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This paper proposes RaDro; a system that leverages millimeter-waves (mmWave) to precisely localize and track drones in indoor environments. Unlike commonly used alternative technologies, RaDro is cost-effective and can penetrate obstacles, a bonus in non-line-of-sight (NLoS) scenarios, which enhances its reliability for tracking objects in complex environments. It does this without the need for tags or anchors to be attached to the drone, achieving 3D tracking with just a single radar point, significantly streamlining the deployment process. Comprehensive experiments are conducted in different scenarios to evaluate RaDro's performance. These include employing different drone models with different sizes to execute a range of aerial manoeuvres across different flight arenas, each with its own settings and clutter, and encountering various LoS and NLoS scenarios in dynamic environments. The experiments aimed to assess the capabilities of the system to extract coarse-grained and fine-grained information for drone detection, motion recognition, and localization. The results showcase precise localization, achieving a 50% reduction in localization error compared to the conventional baseline. This localization accuracy remains resilient even when confronted with interference from other moving sources. The results also demonstrate the system's ability to accurately localize drones in NLoS scenarios where existing state-of-the-art optical technologies cannot work.<\/jats:p>","DOI":"10.1145\/3678549","type":"journal-article","created":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T14:36:21Z","timestamp":1725892581000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["RaDro: Indoor Drone Tracking Using Millimeter Wave Radar"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4896-424X","authenticated-orcid":false,"given":"Heba","family":"Abdelnasser","sequence":"first","affiliation":[{"name":"Department of Computing, Imperial College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3136-2341","authenticated-orcid":false,"given":"Mohammad","family":"Heggo","sequence":"additional","affiliation":[{"name":"Department of Computing, Imperial College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6351-1698","authenticated-orcid":false,"given":"Oscar","family":"Pang","sequence":"additional","affiliation":[{"name":"Aerial Robotics Laboratory, Imperial College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9720-2463","authenticated-orcid":false,"given":"Mirko","family":"Kovac","sequence":"additional","affiliation":[{"name":"Aerial Robotics Laboratory, Imperial College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9786-7257","authenticated-orcid":false,"given":"Julie A.","family":"McCann","sequence":"additional","affiliation":[{"name":"Department of Computing, Imperial College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,9,9]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2746285.2755969"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/VTC2024-Spring62846.2024.10683414"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2015.7218525"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/SCOPES.2016.7955787"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCS.2009.934469"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/COMSNETS51098.2021.9352894"},{"key":"e_1_2_1_7_1","unstructured":"AB Bitcraze. 2022. 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