Application for autonomous underwater vehicle initial alignment with divided difference filter

Abstract

Regarding the problem of the Autonomous Underwater Vehicle (AUV) departing from the mother ship and starting up, this paper proposed a divided difference filter (DDF) basing on the Stirling interpolation formula. When AUV separated from the mother ship and restarted, the coarse alignment was not ideal. Its level misalignment error precision was high, but its heading misalignment error precision was low. The large heading misalignment error model was applied to the fine alignment on moving base. The large heading misalignment error model was nonlinear. The first order divided difference (DD1) filter and the second order divided difference (DD2) filter were adopted to the nonlinear filtering. Simulation results show that the DD1 alignment precision is equivalent with Extended Kalman Filter (EKF), but the alignment time shorts by 33%. The DD2 alignment precision is equivalent with Unscented Kalman Filter (UKF), but the alignment time shorts by 28%. The alignment precision raises by 60% compared to the EKF.