GNSS Precise Point Positioning Based on Dynamic Kalman Filter with Attenuation Factor

This paper addresses the Kalman filter divergence problem for Global Navigation Satellite System (GNSS) in Precise Point Positioning (PPP). Continuous improvement of precision of GNSS PPP makes it widely used in various fields, however the Kalman filter divergence resolutions for PPP signal attenuating and satellite missing condition are still insufficient. Kalman filter is a recursive, linear unbiased, minimum variance method. Compared with the standard Kalman filter, the dynamic Kalman filter with attenuation factor in this paper makes up for the Kalman filter divergence problem. The effectiveness of dynamic Kalman Filter is demonstrated via matlab simulation.