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Implementation and Performance Analysis of Constellation Dynamic Selection in Multi-Constellation RAIM.

Qian Meng1, Yuan Zhuang2, Shengying Li1

  • 1School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.

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Summary
This summary is machine-generated.

This study introduces dynamic constellation selection for Advanced Receiver Autonomous Integrity Monitoring (ARAIM) in Global Navigation Satellite System (GNSS) applications. The method enhances integrity availability and reduces computational load, crucial for safety-critical aviation navigation.

Keywords:
ARAIMGNSSintegritymulti-constellationnavigationpositioning

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Area of Science:

  • Navigation Systems
  • Aerospace Engineering
  • Satellite Technology

Background:

  • Global Navigation Satellite System (GNSS) is vital for aerospace and transportation, with integrity being paramount for safety-critical applications.
  • Advanced Receiver Autonomous Integrity Monitoring (ARAIM) offers potential for vertical navigation in civil aviation but faces challenges in computational complexity and fault-tolerant positioning with multi-constellation GNSS.
  • Current ARAIM methods can be computationally intensive and may have performance limitations in fault modes when using multiple satellite constellations.

Purpose of the Study:

  • To propose and implement a constellation dynamic selection concept within ARAIM to enhance integrity risk control for safety-critical applications.
  • To analyze the performance of ARAIM using dynamic selection, focusing on integrity availability and computational complexity.
  • To address the limitations of fixed constellation selection in ARAIM and improve robustness in various operational scenarios.

Main Methods:

  • Developed and implemented a dynamic constellation selection strategy for ARAIM, prioritizing the two constellations with the best vertical geometry performance.
  • Conducted performance analysis through simulations and experiments using actual GNSS signals.
  • Validated the method's applicability and generality using statistical data from observation stations.

Main Results:

  • The proposed dynamic selection method significantly reduces computational complexity to less than 10% compared to using four constellations.
  • Achieved 100% integrity availability under LPV-200 criteria across worldwide coverage experiments.
  • Demonstrated superior performance in integrity availability and computational efficiency compared to fixed constellation ARAIM methods.

Conclusions:

  • Constellation dynamic selection in ARAIM offers a superior approach for safety-critical GNSS applications by balancing integrity and computational load.
  • The method provides robust performance, high integrity availability, and reduced complexity, making it suitable for current and future GNSS constellations.
  • This approach is applicable and generalizable for enhancing GNSS-based vertical navigation in civil aviation.