Moving base alignment of a fiber optic gyro inertial navigation system for autonomous underwater vehicle using Doppler velocity log

Abstract This paper presents a novel moving base alignment for the autonomous underwater vehicle (AUV) fiber optic gyro (FOG) inertial navigation system (INS). Unlike several current techniques, the high requirement with navigation computer cause by the large dimension of the state variables is resolved by introducing two-stage Kalman filter (TKF) in the method of moving base alignment. In addition, the accuracy of moving base alignment for FOG INS is influenced by the observation accuracy of Doppler velocity log (DVL), which caused by measurement technology, ocean current and measurement environment. In order to inhibiting the measurement noise of DVL, adaptive two-stage Kalman filter (ATKF) is introduced in the moving base alignment. The parameter of unknown measurement noise is obtained by comparing the prediction error of the observation by two different ways. The effectiveness of this approach was demonstrates by simulation and experimental study. The result shows the method of moving base alignment using ATKF can estimate misalignment angles much better than KF for AUV FOG INS.