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Deep Learning Cognitive Radar For Micro UAS Detection and Classification PDF

22 Pages·2020·English
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by ['濱田千寛']| 2020| 22 pages| English

About Deep Learning Cognitive Radar For Micro UAS Detection and Classification

1) The document proposes a deep learning cognitive radar system using a low-complexity binarized deep belief network (DBN) to detect and classify micro unmanned aerial systems (UASs) based on Doppler radar signals. 2) Spectral correlation functions (SCF) are used to characterize features from the radar signals and generate patterns to represent different types of UASs. 3) A binarized DBN classifier is trained on the SCF patterns to automatically detect and identify UASs in real-time. The DBN is formed by stacking restricted Boltzmann machines and uses a softmax output layer.

Detailed Information

Author:['濱田千寛']
Publication Year:2020
Pages:22
Language:English
Format:PDF
Price:FREE
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