A Fuzzy-Innovation-Based Adaptive Kalman Filterfor Enhanced Vehicle Positioning in DenseUrban Environments.

In this paper, a fuzzy-innovation based adaptive extended Kalman filter (FI-AKF)is proposed to improve the performance of the GNSS/INS fusion system, which is degradeddue to satellite signal cutoff and attenuation and inaccurate modeling in dense urbanenvironments. The information used for sensor fusion is obtained from real-time kinematic (RTK),micro-electro-mechanical system based inertial measumrement unit (MEMS-IMU), and on-boarddiagnostics (OBD). The fuzzy logic system is proposed to adaptively update the measurementcovariance matrix of the RTK according to the position dilution of precision (PDOP), the numberof receivable satellites, and the innovation of the extended Kalman filter (EKF).