Anti-swarm UAV radar system based on detection data fusion

WANG Pengfei ¹HU Jinfeng ²HU Wen ³WANG Weiguang ⁴DONG Hao⁴

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作者信息

1. School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;China Airborne Missile Academy,Luoyang 471009,China
2. School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;Yangtze Delta Region Institute(Quzhou),University of Electronic Science and Technology of China,Quzhou 324003,China
3. College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
4. Yangtze Delta Region Institute(Quzhou),University of Electronic Science and Technology of China,Quzhou 324003,China
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Abstract

There is a growing body of research on the swarm unmanned aerial vehicle(UAV)in recent years,which has the characteristics of small,low speed,and low height as radar tar-get.To confront the swarm UAV,the design of anti-UAV radar system based on multiple input multiple output(MIMO)is put forward,which can elevate the performance of resolution,angle accuracy,high data rate,and tracking flexibility for swarm UAV detection.Target resolution and detection are the core problem in detecting the swarm UAV.The distinct advantage of MIMO system in angular accuracy measurement is demonstrated by comparing MIMO radar with phased array radar.Since MIMO radar has better performance in resolution,swarm UAV detec-tion still has difficulty in target detection.This paper proposes a multi-mode data fusion algorithm based on deep neural net-works to improve the detection effect.Subsequently,signal pro-cessing and data processing based on the detection fusion algo-rithm above are designed,forming a high resolution detection loop.Several simulations are designed to illustrate the feasibility of the designed system and the proposed algorithm.

Key words

swarm/radar/high resolution/deep neural network/fusion algorithm

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基金项目

Municipal Gavemment of Quzhou(2022D0009)

Municipal Gavemment of Quzhou(2022D013)

Municipal Gavemment of Quzhou(2022D033)

Science and Technology Project of Sichuan Province(2023YFG0176)

出版年

2024

系统工程与电子技术(英文版)

中国航天科工防御技术研究院中国宇航学会中国系统工程学会中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD

影响因子：0.64

ISSN：1004-4132

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