02040naa a22003138i 4500 5324 5324 00005324 FR-PaOEC 20211006062617.0 a o d i cr || |||m|n|| 190601s2018 ||| o i|0| 0 eng d (FR-PaOEC) FR-PaOEC ES-MaONT Martín, Juan Pablo 3357 Opportunities and challenges of global flight data acquisition /​ Juan Pablo Martín and Martín Gabriel Riolfo Geneva : International Telecommunication Union, 2018. 7 p. texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier Receptors on-board satellites are being implemented to track civil aircrafts all around the world. This new scenario requires novel methods to process the signals in order to efficiently retrieve more updated and reliable position and status data of every aircraft. To reach the required performance, it is indeed needed to engage carefully chosen algorithms of data analysis and processing. Machine learning algorithms, in particular k-nearest neighbors and support vector machines, are employed to estimate the potential success in decodifying ADS-B messages in highly congested areas, and simulations are performed to obtain the training and testing signals. First, the ADS-B communication system is described; second, multivariate analysis and machine learning algorithms are studied. Finally, the results obtained from machine learning methods are compared and future studies are proposed. Tecnologías habilitadoras digitales 18 Science and Technology Riolfo, Martín Gabriel 3358 4843 ITU Journal: ICT Discoveries Vol. 2018, no. 2, p. 103-109 2018:2<103 2616-8375 itu-ilibrary.org https://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I2-2018-13-PDF-E.pdf Acceso al documento 0 pdf ART udc 0 0 0 3 1 6274 01 01 online 2019-09-12 0 1000020175573 2019-09-12 00:00:00 2019-09-12 2019-09-12 ART pdf