Smart forwarding deceptive jamming distribution optimal algorithm

• Published in: IET radar, sonar & navigation Vol. 18; no. 6; pp. 953 - 964
• Main Authors: Tang, Chengkai, Ding, Jiawei, Qi, Huaiyuan, Zhang, Lingling
• Format: Journal Article
• Language: English
• Published: Wiley 01.06.2024
• Subjects: feedforward neural nets; GNSS jamming; normal distribution; optimisation
• ISSN: 1751-8784; 1751-8792
• DOI: 10.1049/rsn2.12540

With the frequent occurrence of drone black flying in large stadiums and airports, the requirement of precise electromagnetic interference to achieve unmanned aerial vehicle (UAV) displacement and forced landing in these protected area became urgent. Since traditional suppression jamming will affect normal communication, and forwarding deceptive jamming has coverage hole, a smart forwarding deceptive jamming distribution optimal algorithm (SFDJDO) is proposed. It gives a mapping error scale factor and the optimal distribution of multistation forwarding equivalent mapping to solve the problem of distortion on the mapping scale caused by different distribution methods and reduces the influence of the mapping errors and the differences between the virtual and real point neighborhoods of the jamming source. A comparison of the proposed SFDJDO method to the existing jamming source distribution optimisation method is conducted in the aspect of area mapping and trajectory mapping. The findings reveal that when the GNSS receiver clock bias is within the capture range, SFDJDO demonstrates significant enhancements in mapping precision and jamming success rates. The authors have established an interference distribution model based on scale changes. A smart forwarding deceptive jamming distribution optimal algorithm (SFDJDO) is proposed. The authors’ method has significantly improved the success rate of interference. When the target suddenly appears, the authors can quickly implement interference.