Adaptive Fading Kalman Filter with Q-adaptation for estimation of AUV dynamics

This article is basically focused on application of the Robust Kalman Filter (RKF) algorithm to the estimation of high speed an autonomous underwater vehicle (AUV) dynamics. In the normal operation conditions of AUV, conventional Kalman filter gives sufficiently good estimation results. However, if any kind of malfunction occurs in the system, KF gives inaccurate results and diverges by time. This study, introduces Adaptive Fading Kalman Filter (AFKF) algorithm with the filter gain correction for the case of system malfunctions. By the use of defined variables named as single and multiple fading factors, the estimations are corrected without affecting the characteristic of the accurate ones.