IMM Algorithm for GPS Navigation of Vehicle

Kalman filters were used extensively in data processing of GPS dynamic positioning,while the application of Kalman Filters required that the dynamic model was practical and reliable,but in actual the vehicle motion was complex and changeful,which made it was impossible to express the motion by single model,anyhow model errors often occured in the filters based on single model.In view of the problem,the interacting multiple model(IMM) algorithm,which was used extensively in maneuvering target tracking,was introducted to vehicle navigation.The constant velocity(CV) model and current statistics(CS) model were selected according to vehicle movement characteristics,and the state variables of every direction were decoupled in order to decrease calculation amount.Simulation results showed that,as the vehicle was maneuvering,the performances of the algorithm developed and the adaptive algorithm based on single model were almost same,but while the vehicle was non-maneuvering,the former was superior to the latter obviously.