Acta Geodaetica et Cartographica Sinica ›› 2017, Vol. 46 ›› Issue (12): 1929-1938.doi: 10.11947/j.AGCS.2017.20170111

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Comparison and Analysis of Three GPS+BDS PPP Models

ZANG Nan1, LI Bofeng1,2, SHEN Yunzhong1   

  1. 1. College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China;
    2. State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China
  • Received:2017-03-09 Revised:2017-07-03 Online:2017-12-20 Published:2017-12-28
  • Supported by:
    The National Natural Science Foundation of China (Nos.41622401 41574031 41374023) The Open Fund of the State Key Laboratory of Geodesy and Earth's Dynamics(No.SKLGED2016-3-1-EZ)

Abstract: In general,ionosphere-free model and uncombined model are applied for GNSS precise point positioning (PPP).This paper detailed analyzes the correlation of different parameters of each model,and deducevarious PPP functional model by means of parameterization methods.And uncombined PPP with ionospheric parameter constrains i.e.ionosphere-weighted model can fasten PPP convergence effectively.This paper takes advantage of GPS-only and GPS and BDS combination dataset as example for positioning in different PPP models.In the perspective of positioning accuracy and convergence time,positioning performance are detailed analyzed in both static PPP and simulated dynamic PPP modes.The results demonstrate that GPS-only has the similar accuracy with GPS+BDS combination,and both ionosphere-free model and uncombined model static PPP can achieve the positioning accuracy of millimeter to centimeter level,while the horizontal positioning accuracy of dynamic PPP is superior to 3 cm and the vertical positioning accuracy is superior to 5 cm.In terms of convergence time,ionosphere-free model is superior to uncombined model,and the convergence time of ionosphere-weighted model is the shortest.Compared to the ionosphere-free model,the ionosphere-weighted model can decrease about 15% convergence time,while it can decrease about 34% convergence time compared to the uncombined model in the dynamic positioning.

Key words: PPP, functional model, parameterization, prior ionospheric constrains, GPS+BDS

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