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

Peng Zhao1, Mathieu Joerger2, Xiao Liang3

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Summary
This summary is machine-generated.

This study improves Advanced Receiver Autonomous Integrity Monitoring (ARAIM) by developing a tighter integrity risk bound for Residual-Based (RB) methods. The new approach accurately accounts for both fault and bias vectors, enhancing navigation safety.

Keywords:
ARAIMChi-squaredFault Detection and ExclusionGNSSIntegrityRAIM

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Area of Science:

  • Navigation Systems
  • Aerospace Engineering
  • Signal Processing

Background:

  • Advanced Receiver Autonomous Integrity Monitoring (ARAIM) is crucial for modern navigation systems.
  • Residual-Based (RB) methods are used for integrity risk bounding in ARAIM.
  • Existing RB methods have limitations in accounting for worst-case nominal bias vectors.

Purpose of the Study:

  • To develop a novel, tight integrity risk bound for Residual-Based (RB) Advanced Receiver Autonomous Integrity Monitoring (ARAIM).
  • To address the limitations of previous methods by accounting for both fault and nominal bias vectors simultaneously.
  • To improve the accuracy and reliability of integrity risk assessment in GNSS navigation.

Main Methods:

  • Development of a new bounding method in parity space for RB-ARAIM.
  • Derivation of a direct relationship between mean estimation error and the RB test statistic non-centrality parameter.
  • Inclusion of both multi-satellite fault vectors and all-in-view nominal bias vectors in the bounding process.

Main Results:

  • A tighter integrity risk bound for RB-ARAIM is established.
  • The proposed method effectively accounts for worst-case scenarios involving both faults and nominal biases.
  • Evaluated ARAIM performance demonstrates significant improvement over previous approaches.

Conclusions:

  • The new parity space bounding method enhances the accuracy of integrity risk assessment in RB-ARAIM.
  • This advancement contributes to safer and more reliable autonomous navigation systems.
  • The findings provide a more robust framework for integrity monitoring in the presence of bounded errors and faults.