{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:12:40Z","timestamp":1760058760096,"version":"build-2065373602"},"reference-count":61,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T00:00:00Z","timestamp":1745625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Detection and tracking of marine weak targets can be effectively solved by track-before-detect (TBD) algorithms based on particle filtering. However, these algorithms are susceptible to influence from neighboring targets, leading to potential issues like misassociation and tracking failure. In this paper, an auxiliary particle flow track-before-detect algorithm designed for marine neighboring weak targets is proposed which can effectively track marine neighboring weak targets under long-tail sea clutter. Firstly, marine neighboring targets are modeled by the generalized Pareto model, and an offline lookup table is utilized to obtain a non-closed solution, decreasing calculation cost. Subsequently, prediction is employed to classify targets, and measurement information is iteratively used to determine the sequence of target updates, effectively suppressing influence from neighboring targets. Finally, particles with higher measurement energy are chosen, and the Geodesic particle flow is employed to guide the particles toward better importance distribution, which enhances the accuracy of target trajectory estimation. Simulation experiments indicate that compared with track-before-detect algorithms based on parallel partition (PP) and auxiliary parallel partition (APP), the proposed algorithm shows an increase of 43.1% and 25.8% in detection probability at 6 dB, and a reduction of 76.6% and 66.2% in Root Mean Square Error (RMSE). Detection ability and trajectory estimation performance are effectively improved in the simulation, and excellent tracking performance is also confirmed in real clutter experiments.<\/jats:p>","DOI":"10.3390\/rs17091547","type":"journal-article","created":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T05:21:31Z","timestamp":1745817691000},"page":"1547","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Auxiliary Particle Flow Track-Before-Detect Algorithm for Marine Neighboring Weak Targets"],"prefix":"10.3390","volume":"17","author":[{"given":"Fan","family":"Zhang","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1981","DOI":"10.1109\/TAES.2021.3054715","article-title":"A Bernoulli Track-Before-Detect Filter for Interacting Targets in Maritime Radar","volume":"57","author":"Kim","year":"2021","journal-title":"IEEE Trans. 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