ORCID
- Sanjay Sharma: 0000-0002-5062-3199
Abstract
This report presents a fuzzy multi-sensor data fusion process forcombining heading estimates from three separate Kalman filters withthe aim of constructing a fault tolerant navigation system for theSpringer Uninhabited Surface Vehicle (USV). A single gyroscopic unitand three independent compasses are used to acquire data onboard thevessel. The inertial data from the gyroscope is combined in turn withthe readings from each compass via a separate Kalman filter (KF). Thethree ensuing KF estimates of the heading angle of the vehicle are thenfused via a fuzzy system designed to produce accurate headinginformation even in the face of a failure in one of the compasses. Asimulation study demonstrates the effectiveness of the proposed fuzzydata fusion process.
Publication Date
2014-04-11
Volume
MIDAS.SMSE.2014.TR.010
Publisher
MIDAS - Marine and Industrial Dynamic Analysis, Plymouth University
Deposit Date
2025-08-08
Recommended Citation
Liu, W., Motwani, A., Sharma, S., Sutton, R., & Bucknall, R. (2014) 'Fault Tolerant Navigation of USV using Fuzzy Multi-sensor Fusion', MIDAS - Marine and Industrial Dynamic Analysis, Plymouth University: Retrieved from https://pearl.plymouth.ac.uk/more-fose-research/176
