Improved precise point positioning in the presence of ionospheric scintillation

Abstract

Ionospheric disturbances can be detrimental to accuracy and reliability of GNSS positioning. We focus on how ionospheric scintillation induces significant degradation to Precise Point Positioning (PPP) and how to improve the performance of PPP during ionospheric scintillation periods. We briefly describe these problems and give the physical explanation of highly correlated phenomenon of degraded PPP estimates and occurrence of ionospheric scintillation. Three possible reasons can contribute to significant accuracy degradation in the presence of ionospheric scintillation: (a) unexpected loss of lock of tracked satellites which greatly reduces the available observations and considerably weakens the geometry, (b) abnormal blunders which are not properly mitigated by positioning programs, and (c) failure of cycle slip detection algorithms due to the high rate of total electronic content. The latter two reasons are confirmed as the major causes of sudden accuracy degradation by means of a comparative analysis. To reduce their adverse effect on positioning, an improved approach based on a robust iterative Kalman filter is adopted to enhance the PPP performance. Before the data enter the filter, the differential code biases are used for GNSS data quality checking. Any satellite whose C1---P1 and P1---P2 biases exceed 10 and 30 m, respectively, will be rejected. Both the Melbourne---Wubbena and geometry-free combination are used for cycle slip detection. But the thresholds are set more flexibly when ionospheric conditions become unusual. With these steps, most of the outliers and cycle slips can be effectively detected, and a first PPP estimation can be carried out. Furthermore, an iterative PPP estimator is utilized to mitigate the remaining gross errors and cycle slips which will be reflected in the posterior residuals. Further validation tests based on extensive experiments confirm our physical explanation and the new approach. The results show that the improved approach effectively avoids a large number of ambiguity resets which would otherwise be necessary. It reduces the number of re-parameterized phase ambiguities by approximately half, without scarifying the accuracy and reliability of the PPP solution.