Threat evaluation (TE) is essential in battlefield situation awareness and military decision-making. The current processing methods for uncertain information are not effective enough for their excessive subjectivity and difficulty to obtain detailed information about enemy weapons. In order to optimize TE on uncertain information, an approach based on interval Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the interval SD-G1 (SD standard deviation) method is proposed in this article. By interval SD-G1 method, interval number comprehensive weights can be calculated by combining subjective and objective weights. Specifically, the subjective weight is calculated by interval G1 method, which is an extension of G1 method into interval numbers. And the objective weight is calculated by interval SD method, which is an extension of SD method with the mean and SD of the interval array defined in this paper. Sample evaluation results show that with the interval SD-G1 method, weights of target threat attributes can be better calculated, and the approach combining interval TOPSIS and interval SD-G1 can lead to more reasonable results. Additionally, the mean and SD of interval arrays can provide a reference for other fields such as interval analysis and decision-making.

中文翻译：

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具有新区间数综合权重的区间TOPSIS对不确定信息的威胁评价

威胁评估 (TE) 在战场态势感知和军事决策中至关重要。现有的不确定信息处理方法主观性过强，难以获取敌方武器的详细信息，因此效果不佳。为了优化不确定信息上的TE，本文提出了一种基于与理想解相似的区间技术（TOPSIS）和区间SD-G1（SD标准偏差）方法的方法。通过区间SD-G1方法，可以结合主客观权重计算区间数综合权重。具体来说，主观权重采用区间G1法计算，是G1法对区间数的扩展。目标权重采用区间SD法计算，这是SD方法的扩展，具有本文定义的区间数组的均值和SD。样本评价结果表明，区间SD-G1方法可以更好地计算目标威胁属性的权重，区间TOPSIS和区间SD-G1相结合的方法可以得到更合理的结果。此外，区间数组的均值和标准差可以为区间分析和决策等其他领域提供参考。