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Beitrag in Sammelwerk/Tagungsband

  • Stefan Kunze
  • Alexander Weinberger

Concept for a Geo-Awareness-System for Civilian Unmanned Aerial Systems

pg. 1-6.

  • (2021)

DOI: 10.1109/RADIOELEKTRONIKA52220.2021.9420196

With the rising number of drones, the lower air space is getting ever more crowded and serious safety issues arise, as long as drone traffic remains unregulated. In this paper conceptional considerations for a geo-awareness system for civilian drones are presented. Hereby, a special focus is laid on those types of drones, which are typically used for recreational purposes by inexperienced pilots.
  • TC Freyung
  • DIGITAL
Vortrag

  • Alexander Weinberger

Einsatz von Software Defined Radio zur Detektion und Analyse von Funksignalen ziviler Drohnen

In: U.T.SEC 2019 - Summit for Drones, Unmanned Technologies & Security

Nürnberg

  • 06.03.2019 (2019)
  • Elektrotechnik und Medientechnik
  • TC Freyung
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Stefan Kunze
  • Alexander Weinberger
  • Rainer Pöschl

A Software Defined Radio Based Implementation for the Radio Frequency Analysis of Signals from Unmanned Aerial Systems

  • (2019)
  • Elektrotechnik und Medientechnik
  • TC Freyung
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Stefan Kunze
  • M. Schiefer
  • Alexander Weinberger

A GNU Radio Imprementation for Frequency Hopping Spread Spectrum Receiver Synchronization

  • (2019)
  • Elektrotechnik und Medientechnik
  • TC Freyung
  • DIGITAL
Vortrag

  • Stefan Kunze
  • Alexander Weinberger
  • Rainer Pöschl

Concept for a Software Defined Radio Based System for Detection, Classification and Analysis of Radio Signals from Civilian Unmanned Aerial Systems

In: the 2nd URSI Atlantic Radio Science Conference (URSI AT-RASC)

Maspalomas, Gran Canaria, Spanien

  • 28.05.-01.06.2018 (2018)
  • TC Freyung
  • Elektrotechnik und Medientechnik
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Stefan Kunze
  • Alexander Weinberger
  • Rainer Pöschl

Concept for a Software Defined Radio Based System for Detection, Classification and Analysis of Radio Signals from Civilian Unmanned Aerial Systems

  • (2018)

DOI: 10.23919/URSI-AT-RASC.2018.8471398

The recent advances in the field of civilian Unmanned Aerial Systems have enabled a wide range of applications and facilitated their wide spread use. However, these systems can also pose a threat to the civilian population. As part of a research project to counter these threats, a Software Defined Radio based system for detection, classification and analysis of radio signals from civilan drones is proposed in this paper. A short look at related work, focusing on the application of machine learning techniques for the classification of radio signals is presented and a concept for the implementation of detection and classification system is proposed.
  • Elektrotechnik und Medientechnik
  • TC Freyung
  • DIGITAL