Application of Machine Learning for Drone Classification using Radars

被引：6

作者：

Hudson, Sinclair ^{[1
]}

Balaji, Bhashyam ^{[2
]}

机构：

[1] Univ Waterloo, 200 Univ Ave W, Waterloo, ON, Canada

[2] Def RD Canada, Radar Sensing & Exploitat Sect, Ottawa Res Ctr, 3701 Carling Ave, Ottawa, ON K1A 0Z4, Canada

来源：

SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXX | 2021年 / 11756卷

关键词：

Drone Classification; RADAR; Convolutional Neural Networks;

D O I：

10.1117/12.2588694

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页数：13

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