Convolutional Neural Network Assisted Detection and Localization of UAVs with a Narrowband Multi-site Radar

Martinez J, Kopyto D, Schütz M, Vossiek M (2018)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2018

Publisher: IEEE

Event location: Munich DE

DOI: 10.1109/icmim.2018.8443549

Abstract

We present an approach to detect and locate non-cooperative UAVs from their micro-Doppler signature using a narrowband radar in a multi-site configuration. We describe a method for the localization of rotating objects with the geometric information obtained exclusively from their micro-Doppler signatures. This approach only requires very simple transceivers with CW waveforms, in a cost-effective multi-site architecture. A convolutional neural network is used to detect and identify the UAVs by extracting the characteristic features of their micro-Doppler signature. We present simulated and preliminary experimental data that show the technical viability of this concept.

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How to cite

APA:

Martinez, J., Kopyto, D., Schütz, M., & Vossiek, M. (2018). Convolutional Neural Network Assisted Detection and Localization of UAVs with a Narrowband Multi-site Radar. In Proceedings of the IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM 2018). Munich, DE: IEEE.

MLA:

Martinez, Javier, et al. "Convolutional Neural Network Assisted Detection and Localization of UAVs with a Narrowband Multi-site Radar." Proceedings of the IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM 2018), Munich IEEE, 2018.

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