基于模糊数据融合的空中来袭目标数据处理方法

A data processing method of air attack targets based on fuzzy data fusion

针对舰艇编队远洋作战时空中来袭目标批次多、快速探测不够精准的问题,为克服海量多源模糊不确定信息的影响,首先引入云模型算法,并对其进行适应性改进,基于黄金分割法采用正态云生成算法生成标准云,得出来袭目标数据云的区间隶属度,再利用模糊熵进行改进,得出区间非隶属模糊熵;然后,采用区间毕达哥拉斯模糊集的概念对其进行融合处理,判断来袭目标信息,提出来袭目标识别的置信度,给出最准确的目标识别判断;最后,结合算例对该方法进行了正确性验证。研究结果表明:所提方法可有效提高舰艇编队防御拦截空袭目标群快速处理能力,确保解算数据的可靠性,为编队防空快速识别决策提供了参考依据。

In order to overcome the influence of massive multi-source fuzzy uncertain information,cloud model algorithm was introduced to make adaptive improvement on the cloud model algorithm.Based on the golden section method,normal cloud generation algorithm was adopted to generate standard cloud,and the interval membership degree of the target data cloud was obtained.Using fuzzy entropy for improvement,the interval non-membership fuzzy entropy was obtained.And then,the concept of interval Pythagorean fuzzy set was used for fusion processing to judge the incoming target information,and the confidence of target recognition was proposed to give the most accurate target recognition judgment.Finally,the correctness of the proposed method was verified by an example.The research results show that the method can effectively improve the fast processing ability of ship formation defense and intercept air raid target group,and thus ensure the reliability of the solved data,and provide a reference for the rapid identification and decision of air defense of the formation.