Abstract
Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) is an attractive positioning technology due to its high precision and flexibility. However, the vulnerability of PPP brings a safety risk to its application in the field of life safety, which must be evaluated quantitatively to provide integrity for PPP users. Generally, PPP solutions are processed recursively based on the extended Kalman filter (EKF) estimator, utilizing both the previous and current measurements. Therefore, the integrity risk should be qualified considering the effects of all the potential observation faults in history. However, this will cause the calculation load to explode over time, which is impractical for long-time missions. This study used the innovations in a time window to detect the faults in the measurements, quantifying the integrity risk by traversing the fault modes in the window to maintain a stable computation cost. A non-zero bias was conservatively introduced to encapsulate the effect of the faults before the window. Coping with the multiple simultaneous faults, the worst-case integrity risk was calculated to overbound the real risk in the multiple fault modes. In order to verify the proposed method, simulation and experimental tests were carried out in this study. The results showed that the fixed and hold mode adopted for ambiguity resolution is critical to an integrity risk evaluation, which can improve the observation redundancy and remove the influence of the biased predicted ambiguities on the integrity risk. Increasing the length of the window can weaken the impact of the conservative assumption on the integrity risk due to the smoothing effect of the EKF estimator. In addition, improving the accuracy of observations can also reduce the integrity risk, which indicates that establishing a refined PPP random model can improve the integrity performance.
Highlights
Publisher’s Note: MDPI stays neutralPrecise single positioning (PPP) technology can provide high-precision positioning for Global Navigation Satellite System (GNSS) users with the help of precise correction information, and by utilizing the code and carrier phase observations [1,2,3]
extended Kalman filter (EKF) estimator is widely adopted in Precise Point Positioning (PPP) algorithms, which is implemented based on the following prediction model: xk = Φk|k−1 xk−1 + Γk wk where wk ∼ N (0, Qk )
It can be seen that if the strategy of ambiguity fixed is not adopted, the integrity risk is almost equal to one all the time, which means that the algorithm will not be available
Summary
Precise single positioning (PPP) technology can provide high-precision positioning for Global Navigation Satellite System (GNSS) users with the help of precise correction information, and by utilizing the code and carrier phase observations [1,2,3]. The positioning accuracy of the kinematic PPP solution with float-ambiguity after convergence can reach the decimeter to centimeter level. An even better solution and shorter convergence time can be obtained with the integer carrier-phase ambiguities resolved correctly [4,5,6,7,8]. RTK, PPP is an absolute positioning technology that requires no reference stations and can be applied anywhere in the world. For users in the field relating to life safety, the accuracy is no longer the most concerning requirement but the safety, with regard to jurisdictional claims in published maps and institutional affiliations
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