Fusion of Navigation Solutions from Different Navigation Systems for an Autonomous Underwater Vehicle

This paper considers the vehicle navigation problem for an autonomous underwater vehicle (AUV) with six degrees of freedom. We approach this problem using an error state formulation of the Kalman filter. Integration of the vehicle's high-rate inertial measurement unit's (IMU's) accelerometers and gyros allow time propagation while other sensors provide measurement corrections. The low-rate aiding sensors include a Doppler velocity log (DVL), an acoustic long baseline (LBL) system that provides round-trip travel times from known locations, a pressure sensor for aiding depth, and an attitude sensor. Measurements correct the filter independently as they arrive, and as such, the filter is not dependent on the arrival of any particular measurement. Different navigation systems are constructed each consisting of a particular set of sensors. The navigation solution from all these systems is fused using decentralized Kalman filtering approach. Autonomous operation requires that there is to be no sharing of measurement information among local filters. Simulation results are provided.