AUV Cooperative Navigation Algorithm Based on Interactive Multiple Model Factor Graph

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 interactive multiple model factor graph is proposed.MethodCombining 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 estimation of ocean current velocity and AUV position is output via weighted fusion based on model probabilities.Result Simulation results show that in dynamic ocean current environments, the average positioning error of the proposed interactive multiple model factor graph algorithm is reduced by 17.04% and 19.13% respectively compared with the interactive multiple model Kalman filter algorithm and the traditional factor graph algorithm. The ocean current velocity estimation error is decreased by 11.78% and 32.08% respectively compared with the two contrast algorithms.Conclusion The proposed algorithm has the advantages of strong robustness and high precision in dynamic marine environments.