INS/GPS Aided by Frequency Contents of Vector Observations With Application to Autonomous Surface Crafts

This paper presents a high-accuracy, multirate inertial navigation system (INS) integrating global positioning system (GPS) measurements and advanced vector aiding techniques for precise position and attitude estimation of autonomous surface crafts (ASCs). Designed to be implemented and tested in the DELFIMx catamaran developed at ISR/IST, the navigation system comprises an advanced inertial integration algorithm to account for coning and sculling motions, combined with an extended Kalman filter (EKF) for inertial sensor error compensation. Aiding gravitational observations are optimally exploited in the EKF, by deriving a sensor integration technique that takes into account the vehicle's dynamics bandwidth information to properly trace measurement disturbances and extract the relevant sensor information. The proposed aiding technique and the performance of the navigation system are assessed using experimental data obtained at seatrials with a low-cost hardware architecture installed on-board the DELFIMx platform. It is shown that the low frequency information embodied in pendular measurements improves the compensation of inertial sensor bias and noise, and consequently enhances the performance of position and attitude estimation. The overall improvements obtained with the vector aiding observations are also illustrated for the case of GPS signal outage, emphasizing the extended autonomy of the navigation system with respect to position aiding.