Study on the Predictive Processing Method of the Kalman Filter of Customer Based on the PRC and RRC in the RBN/DGPS

摘要

Because of the differences between reference station and customer in the ionospheric and tropospheric path through which satellite signal passes, the influence of the error of satellite ephemeris, and environmental noise, there are the residual errors of actual PRC (pseudorange correction) and RRC (range rate correction) in customer, compared with the PRC and RRC broadcast by reference station. The errors are small when there is short distance between them and large when long. This paper studies the predictive processing method of the Kalman filter of the customer based on the PRC and RRC in the RBN/DGPS before they are inducted to correct. A mathematical model is established. By means of computer imitation, the error of PRC in customer can be reduced to about 0.1m, and verification is made with the PRC of PRN4# satellite sent by reference station. The result shows that the method can effectively improve the positioning accuracy of the customer in RBN/DGPS.