区间不确定性下的空中作战行动过程优选方法

doi:10.7527/S1000-6893.2020.24282

Abstract

Abstract: This paper proposes an optimized selection method for the design of air combat Course of Action (COA) based on Dynamic Influence Nets (DINs) and interval multi-objective optimization according to the theory of DINs and the improved Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ). We first analyzed the basic concepts of air combat COA, established the static and dynamic models separately, and performed a detailed analysis of parameter uncertainty. Then, based on the improved Kendall concordance test method, we determined the key parameters after the consistency test, and designed the DINs probability propagation algorithm. Subsequently, the correlation between the realization probability of desired effects and each key parameter was analyzed, and the improved NSGA-Ⅱ algorithm was used to solve the model after the analysis of the effect evaluation index of COA optimization. Finally, through multiple sets of simulation cases, the rationality of the model and the effectiveness and superiority of the algorithm were verified.

Key words: Course of Action (COA), Dynamic Influence Nets (DINs), improved Non-dominated Sorting Genetic Algorithm II (NSGA-Ⅱ), parameter uncertainty, Kendall concordance test

CLC Number:

ZHONG Yun, WAN Lujun, ZHANG Jieyong. Optimized selection method for air combat course of action with interval uncertainty[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(2): 324282-324282.

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Optimized selection method for air combat course of action with interval uncertainty

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