Fusion of multiple sensor measurements for navigation of an unmanned marine surface vehicle

Abstract

This paper proposes a method for fused navigation of an unmanned marine surface vehicle (UMSV). The method also detects the outlier and interference of global positioning system (GPS) simultaneously. The method fuses available sensor measurements through extended Kalman filter (EKF) to find the location and attitude of the vehicle. The method uses error covariance of estimated location for detection of GPS outlier and interference. When outlier and interference of the GPS is detected, the method excludes GPS data from navigation process. The measurements to be fused for the navigation are position by GPS, acceleration, angular rate, magnetic field, linear velocity, and range and bearing to acoustic beacons. The method is tested through simulated data and measurement data produced through navigation of a vehicle. The results show that the method detects GPS outlier and interference as well as the GPS recovery, which frees the UMSV navigation from the problem of GPS abnormality. The method is applicable to the vehicle navigation where the UMSV is out of reach from the GPS jamming detection network such as GAARDIAN (GNSS Availability Accuracy Reliability and Integrity Assessment for Timing and Navigation) or jammer detection and location (JLOC) system. ？ 2016 Institute of Control, Robotics and Systems - ICROS.