Receiver Signal Processing to Resist GNSS Jamming and Spoofing Attacks
Project Description: 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 is against jamming.
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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.
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We instead propose 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 us 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.
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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. 
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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, we propose to develop new algorithms using data-adaptive multiple model filters and direct phase estimation of GNSS dataless pilot signals. These methods will allow us to much longer averaging times to improve jamming resistance. 
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US DOT Priorities: This research project directly targets the US DOT’s research priority area of Reducing Transportation Cybersecurity Risks. We will be investigating novel GNSS receiver signal processing solutions to help ensure resilience to jamming and spoofing. The unmitigated effects of such GNSS interference on individual surface vehicles can cause cyber physical disruptions in transportation that can range from denial of service (shutdown of the transportation system) during a jamming event to a major threat to public safety in the case of a spoofing attack. We will develop, implement, and test advanced GNSS signal processing techniques that significantly surpass existing methods and algorithms for jamming resistance and spoofing detection and exclusion. The results would ultimately be deployable in the individual vehicles that existing in the greater transportation ecosystem.
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Outputs: In this jumpstart project, we will develop and provide:
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new algorithms to detect GNSS spoofing using complex correlation samples to decompose the received signal into its authentic and counterfeit components;
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a new approach to allow GNSS receivers to track carrier phase and frequency during extremely low carrier-to-noise power conditions caused by jamming;
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data supporting validation of the spoofing detection and jamming resistance methods through simulation and experimental testing.
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We expect interest in this research from GNSS receiver manufacturers and will actively encourage those on CARNATIONS External Advisory Board to contribute feedback and collaborate throughout the effort.
Outcomes/Impacts: GNSS radio-frequency interference can cause widespread delays or cascading failures across multiple modes of transportation. The aim of this project is to advance GNSS signal processing technologies addressing the types of radio-frequency interference attacks that are the most difficult to defend against. The results of this project will be shared with the DOT, GNSS researchers, industry, and standardization bodies.
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Final Research Report: (Upon completion of the project we will a provide link to the final report.)