In-motion initial alignment method for DVL-aided SINS under wave disturbance for AUV

This work discusses the implementation of inertial navigation system aided by Doppler Velocity Log (DVL) for the Autonomous Underwater Vehicles (AUV) applications. Due to disturbance from waves, the complicated underwater environment, to achieve Strapdown Inertial Navigation System (SINS) alignment accuracy within a short period of time is still a challenging problem. The difficulty for underwater SINS alignment is in designing the process covariance matrix and measurement noise covariance matrix, worse still, in most practical applications the process covariance matrix R, and measurement noise covariance matrix will change in the process of alignment. This paper highlights the use of fuzzy logic techniques to the adaptation of R, and we introduce the output of DVL as a reference of the change of external environment. And simulation experiment has been designed to evaluate our proposed algorithms, and results show that in our approach the Kalman filter needs less time to converge and has higher precision.