Wide-Area Instantaneous cm-Level Precise Point Positioning: Method and Service System

ZHAO Qile; TAO Jun; GUO Jing; CHEN Guo; XU Xiaolong; ZHANG Qiang; ZHANG Gaojian; XU Shengyi; LI Junqiang

doi:10.13203/j.whugis20230202

Volume 48 Issue 7

Jul. 2023

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Geomatics and Information Science of Wuhan University > 2023 > 48(7): 1058-1069. > DOI: 10.13203/j.whugis20230202

ZHAO Qile, TAO Jun, GUO Jing, CHEN Guo, XU Xiaolong, ZHANG Qiang, ZHANG Gaojian, XU Shengyi, LI Junqiang. Wide-Area Instantaneous cm-Level Precise Point Positioning: Method and Service System[J]. Geomatics and Information Science of Wuhan University, 2023, 48(7): 1058-1069. DOI: 10.13203/j.whugis20230202

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Wide-Area Instantaneous cm-Level Precise Point Positioning: Method and Service System

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GNSS Research Center, Wuhan University, Wuhan 430079, China

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Received Date: June 03, 2023
Available Online: July 07, 2023
Published Date: July 04, 2023

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Abstract

Objectives Although the precise point positioning (PPP) can provide global cm-level positioning, it takes tens of minutes to converge. While PPP-RTK (real-time kinematic) relies on regional reference stations to provide atmospheric delay corrections to accelerate the convergency, however, only the regional service can be provided.
Methods PPP with multi-frequency and multi-GNSS observations is presented, and only the satellite orbit, clock and observable-specific signal bias (OSB) are needed to achieve instantaneous cm-level positioning. This approach solves the problems of slow convergence of PPP as well as the limited-service scope of PPP-RTK. Furthermore, a wide-area instantaneous cm-level service system compatible with BDS(BeiDou satellite navigation system) PPP-B2b service is proposed, and the performance of real-time orbit, clock and OSB is evaluated.
Results The results of static and in-vehicle kinematic data in China confirm that the system can provide cm-level precision positioning within 1 min.
Conclusions It's implied that our system bears the ability to meet the needs of fast, high-precision and high-confidence positioning in autonomous driving and other fields around the world.

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