Investigating GNSS PPP–RTK with external ionospheric constraints

Abstract

Real-Time Kinematic Precise Point Positioning (PPP–RTK) is inextricably linked to external ionospheric information. The PPP–RTK performances vary much with the accuracy of ionospheric information, which is derived from different network scales, given different prior variances, and obtained under different disturbed ionospheric conditions. This study investigates the relationships between the PPP–RTK performances, in terms of precision and convergence time, and the accuracy of external ionospheric information. The statistical results show that The Time to First Fix (TTFF) for the PPP–RTK constrained by Global Ionosphere Map (PPP–RTK-GIM) is about 8–10 min, improved by 20%–50% as compared with that for PPP Ambiguity Resolution (PPP-AR) whose TTFF is about 13–16 min. Additionally, the TTFF of PPP–RTK is 4.4 min, 5.2 min, and 6.8 min, respectively, when constrained by the external ionospheric information derived from different network scales, e.g. small-, medium-, and large-scale networks, respectively. To analyze the influences of the optimal prior variances of external ionospheric delay on the PPP–RTK results, the errors of 0.5 Total Electron Content Unit (TECU), 1 TECU, 3 TECU, and 5 TECU are added to the initial ionospheric delays, respectively. The corresponding convergence time of PPP–RTK is less than 1 min, about 3, 5, and 6 min, respectively. After adding the errors, the ionospheric information with a small variance leads to a long convergence time and that with a larger variance leads to the same convergence time as that of PPP-AR. Only when an optimal prior variance is determined for the ionospheric delay in PPP–RTK model, the convergence time for PPP–RTK can be shorten greatly. The impact of Travelling Ionospheric Disturbance (TID) on the PPP–RTK performances is further studied with simulation. It is found that the TIDs increase the errors of ionospheric corrections, thus affecting the convergence time, positioning accuracy, and reliability of PPP–RTK.

Review of PPP–RTK: achievements, challenges, and opportunities

“…Since the concept of PPP-RTK was first proposed by Wübbena et al (2005), many researchers implemented the PPP-RTK method and carried out several experimental verifications (Li et al, 2011(Li et al, , 2014Oliveira et al 2017;Psychas et al, 2021;Teunissen et al, 2010;Zhang et al, 2022). The flow of PPP-RTK generally goes through two major phases: the server phase which is to derive the precise orbit, clock, UPD, and atmospheric corrections based on the observations at network stations, and the user phase, where the corrections derived from network enable the fast AR of absolute positioning.…”

“…In this case, the PPP-RTK solution influenced by the ionospheric scintillation is unacceptable for some high-safety applications such as autonomous driving. Besides, Zhang et al (2022) indicate that the high occurrence rate of Traveling Ionospheric Disturbance (TID, Hernández-Pajares et al, 2006 and its complicated characteristics also impact the operation of PPP-RTK service, especially at the beginning of each reinitialized period. Currently, the influence of ionosphere irregularities on PPP-RTK has been found, and more attention should be paid to the identification of ionosphere activities and the alleviation of its effect on the PPP-RTK.…”

The Performance of Three-Frequency GPS PPP-RTK with Partial Ambiguity Resolution

“…Because atmospheric augmented PPP AR can achieve fast and reliable positioning performance, which is similar to the positioning and convergence performance of real-time kinematics (RTK), this technology is also called PPP-RTK [11]. Benefiting from the many advantages of PPP-RTK, great efforts have been made to work on PPP-RTK with promising results in recent years [12][13][14][15][16][17][18][19][20][21]. Li et al (2011) performed an atmospheric augmented PPP ambiguity resolution experiment by using atmospheric corrections derived from a network with an average distance of approximately 60 km.…”

Leveraging the CYGNSS Spaceborne GNSS‐R Observations to Detect Ionospheric Irregularities Over the Oceans: Method and Verification

“…The resulting ionospheric irregularities of the plasma density could significantly cause rapid fluctuations in the intensity, phase, angle of arrival, and direction of trans‐ionospheric radio signals at frequencies <3 GHz in a stochastic manner (Guo et al., 2019; Yuan & Ou, 2001). Further, they would influence the performance of high‐precision devices and applications which include global navigation satellite systems (GNSS) (Luo et al., 2020; Peng et al., 2021; Sreeja et al., 2020; Yuan, 2002; Zhang et al., 2022). Therefore, monitoring or forecasting the equatorial ionospheric irregularities is becoming an essential space weather science issue and also is crucial for the anti‐interference ability, high reliability, and high integrity of GNSS service applications, especially in autonomous driving and air traffic.…”