Firefly algorithm-SVM-based on radar threat level identification method

Tao Shen; Lianfeng Wang; Yang Yang

doi:10.1117/12.3025843

6 May 2024 Firefly algorithm-SVM-based on radar threat level identification method

Tao Shen, Lianfeng Wang, Yang Yang

Proceedings Volume 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023); 131610W (2024) https://doi.org/10.1117/12.3025843
Event: Fourth International Conference on Telecommunications, Optics and Computer Science (TOCS 2023), 2023, Xi’an, China

Abstract

In cognitive electronic warfare, the emergence of multifunctional radars with multiple tasks and working modes of search, confirmation, tracking, identification, and guidance has brought great difficulties to defense and jamming. Especially for the jammer, it is very likely that the radar party will fail to fail and expose its own target if it does not know the intention of the radar party. In order to solve the problems of radar behavior intent identification and threat level analysis of the jammer, we propose a radar threat level recognition method based on the improved support vector machine method of the firefly algorithm, which is of great significance to solve the problems of the exposed target that the jammer may cause by the jammer to start the machine, the difficulty in implementing efficient, real-time and effective jamming, and the threat to the security of the protected area. In this paper, the radar threat level analysis problem is modeled as a classification problem, and for the specific problem that the radar information intercepted by the jammer is extremely limited, considering the good accuracy of the support vector machine method in solving the small sample problem, the support vector machine is selected as the classification model and optimized. Finally, the simulation data experiment is given, and the experimental results show that the support vector machine method optimized by the Firefly algorithm shows good accuracy in the radar threat level analysis problem, that is, the proposed method has good accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tao Shen, Lianfeng Wang, and Yang Yang "Firefly algorithm-SVM-based on radar threat level identification method", Proc. SPIE 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023), 131610W (6 May 2024); https://doi.org/10.1117/12.3025843

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KEYWORDS

Radar

Radar signal processing

Mathematical optimization

Detection and tracking algorithms

Support vector machines

Data modeling

Pattern recognition

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