This paper considers the problem of constructing a globally convergent position-and velocity estimator with close-to-optimal noise properties using hydroacoustic long baseline measurements. Three ways of improving the range robustness of the three stage filter for long baseline measurements with unknown wave speed are suggested. One addition is employing depth measurements in addition to pseudo-range measurements, thus increasing range noise robustness and relaxing requirements for transponder placement from not co-planar to not co-linear. Furthermore, a Kalman Filter with a linear measurement model is used, instead of a pseudo-linear time-varying measurement model and a step solving an optimization problem is also added. The proposed scheme is validated through simulation and compared to a standard Extended Kalman Filter and a perfect (non-implementable) Linearized Kalman Filter using real states as linearization point. Simulations suggest that the improved three stage filter will have similar stationary performance as the EKF while having significantly better transient performance and stability subjected to inaccurate initial estimates.
This paper provides a novel formulation relating underwater range measurements to body-fixed position when several acoustic transceivers are mounted on the vehicle and only one transponder is placed in the vehicle's surroundings. This formulation is used in a novel three-stage filter for aided inertial navigation that has both global convergence and nearoptimal performance w.r.t. variance of the estimate. It estimates both the position and velocity of the vehicle, and relies on a globally stable attitude observer to provide estimates of the attitude and angular rate sensor bias. Two different formulations of the novel three-stage filter were tested in simulations and shown to track the true position.
When an underwater intervention vehicle is close to large metallic structures, e.g. subsea oil and gas facilities, magnetic disturbances might render magnetic field measurements biased or useless. This loss of information is critical for attitude estimation, and consequently, for the safety of the operation. In this paper, a three-stage filter for joint position and attitude estimation is developed, replacing the magnetic field measurements with hydroacoustic measurements. This solution assumes a hydroacoustic sensor set up with multiple transponders on the sea floor and 3 or more transceivers on the vehicle. The three-stage filters is shown to yield GES error dynamics of both the translational and rotational motion. The three-stage filter is shown in simulations to successfully estimate both the true position and attitude of the vehicle.
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