Estimating process noise variance of PPP-RTK corrections

a means for sensing the ionospheric time-variability

Journal Article (2023)
Author(s)

Parvaneh Sadegh Nojehdeh (University of Melbourne)

A. Khodabandeh (University of Melbourne)

Kourosh Khoshelham (University of Melbourne)

A. Amiri Simkooei (TU Delft - Optical and Laser Remote Sensing)

Research Group
Optical and Laser Remote Sensing
Copyright
© 2023 Parvaneh Sadegh Nojehdeh, Amir Khodabandeh, Kourosh Khoshelham, A. Amiri Simkooei
DOI related publication
https://doi.org/10.1007/s10291-023-01577-4
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 Parvaneh Sadegh Nojehdeh, Amir Khodabandeh, Kourosh Khoshelham, A. Amiri Simkooei
Research Group
Optical and Laser Remote Sensing
Issue number
1
Volume number
28
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

The provision of accurate ionospheric corrections in PPP-RTK enormously improves the performance of single-receiver user integer ambiguity resolution (IAR), thus enabling fast high precision positioning. While an external provider can disseminate such corrections to the user with a time delay, it is the task of the user to accurately time-predict the corrections so that they become applicable to the user positioning time. Accurate time prediction of the corrections requires a dynamic model in which the process noise of the corrections has to be correctly specified. In this contribution, we present an estimation method to determine the process noise variance of PPP-RTK corrections using single-receiver GNSS data. Our focus is on variance estimation of the first-order slant ionospheric delays, which allows one to analyze how the ionospheric process noise changes as a function of the solar activity, receiver local time, and receiver geographic latitude. By analyzing 11-year GNSS datasets, it is illustrated that estimates of the ionospheric process noise are strongly correlated with the solar flux index F10.7. These estimates also indicate a seasonal variation, with the highest level of variation observed during the spring and autumn equinoxes.

Files

S10291_023_01577_4.pdf
(pdf | 1.99 Mb)
- Embargo expired in 10-06-2024
License info not available