{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T15:26:39Z","timestamp":1767626799145,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T00:00:00Z","timestamp":1750809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>With the rapid advancement of drone technology, the demand for the precise detection and identification of drones has been steadily increasing. Existing detection methods, such as radio frequency (RF), radar, optical, and acoustic technologies, often fail to meet the accuracy and speed requirements of real-world counter-drone scenarios. To address this challenge, this paper proposes a novel drone detection and identification algorithm based on transmission signal analysis. The proposed algorithm introduces an innovative feature extraction method that enhances signal analysis by extracting key characteristics from the signals, including bandwidth, power, duration, and interval time. Furthermore, we developed a signal processing algorithm that achieves efficient and accurate drone identification through bandwidth filtering and the matching of duration and interval time sequences. The effectiveness of the proposed approach is validated using the DroneRF820 dataset, which is specifically designed for drone identification and counter-drone applications. The experimental results demonstrate that the proposed method enables highly accurate and rapid drone detection.<\/jats:p>","DOI":"10.3390\/info16070541","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T05:53:13Z","timestamp":1750917193000},"page":"541","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Novel Matching Algorithm for Effective Drone Detection and Identification by Radio Feature Extraction"],"prefix":"10.3390","volume":"16","author":[{"given":"Teng","family":"Wu","sequence":"first","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Beijing Key Laboratory of Software Security Engineering Technology, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Yan","family":"Du","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Beijing Key Laboratory of Software Security Engineering Technology, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Runze","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Beijing Key Laboratory of Software Security Engineering Technology, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Hui","family":"Xie","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Software Security Engineering Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"School of Computer Science, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Shengjun","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Beijing Key Laboratory of Software Security Engineering Technology, Beijing Institute of Technology, Beijing 100081, China"}]},{"given":"Changzhen","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Beijing Key Laboratory of Software Security Engineering Technology, Beijing Institute of Technology, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102894","DOI":"10.1016\/j.adhoc.2022.102894","article-title":"A survey of cyber security threats and solutions for UAV communications and flying ad-hoc networks","volume":"133","author":"Tsao","year":"2022","journal-title":"Ad Hoc Netw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"102369","DOI":"10.1016\/j.inffus.2024.102369","article-title":"A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management","volume":"108","author":"Boroujeni","year":"2024","journal-title":"Inf. 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