Multi-Source, Fault-Tolerant, and Robust Navigation Method for Tightly Coupled GNSS/5G/IMU System.

Area of Science:

• Navigation Systems Engineering
• Signal Processing
• Sensor Fusion

Background:

• Global Navigation Satellite Systems (GNSS) face limitations in precision and reliability due to interference.
• Fifth-generation (5G) networks offer enhanced communication infrastructure for extended coverage.
• Multi-sensor faults in navigation systems degrade performance in dynamic environments.

Purpose of the Study:

• To develop an advanced, tightly coupled GNSS/5G/IMU integration framework for distributed PNT systems.
• To implement robust fault detection and sensor recovery mechanisms for enhanced navigation reliability.
• To improve the accuracy and resilience of positioning, navigation, and timing services.

Main Methods:

• Developed a weighted, robust adaptive filter (MCC-WRAF) based on the maximum correntropy criterion for multi-source fusion.
• Proposed a time-sequential, observation-driven full-source fault detection and sensor recovery validation strategy using a sliding window.
• Introduced a covariance-optimal, inflation-based integrity protection mechanism for PNT service availability.

Main Results:

• The proposed framework effectively mitigates undetected fault impacts and improves detection sensitivity.
• Alarm response times were significantly reduced in various fault scenarios (step, ramp, mixed).
• Dynamic positioning accuracy improved to 0.83 m (1σ), outperforming EKF and MRAKF by 28.3% and 53.1% respectively.

Conclusions:

• The integrated GNSS/5G/IMU system with advanced fault detection enhances navigation accuracy and reliability.
• The MCC-WRAF and validation strategy effectively handle multi-sensor faults in complex scenarios.
• This approach provides a robust solution for positioning, navigation, and timing services in challenging environments.