Implementation and Performance Analysis of a Chi-square Test based GNSS Signal Anomaly Detection

Implementation and Performance Analysis of a Chi-square Test based GNSS Signal Anomaly Detection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Implementation and Performance Analysis of a Chi-square Test based GNSS Signal Anomaly Detection Mohammad Zahidul H. Bhuiyan, Muwahida Liaquat, Saiful Islam, Into Pääkkönen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6750861/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Global Navigation Satellite System (GNSS) signal anomalies in the form of man-made intentional interferences (i.e., jamming or spoofing) have raised the need for effective detection, localization, classification, and mitigation of such unwanted interferences on those protected frequency bands. This work introduces a novel GNSS signal anomaly detection technique that employs a Chi-Square Test on raw digitized intermediate frequency (IF) samples to identify any interference signals on GNSS frequency bands. In this context, ’anomaly’ refers to any man-made interference, including jamming or spoofing. The proposed technique is implemented, tested, and its performance analyzed using an open-source software-defined receiver named FGI-GSRx across various publicly available GNSS data sources and a real-world jammer test campaign. The results demonstrate that the Chi-Square Test achieves an impressive anomaly detection accuracy of over 99% with no false alarms across all datasets representing realistic signal propagation environments. Additionally, the raw GNSS data samples from the jammer test campaign are publicly shared to enable other researchers to develop, test, and validate anomaly detection and mitigation techniques using common datasets. Global Navigation Satellite System Interference Spoofing Anomaly Detection Software-defined Receiver Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Mar, 2026 Reviews received at journal 11 Mar, 2026 Reviewers agreed at journal 13 Jan, 2026 Reviewers invited by journal 26 Jun, 2025 Editor assigned by journal 26 Jun, 2025 Submission checks completed at journal 27 May, 2025 First submitted to journal 26 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6750861","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":462802055,"identity":"3df60b30-afe8-4ecf-a2ed-f7b2b5bbaf66","order_by":0,"name":"Mohammad Zahidul H. 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