Zhou Ying, Tang Yongchuan, Zhao Xiaozhe
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China.
Entropy (Basel). 2019 May 14;21(5):495. doi: 10.3390/e21050495.
Uncertain information exists in each procedure of an air combat situation assessment. To address this issue, this paper proposes an improved method to address the uncertain information fusion of air combat situation assessment in the Dempster-Shafer evidence theory (DST) framework. A better fusion result regarding the prediction of military intention can be helpful for decision-making in an air combat situation. To obtain a more accurate fusion result of situation assessment, an improved belief entropy (IBE) is applied to preprocess the uncertainty of situation assessment information. Data fusion of assessment information after preprocessing will be based on the classical Dempster's rule of combination. The illustrative example result validates the rationality and the effectiveness of the proposed method.
空战态势评估的每个过程中都存在不确定信息。为解决这一问题，本文提出一种改进方法，以处理Dempster-Shafer证据理论（DST）框架下空战态势评估的不确定信息融合。关于军事意图预测的更好融合结果有助于空战态势下的决策。为获得更准确的态势评估融合结果，应用改进的信度熵（IBE）对态势评估信息的不确定性进行预处理。预处理后的评估信息的数据融合将基于经典的Dempster组合规则。示例结果验证了所提方法的合理性和有效性。
