{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:02:08Z","timestamp":1760144528432,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,28]],"date-time":"2024-04-28T00:00:00Z","timestamp":1714262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"The National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12074315","52231013","62101549"],"award-info":[{"award-number":["12074315","52231013","62101549"]}],"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>In environments with a low signal-to-reverberation ratio (SRR) characterized by fluctuations in clutter number and distribution, particle filter-based tracking methods may experience significant fluctuations in the posterior probability of existence. This can lead to interruptions or even loss of the target trajectory. To address this issue, an adaptive PF-based tracking method (APF) with joint reverberation suppression is proposed. This method establishes the state space model under the Bayesian framework and implements it through particle filtering. To keep the weak target echoes, all the non-zero entries contained in the sparse matrix processed by the low-rank and sparsity decomposition (LRSD) are treated as the measurements. The prominent feature of this approach is introducing an adaptive measurement likelihood ratio (AMLR) into the posterior update step, which solves the problem of unstable tracking due to the strong fluctuation in the number of point measurements per frame. The proposed method is verified by four shallow water experimental datasets obtained by an active sonar with a uniform horizontal linear array. The results demonstrate that the tracking frame success ratio of the proposed method improved by over 14% compared with the conventional PF tracking method.<\/jats:p>","DOI":"10.3390\/rs16091569","type":"journal-article","created":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T04:26:16Z","timestamp":1714364776000},"page":"1569","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Adaptive Tracking Method for Moving Target in Fluctuating Reverberation Environment"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-4904-671X","authenticated-orcid":false,"given":"Ning","family":"Wang","sequence":"first","affiliation":[{"name":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Ocean Acoustics and Sensing, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi\u2019an 710072, China"}]},{"given":"Rui","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Ocean Acoustics and Sensing, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi\u2019an 710072, China"}]},{"given":"Kunde","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Ocean Acoustics and Sensing, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi\u2019an 710072, China"},{"name":"Ocean Institute, Northwestern Polytechnical University, Taicang 215400, China"}]},{"given":"Zipeng","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ocean Acoustics and Sensing, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi\u2019an 710072, China"},{"name":"Ocean Institute, Northwestern Polytechnical University, Taicang 215400, China"}]},{"given":"Zhanchao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"},{"name":"Key Laboratory of Ocean Acoustics and Sensing, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi\u2019an 710072, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4661","DOI":"10.1109\/TGRS.2015.2405672","article-title":"Automatic Sea-Surface Obstacle Detection and Tracking in Forward-Looking Sonar Image Sequences","volume":"53","author":"Karoui","year":"2015","journal-title":"IEEE Trans. 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