Contribution to the design of Smart Jamming waveforms for UAVs counter-measurement

被引:0
|
作者
Aouladhadj, Driss [1 ]
Kpre, Ettien [1 ]
de Freitas, Mauro [1 ]
Deniau, Virginie [2 ]
Gransart, Christophe [2 ]
Gaquiere, Christophe [1 ]
机构
[1] MC2 Technol, F-59493 Villeneuve Dascq, France
[2] Univ Gustave Eiffel, COSYS LEOST, IFSTTAR, F-59650 Villeneuve Dascq, France
来源
2022 3RD URSI ATLANTIC AND ASIA PACIFIC RADIO SCIENCE MEETING (AT-AP-RASC) | 2022年
关键词
RF sensing; jamming; UAV; detection; classification; Convolutional Neural Network; confusion matrix;
D O I
暂无
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
In recent years, the fight against unmanned aerial vehicles (UAVs) has become a primary concern due to the ease of obtaining a capable drone and the advent of numerous incidents perpetrated with UAVs flying over public or critical sites. Thus, drone jammers are developed and proposed to law enforcement agencies to counter this type of threat. However, these jamming devices can also affect other communications in the same industrial, scientific and medical (ISM) band. In this context, based on Radio Frequency (RF) sensing, a neutralization strategy is proposed in this paper. This RF analysis aims to recognize the drone type in order to optimize the jamming signal and then reducing the total power required to intercept the drone. This strategy should minimize possible collateral effects on other communications.
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页数:3
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