摘要
针对弹道导弹目标融合识别系统中,传感器接收到的信息具有模糊性与不确定性的特点,提出了一种基于Dempster-Shafer(D-S)理论的导弹目标时空域信息融合模型;针对模型中影响传感器融合识别性能因素的多元性与各因素权重分配的不合理性,在引入证据网路的基础上,提出了一种基于弹道导弹目标影响因素的融合识别性能证据网络结点模型,并通过分析各结点之间的关系,采用多属性决策和群决策分析权重的方法,提出了一种结点权重分配方法。仿真验证了算法的可行性与有效性。
Aiming at the fuzziness and uncertainty of the information received by the sensors in the ballistic missile（ BM） target fusion recognition system,a kind of temporal spatial information fusion model of BM targets based on Dempster Shafer（ D-S） theory is put forward to solve the problem; secondly,the factor which affects the capability of sensor fusion recognition is diverse and the weights of allocation of each factor is unreasonable,based on the evidential network,a kind of fusion recognition performance evidential network nodes model considering influence factors of BM targets is put forward. By analyzing the relationship of those nodes and using the method of multiple attribute decision-making and group decision to analyze the factor weight,a method of assigning node weight is put forward. Finally,simulation shows that this algorithm is of feasibility and validity.
出处
《现代防御技术》
北大核心
2016年第5期52-60,共9页
Modern Defence Technology
关键词
弹道导弹
信息融合
D-S理论
证据网路
多属性决策
群决策
ballistic mission
information fusion
D-S theory
evidential network
multiple attribute decision-making
group decision
