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    Triple Frequency precise point positioning with multi-constellation GNSS

    Access Status
    Open access via publisher
    Authors
    Deo, Manoj
    El-Mowafy, Ahmed
    Date
    2017
    Type
    Conference Paper
    
    Metadata
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    Citation
    Deo, M. and El-Mowafy, A. 2017. Triple Frequency precise point positioning with multi-constellation GNSS. In: International Global Navigation Satellite Systems Association IGNSS Conference 2016, 6th Dec 2016, Sydney, Australia.
    Source Conference
    International Global Navigation Satellite Systems Association IGNSS Conference 2016
    Additional URLs
    http://www.ignss2016.unsw.edu.au/2016-proceedings
    Faculty
    Faculty of Science and Engineering
    School
    School of Earth and Planetary Sciences (EPS)
    URI
    http://hdl.handle.net/20.500.11937/75894
    Collection
    • Curtin Research Publications
    Abstract

    The availability of signals on three or more frequencies from multiple GNSS constellations provides opportunities for improving precise point positioning (PPP) convergence time and accuracy, compared to when using dual-frequency observations from a single constellation. Although the multi-frequency and multi-constellation (MFMC) data may be used with present day precise orbit and clock products, there are several biases that must be considered to get the best results. When using IGS products, the precise orbit and clock corrections are generated using dual-frequency ionosphere-free combinations of a ‘base’ pair of signals, and usage of other signals in the PPP model results in differential code biases (DCB). Other biases to consider include differential phase biases (DPB) for the satellites and receiver and satellite antenna offsets for individual frequencies. Integrating multi-constellation data introduces additional biases, such as inter-system hardware and time biases and inter-frequency bias. Although the integration of MFMC data introduces such biases, it improves the measurement model strength and hence can potentially improve PPP performance through reducing solution convergence time and increasing precision and accuracy. A brief overview of the MFMC biases and strategies that may be used to treat them is discussed. A proposed PPP model that uses triple frequency ionosphere-free low-noise linear combination for float ambiguity estimation is tested and analysed. MFMC data from four Australian sites is used to demonstrate the improvements in PPP solution convergence time, accuracy and precision, when comparing single- to multi-constellation GNSS data.

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