Cloud-Based GNSS Interference Detection for Aircraft Spoofing Alerts
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Solution Overview
Problem
Aircraft are vulnerable to GNSS spoofing and jamming events, leading to navigation failures, ADS-B malfunctions, and critical system failures, compromising safety and causing flight cancellations and delays.
Innovation Solution
A cloud-based alert system processes GNSS data from multiple sources to detect spoofing events in real-time, providing alerts to aircraft crews through EFB tablets or other onboard systems, utilizing external GNSS receivers and deep learning models to analyze anomalous flight and signal characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If aircraft rely on GNSS data for navigation, then navigation efficiency and flight operations are improved, but vulnerability to spoofing and jamming events increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring GNSS signal characteristics and comparing them against expected patterns before spoofing can successfully compromise navigation. The cloud-based system analyzes signal anomalies, elevation/azimuth inconsistencies, and other indicators in advance to detect potential spoofing events before they affect aircraft navigation operations.
Solution Approach 2:
A cloud-based intermediary system is introduced between the GNSS satellites and the aircraft navigation systems. This intermediary analyzes GNSS signal data from multiple sources, compares signal characteristics against known patterns, and provides authentication verification before allowing the navigation system to use the GNSS data, thereby mediating the trust relationship.
2Measurement precision
If cloud-based processing is used to detect spoofing events, then detection accuracy is improved, but data transmission time and system complexity increase
Solution Approach 1:
The system performs preliminary analysis of GNSS signal characteristics onboard the aircraft before transmitting data to the cloud. By pre-processing signals and identifying obvious anomalies locally, the system reduces the amount of data that needs to be transmitted and can provide immediate alerts for critical issues without waiting for cloud processing.
Solution Approach 2:
The system transitions from single-source onboard processing to a multi-dimensional distributed architecture where signal analysis occurs at multiple levels: onboard pre-processing, cloud-based comprehensive analysis, and ground station verification. This dimensional expansion allows parallel processing that maintains accuracy while reducing overall latency.
3Reliability
If multiple GNSS receiver sources are monitored, then spoofing detection capability is improved, but device complexity and processing requirements increase
Solution Approach 1:
The cloud-based system serves multiple functions simultaneously: it acts as a data aggregation point for multiple GNSS receivers, a signal analysis engine, an authentication verification system, and a communication hub between aircraft and ground stations. This multi-functionality consolidates what would otherwise require separate complex systems into a single unified platform.
Solution Approach 2:
Instead of requiring each aircraft to independently implement complex spoofing detection algorithms and maintain multiple receiver systems, the invention uses copying by having the cloud system replicate the analysis function across all connected receivers. The same detection algorithms and reference data are copied and applied uniformly to signals from multiple sources, reducing individual system complexity.
Data Source
AI summary
The technology disclosed teaches distributed networks and methods for cloud processing for global navigation satellite system (GNSS) interference data from a plurality of GNSS receivers to alert aircraft personnel to GNSS spoofing of aircraft guidance systems. The technology disclosed includes receiving at a cloud-based server, GNSS interference data from the plurality of GNSS receivers, analyzing the GNSS interference data upon receipt, identifying an interference event from the analyzed GNSS interference data, and in response to an identified interference event, the cloud-based server providing an alert to EFB tablet devices onboard the aircraft thereby causing notification of aircraft personnel of a potential spoofing event.