Receiver Signal Processing to Resist GNSS Jamming and Spoofing Attacks
This project will follow two paths in parallel, both involving advanced Global Navigation Satellite System (GNSS) receiver signal processing. The first is focused on defending against spoofing, the second against jamming. (1) GNSS signal correlation monitoring approaches have been proposed as powerful means to detect spoofing. A sampled signal can be represented in the form of a complex number, I (in-phase) and Q (quadrature), as a function of code delay and Doppler offset. Existing monitoring concepts use the magnitudes of these complex samples, performing a two-dimensional sweep in code delay and Doppler. Spoofing is detectable if two or more correlation peaks are distinguishable in the search space. In practice, this method is not reliable when multipath is present and for spoofed signals closely matching the true ones. The research team instead proposes to use the original complex correlation samples to directly decompose the received signal into its components—true, spoofed, and multipath—including their signal amplitudes, Doppler frequencies, code delays, and carrier phases. This new method will allow the research team to detect the difficult cases that existing receiver-based monitoring techniques cannot, where the spoofed and true signals are nearly aligned in code delay and Doppler, but their complex correlation shows distinct peaks. (2) Carrier tracking in GNSS receivers is especially vulnerable to jamming. The function is generally implemented using a Phase Lock Loop (PLL), which reconstructs the received carrier and produces the carrier-phase ranges essential to high-precision navigation. During a jamming event, the additive noise pumped into the PLL leads to accumulated error in carrier reconstruction and ultimately loss of phase lock. The PLL is a feedback control system, where the averaged I and Q samples serve as the sensor inputs to a classical controller. However, carrier ‘tracking’ can also be understood as an estimation problem amenable to Kalman filtering. Kalman filter implementations are more flexible than PLLs because their component dynamic and measurement models can be designed to suit the needs of specific scenarios, including jamming resistance. A major challenge in using a Kalman filter for GNSS carrier phase tracking is that it is a hybrid stochastic estimation problem, requiring simultaneous estimation of discrete navigation data bits and continuous carrier phase. To overcome the problem, the research proposes to develop new algorithms using data-adaptive multiple model filters and direct phase estimation of GNSS dataless pilot signals. These methods will allow the research team to much longer averaging times to improve jamming resistance.
- Record URL:
Language
- English
Project
- Status: Active
- Funding: $Federal $210,000, Cost-share $105,000
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Contract Numbers:
Illinois Institute of Technology/69A3552348324
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Center for Assured and Resilient Navigation in Advanced Transportation Systems
Illinois Institute of Technology
Chicago, IL United States 60616 -
Project Managers:
Narang, Aashish
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Performing Organizations:
Center for Assured and Resilient Navigation in Advanced Transportation Systems
Illinois Institute of Technology
Chicago, IL United States 60616 -
Principal Investigators:
Pervan, Boris
Khanafseh, Samer
- Start Date: 20231001
- Expected Completion Date: 20240930
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Subprogram: University Transportation Centers
Subject/Index Terms
- TRT Terms: Computer security; Monitoring; Navigation; Satellite navigation systems
- Subject Areas: Data and Information Technology; Security and Emergencies; Transportation (General);
Filing Info
- Accession Number: 01906657
- Record Type: Research project
- Source Agency: Center for Assured and Resilient Navigation in Advanced Transportation Systems
- Contract Numbers: Illinois Institute of Technology/69A3552348324
- Files: UTC, RIP
- Created Date: Jan 31 2024 2:35PM