Distributed fusion algorithm based on IMM-PF

Distributed fusion algorithm for nonlinear/non-Gaussian situations is addressed.The usual fusion approach is based on extended Kalman filter(EKF) which often leads to poor convergence and erratic filter behavior in highly nonlinear systems.Particle filtering(PF) is quite convenient in nonlinear/non-Gaussian filtering problems.Based on PF,a distributed fusion algorithm is developed,which can be used in nonlinear/non-Gaussian applications.At the sensor level,observer maintains its own estimate with an interacting multiple model particle filter(IMM-PF),and at the fusion level,the full state estimate is processed by using nonlinear fusion rule.Simulation results show that the proposed method can significantly improve the state estimation precision of the multisensor system.