A New Method to Bound the Integrity Risk for Residual-Based ARAIM

Peng Zhao, Mathieu Joerger, Xiao Liang, Boris Pervan, Yongming Liu

Research output: Contribution to journalArticlepeer-review

Abstract

This article develops a tight integrity risk bound for residual-based (RB) advanced receiver autonomous integrity monitoring (ARAIM). ARAIM measurement models include nominal biases accounting for unknown but bounded errors, and faults of unbounded magnitude. In RB methods, upper bounding the integrity risk requires that one finds the worst-case directions of both the multisatellite fault vector and of the all-in-view nominal bias vector. Previous methods only account for the worst-case fault direction assuming zero nominal bias. To address this issue, in this article, we derive a new bounding method in parity space. The method establishes a direct relationship between mean estimation error and RB test statistic noncentrality parameter, which accounts for both faults and nominal errors. ARAIM performance is evaluated to quantify the improvement provided by the proposed method over previous approaches.

Original languageEnglish (US)
Article number9271821
Pages (from-to)1378-1385
Number of pages8
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume57
Issue number2
DOIs
StatePublished - Apr 2021
Externally publishedYes

Keywords

  • Advanced receiver autonomous integrity monitoring (ARAIM)
  • chi-squared
  • fault detection (FD) and exclusion
  • global navigation satellite systems (GNSS)
  • integrity
  • receiver autonomous integrity monitoring (RAIM)

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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