GNSS Differential Code Bias Determination Using Rao‐Blackwellized Particle Filtering

Ben Reid*, David R. Themens, Anthony Mccaffrey, P. T. Jayachandran, Mainul Hoque, Andrew J. Mazzella

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

The Assimilative Canadian High Arctic Ionospheric Model (A-CHAIM) is a near-real-time data assimilation model of the high latitude ionosphere, incorporating measurements from many instruments, including slant Total Electron Content measurements from ground-based Global Navigation Satellite System (GNSS) receivers. These measurements have receiver-specific Differential Code Biases (DCB) which must be resolved to produce an absolute measurement, which are resolved simultaneously with the ionospheric state using Rao-Blackwellized particle filtering. These DCBs are compared to published values and to DCBs determined using eight different Global Ionospheric Maps (GIM), which show small but consistent systematic differences. The potential cause of these systematic biases is investigated using multiple experimental A-CHAIM test runs, including the effect of plasmaspheric electron content. By running tests using the GIM-derived DCBs, it is shown that using A-CHAIM DCBs produces the lowest overall error, and that using GIM DCBs causes an overestimation of the topside electron density which can exceed 100% when compared to in situ measurements from DMSP.
Original languageEnglish
Article numbere2023SW003611
Number of pages26
JournalSpace Weather
Volume22
Issue number5
Early online date25 Apr 2024
DOIs
Publication statusPublished - May 2024

Keywords

  • data assimilation
  • GNSS
  • Differential Code Bias (DCB)
  • Particle Filter
  • Rao-Blackwellized particle filter
  • real time
  • Ionosphere
  • plasmasphere
  • Total electron content (TEC)

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