Unmanned Aircraft Selection for Electronic Warfare: A Combined Multicriteria Decision Analysis Approach

This study demonstrates the utility of combining different methods of Multicriteria Decision Analysis (MCDA) for selecting Unmanned Aircraft (UA) in Electronic Warfare (EW) applications. We begin by emphasizing the significance of EW in military operations and the critical importance of choosing the most suitable UAs for this dynamic arena. Our primary goal is to identify the optimal UA among various options, meticulously considering distinct EW criteria. We implement three MCDA techniques: the Analytic Hierarchy Process (AHP), AHP-Gaussian, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Notably, these methods consistently converge in favor of Alternative 4, substantiating the robustness and minimizing subjective bias. These findings hold profound implications for strategic decision-making within EW operations and offer a sturdy framework for UA selection. This study not only advances the understanding of UA selection within EW but also underscores MCDA's enduring value as a potent tool for guiding strategic choices. We anticipate that this work will inspire future research in UA selection, including the exploration of more intricate aircraft and the optimization of EW capabilities through sensor allocation and radiation-absorbing materials. Effective UA integration into EW is pivotal for modern military success, and our research provides a comprehensive roadmap to achieve this objective.