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Ship-to-Ship State Observer Using Sensor Fusion and the Extended Kalman Filter
Author(s) -
Sondre Sanden Tørdal,
Geir Hovland
Publication year - 2019
Publication title -
journal of offshore mechanics and arctic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.559
H-Index - 46
eISSN - 1528-896X
pISSN - 0892-7219
DOI - 10.1115/1.4041643
Subject(s) - kalman filter , extended kalman filter , sensor fusion , observer (physics) , inertial measurement unit , computer science , computer vision , relative motion , orientation (vector space) , filter (signal processing) , inertial frame of reference , control theory (sociology) , artificial intelligence , mathematics , physics , geometry , control (management) , quantum mechanics , mechanics
In this paper, a solution for estimating the relative position and orientation between two ships in six degrees-of-freedom (6DOF) using sensor fusion and an extended Kalman filter (EKF) approach is presented. Two different sensor types, based on time-of-flight and inertial measurement principles, were combined to create a reliable and redundant estimate of the relative motion between the ships. An accurate and reliable relative motion estimate is expected to be a key enabler for future ship-to-ship operations, such as autonomous load transfer and handling. The proposed sensor fusion algorithm was tested with real sensors (two motion reference units (MRS) and a laser tracker) and an experimental setup consisting of two Stewart platforms in the Norwegian Motion Laboratory, which represents an approximate scale of 1:10 when compared to real-life ship-to-ship operations.

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