Anti-swarm UAV radar system based on detection data fusion

doi:10.23919/JSEE.2023.000077

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (5): 1167-1176.doi: 10.23919/JSEE.2023.000077

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Anti-swarm UAV radar system based on detection data fusion

Pengfei WANG¹^,²^,*(), Jinfeng HU¹^,³(), Wen HU⁴(), Weiguang WANG³(), Hao DONG³()

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

Received:2023-01-29 Accepted:2023-05-09 Online:2024-10-18 Published:2024-11-06
Contact: Pengfei WANG E-mail:66540555@qq.com;hujf@uestc.edu.cn;huwen@nuaa.edu.cn;13813018269@163.com;17351380098@nuaa.edu.cn
About author:
WANG Pengfei was born in 1982. He received his B.S. degree from Tianjin University in computer science and technology. He is a professor in China Airborne Missile Academy. His research interest is radar signal processing. E-mail: 66540555@qq.com

HU Jinfeng was born in 1976. He received his Ph.D. degree from University of Electronic Science and Technology in signal and information processing. He is a professor in University of Electronic Science and Technology of China. His research interest is radar signal processing. E-mail: hujf@uestc.edu.cn

HU Wen was born in 1979. He received his Ph.D. degree from Nanjing University of Science and Technology in communications engineering. He is a professor in Nanjing University of Aeronautics and Astronautics. His research interests is communications engineering. E-mail: huwen@nuaa.edu.cn

WANG Weiguang was born in 1994. He received his M.S. degree from Nanjing University of Aeronautics and Astronautics in communication and information systems. His research interest is signal and data processing. E-mail: 13813018269@163.com

DONG Hao was born in 1998. He received his M.S. degree from Nanjing University of Aeronautics and Astronautics, in communications engineering. His research interest is signal and data processing. E-mail: 17351380098@nuaa.edu.cn
Supported by:
This work was supported by the Municipal Gavemment of Quzhou (2022D0009;2022D013;2022D033) and the Science and Technology Project of Sichuan Province (2023YFG0176)

Abstract

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 target. 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 detection still has difficulty in target detection. This paper proposes a multi-mode data fusion algorithm based on deep neural networks to improve the detection effect. Subsequently, signal processing and data processing based on the detection fusion algorithm 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

Pengfei WANG, Jinfeng HU, Wen HU, Weiguang WANG, Hao DONG. Anti-swarm UAV radar system based on detection data fusion[J]. Journal of Systems Engineering and Electronics, 2024, 35(5): 1167-1176.

Figures/Tables 15

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Anti-swarm UAV radar system based on detection data fusion

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