{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T05:56:51Z","timestamp":1761631011483,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T00:00:00Z","timestamp":1669161600000},"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","doi-asserted-by":"publisher","award":["61971392"],"award-info":[{"award-number":["61971392"]}],"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>As the radar resolution improves, the extended structure of the targets in radar echoes can make a significant contribution to improving tracking performance, hence specific trackers need to be designed for these targets. However, traditional radar target tracking methods are mainly based on the accumulation of the target\u2019s motion information, and the target\u2019s appearance information is ignored. In this paper, a novel tracking algorithm that exploits both the appearance and motion information of a target is proposed to track a single extended target in maritime surveillance scenarios by incorporating the Bayesian motion state filter and the correlation appearance filter. The proposed algorithm consists of three modules. Firstly, a Bayesian module is utilized to accumulate the motion information of the target. Secondly, a correlation module is performed to capture the appearance features of the target. Finally, a fusion module is proposed to integrate the results of the former two modules according to the Maximum A Posteriori Criterion. In addition, a feedback structure is proposed to transfer the fusion results back to the former two modules to improve their stability. Besides, a scale adaptive strategy is presented to improve the tracker\u2019s ability to cope with targets with varying shapes. In the end, the effectiveness of the proposed method is verified by measured radar data. The experimental results demonstrate that the proposed method achieves superior performance compared with other traditional algorithms, which simply focus on the target\u2019s motion information. Moreover, this method is robust under complicated scenarios, such as clutter interference, target shape changing, and low signal-to-noise ratio (SNR).<\/jats:p>","DOI":"10.3390\/rs14235937","type":"journal-article","created":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T02:54:05Z","timestamp":1669258445000},"page":"5937","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Marine Extended Target Tracking for Scanning Radar Data Using Correlation Filter and Bayes Filter Jointly"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1963-003X","authenticated-orcid":false,"given":"Jiaqi","family":"Liu","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8560-2059","authenticated-orcid":false,"given":"Zhen","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7238-8364","authenticated-orcid":false,"given":"Di","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1259-7660","authenticated-orcid":false,"given":"Weidong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8281-9244","authenticated-orcid":false,"given":"Chang","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A new approach to linear filtering and prediction problems","volume":"1","author":"Kalman","year":"1960","journal-title":"Trans. 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