An Inter-Frequency Cross-Validation Approach for Pseudo-Range Fault Detection in GNSS Relative Positioning

Area of Science:

• Geomatics Engineering
• Satellite Navigation Systems
• Signal Processing

Background:

• Faulty pseudorange measurements in Global Navigation Satellite System (GNSS) relative positioning can cause significant errors.
• High-performance fault detection and exclusion (FDE) is crucial for reliable GNSS applications.
• Existing methods like Advanced Receiver Autonomous Integrity Monitoring (ARAIM) have limitations in accuracy and computational efficiency.

Purpose of the Study:

• To propose an effective fault detection and exclusion (FDE) method for pseudorange-based GNSS relative positioning.
• To utilize inter-frequency cross-validation (IFCV) for enhanced detection and exclusion of faulty measurements.
• To improve positioning accuracy and computational efficiency compared to conventional methods.

Main Methods:

• Developed an Inter-Frequency Cross-Validation (IFCV) technique for GNSS relative positioning.
• Employed multi-frequency differenced pseudorange measurements to create inter-frequency test statistics.
• Utilized a conservative strategy for excluding multiple faults to ensure robust position determination.

Main Results:

• The proposed IFCV method demonstrated significantly lower false alarm rates (0.03%) and missed detection rates (0%) compared to ARAIM.
• IFCV improved positioning accuracy by 78%, outperforming ARAIM's 55% improvement after fault injection.
• IFCV achieved a computational efficiency improvement of 10^4 over ARAIM.

Conclusions:

• The IFCV method offers a superior approach to fault detection and exclusion in GNSS relative positioning.
• IFCV provides enhanced accuracy and remarkable computational efficiency, making it a viable alternative to ARAIM.
• The method's effectiveness in handling multiple outliers ensures robust and reliable positioning solutions.