José Ortega’s scientific contributions

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Publications (2)


Improve decision-making process in Air Command and Control Systems with meteorological data fusion
  • Conference Paper

December 2021

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18 Reads

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5 Citations

Jose Ortega

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Sara Lorduy

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[...]

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Fig. 2. Flying object detections can be filtered by a classifier to reduce the number of false alarms Source: [36].
Fig. 5. Thermal object detection; implementation of an algorithm for object detection using a thermal camera. Source: Created by the authors.
Fig. 6. (a) mmWave Software-Defined Radio (SDR) from NI [63]. (b) mmWave radar kit from Ancortek Source: [64].
A review of algorithms, methods, and techniques for detecting UAVs and UAS using audio, radiofrequency, and video applications
  • Article
  • Full-text available

May 2020

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825 Reads

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31 Citations

TecnoLógicas

Unmanned Aerial Vehicles (UAVs), also known as drones, have had an exponential evolution in recent times due in large part to the development of technologies that enhance the development of these devices. This has resulted in increasingly affordable and better-equipped artifacts, which implies their application in new fields such as agriculture, transport, monitoring, and aerial photography. However, drones have also been used in terrorist acts, privacy violations, and espionage, in addition to involuntary accidents in high-risk zones such as airports. In response to these events, multiple technologies have been introduced to control and monitor the airspace in order to ensure protection in risk areas. This paper is a review of the state of the art of the techniques, methods, and algorithms used in video, radiofrequency, and audio-based applications to detect UAVs and Unmanned Aircraft Systems (UAS). This study can serve as a starting point to develop future drone detection systems with the most convenient technologies that meet certain requirements of optimal scalability, portability, reliability, and availability.

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Citations (2)


... En este contexto, la detección de desviaciones en las características típicas de trayectorias de aeronaves, conocidas como anomalías, pueden comprometer la seguridad de las operaciones aéreas. Las anomalías pueden surgir por diversas causas, como condiciones meteorológicas adversas [1], [2], fallos técnicos o errores humanos. Ayudando también a reducir el impacto medioambiental, al reconocer desviaciones que podrían incrementan el consumo de combustible y las emisiones de gases contaminantes [3]. ...

Reference:

Detección de anomalías en trayectorias de vuelo utilizando autoencodersy segmentación del espacio aéreo basada en regiones de Voronoi
Improve decision-making process in Air Command and Control Systems with meteorological data fusion
  • Citing Conference Paper
  • December 2021

... Thus, effective drone detection is essential for early warning to prevent harmful actions [1,2]. Research methods for drone detection fall into three main categories: radar-based [3][4][5][6], acoustic-based [7,8], and image-based [3, 9, 9-11, 11, 12], with Radio Frequency (RF)-based detection [1,[13][14][15][16][17][18] currently regarded as the most advantageous. RF detection tracks drones by their communication signatures, utilizing algorithms to scan known frequencies regardless of weather or time of day. ...

A review of algorithms, methods, and techniques for detecting UAVs and UAS using audio, radiofrequency, and video applications

TecnoLógicas