Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction

Area of Science:

• Navigation Systems Engineering
• Control Systems Theory
• Signal Processing

Background:

• Navigation integrity is crucial for safety-critical applications.
• Tightly coupled Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS) are widely used.
• Potential faults in Kalman Filter prediction and Inertial Measurement Unit (IMU) failures can compromise navigation accuracy.

Purpose of the Study:

• To propose an efficient Fault Detection and Exclusion (FDE) scheme for GNSS-INS navigation.
• To address potential faults in the Kalman Filter state prediction step ('filter fault').
• To enhance navigation integrity in safety-critical applications.

Main Methods:

• Derivation of an integration model to capture GNSS and filter fault impacts.
• Development of two independent hypothesis-test-based detectors for GNSS and filter faults.
• Implementation of an exclusion function for removing faulty measurements and recovering from filter faults.

Main Results:

• The proposed FDE scheme effectively detects and excludes GNSS and filter faults.
• The integration model accurately represents fault characteristics.
• Simulations demonstrate high efficiency and effectiveness across various fault scenarios.

Conclusions:

• The developed FDE scheme ensures navigation integrity for safety-critical systems.
• The method successfully mitigates GNSS measurement faults and internal filter faults.
• Optimized decision strategies minimize incorrect exclusion events, improving overall system reliability.