{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rf-based-direction-finding-of-uavs-using-dnn","title":"RF-Based Direction Finding of UAVs Using DNN","arxiv_id":"1712.01154","date":"2017-12-01","proceeding":null,"authors":["Samith Abeywickrama","Lahiru Jayasinghe","Hua Fu","Subashini Nissanka","Chau Yuen"],"abstract":"This paper presents a sparse denoising autoencoder (SDAE)-based deep neural\nnetwork (DNN) for the direction finding (DF) of small unmanned aerial vehicles\n(UAVs). It is motivated by the practical challenges associated with classical\nDF algorithms such as MUSIC and ESPRIT. The proposed DF scheme is practical and\nlow-complex in the sense that a phase synchronization mechanism, an antenna\ncalibration mechanism, and the analytical model of the antenna radiation\npattern are not essential. Also, the proposed DF method can be implemented\nusing a single-channel RF receiver. The paper validates the proposed method\nexperimentally as well.","url_abs":"http://arxiv.org/abs/1712.01154v3","url_pdf":"http://arxiv.org/pdf/1712.01154v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"rf-based-direction-finding-of-uavs-using-dnn","repo_url":"https://github.com/LahiruJayasinghe/DeepDOA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"rf-based-direction-finding-of-uavs-using-dnn","repo_url":"https://github.com/mohizahmad/DeepDOA-master","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"denoising","task_name":"Denoising"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}