Ionospheric augmentation is one of the most important dependences of PPP-RTK. Because of the dispersive features of the ionosphere, the ionospheric information is usually coupled with satellite- and receiver-related biases. This will pose a hidden trouble of inconsistent ionospheric corrections if different numbers of reference stations are involved in calculation. In this paper, we aimed at introducing a consistent regional vertical ionospheric model (RVIM) by estimating receiver biases. We first presented the inconsistent ionospheric corrections under sparse networks. Then the RVIM is compared with the International GNSS Service (IGS) final global ionospheric map (GIM) product, and the average of differences between them is 1.13 TECU. Furthermore, the slant ionospheric corrections were employed as a reference to evaluate both RVIM and GIM. The mean RMS values are 1.48 and 2.23 TECU for the RVIM and GIM, respectively. Finally, we applied the RVIM into PPP-RTK. Results indicate that the PPP-RTK with RVIM constraints achieves improvements in horizontal errors, vertical errors, and convergence time by 43.45, 29.3, and 22.6% under the 68% confidence level, compared with the conventional PPP-AR.


    Access

    Download


    Export, share and cite



    Title :

    A Consistent Regional Vertical Ionospheric Model and Application in PPP-RTK Under Sparse Networks


    Contributors:
    Sijie Lyu (author) / Yan Xiang (author) / Tiantian Tang (author) / Ling Pei (author) / Wenxian Yu (author) / Trieu-Kien Truong (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Regional ionospheric mapping

    Reinisch, B.W. / Huang, X. / Sales, G.S. | Elsevier | 1993


    Regional Ionospheric Mapping

    Reinisch, B.W. | Online Contents | 1993


    An adaptable regional empirical ionospheric model

    Dvinskikh, N.I. / Naidenova, N.Ya. | Elsevier | 1991



    A regional adaptive and assimilative three-dimensional ionospheric model

    Sabbagh, Dario / Scotto, Carlo / Sgrigna, Vittorio | Elsevier | 2015