GNSS Signal Simulation for Multipath and Obscuration Testing
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Solution Overview
Problem
Connected and autonomous vehicles (CAVs) face challenges in ensuring cyber-physical resilience, particularly in positioning, navigation, and timing (PNT) functions, due to the risk of cyber-attacks and the need for robust testing infrastructure to validate their performance under various environmental conditions.
Innovation Solution
A testing platform that shields CAVs from ambient cellular and GNSS signals, generating simulated signals to replicate real-world environments, including multipath and obscuration effects, allowing for real-time testing of resilience against spoofing and jamming attacks, while integrating inertial measurement units for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CAVs use real ambient cellular and GNSS signals for testing, then the testing environment is simple and costs are low, but the testing realism and resilience validation are insufficient
Solution Approach 1:
The patent introduces signal shielding structures (Faraday cages) and simulated signal generation systems as intermediaries between the CAV and the external environment. The shielding structures block real ambient signals while the simulation systems generate controlled test signals, creating an intermediary testing environment that validates resilience without requiring complex real-world attack scenarios
Solution Approach 2:
The patent creates simplified copies of real-world signal environments through simulated cellular and GNSS signals. These simulated signals replicate the characteristics of real signals under various conditions (multipath, obscuration, jamming, spoofing) without requiring actual exposure to dangerous cyber-physical attacks, thus validating resilience in a controlled manner
2Reliability
If CAVs are tested in real-world environments with ambient signals, then the testing setup is simple, but the ability to control and validate resilience against cyber-attacks is insufficient
Solution Approach 1:
The patent implements preliminary shielding of the CAV using Faraday cages before testing begins. This preliminary action blocks all external signals and creates a controlled environment where simulated signals can be introduced without contamination from real ambient signals, enabling systematic validation of cyber-security resilience against various attack scenarios
Solution Approach 2:
The patent introduces simulated signal generation systems as intermediaries that can precisely control signal characteristics. These systems generate controlled cellular and GNSS signals with known properties (including simulated attacks), allowing systematic testing of resilience without the unpredictability of real-world environments
3Reliability
If ambient signals are used for testing, then signal generation costs are low, but multipath and obscuration effects cannot be accurately simulated
Solution Approach 1:
The patent applies different signal characteristics to different spatial locations and time periods. The simulated signals incorporate location-specific multipath and obscuration effects that match the actual test environment geometry, creating locally accurate signal conditions that validate environmental impairment response without requiring complex physical environments
Solution Approach 2:
The patent dynamically changes signal parameters (delay, amplitude, frequency offset, phase) to simulate various environmental conditions. By modifying these parameters in the simulated signals, the system can reproduce multipath, obscuration, and other impairments without physically recreating the challenging environments
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables comprehensive and realistic testing of CAVs, improving their resilience against cyber-attacks and environmental impairments, ensuring safe and reliable navigation and communication systems.
Implementation Method 1
shielding a cellular receiving antenna of the connected vehicle from ambient cellular signals
Implementation Method 2
generating the simulated cellular signals to feed to the connected vehicle, in real time, simulating with at least one vehicle and/or infrastructure source modified according to the augmented environment
Implementation Method 3
integrating inertial measurement units for enhanced accuracy
Data Source
AI summary
The disclosed technology teaches testing an autonomous vehicle: shielding a GNSS receiving antenna of the vehicle from ambient GNSS signals while the vehicle is under test and supplanting the ambient GNSS signals with simulated GNSS signals. Testing includes using a GNSS signal generating system: receiving the ambient GNSS signals using an antenna of the system and determining a location and acceleration of the vehicle from the GNSS signals, accessing a model of an augmented environment that includes multi-pathing and obscuration of the GNSS signals along a test path, based on the determined location—generating the simulated GNSS signals to feed to the vehicle, in real time—simulating at least one constellation of GNSS satellite sources modified according to the augmented environment, based on the determined location, and feeding the simulated signals to a receiver in the vehicle, thereby supplanting ambient GNSS as the autonomous vehicle travels along the test path.