{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T20:55:04Z","timestamp":1791924904629,"version":"4.3.4"},"reference-count":63,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Autonomous navigation and mooring in confined waters require a navigation solution that remains reliable when individual sensing channels are delayed, unavailable, or environmentally degraded. A risk- and integrity-aware architecture was developed for joint processing of RTK-GNSS, inertial and heading measurements, short-range radar, LiDAR, camera, AIS, ultrasonic ranging, propulsion feedback, environmental, and mooring-line tension data. Asynchronous time alignment is combined with sensor-quality assessment, innovation-based fault detection and isolation, covariance adaptation, active-set reconfiguration, protection-level monitoring, and risk-dependent allocation of authority between automation and the operator. The system was evaluated during a five-day campaign comprising 40 runs, four operational phases, 480 synchronized evaluation epochs, and 16 controlled single-sensor or combined sensor-degradation events. Under nominal conditions, horizontal-position and heading RMSE were 0.043 m and 0.176\u00b0, respectively. All 64 fault-active diagnostic records were identified; mean event-log detection and controlled-recovery latencies were 3.17 s and 6.34 s. Horizontal protection-level coverage was 99.3% for single-fault epochs and 100% for combined-fault epochs. One combined-fault docking run contained five consecutive aborted decision epochs, while no unsafe-autonomy event was recorded. The measurements therefore indicate bounded degradation of the navigation solution and conservative transfer of authority when sensing integrity decreases. Because all injected-fault runs were acquired under adverse weather whereas nominal runs were acquired under calm or moderate conditions, the condition-class RMSE differences reported below are descriptive and must not be interpreted as isolated causal effects of sensor faults.<\/jats:p>","DOI":"10.3390\/s26185702","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:55:46Z","timestamp":1788879346000},"page":"5702","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Risk-Aware Fault-Tolerant Multisensor Fusion for Human\u2013Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters"],"prefix":"10.3390","volume":"26","author":[{"given":"Sergey I.","family":"Kondratyev","sequence":"first","affiliation":[{"name":"Rector\u2019s Office, Admiral Ushakov Maritime State University, 93 Lenin Ave., Novorossiysk 353918, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evgeniy V.","family":"Khekert","sequence":"additional","affiliation":[{"name":"Rector\u2019s Office, Admiral Ushakov Maritime State University, 93 Lenin Ave., Novorossiysk 353918, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0620-9561","authenticated-orcid":false,"given":"Nikita V.","family":"Martyushev","sequence":"additional","affiliation":[{"name":"Department of Information Technologies, Tomsk Polytechnic University, Tomsk 634050, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8686-9556","authenticated-orcid":false,"given":"Boris V.","family":"Malozyomov","sequence":"additional","affiliation":[{"name":"Department of Electrotechnical Complexes, Novosibirsk State Technical University, 20 Karl Marx Avenue, Novosibirsk 630073, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vladislav V.","family":"Kukartsev","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Siberian Federal University, Krasnoyarsk 660041, Russia"},{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, Moscow 105005, Russia"},{"name":"Department of Applied Computer Science, Russian State Agrarian University\u2014Moscow Timiryazev Agricultural Academy, Moscow 127434, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valeriya V.","family":"Tynchenko","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Siberian Federal University, Krasnoyarsk 660041, Russia"},{"name":"Center for Continuing Education, Bauman Moscow State Technical University, Moscow 105005, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tatyana Aleksandrovna","family":"Panfilova","sequence":"additional","affiliation":[{"name":"Center for Continuing Education, Bauman Moscow State Technical University, Moscow 105005, Russia"},{"name":"Department of Technological Machines and Equipment for the Oil and Gas Complex, Siberian Federal University, Krasnoyarsk 660041, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8963-7830","authenticated-orcid":false,"given":"Yadviga Aleksandrovna","family":"Tynchenko","sequence":"additional","affiliation":[{"name":"Center for Continuing Education, Bauman Moscow State Technical University, Moscow 105005, Russia"},{"name":"Department of Technological Machines and Equipment for the Oil and Gas Complex, Siberian Federal University, Krasnoyarsk 660041, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9380-0968","authenticated-orcid":false,"given":"Natalia I.","family":"Kozhukhova","sequence":"additional","affiliation":[{"name":"Department of Material Science and Material Technology, Belgorod State Technological University Named After V.G. 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