Adaptive Kalman Filtering Method to the Data Processing of GPS Deformation Monitoring

This paper introduced the principle of Kalman filtering and modeling methods, however, there existed some problems with the standard Kalman filtering. Combined with the characteristics of GPS deformation monitoring data, this paper improved the algorithm of the standard Kalman filtering and proposed the Adaptive Kalman filtering method. The authors took the data of GPS deformation monitoring as an example, carried out AKF method in the VB platform, and compared the treatment results with the original data. The results show that the AKF can effectively suppress the phenomenon of divergence emerged filtering with the systematic statistical properties of real-time dynamic estimation and make the results more stable and reasonable. The results show that the Adaptive Kalman Filter proposed in this paper is more effective than the traditional methods.