Spoofing Detection using Decomposition of the Complex Cross Ambiguity Function with Measurement Correlation

Sahil Ahmed, Samer Khanafseh, Boris Pervan

Abstract:	Abstract—In this paper, we describe, implement, and validate the decomposition of the Complex Cross Ambiguity Functions (CCAF) of spoofed Global Navigation Satellite System (GNSS) signals into their constitutive components. We advance prior work in [1] and [2] by specifically accounting for correlation of thermal noise across the code delay and Doppler measurement space and by increasing the pre-detection integration time to reduce its overall impact. We also characterize the CCAF distortion by code cross-correlation and thermal noise. The method is applicable to spoofing scenarios that can lead to Hazardous Misleading information (HMI) and are difficult to detect by other means. It can identify spoofing in the presence of multipath and when the spoofing signal is power matched and offsets in code delay and Doppler frequency are relatively close to the true signal. Spoofing can be identified at an early stage within the receiver and even applicable for dynamic users. Index Terms—Complex Cross Ambiguity Function, GNSS spoofing detection, measurement correlation, particle swarm decomposition
Published in:	2023 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 24 - 27, 2023 Hyatt Regency Hotel Monterey, CA
Pages:	500 - 510
Cite this article:	Ahmed, Sahil, Khanafseh, Samer, Pervan, Boris, "Spoofing Detection using Decomposition of the Complex Cross Ambiguity Function with Measurement Correlation," 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2023, pp. 500-510. https://doi.org/10.1109/PLANS53410.2023.10140060
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