SNR‐dependent drone classification using convolutional neural networks

SNR‐dependent drone classification using convolutional neural networks

Abstract Radar sensing offers a method of achieving 24‐h all‐weather drone surveillance, but in order to be maximally effective, systems need to be able to discriminate between birds and drones. This work examines drone‐bird classification performance as a function of signal to noise ratio (SNR). Cl...

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Bibliographic Details
Main Authors: Holly Dale, Chris Baker, Michail Antoniou, Mohammed Jahangir, George Atkinson, Stephen Harman
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:IET Radar, Sonar & Navigation
Subjects:
optimisation
signal classification
radar signal processing
radar cross‐sections
Bayes methods
Gaussian noise
Online Access:https://doi.org/10.1049/rsn2.12161

Internet

https://doi.org/10.1049/rsn2.12161

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