Objective Aiming at the problem of degraded accuracy in autonomous underwater vehicle (AUV) cooperative navigation caused by ocean current interference in complex marine environments, a cooperative navigation algorithm based on interacting multiple model factor graph (IMM-FG) is proposed.
Method Combining the flexible modeling capability of factor graph and the dynamic adaptability of interactive multiple models, the ocean current velocity is modeled as a multi-mode system. By generating multiple ocean current models, the factor graph algorithm is executed in parallel for state estimation, and then the optimal estimates of current velocity and AUV position are obtained by weighted fusion based on model probabilities.
Result Simulation results show that under time-varying ocean currents, the average positioning error of the proposed interactive multiple model factor graph algorithm is reduced by 17.40% and 19.52% respectively compared with the interacting multiple model extended Kalman filter (IMM-EKF) algorithm and the traditional factor graph (FG) algorithm. The ocean current velocity estimation error is decreased by 35.85% and 55.27% respectively compared with the IMM-EKF and the traditional FG algorithm, respectively.
Conclusion The proposed algorithm has the advantages of strong robustness and high precision in dynamic marine environments.
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