Fan Chengli, Fu Qiang, Song Yafei, Lu Yingqi, Li Wei, Zhu Xiaowen
Air Defense and Antimissile College, Air Force Engineering University, Xi'an 710051, China.
Entropy (Basel). 2022 Dec 14;24(12):1825. doi: 10.3390/e24121825.
Existing missile defense target threat assessment methods ignore the target timing and battlefield changes, leading to low assessment accuracy. In order to overcome this problem, a dynamic multi-time fusion target threat assessment method is proposed. In this method, a new interval valued intuitionistic fuzzy weighted averaging operator is proposed to effectively aggregate multi-source uncertain information; an interval-valued intuitionistic fuzzy entropy based on a cosine function (IVIFECF) is designed to determine the target attribute weight; an improved interval-valued intuitionistic fuzzy number distance measurement model is constructed to improve the discrimination of assessment results. Specifically, first of all, we define new interval-valued intuitionistic fuzzy operation rules based on algebraic operations. We use these rules to provide a new model of interval-valued intuitionistic fuzzy weighted arithmetic averaging (IVIFWAA) and geometric averaging (IVIFWGA) operators, and prove a number of algebraic properties of these operators. Then, considering the subjective and objective weights of the incoming target, a comprehensive weight model of target attributes based on IVIFECF is proposed, and the Poisson distribution method is used to solve the time series weights to process multi-time situation information. On this basis, the IVIFWAA and IVIFWGA operators are used to aggregate the decision information from multiple times and multiple decision makers. Finally, based on the improved TOPSIS method, the interval-valued intuitionistic fuzzy numbers are ordered, and the weighted multi-time fusion target threat assessment result is obtained. Simulation results of comparison show that the proposed method can effectively improve the reliability and accuracy of target threat assessment in missile defense.
现有的导弹防御目标威胁评估方法忽略了目标的时效性和战场变化，导致评估准确率较低。为克服这一问题，提出一种动态多时刻融合目标威胁评估方法。该方法中，提出一种新的区间值直觉模糊加权平均算子，以有效聚合多源不确定信息；设计一种基于余弦函数的区间值直觉模糊熵（IVIFECF）来确定目标属性权重；构建一种改进的区间值直觉模糊数距离度量模型，以提高评估结果的区分度。具体而言，首先基于代数运算定义新的区间值直觉模糊运算规则。利用这些规则给出区间值直觉模糊加权算术平均（IVIFWAA）和几何平均（IVIFWGA）算子的新模型，并证明这些算子的若干代数性质。然后，考虑来袭目标的主客观权重，提出一种基于IVIFECF的目标属性综合权重模型，采用泊松分布方法求解时间序列权重，以处理多时刻态势信息。在此基础上，利用IVIFWAA和IVIFWGA算子聚合来自多个时刻和多个决策者的决策信息。最后，基于改进的TOPSIS方法对区间值直觉模糊数进行排序，得到加权多时刻融合目标威胁评估结果。对比仿真结果表明，所提方法能有效提高导弹防御中目标威胁评估的可靠性和准确率。
