| Summary: | 碩士 === 國防管理學院 === 國防資訊研究所 === 96 === In recent years, with the development of new technologies of microelectronics, computers, artificial intelligence, automatic driving, signal processing etc. as well as the successful invention of various small electronic warfare equipment, UAVs（Unmanned Aerial Vehicles）have developed into electronic warfare platforms with multiple functions of conducting electronic warfare reconnaissance, electronic jamming, anti-radiation attack etc. Furthermore, there have been conspicuous development and application of UAVs in the field of national defense. All of these show a tendency of UAVs’ more vital importance in the scientific and technological development in the future.
The TUAV（Tactical Unmanned Aerial Vehicle）is a type of UAV, which with the development of technologies, will be largely used because of its high mobility, low risk, low cost and capability of meeting an operational thinking of “zero casualty” if considering the war pattern in the future. The assignment of task targets is a significant issue in terms of synergetic control and autonomy of multiple UAV system. It is a crucial part of the task scheme research for the task orientation in the air defense operational command system. In this thesis, we analyze the target assignment of automatic command system and set up patterns of target assignment for various air attack situations. The task is to bring into the advantages of each TUAV, to look for the best schemes conforming to assignment principles by applying the optimization principle under designated conditions and restrictions, to gain the best distribution of firepower resources under a limited offer, to bring into the efficiency of weapon systems, and to gain the best overall benefits.
We select the multiple-TUAV assignment process to analyze the model which is computed based on the genetic algorithm, and get the optimal multiple-TUAV target assignment solution against the multiple targets scenario. The results demonstrate that the algorithm can converge to the ideal steady state with high speed and provide us several optimal solutions by utilizing the toolbox of MATLAB in a fixed timeframe.
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