Fault Tolerant Navigation of USV using Fuzzy Multi-sensor Fusion

This report presents a fuzzy multi-sensor data fusion process for combining heading estimates from three separate Kalman filters with the aim of constructing a fault tolerant navigation system for the Springer Uninhabited Surface Vehicle (USV). A single gyroscopic unit and three independent compasses are used to acquire data onboard the vessel. The inertial data from the gyroscope is combined in turn with the readings from each compass via a separate Kalman filter (KF). The three ensuing KF estimates of the heading angle of the vehicle are then fused via a fuzzy system designed to produce accurate heading information even in the face of a failure in one of the compasses. A simulation study demonstrates the effectiveness of the proposed fuzzy data fusion process.