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DOI 10.3390/s26185702

Медицинская библиотека · Sensors (Basel, Switzerland) · 2026

Risk-Aware Fault-Tolerant Multisensor Fusion for Human-Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters.

Kondratyev Sergey I, Khekert Evgeniy V, Martyushev Nikita V, Malozyomov Boris V, Kukartsev Vladislav V, Tynchenko Valeriya V, Panfilova Tatyana Aleksandrovna, Tynchenko Yadviga Aleksandrovna, Kozhukhova Natalia I

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Аннотация

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°, 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.

Для цитирования: Kondratyev Sergey I, Khekert Evgeniy V, Martyushev Nikita V, Malozyomov Boris V, Kukartsev Vladislav V, Tynchenko Valeriya V, Panfilova Tatyana Aleksandrovna, Tynchenko Yadviga Aleksandrovna, Kozhukhova Natalia I. Risk-Aware Fault-Tolerant Multisensor Fusion for Human-Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters.. Sensors (Basel, Switzerland). 2026. DOI: 10.3390/s26185702.
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