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Millimetre Wave Radar System for Safe Flight of Drones in Human-Transited Environments
It is undeniable that more and more tasks in which drones work autonomously are becoming essential. Of particular importance are indoor human-transited environments. These entail a challenge for drone flights as the safety of people must be ensured at all times while they are in the vicinity of flig...
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| creator | Parralejo, Felipe Paredes, Jose A. Aranda, Fernando J. Alvarez, Fernando J. Moreno, Jose A. |
| description | It is undeniable that more and more tasks in which drones work autonomously are becoming essential. Of particular importance are indoor human-transited environments. These entail a challenge for drone flights as the safety of people must be ensured at all times while they are in the vicinity of flights. Millimetre-wave radar has proven to be a technology that provides accurate position and velocity measurements, making it ideal for monitoring spaces in search of moving targets. Thus, this work proposes a security system based on millimetre-wave radar, using a processing workflow based on machine learning techniques to detect humans and interrupt drone flights until people are in a safe place. The feasibility of the system is demonstrated experimentally, with accuracy, precision, recall and F1 score greater than 99% and a real-time system performance video. |
| doi_str_mv | 10.1109/IPIN57070.2023.10332501 |
| format | conference_proceeding |
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The feasibility of the system is demonstrated experimentally, with accuracy, precision, recall and F1 score greater than 99% and a real-time system performance video.</description><subject>Airborne radar</subject><subject>collision avoidance</subject><subject>drone</subject><subject>Machine learning</subject><subject>mmWave radar</subject><subject>Radar detection</subject><subject>Radar tracking</subject><subject>safe flight</subject><subject>Safety</subject><subject>Spaceborne radar</subject><subject>Velocity measurement</subject><issn>2471-917X</issn><isbn>9798350320114</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kF1LwzAUhqMgOGb_gWD-QOc5Sdo0lzI3V5gf6Py4G2l7opE2laYO9u8dqFfvAw88Fy9jFwgzRDCX5UN5l2nQMBMg5AxBSpEBHrHEaFPIDKQARHXMJkJpTA3qt1OWxPgJAJgj5lBM2Mutb1vf0TgQf7U74o-2sQN_2seROu76A1pHfNn694-R945fD32gyH3gq-_OhnQz2BD9SA1fhJ0_yI7CGM_YibNtpORvp-x5udjMV-n6_qacX61Tj2jGtECTN4qkM7XKnVZQSVKFNlqQIMidc0oXUKPKgAolLUFtq4yqStZolKrllJ3_dj0Rbb8G39lhv_2_Qv4AqkZTIg</recordid><startdate>20230925</startdate><enddate>20230925</enddate><creator>Parralejo, Felipe</creator><creator>Paredes, Jose A.</creator><creator>Aranda, Fernando J.</creator><creator>Alvarez, Fernando J.</creator><creator>Moreno, Jose A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20230925</creationdate><title>Millimetre Wave Radar System for Safe Flight of Drones in Human-Transited Environments</title><author>Parralejo, Felipe ; Paredes, Jose A. ; Aranda, Fernando J. ; Alvarez, Fernando J. ; Moreno, Jose A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i119t-8196d4e3f9c46f740b3e487972e2e06fff4780c1450e843ae0cab5ebb3c1944c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Airborne radar</topic><topic>collision avoidance</topic><topic>drone</topic><topic>Machine learning</topic><topic>mmWave radar</topic><topic>Radar detection</topic><topic>Radar tracking</topic><topic>safe flight</topic><topic>Safety</topic><topic>Spaceborne radar</topic><topic>Velocity measurement</topic><toplevel>online_resources</toplevel><creatorcontrib>Parralejo, Felipe</creatorcontrib><creatorcontrib>Paredes, Jose A.</creatorcontrib><creatorcontrib>Aranda, Fernando J.</creatorcontrib><creatorcontrib>Alvarez, Fernando J.</creatorcontrib><creatorcontrib>Moreno, Jose A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Parralejo, Felipe</au><au>Paredes, Jose A.</au><au>Aranda, Fernando J.</au><au>Alvarez, Fernando J.</au><au>Moreno, Jose A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Millimetre Wave Radar System for Safe Flight of Drones in Human-Transited Environments</atitle><btitle>2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN)</btitle><stitle>IPIN</stitle><date>2023-09-25</date><risdate>2023</risdate><spage>1</spage><epage>6</epage><pages>1-6</pages><eissn>2471-917X</eissn><eisbn>9798350320114</eisbn><abstract>It is undeniable that more and more tasks in which drones work autonomously are becoming essential. Of particular importance are indoor human-transited environments. These entail a challenge for drone flights as the safety of people must be ensured at all times while they are in the vicinity of flights. Millimetre-wave radar has proven to be a technology that provides accurate position and velocity measurements, making it ideal for monitoring spaces in search of moving targets. Thus, this work proposes a security system based on millimetre-wave radar, using a processing workflow based on machine learning techniques to detect humans and interrupt drone flights until people are in a safe place. The feasibility of the system is demonstrated experimentally, with accuracy, precision, recall and F1 score greater than 99% and a real-time system performance video.</abstract><pub>IEEE</pub><doi>10.1109/IPIN57070.2023.10332501</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | EISSN: 2471-917X |
| ispartof | 2023 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2023, p.1-6 |
| issn | 2471-917X |
| language | eng |
| recordid | cdi_ieee_primary_10332501 |
| source | IEEE Xplore All Conference Series |
| subjects | Airborne radar collision avoidance drone Machine learning mmWave radar Radar detection Radar tracking safe flight Safety Spaceborne radar Velocity measurement |
| title | Millimetre Wave Radar System for Safe Flight of Drones in Human-Transited Environments |
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