Static IoT GNSS Fix Comparison for Spoofing Detection
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Solution Overview
Problem
Current techniques for detecting spoofed Global Navigation Satellite System (GNSS) signals are unreliable and unable to distinguish between spoofing and a bad environment, posing navigation risks and potential disastrous consequences.
Innovation Solution
A system utilizing static Internet of Things (IoT) devices to compare long-term and short-term GNSS fixes, detect spoofing by analyzing differences in averages, and a server to analyze data from multiple IoT devices using machine learning to determine spoofing, providing reliable detection and location of spoofer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current techniques are used to detect spoofed GNSS signals, then detection can be performed, but the detection is unreliable and cannot distinguish between spoofing and bad environment
Solution Approach 1:
The patent segments the detection process into multiple independent components: individual IoT devices perform local GNSS fix comparisons between short-term and long-term averages, then transmit results to a server for aggregated analysis. This segmentation allows the system to distinguish between local environmental issues (affecting single devices) and actual spoofing (affecting multiple devices), thereby improving both reliability and measurement precision.
Solution Approach 2:
The patent merges data from multiple IoT devices at the server level. By combining detection results from geographically distributed devices and analyzing patterns across the network, the system can reliably distinguish genuine spoofing events from local environmental interference, resolving the contradiction between detection reliability and accuracy.
2Area of stationary object
If static IoT devices are deployed for spoofing detection, then wide coverage and low cost are achieved, but the system requires sophisticated analysis to distinguish spoofing from environmental factors
Solution Approach 1:
The patent divides the detection function across numerous simple static IoT devices distributed geographically. Each device performs basic local analysis comparing short-term and long-term GNSS fixes, while the server handles the complex pattern recognition. This segmentation enables wide coverage with low-cost devices while managing analysis complexity through distributed architecture.
Solution Approach 2:
The server acts as an intermediary that receives simple data from multiple static IoT devices and performs the sophisticated analysis. This intermediary approach allows static devices to maintain simplicity while the centralized server handles the complex task of distinguishing spoofing from environmental factors, resolving the contradiction between coverage area and analysis complexity.
3Measurement precision
If individual devices perform spoofing detection, then local detection is possible, but false alarms occur due to inability to distinguish spoofing from bad environment
Solution Approach 1:
The patent segments the detection system so that individual IoT devices perform local short-term versus long-term GNSS fix comparisons, while the server aggregates results from multiple devices. This segmentation enables local detection capability while using multi-device correlation to filter false alarms, simultaneously improving measurement precision and reliability.
Solution Approach 2:
The system implements feedback through the server's centralized analysis of data from multiple devices. When individual devices detect potential spoofing, the server cross-references this with data from other devices to confirm or refute the detection. This feedback mechanism reduces false alarms while maintaining local detection capability, resolving the contradiction between measurement precision and reliability.
Data Source
AI summary
In an aspect, a user equipment (UE) receives a spoofing alert message from either a server or an internet-of-things (IOT) device that indicates whether a spoofed Global Navigation Satellite System (GNSS) condition is present. Based on determining that the spoofing alert message indicates that a spoofed GNSS condition is present, the UE determines, based on the spoofing alert message, a location of a spoofer broadcasting a spoofed GNSS signal, determines, based on the location of the spoofer and a current location of the UE, that the UE is within a receiving area of the spoofed GNSS signal, and determines a position of the UE without using the spoofed GNSS signal.