Impact of cascading faults on mega-constellation-augmented GNSS PPP integrity

Danielle Racelis, Mathieu Joerger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we quantify integrity for a GNSS-PPP system when augmented with mega-constellation satellites (GNSS-MC). The geometric diversity provided by signals from fast-moving LEO satellites is exploited for rapid estimation of floating valued cycle ambiguities. Further, the improved redundancy provided by mega-constellation satellite signals in addition to GNSS enable efficient fault detection using carrier phase Advanced Receiver Autonomous Integrity Monitoring (ARAIM). The proposed framework assumes that mega-constellation (MC) satellite orbit and clock determination is based on their spaceborne GNSS receivers. We quantify the impact on integrity of GNSS faults, which not only affect the potential users on earth, but also the spaceborne MC receiver data. Given that GNSS faults can cascade to constellation-wide MC faults, this work determines the conditions where GNSS-MC improves integrity, and quantifies this improvement as compared to GNSS only.

Original languageEnglish (US)
Title of host publicationProceedings of the 33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020
PublisherInstitute of Navigation
Pages3055-3070
Number of pages16
ISBN (Electronic)0936406267, 9780936406268
DOIs
StatePublished - 2020
Externally publishedYes
Event33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020 - Virtual, Online
Duration: Sep 22 2020Sep 25 2020

Publication series

NameProceedings of the 33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020

Conference

Conference33rd International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS+ 2020
CityVirtual, Online
Period9/22/209/25/20

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Electrical and Electronic Engineering

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