Optimum jammer deployment

Date

2025-1

Author

Yiğit, Atakan

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Jamming systems are critical in electronic warfare scenarios aimed at disrupting target communication networks. This thesis develops a comprehensive method for optimizing the placement of jamming systems. A mathematical model is proposed to maximize the Line-of-Sight between systems and target areas while enhancing signal strength at these locations. Additionally, the model aims to minimize the risk of detection by enemy systems. Practical applicability is ensured by incorporating constraints such as geographical accessibility, terrain obstacles, and deployment feasibility into a topological map. The study investigates stationary and mobile jamming systems against both stationary and mobile targets. Furthermore, the thesis study explores power allocation optimization for jamming systems, integrating this process with topological maps to enhance operational effectiveness. The objective is to minimize the likelihood of detection while maximizing jamming performance. Another focus is optimizing jammer placement to disrupt self-localization capabilities in target communication networks. While existing studies address this problem in two-dimensional space, this thesis extends it to three-dimensional scenarios, offering a novel approach to jammer deployment. The findings improve the effectiveness of electronic warfare operations by disrupting enemy communications and providing strategic advantages. The proposed optimization method minimizes jammer usage while ensuring effective coverage and optimizing resource allocation. Comprehensive simulations and constraints provide tools for informed military decision-making and adaptability to dynamic battlefield conditions. This thesis makes significant contributions to academic literature and practical military applications in electronic warfare, combining theoretical innovation with real-world applicability.

Subject Keywords

Jammer placement, Optimization, Line-of-Sight, Power, Signal level

URI

https://hdl.handle.net/11511/113383

Collections

Graduate School of Natural and Applied Sciences, Thesis