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    PPP-RTK and inter-system biases: the ISB look-up table as a means to support multi-system PPP-RTK

    240846_240846.pdf (411.8Kb)
    Access Status
    Open access
    Authors
    Khodabandeh, Amir
    Teunissen, Peter
    Date
    2016
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Khodabandeh, A. and Teunissen, P. 2016. PPP-RTK and inter-system biases: the ISB look-up table as a means to support multi-system PPP-RTK. Journal of Geodesy. 90 (9): pp. 837-851.
    Source Title
    Journal of Geodesy
    DOI
    10.1007/s00190-016-0914-9
    ISSN
    0949-7714
    School
    Department of Spatial Sciences
    Remarks

    The final publication is available at Springer via http://doi.org/10.1007/s00190-016-0914-9

    URI
    http://hdl.handle.net/20.500.11937/22500
    Collection
    • Curtin Research Publications
    Abstract

    PPP-RTK has the potential of benefiting enormously from the integration of multiple GNSS/RNSS systems. However, since unaccounted inter-system biases (ISBs) have a direct impact on the integer ambiguity resolution performance, the PPP-RTK network and user models need to be flexible enough to accommodate the occurrence of system-specific receiver biases. In this contribution we present such undifferenced, multi-system PPP-RTK full-rank models for both network and users. By an application of (Formula presented.)-system theory, the multi-system estimable parameters are presented, thereby identifying how each of the three PPP-RTK components are affected by the presence of the system-specific biases. As a result different scenarios are described of how these biases can be taken into account. To have users benefit the most, we propose the construction of an ISB look-up table. It allows users to search the table for a network receiver of their own type and select the corresponding ISBs, thus effectively realizing their own ISB-corrected user model. By applying such corrections, the user model is strengthened and the number of integer-estimable user ambiguities is maximized.

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