Spoofing Detection in Real-Time Kinematic Positioning
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Solution Overview
Problem
Current GNSS receivers are vulnerable to spoofing attacks, which can manipulate position, velocity, and time readings, posing a significant threat as their reliance increases in critical applications like transportation and autonomous systems.
Innovation Solution
A GNSS receiver system with a first and reference antenna, capable of performing carrier phase measurements, single and double difference calculations, and ambiguity resolution to detect spoofing by determining if the baseline vector yields a zero solution, issuing a notification when spoofing is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If GNSS receivers rely more on civil GNSS for critical applications, then the dependence and utility increase, but the vulnerability to spoofing attacks increases
Solution Approach 1:
The system performs preliminary actions by calculating predicted double differences based on known satellite positions and baseline vectors before receiving actual GNSS signals. This pre-computed reference data enables immediate comparison with received signals to detect spoofing attempts, addressing the vulnerability before it can compromise the positioning system.
Solution Approach 2:
The system implements feedback by continuously comparing measured double differences from received GNSS signals against predicted double differences. When discrepancies exceed thresholds, the system generates spoofing detection alerts and can switch to alternative positioning methods, creating a closed-loop defense mechanism that responds to spoofing threats in real-time.
2Reliability
If spoofing detection capabilities are added to GNSS receivers, then security against spoofing improves, but device complexity increases
Solution Approach 1:
The spoofing detection system leverages the existing RTK positioning infrastructure and signal processing chains already present in modern GNSS receivers. By reusing the same antenna elements, carrier phase measurement capabilities, and double difference calculation mechanisms intended for positioning, the system achieves multi-functionality without requiring separate dedicated spoofing detection hardware.
Solution Approach 2:
The system introduces an intermediary computational layer that processes existing GNSS measurements through additional algorithms. Rather than adding complex hardware, it uses software-based intermediaries including predicted double difference calculations, threshold comparisons, and ambiguity resolution checks to detect spoofing while maintaining compatibility with standard receiver architectures.
3Speed
If real-time spoofing detection is implemented, then detection speed improves, but computational load increases
Solution Approach 1:
The system extracts only the critical elements needed for spoofing detection from the full GNSS signal processing chain. It focuses specifically on carrier phase measurements and double difference calculations, extracting these specific observables from the received signals while ignoring other less relevant processing steps, thereby reducing computational energy requirements.
Solution Approach 2:
The system changes parameters by working in the double difference domain rather than raw pseudorange or carrier phase measurements. This parameter transformation simplifies the detection mathematics and reduces computational complexity, as double differences eliminate many common error sources and simplify the comparison between predicted and measured values.
Data Source
AI summary
A GNSS receiver has a first antenna and a reference antenna. From the measurement of a carrier phase L1k of GNSS signals at the first antenna and a reference carrier phase L0k at the reference antenna, a single difference L10k is obtained, whereby calculating a double difference L10k0=L10k−L100 between a k-th GNSS satellite and a reference satellite (k=0). The double difference L10k0 is also predicted using known satellite position information as a function of a differencing vector ek0 between a unit line-of-sight direction vector ek of the k-th satellite and that of the reference satellite e0 and a base line vector Δ with a second integer bias N10k0. A real time kinematic (RTK) positioning solution is calculated with ambiguity resolution based on the predicted value of L10k0 and the calculated value of L10k0. A spoofing is detected if the RTK positioning solution yields Δ=0.