{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T05:07:24Z","timestamp":1778908044760,"version":"3.51.4"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>This paper presents research on a complete, closed-loop environmental perception strategy at the system level and on standardized sea trial verification methods for unmanned surface vehicles (USVs) in typical maritime mission scenarios. Existing research on USV perception mostly focuses on optimizing discrete functional algorithms, such as object detection and tracking, with verification performed only in specific scenarios. These works generally lack task-matched perception schemes covering the full operation cycle and corresponding standardized, reproducible verification systems, making them difficult to adapt to the full-cycle execution requirements of real, complex maritime tasks. To address the above issues, this paper proposes a systematic environmental perception strategy for typical USV operation tasks, establishes a complete workflow from object detection to obstacle avoidance perception and decision-making, and designs two sets of standardized sea trial schemes for core tasks. These schemes provide unified specifications and an evaluation benchmark for verifying the real-world performance of USV environmental perception systems. Finally, full-cycle sea trials on a real ship are completed, and the test results verify the engineering practicability of the proposed perception strategy, as well as the reproducibility, standardization, and extensibility of the established test system, with the laser positioning hit rate improved by 82% and 54% under green-water and foggy conditions compared with the conventional miss distance-based method.<\/jats:p>","DOI":"10.3390\/systems14050479","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T07:43:51Z","timestamp":1777448631000},"page":"479","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Environmental Perception Strategies and Sea Trial Methods for Unmanned Surface Vehicles in Typical Mission Scenarios"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6216-4893","authenticated-orcid":false,"given":"Qingze","family":"Yu","sequence":"first","affiliation":[{"name":"Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronghua","family":"Huang","sequence":"additional","affiliation":[{"name":"Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangnian","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2358","DOI":"10.1109\/TVT.2021.3136670","article-title":"Autonomous Pilot of Unmanned Surface Vehicles: Bridging Path Planning and Tracking","volume":"71","author":"Wang","year":"2022","journal-title":"IEEE Trans. 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