GNSS Signal Acquisition Using Narrow Search Windows Against Spoofing
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Solution Overview
Problem
Existing GNSS systems are vulnerable to spoofing attacks, where adversaries inject falsified signals that can override legitimate satellite signals, leading to incorrect location determination with significant consequences.
Innovation Solution
Implementing a GNSS receiver that uses non-GNSS position information to define a narrow search window for acquiring and tracking GNSS signals, excluding spoofing signals through techniques like grid-based and loop-based tracking, and determining updated position information based on frequency and code phase offsets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a wide search window is used to acquire GNSS signals, then the probability of acquiring legitimate signals is improved, but the vulnerability to spoofing attacks increases
Solution Approach 1:
The system performs preliminary actions by determining non-GNSS position information from other data sources before acquiring GNSS signals. This preliminary position information is used to predict expected signal parameters and define a narrow search window, allowing the system to prepare rejection criteria for spoofing signals before they are encountered
Solution Approach 2:
Instead of using a uniform wide search window, the system applies local quality by creating a narrow, targeted search window based on predicted signal parameters from non-GNSS position data. This localized approach concentrates the search in the specific frequency and code phase region where legitimate signals are expected to be found
2Object-affected harmful factors
If a narrow search window is used to exclude spoofing signals, then spoofing resistance is improved, but the difficulty of detecting and measuring legitimate signals increases
Solution Approach 1:
The system performs preliminary calculations to predict the frequency and code phase of legitimate GNSS signals based on non-GNSS position information and satellite ephemeris data. These predictions are made before the actual signal acquisition, enabling the system to know where to look for legitimate signals
Solution Approach 2:
The system uses feedback by comparing received signal parameters against predicted parameters derived from non-GNSS position data. When received frequency and code phase match predictions within expected tolerances, the signal is accepted as legitimate; when they diverge beyond thresholds, the signal is rejected as spoofing
3Measurement precision
If non-GNSS position information is used to predict GNSS signal parameters, then location accuracy is improved, but the device complexity increases
Solution Approach 1:
The system applies universality by using non-GNSS position information (from cellular towers, Wi-Fi, inertial sensors, or map matching) for multiple purposes: not only for general location determination but also for predicting GNSS signal parameters like frequency and code phase. This multi-functional use of existing data reduces the need for additional specialized components
Data Source
AI summary
A method of determining a location of a mobile device in the presence of a spoofing signal includes receiving a GNSS signal and detecting a spoofing condition based on a signal strength of the GNSS signal. The spoofing condition may comprise an increase in the signal strength, the signal strength exceeding a threshold value, an increase in a noise floor related to a measurement of the signal strength, or a combination thereof. The method may further comprise, responsive to detecting the spoofing condition, providing an indication of the GNSS signal as a spoofing signal.