Study of Improved Arithmetic of Kalman Filter on How to Improve the Precision with Global Position System
Yinghui Tang · Modern Electronics Technique · 2008
In this paper,we introduce a new algorithm of improving GPS positioning precision.This algorithm is based on the least-square method and normal Kalman filter.This algorithm can effectively restrain the filter′s divergence caused by the initial value of filter and system-noise-variance and measurement-noise-variance.The receiver position and clock offset can be estimated via measuring the pseudo ranges.Kalman filter is used to confirm the errors of paremeters instead of the parameters themselves,which reduces the operation errors and improves the positioning accuracy efficiently.During the estimation,the mass measurement data do not have to be saved.The data measured dynamically can be easily processed in real time.This simulation results indicate that it has positioning precision and high convergent rate.