Improving Smartphone PPP and RTK Performance Using Time-Differenced Carrier Phase Observations

Abstract

The availability of GNSS carrier-phase measurements from smartphones and tablets has made accurate positioning possible with smartphones. However, it requires the development of advanced positioning algorithms to process the GNSS measurements from smartphones. In this research, we propose the use of time-differenced carrier-phase (TDCP) observations, instead of raw Doppler observations to improve precise point positioning (PPP) and real-time kinematic (RTK) performance with smartphones. Although the GNSS Doppler observations can contribute to the velocity estimation of a moving object and subsequently the positioning solutions, the current Doppler observations from the Android smartphones are found biased with respect to the carrier-phase observations. This would affect the positioning performance in PPP and RTK. Our research results demonstrate that a positioning algorithm introducing velocity vector estimates from time-differenced carrier-phase observations as weighted constraints along with the GNSS pseudorange and carrier-phase observations can improve the positioning performance of both PPP and RTK with smartphones. Implemented into a constrained Kalman Filter for both PPP and RTK methods, the positioning models along with mathematical equations and their positioning performance have be assessed using the training datasets from the "Google Smartphone Decimeter Challenge, 2021 and 2022". An improvement on the RMS of horizontal positioning is achieved when employing the TDCP observations in both kinematic tests. A significant improvement in 50th percentile error, the maximum absolute of the horizontal error and the positioning performance in the beginning epochs is also confirmed using the proposed method.