GPS positioning algorithm based on UKF

The extended Kalman filter deals with nonlinear problems using Taylor series expansion, leading to degraded performance. The UKF is adopted for GPS positioning in this paper. After formulating the UKF algorithm, a relationship between the linearized approximation error of GPS pseudorange equation and the positioning error is analyzed. The validity of UKF in GPS positioning is discussed. Pseudorange and Doppler shift measurements are used and the current statistics model is utilized in data processing. Simulation and field experiment are carried out by employing Spirent GPS simulator and NovAtel differential positioning system as well as NovAtel receiver, respectively. The results show that UKF has better performance than EKF when there are large errors in initial state values of the system.