Research on Cooperative Interference Allocation of Jamming Resources Based on Improved Genetic Algorithm

Authors

Zhixia Xu, Rocket Force University of Engineering, Xi'an 710025, China
Rui Wang, Rocket Force University of Engineering, Xi'an 710025, China
Nan Sun, Rocket Force University of Engineering, Xi'an 710025, China
Bing He, Rocket Force University of Engineering, Xi'an 710025, China
Xiaowei Shen, Rocket Force University of Engineering, Xi'an 710025, China
Xiaofei Zhu, Rocket Force University of Engineering, Xi'an 710025, China

Abstract

Abstract: To address the cooperative interference allocation of jamming tasks, a cooperative interference allocation method of jamming resources was proposed based on the improved genetic algorithm. In search and tracking modes of the target radar, a threat level assessment was conducted by the technique for order preference by similarity to an ideal solution (TOPSIS) based on the entropy weight method. The factors affecting the jamming effectiveness of jammers were analyzed. A cooperative interference evaluation model of jamming effectiveness was established, and the allocation model of jamming resources was built with the total interference effectiveness of multiple jammers as the objective function and the interference ability of a single jammer as the constraint condition. The genetic algorithm was improved by incorporating elite preservation operations and applying self-adaptive parameters, and the allocation model of jamming resources was optimized. The simulation results have shown that the improved genetic algorithm has significantly enhanced the operating speed and optimization probability compared with the standard genetic algorithm, effectively solving the cooperative interference allocation of jamming resources.

Recommended Citation

Xu, Zhixia; Wang, Rui; Sun, Nan; He, Bing; Shen, Xiaowei; and Zhu, Xiaofei (2025) "Research on Cooperative Interference Allocation of Jamming Resources Based on Improved Genetic Algorithm," Journal of System Simulation: Vol. 37: Iss. 12, Article 17.
DOI: 10.16182/j.issn1004731x.joss.25-FZ0648
Available at: https://dc-china-simulation.researchcommons.org/journal/vol37/iss12/17

First Page

3176

Last Page

3188

CLC

TP391.9

Recommended Citation

Xu Zhixia, Wang Rui, Sun Nan, et al. Research on Cooperative Interference Allocation of Jamming Resources Based on Improved Genetic Algorithm[J]. Journal of System Simulation, 2025, 37(12): 3176-3188.

Corresponding Author

He Bing

DOI

10.16182/j.issn1004731x.joss.25-FZ0648