Dynamic initial alignment of the MEMS-based low-cost SINS for AUV based on unscented Kalman filter

For the high-speed and light Autonomous Underwater Vehicle (AUV), it is moving freely, and the speed and attitude are in dynamic movement. And for the micro electromechanical system (MEMS) technology based low-cost strapdown inertial navigation system (SINS), over too large bias drift errors not only made the system functions nonlinear, but also made the estimation for misalignment angle converge to a false value. Therefore, this paper concerns the MEMS-based low-cost SINS initial alignment under the dynamic movement with large initial error. A nonlinear mathematics model of SINS initial alignment has been derived. The nonlinear filter unscented Kalman filter (UKF) is investigated in the nonlinear system to estimate the initial attitude and the MEMS sensor biases simultaneously. The simulation indicated that the algorithm is suitable for initial alignment.