Interacting multiple model integrated navigation algorithm based on expected-mode augmentation for AUV
Le Wang · Optics and Precision Engineering · 2014
An Interactive Multiple Model(IMM)filter algorithm based on Expected-mode Augmentation(EMA)named EMA-IMM algorithm is proposed to overcome the uncertain model and time-varied model parameters of the integrated navigation system for an Autonomous Underwater Vehicle(AUV) in a tough environment.The EMA-IMM algorithm mainly uses the probability of models obtained from the recursive estimate processing for making decision.It filters for the base grids of fixed structure to obtain a fined amendatory model set firstly.Then the amendatory model is filtered to obtain an expected model consisting of a small number of amendatory model grids that are close to the real model.Through a further filtering using the expected model,the suboptimal solution approximate to thereal model will be ultimately achieved.Simulation results on the integrated navigation system show that the EMA-IMM algorithm can improve the estimation precisions of longitude and latitude by 97% and 44%respectively as compared with the Kalman filtering algorithm and by 22%and 19% with the IMM algorithm,which proves the superiority of the proposed EMA-IMM algorithm.