Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-27185
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Horn, Claus | - |
dc.contributor.author | Nyfeler, Matthias | - |
dc.contributor.author | Müller, Georg | - |
dc.contributor.author | Schüpbach, Christof | - |
dc.date.accessioned | 2023-03-02T16:49:38Z | - |
dc.date.available | 2023-03-02T16:49:38Z | - |
dc.date.issued | 2022-10-19 | - |
dc.identifier.isbn | 978-84-09-45050-3 | de_CH |
dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/27185 | - |
dc.description.abstract | We develop a multi-timescale deep learning algorithm to detect drones from radio signals. While previous approaches focused on the analysis of high-frequency radio data alone we integrate signals from the higher timescale of the drone communication protocol in an end-to-end architecture. To this end, we develop a new meta-CNN layer, which generalizes the idea of the standard CNN (which slides a single, fully connected kernel along a higher-level input) towards arbitrarily complex kernel models. To detect higher timescale patterns our system uses an LSTM layer in the top layers. As a result, our model is able to extend drone identification abilities significantly toward very small SNRs. | de_CH |
dc.language.iso | en | de_CH |
dc.publisher | IFSA Publishing | de_CH |
dc.rights | Not specified | de_CH |
dc.subject | Drone signal detection | de_CH |
dc.subject | Deep learning | de_CH |
dc.subject | Multi-timescale modeling | de_CH |
dc.subject.ddc | 629: Luftfahrt- und Fahrzeugtechnik | de_CH |
dc.title | Drone radio signal detection with multi-timescale deep neural networks | de_CH |
dc.type | Konferenz: Paper | de_CH |
dcterms.type | Text | de_CH |
zhaw.departement | Life Sciences und Facility Management | de_CH |
zhaw.organisationalunit | Institut für Computational Life Sciences (ICLS) | de_CH |
dc.identifier.doi | 10.21256/zhaw-27185 | - |
zhaw.conference.details | 4th International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI), Corfu, Greece, 19-21 October 2022 | de_CH |
zhaw.funding.eu | No | de_CH |
zhaw.originated.zhaw | Yes | de_CH |
zhaw.pages.end | 143 | de_CH |
zhaw.pages.start | 140 | de_CH |
zhaw.parentwork.editor | Yurish, Sergey Y. | - |
zhaw.publication.status | acceptedVersion | de_CH |
zhaw.publication.review | Editorial review | de_CH |
zhaw.title.proceedings | Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence | de_CH |
zhaw.webfeed | Bio-Inspired Modelling and Learning Systems | de_CH |
zhaw.funding.zhaw | Drohnenalarm | de_CH |
zhaw.author.additional | No | de_CH |
zhaw.display.portrait | Yes | de_CH |
Appears in collections: | Publikationen Life Sciences und Facility Management |
Files in This Item:
File | Description | Size | Format | |
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2022_Horn-etal_Drone-radio-signal-detection_ASPAI-fullpaper.pdf | Accepted Version | 303.23 kB | Adobe PDF | ![]() View/Open |
Show simple item record
Horn, C., Nyfeler, M., Müller, G., & Schüpbach, C. (2022). Drone radio signal detection with multi-timescale deep neural networks [Conference paper]. In S. Y. Yurish (Ed.), Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence (pp. 140–143). IFSA Publishing. https://doi.org/10.21256/zhaw-27185
Horn, C. et al. (2022) ‘Drone radio signal detection with multi-timescale deep neural networks’, in S.Y. Yurish (ed.) Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence. IFSA Publishing, pp. 140–143. Available at: https://doi.org/10.21256/zhaw-27185.
C. Horn, M. Nyfeler, G. Müller, and C. Schüpbach, “Drone radio signal detection with multi-timescale deep neural networks,” in Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence, Oct. 2022, pp. 140–143. doi: 10.21256/zhaw-27185.
HORN, Claus, Matthias NYFELER, Georg MÜLLER und Christof SCHÜPBACH, 2022. Drone radio signal detection with multi-timescale deep neural networks. In: Sergey Y. YURISH (Hrsg.), Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence. Conference paper. IFSA Publishing. 19 Oktober 2022. S. 140–143. ISBN 978-84-09-45050-3
Horn, Claus, Matthias Nyfeler, Georg Müller, and Christof Schüpbach. 2022. “Drone Radio Signal Detection with Multi-Timescale Deep Neural Networks.” Conference paper. In Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence, edited by Sergey Y. Yurish, 140–43. IFSA Publishing. https://doi.org/10.21256/zhaw-27185.
Horn, Claus, et al. “Drone Radio Signal Detection with Multi-Timescale Deep Neural Networks.” Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence, edited by Sergey Y. Yurish, IFSA Publishing, 2022, pp. 140–43, https://doi.org/10.21256/zhaw-27185.
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