiding high\u2013dimensional matrix operations, allowing the computational complexity to be reduced from OK3 to OK2. Simulated and real\u2013data results demonstrate the superiority and effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/rs14092133","type":"journal-article","created":{"date-parts":[[2022,5,2]],"date-time":"2022-05-02T07:08:58Z","timestamp":1651475338000},"page":"2133","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Online Sparse DOA Estimation Based on Sub\u2013Aperture Recursive LASSO for TDM\u2013MIMO Radar"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3644-7168","authenticated-orcid":false,"given":"Jiawei","family":"Luo","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"}]},{"given":"Yongwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"}]},{"given":"Jianyu","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"}]},{"given":"Donghui","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5634-6156","authenticated-orcid":false,"given":"Yongchao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"},{"name":"Yangtze Delta Region Institute, University of Electronic Science and Technology of China (UESTC), Quzhou 324003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6761-2269","authenticated-orcid":false,"given":"Yin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"},{"name":"Yangtze Delta Region Institute, University of Electronic Science and Technology of China (UESTC), Quzhou 324003, China"}]},{"given":"Yulin","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi\u2013Tech Zone, Chengdu 611731, China"},{"name":"Yangtze Delta Region Institute, University of Electronic Science and Technology of China (UESTC), Quzhou 324003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2156-6973","authenticated-orcid":false,"given":"Andreas","family":"Jakobsson","sequence":"additional","affiliation":[{"name":"Centre for Mathematical Sciences, Lund University, 221 00 Lund, Sweden"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1109\/JSTSP.2009.2038964","article-title":"Iterative adaptive approaches to MIMO radar imaging","volume":"4","author":"Roberts","year":"2010","journal-title":"IEEE J. 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