Revisión de algoritmos, métodos y técnicas para la detección de UAVs y UAS en aplicaciones de audio, radiofrecuencia y video

Palabras clave: Detección de drones, aprendizaje profundo, aprendizaje de máquina, sensores de sonido, sensores de video, sensores de radiofrecuencia

Resumen

Los vehículos aéreos no tripulados, conocidos también como drones, han tenido una evolución exponencial en los últimos tiempos, debido en gran parte al desarrollo de las tecnologías que potencian su desarrollo, lo cual ha desencadenado en artefactos cada vez más asequibles y con mejores prestaciones, lo que implica el desarrollo de nuevas aplicaciones como agricultura, transporte, monitoreo, fotografía aérea, entre otras. No obstante, los drones se han utilizado también en actos terroristas, violaciones a la privacidad y espionaje, además de haber producido accidentes involuntarios en zonas de alto riesgo de operación como aeropuertos. En respuesta a dichos eventos, aparecen tecnologías que permiten controlar y monitorear el espacio aéreo, con el fin de garantizar la protección en zonas de riesgo. En este artículo se realiza un estudio del estado del arte de la técnicas, métodos y algoritmos basados en video, en análisis de sonido y en radio frecuencia, para tener un punto de partida que permita el desarrollo en el futuro de un sistema de detección de drones, con las tecnologías más propicias, según los requerimientos que puedan ser planteados con las características de escalabilidad, portabilidad, confiabilidad y disponibilidad óptimas.

Biografía del autor/a

Jimmy Flórez, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa Fuerza Aérea Colombiana, Colombia

PhD. in Engineer, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa Fuerza Aérea Colombiana, Comando Aéreo de Combate Número 5, Rionegro- Colombia, jimmy.florez@fac.mil.co

José Ortega, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa Fuerza Aérea Colombiana, Colombia

MSc. in Information and Communication Technologies, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa Fuerza Aérea Colombiana, Comando Aéreo de Combate Número 5, Rionegro - Colombia, jose.ortega@fac.mil.co

Andrés Betancourt, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa, Fuerza Aérea Colombiana, Colombia

Project management specialist, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa, Fuerza Aérea Colombiana, Comando Aéreo de Combate Número 5, Rionegro- Colombia, abetancur.cetad@epfac.co

Andrés García, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa

MSc. in Information and Communication Technologies, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa, Fuerza Aérea Colombiana, Comando Aéreo de Combate Número 5, Rionegro - Colombia, andres.garciares@upb.edu.co

Marlon Bedoya, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa Fuerza Aérea Colombiana, Colombia

Electronic Engineer, Centro de Desarrollo Tecnológico Aeroespacial para la Defensa, Fuerza Aérea Colombiana, Comando Aéreo de Combate Número 5, Rionegro - Colombia, marlon.bedoya@epfac.edu.co

Juan S. Botero*, Instituto Tecnológico Metropolitano, Colombia

PhD. in Electronic Engineer, Grupo Automática, Electrónica y Ciencias Computacionales, Instituto Tecnológico Metropolitano, Medellín- Colombia, juanbotero@itm.edu.co

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Cómo citar
[1]
J. Flórez, J. . Ortega, A. . Betancourt, A. García, M. . Bedoya, y J. S. Botero, «Revisión de algoritmos, métodos y técnicas para la detección de UAVs y UAS en aplicaciones de audio, radiofrecuencia y video», TecnoL., vol. 23, n.º 48, pp. 269–285, may 2020.

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2020-05-15
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