Micro-Doppler-Radar-Based UAV Detection Using Inception-Residual Neural Network

被引：0

作者：

Le, Hai ^{[1
]}

Doan, Van-Sang ^{[2
]}

Le, Dai Phong ^{[1
]}

Nguyen, Huu-Hung ^{[1
]}

Huynh-The, Thien ^{[3
]}

Le-Ha, Khanh ^{[1
]}

Hoang, Van-Phuc ^{[1
]}

机构：

[1] Le Quy Don Tech Univ, 236 Hoang Quoc Viet Str, Hanoi, Vietnam

[2] Vietnam Naval Acad, 30 Tran Phu Str, Nha Trang, Vietnam

[3] Kumoh Natl Inst Technol, Gumi Si, South Korea

来源：

PROCEEDINGS OF 202013TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR COMMUNICATIONS (ATC 2020) | 2020年

关键词：

Neural network; Micro-Doppler radar; Inception-residual neural network; UAV detection; CLASSIFICATION; BIRDS;

D O I：

10.1109/atc50776.2020.9255454

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：

This paper demonstrates the performance evaluation of UAV detection based on micro-Doppler radar image data with the proposed inception-residual neural network (IRNN). Accordingly, the network is designed and analyzed by changing network hyper-parameters through experiment with the Real Doppler RAD-DAR (RDRD) dataset that is collected by the practical measurements. Numerical analysis results show that the proposed network with 16 filters yield a good trade-off between accuracy and time-consuming performances. Moreover, the network is taken into account for competing with three other networks. Due to inception-residual structure, the proposed network remarkably outperforms other ones.

引用

页码：177 / 181

页数：5

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