Data fusion algorithm design of GPS/IMU based on fuzzy adaptive federated Kalman filter

The aim of this paper is to develop a fuzzy adaptive federated Kalman filtering (FAFKF) algorithm which takes contextual information into consideration, and focus on its application to the integrated GPS(Global Positioning System)/IMU(inertial measurement unit) navigation. A No-Reset structure filter that is no information feedback is employed to improve the efficiency of computing, and fault tolerant capability of the system. A fuzzy logic controller is used to compute the information distribution coefficients real-time according to the contextual information which comes from the innovation sequences of each sub-filter and optimally adjust the Kalman filter, so that the accuracy of integrated navigation System is enhanced. Simulation results show that both the precision and fault tolerance of data fusion are improved.