PPP Algorithms based on GR models by applying CLAS and the Fixed Point Smoother

Abstract

We have been developing the PPP algorithms based on our GR (GNSS Regresion) models with applying CLAS (Centimeter Level Augmentation Service) data from Japan Quasi-Zenith-Satellite-System (QZSS)[1]- [7]. In this paper, we examine the accuracy and convergence of positioning estimators applying the fixed-point Kalman smoother. Throughout the numerical experiments the total 3D-RMS error by applying CLAS and fixed-point Kalman smoother is approximately 0.15 [m].