Drone Elevation Angle Classification Based on Convolutional Neural Network With Micro-Doppler of Multipolarization

Multipolarizations of micro-Doppler signature (MDS) were combined to classify the elevation angle of a drone by a convolutional neural network (CNN). We classified the drone's elevation angle based on the MDS, which depends on the elevation angle of the drone. To enhance the classification accu...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Main Authors: Kang, Hyunseong, Kim, Byung Kwan, Park, Jun-Sung, Suh, Jun-Seuk, Park, Seong-Ook
Format: Article
Language:English
Subjects:
Airborne radar
Algorithms
Artificial neural networks
Circular polarization
Classification
Convolutional neural network (CNN)
Doppler sonar
drone-angle classification
Drones
Elevation angle
Handedness
Horizontal polarization
micro-Doppler
multichannel radar system
multipolarization
Neural networks
Polarization
Propellers
Radar
Radar cross-sections
Radar data
Synchronization
Training
Vertical polarization
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Summary:Multipolarizations of micro-Doppler signature (MDS) were combined to classify the elevation angle of a drone by a convolutional neural network (CNN). We classified the drone's elevation angle based on the MDS, which depends on the elevation angle of the drone. To enhance the classification accuracy, we utilized micro-Doppler from multiple polarized radar signals. We utilized and analyzed four different polarizations for the receiver, namely, vertical/horizontal/right-handed circular polarization (RHCP)/left-handed circular polarization (LHCP), while the polarization for the transmitter was vertical. The four receivers with different polarizations were fully synchronized with Tx for accurate MDS measurement for each polarization. The radar data received from the multiple polarizations were combined for the classification algorithm based on CNN. The classification rate of the elevation angles of a drone was improved from 84.745% to 97.9% compared to a single polarization by using multiple polarizations.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2020.3030113