GNSS Signal Forecasting for Spoofing and Jamming Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
GNSS receivers face challenges in urban and rural areas due to signal obscuration and multipath effects, leading to inaccurate positioning and potential system failures in autonomous vehicles and drones, which existing models fail to adequately address.
Innovation Solution
The Forecast Assured Navigation (FAN) technology uses high-definition 3D maps and satellite data to predict GNSS signal obscurations and multipath, providing cloud-based forecasts for improved signal reliability and accuracy, utilizing a cloud-based service to determine line-of-sight, non-line-of-sight, and PDOP for specific locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud-based forecast services are implemented to predict signal obscuration and multipath, then GNSS receiver accuracy is improved, but device complexity and data processing requirements increase
Solution Approach 1:
A cloud-based forecast service acts as an intermediary between the receiver and the environment, providing pre-computed obscuration and multipath predictions. The service uses digital surface models and satellite ephemeris data to generate forecast information that is transmitted to receivers, eliminating the need for receivers to perform complex environmental modeling themselves.
Solution Approach 2:
The forecast service performs preliminary calculations of signal obscuration and multipath effects before the receiver needs the information. By pre-computing these predictions using digital surface models and satellite positions, the system prepares accuracy enhancement data in advance, allowing receivers to directly apply the forecasts without performing complex real-time calculations.
2Measurement precision
If high-definition 3D maps and satellite data are used for forecasting, then signal prediction accuracy is improved, but data transmission time and network bandwidth requirements increase
Solution Approach 1:
The system extracts only the essential forecast information (obscuration predictions, multipath predictions, PDOP values) from the comprehensive 3D map and satellite data, transmitting only these critical parameters to receivers rather than the entire datasets. This extraction process maintains prediction accuracy while significantly reducing data transmission requirements.
Solution Approach 2:
The forecast service provides location-specific predictions tailored to each receiver's position and requested time period. Rather than transmitting universal 3D map data to all receivers, the system generates and transmits only the local forecast information relevant to each receiver's specific location and time of need, optimizing data efficiency.
3Reliability
If real-time forecast updates are provided for moving receivers, then navigation reliability is improved, but processing load and energy consumption increase
Solution Approach 1:
The forecast service provides periodic updates to receivers based on their movement and the time-dependent nature of satellite positions and environmental conditions. Rather than continuous real-time streaming, the system updates forecasts at appropriate intervals, maintaining navigation reliability while reducing the processing load and energy consumption associated with constant data reception and processing.
Data Source
AI summary
Disclosed is a method of detecting and rejecting a spoofing or jamming signal source by receiving at a first device a forecast of a visibility for each Global Navigation Satellite System (GNSS) satellite signal source in the forecast at a GNSS receiver coupled to the first device, calculating from at least an elevation and the received visibility of the satellite signal sources in the forecast a predicted Signal to Noise Ratio (SNR), comparing SNR acquired by the GNSS receiver of one or more of the satellite signal sources to the predicted SNR, detecting a spoofing signal source based on acquiring a higher SNR than predicted or a jamming signal source based on acquiring a lower SNR than predicted, and rejecting the spoofing or jamming signal source based on differences between the acquired and predicted SNR.