GNSS Spoofing Detection via SBAS Satellite Distance Comparison
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Solution Overview
Problem
GNSS receivers are susceptible to spoofing threats, which can lead to erroneous position outputs, potentially causing hazards to avionics safety, especially during aircraft flight or landing approaches.
Innovation Solution
A method and system for detecting satellite signal spoofing by monitoring satellite signals from GNSS and SBAS satellites, computing satellite orbital positions, determining distance values, and comparing them to detect anomalies that indicate spoofing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If GNSS receiver uses standard 24 channel design, then receiver complexity is reduced, but susceptibility to spoofing threats increases
Solution Approach 1:
The system performs preliminary calculations of expected satellite positions and distances before comparing them with actual received signals. By pre-computing what the satellite geometry should be, the system can detect spoofing attempts before they compromise navigation accuracy, thus enhancing security without requiring a complete redesign of the receiver architecture.
Solution Approach 2:
The patent introduces SBAS (Satellite-Based Augmentation System) satellites as intermediary reference points. These additional satellites provide independent position references that mediate between the potential spoofing signals and the receiver's position calculation, allowing the system to cross-validate signals and detect inconsistencies that indicate spoofing attempts.
2Speed
If GNSS receiver processes only current satellite signals, then processing speed is improved, but detection of spoofing anomalies is reduced
Solution Approach 1:
The system pre-calculates expected satellite positions and inter-satellite distances based on orbital mechanics before comparing them with actual signal data. This preliminary computation enables rapid comparison operations that maintain high processing speed while achieving accurate spoofing detection through the contrast between predicted and observed values.
Solution Approach 2:
The system continuously compares actual satellite signal positions with predicted positions and uses the discrepancy feedback to detect spoofing. This feedback mechanism allows the receiver to maintain high processing speed by using efficient comparison algorithms while achieving accurate anomaly detection through iterative validation of satellite geometries.
3Reliability
If SBAS satellites are incorporated for spoofing detection, then spoofing detection capability is improved, but system complexity increases
Solution Approach 1:
The system uses SBAS satellites to serve multiple functions simultaneously: they provide augmentation data for improved navigation accuracy, additional geometric references for spoofing detection, and independent position validation. This multi-functionality enhances spoofing detection capability without requiring separate dedicated hardware systems, thus limiting the increase in overall system complexity.
Solution Approach 2:
The receiver pre-processes SBAS augmentation data to extract expected satellite positions and distances before comparing them with actual GNSS signals. By performing these calculations in advance using standardized orbital mechanics, the system simplifies the real-time processing requirements while maintaining robust multi-satellite spoofing detection capabilities.
Data Source
AI summary
A method for detecting spoofing comprises monitoring signals from GNSS and SBAS satellites with a GNSS receiver; obtaining current time and orbital parameters from the receiver, based on real-time signals from the satellites; computing orbital positions based on the current time and orbital parameters; retrieving past orbital parameters; calculating predicted orbital positions based on the orbital parameters with respect to current time and the past orbital parameters; computing current orbital positions based on current satellite signals; determining a first distance value between two or more of the satellites based on the predicted orbital positions; determining a second distance value between two or more of the satellites based on the current orbital positions; comparing the first and second distance values to obtain a discriminator value; determining whether the discriminator value is greater than a threshold level, and outputting a spoofing alert when the discriminator value is greater than the threshold level.