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12 April 2021 Application of machine learning for drone classification using radars
Sinclair Hudson, Bhashyam Balaji
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Proceedings Volume 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX; 117560C (2021) https://doi.org/10.1117/12.2588694
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
Abstract
Drone classification based on radar return signal is an important task for public safety applications. Determining the make or class of a drone gives information about the potential intent of the UAV. We present a novel method for classifying commercially available drones based on their radar return signal, using a convolutional neural network. Our approach achieves 0.46 mean Average Precision (mAP) on a simulated dataset at 5 dB SNR.
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Sinclair Hudson and Bhashyam Balaji "Application of machine learning for drone classification using radars", Proc. SPIE 11756, Signal Processing, Sensor/Information Fusion, and Target Recognition XXX, 117560C (12 April 2021); https://doi.org/10.1117/12.2588694
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KEYWORDS
Radar
Doppler effect
Fourier transforms
Frequency modulation
Motion analysis
Surveillance
Time-frequency analysis
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