基于Trans-Attention的飞行区航空器监视数据融合方法  

Aircraft surveillance data fusion method in flight area based on Trans-Attention

作　　者：王兴隆[1] 尹昊 丁俊峰 WANG Xinglong;YIN Hao;DING Junfeng(Key Laboratory of Internet of Aircrafts,Civil Aviation University of China,Tianjin 300300,China;Nanjing Les Information Technology Co.,Ltd.,Nanjing 210001,China)

机构地区：[1]中国民航大学飞联网重点实验室,天津300300 [2]南京莱斯信息技术股份有限公司,南京210001

出　　处：《北京航空航天大学学报》2025年第4期1215-1223,共9页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国家自然科学基金面上项目(62173332);国家自然科学基金重点项目(U2133207);天津多元基金项目(21JCYBJCO0700);中国民航大学校级研究生科研创新项目(2022YJS086)。

摘　　要：针对飞行区航空器单一监视源存在监视精度低、位置跳变的问题,提出一种基于Transformer和注意力机制的航空器监视数据融合方法。利用Transformer的编码器结构分别对各监视源数据进行特征提取,通过注意力机制对不同监视源赋予权重值,经过全连接网络进行回归计算,获得最终的融合结果。选取场面监视雷达(SMR)和广播式自动相关监视(ADS-B)系统的监视数据作为融合源,多点定位(MLAT)数据作为真实标签,实验结果表明:所提方法有效降低了单一监视源的监视误差,且融合效果优于基于注意力机制的长短期记忆网络、循环神经网络和扩展卡尔曼滤波融合方法,平均绝对误差分别提升了2.81%、16.73%和35.80%。An aircraft surveillance data fusion method based on a Transformer and attention mechanism is proposed to address the issues of low monitoring accuracy and position jump in a single surveillance source for aircraft in the flight area.Prior to assigning weight values to various surveillance sources via the attention mechanism,features are first extracted from each surveillance source data using the Transformer’s encoder structure.Finally,regression calculations are performed through a fully connected network to obtain the final fusion result.The multilateration(MLAT)data are employed as actual tags,while the surveillance data from the autonomous dependent surveillance-broadcast(ADS-B)system and the surface movement radar(SMR)are chosen as fusion sources.The experimental results show that the proposed method effectively reduces the surveillance error of a single surveillance source,and the fusion effect is better than that of the long short-term memory network based on the attention mechanism,recurrent neural network,and extended Kalman filter fusion methods.The mean absolute error is increased by 2.81%,16.73%and 35.80%respectively.

关 键 词：数据融合 TRANSFORMER 注意力机制 场面监视雷达 广播式自动相关监视 

分 类 号：V351[航空宇航科学与技术—人机与环境工程]