Underwater navigation system with velocity measurement by a receding horizon Kalman filter

The problem of constructing a receding horizon filter for inertial navigation systems affected by external disturbance has been described. Noises are assumed to be bounded, additive and contained in both state and measurement equations. The estimator is designed according to the sliding-window strategy, so that it minimizes the receding horizon estimation cost function. The derived filter is applied to a velocity aided inertial navigation system. It is clearly demonstrated that the derived filter is more accurate than the standard Kalman filter for underwater navigation systems under the action of temporary unknown disturbances based on simulations.