| Citation: | YAN J T，LIU S G. Combination weighting based cloud model evaluation of autonomous capability of ground-attack UAV[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（12）：3500-3510 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0072
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To address the uncertainty in quantitative evaluation of autonomous capability of ground-attack UAVs, an evaluation method with the cloud model is proposed based on combined weightings. Based on the cognitive control structure, the evaluation index system of autonomous capability is constructed from five aspects: perceptual detection, planning and decision-making, combat execution, security management, and learning evolution. The one sidedness of determining the index weight by a single weighting method is overcome, using the combination weighting method based on game theory, and combined with the improved analytic hierarchy process and the improved entropy weight method to determine the combination weight. Considering the fuzziness and randomness of the autonomous capability evaluation process, an evaluation method based on cloud model is proposed for the autonomous capability of ground-attack UAVs, and the floating cloud algorithm is used to realize the effective synthesis of the evaluation index cloud. The simulation results of three ground-attack UAVs show that the proposed method considers both subjective and objective factors of the evaluation object, eliminates the limitations of a single weighting method, and achieves scientific and reasonable weight distribution. The quantitative evaluation of autonomous capability of the cloud model can effectively distinguish autonomous capability levels of different types of ground-attack UAVs, with accurate and reliable evaluation results.
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