Deep Model-Based Optimization of Jamming Effectiveness under Aircraft AESA Radar Operational Environments 


Vol. 50,  No. 11, pp. 1647-1659, Nov.  2025
10.7840/kics.2025.50.11.1647


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  Abstract

We propose a deep learning algorithm to find effective jamming parameters in the aircraft AESA radar operational environment, based on a model-based optimization technique called RoMA. To represent a series of measurements obtained under the operational environment as a single number, we design jamming effectiveness by combining ranging failure rate and average range error. Next, we collect a jamming effectiveness dataset for various radar/jammer parameter combinations by repeatedly running the simulation. Our algorithm consists of two stages: the first is to pre-train a neural network that robustly approximates the function from radar/jammer parameters to jamming effectiveness; the second is to estimate the optimal jamming parameters by exploiting our model. As a result, the proposed method improved jamming effectiveness by an average of 41.2% and up to 80.3% compared to random search, and consistently outperformed other baseline models.

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  Cite this article

[IEEE Style]

H. Cho, B. Shin, C. Moon, S. Hong, U. Byoun, J. Sung, C. Yun, "Deep Model-Based Optimization of Jamming Effectiveness under Aircraft AESA Radar Operational Environments," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 11, pp. 1647-1659, 2025. DOI: 10.7840/kics.2025.50.11.1647.

[ACM Style]

Hanseul Cho, Baekrok Shin, Chaewon Moon, Sang-Geun Hong, U-Ju Byoun, Jin-Yong Sung, and Chulhee Yun. 2025. Deep Model-Based Optimization of Jamming Effectiveness under Aircraft AESA Radar Operational Environments. The Journal of Korean Institute of Communications and Information Sciences, 50, 11, (2025), 1647-1659. DOI: 10.7840/kics.2025.50.11.1647.

[KICS Style]

Hanseul Cho, Baekrok Shin, Chaewon Moon, Sang-Geun Hong, U-Ju Byoun, Jin-Yong Sung, Chulhee Yun, "Deep Model-Based Optimization of Jamming Effectiveness under Aircraft AESA Radar Operational Environments," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 11, pp. 1647-1659, 11. 2025. (https://doi.org/10.7840/kics.2025.50.11.1647)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880