Study of GPS Data De-Noising Method Based on Wavelet and Kalman Filtering

Aiming at the features that GPS signal noise has strong randomness and its effect on GPS data processing accuracy is irregular, This paper will be based on applications of the mathematical tools of wavelet analysis in GPS data de-noising processing, meanwhile Kalman filtering method is introduced, and putting forward the adaptive Kalman filtering method that based on the wavelet analysis. The experimental results have shown that the effect of the adaptive Kalman filtering method based on wavelet analysis is better than which of the wavelet analysis, and with this two methods, the calculation accuracy of observation data is obviously higher than which is never handled by any means. The GPS baseline solution accuracy improved by the two methods are 43%, 35%, all above these have a very important significance in improving the accuracy GPS data processing and expanding the application range of service of GPS.