Adaptive Navigation Performance Evaluation Method for Civil Aircraft Navigation Systems with Unknown Time-Varying...

Area of Science:

• Aviation
• Navigation Systems
• Aerospace Engineering

Background:

• Accurate real-time navigation monitoring is crucial for civil aviation safety.
• Flight management systems (FMS) rely on actual navigation performance (ANP) for position estimation uncertainty.
• Current ANP evaluation accuracy is limited by position estimation covariance matrix (PECM) estimation under unknown noise.

Purpose of the Study:

• To address ANP misevaluation caused by inaccurate PECM estimation in traditional models.
• To propose an adaptive PECM estimation method for improved navigation system performance.
• To enhance the accuracy of ANP evaluation for ensuring flight safety.

Main Methods:

• Developed an adaptive PECM estimation method utilizing variational Bayes (VB).
• Integrated the proposed adaptive PECM method with a novel 3D ANP model.
• Evaluated the method's effectiveness in improving ANP accuracy under time-varying noise conditions.

Main Results:

• The adaptive PECM estimation method significantly improves ANP evaluation accuracy.
• The proposed 3D ANP model enhances the reliability of navigation performance assessment.
• The method effectively handles unknown time-varying noise, a common challenge in navigation systems.

Conclusions:

• The adaptive PECM estimation method offers a robust solution for ANP misevaluation.
• Improved ANP accuracy directly contributes to enhanced navigation integrity and flight safety.
• This research provides a valuable advancement for airborne integrated navigation systems in civil aviation.