Improving ambiguity resolution and cycle slip detection from combined triple-frequency GNSS observations

Abstract

This thesis improves ambiguity resolution and cycle slip detection taking advantage of the benefits of combined triple-frequency signals. Multi Global Navigation Satellite System (GNSS) are transmitting triple-frequency signals. Compared to dual-frequency, the additional signal is anticipated to bring more combinations with longer wavelength, better elimination of ionospheric delay and lower measurement noise. This thesis starts with the study on selecting the optimally combined signals for three-carrier ambiguity resolution (TCAR) in geometry-free (GF) and geometry-based (GB) mode. This thesis proposes a theoretical and empirical integrated method, which first selects the possible optimal combined signals in theory and then refines these signals with real triple-frequency GPS data, observed at eleven baselines of different lengths. An interpolation technique is also adopted in order to show changes of the AR performance with the increase in baseline length. The results show that the AR success rate can be improved by 3% in GF mode and 8% in GB mode at certain intervals of the baseline length, compared to that using traditional combined signals. Therefore, the TCAR can perform better by applying the combined signals proposed in this thesis. In order to detect cycle slips during low ionospheric conditions, this thesis proposes a cycle slip detection and correction method based on the traditional extra-wide-lane Hatch-Melbourne-Wubbena (HMW) combination and also the modified triple-frequency HMW combinations. Instead of using the combined code signals directly in the traditional HMW combination, the modified HMW combination adopts the original code signals and one combined phase signal with corrected cycle slips to eliminate the ionospheric bias and reduce the effect of the noise induced by the code measurement. In order to determine the optimally combined signals and the corresponding coefficients in the modified HMW combination, four constrained conditions are proposed based on the maximum acceptable ionospheric bias and measurement noise of the combination in the process of cycle slip detection. Two optimally combined signals are selected, however the second best signal cannot maintain a 100% success rate when epoch intervals are increased, due to the effect of the remaining ionospheric bias. In order to solve this problem, a scale factor is introduced to balance the corrected percentage of the ionospheric bias and the amplification of the measurement noise. These selected signals are further tested with real triple-frequency GPS, Galileo and BDS observations. Compared to the cycle slip detection method using single-/dual-frequency, the proposed triple-frequency cycle slip detection method can provide a more reliable performance, especially in detecting small cycle slips in the observations with large data epoch intervals. Compared with Huang et al. [1], results show that the proposed method can provide a higher success rate in detecting cycle slips in the observations of satellites in medium earth orbit with low elevation angles and large epoch intervals (up to 30 s). In order to detect and correct cycle slips under the observation condition of high ionospheric activities, this thesis modifies the detection process of the previous method and reselects the combined triple-frequency signals by minimizing the measurement noise without considering the ionospheric bias. The first-order time-differenced ambiguity is applied with a proposed outliers elimination method, the ionospheric trend in it can be obtained by applying the robust locally weighted scatter plot smoothing technique. The residuals between the fit models and the time-differenced ambiguities are adopted as detection value. In order to properly determine cycle slips, five threshold determination methods are proposed and discussed. The results from testing with GNSS datasets collected under different ionospheric activities reveal the proposed cycle slip detection method is effective in detecting and correcting cycle slips under high ionospheric activities even during the data intervals up to 30 s. The detection performance is not affected by the magnitude of the cycle slip, the level of ionospheric activities, the location where the data was collected, and the type of receivers and antennas.

Date of Award	8 Mar 2019
Original language	English
Awarding Institution	Univerisity of Nottingham
Supervisor	Craig M. Hancock (Supervisor), Gethin Wyn Roberts (Supervisor), Lawrence Lau (Supervisor) & Ruibin Bai (Supervisor)