Algorithm of GPS phase smoothing pseudo-range based on adaptive attenuation factor Kalman filtering

The main purpose of carrier phase smoothing pseudo-range is to reduce large random error of pseudo-range measurement values, by using high-precision carrier phase measurement values as the supplementary information. In view of the unknown time-varying noise in GPS pseudo-range measurement, an algorithm of adaptive attenuation factor kalman filter (AFKF) was put forward, which was based on maximum a posteriori (MAP) time-varying noise statistical estimator. In order to avoid the divergence of filtering process, the effect of old data could be gradually forgotten by using estimator with attenuation weighted factors, while the proportion of new data could be increased. Simulation analysis was carried out on the measured data of tracking station of a International Global Navigation Satellite System Service (IGS), by using the AFKF algorithm combining with carrier phase smoothing pseudo-range principle. And the double differential and the three differential pseudo-ranges were proposed to intuitively reflect the effects of different algorithms. Experimental results show that the AFKF algorithm can obtain better effect in application of pseudo-range smoothing, compared with the standard KF algorithm.