摘要
在多平台纯方位信息融合中,存在多平台的方位关联和单平台的参数估计(或目标定位)困难,因为两者相互依赖和制约。造成相对不同平台的方位不能进行时间空间对准、虚假目标不能消除。为此,提出了一种分布式信息融合结构,并建立了相应的数据互联与参数估计联合优化模型。在这种结构和模型中,首先由各平台对本地传感器探测的纯方位信息完成融合并输出方位序列,然后在融合中心按分层节点对方位序列的数据互联与参数估计进行联合优化处理,每个融合节点仅处理两个平台信息,最后节点输出融合结果。仿真计算结果表明,这种优化模型是解决关联和估计问题的一个有效方法,可以提高多平台纯方位信息融合的性能。
For multi-platform bearings-only information fusion(MPBOIF)there are the difficulties of data association(DA)in multi-platform bearings and parameter estimation(PE)(or location)with in single platform bearings,and they are depend on and constrain each other,causing the time and space cannot perform alignment in different platforms and false targets cannot be cleared up.Therefore a distributed information fusion structure(DDIFS)is introduced,by which bearing sequences are outputted after information fusion of every platform,and in fusion center the sequences are used to DA and PE by building a united optimization model(UOM).one UOM deals with only two platforms every time and the fusion results are outputted at the last fusion node.Simulation computation results indicate that the UOM is effective in solving DA and PE problems,and could improve performance of MPBOIF.
作者
李洪瑞
丁迎迎
LI Hong-rui;DING Ying-ying(Jiangsu Automaiion Research Institute,Lianyungang 222061,China)
出处
《火力与指挥控制》
CSCD
北大核心
2019年第7期17-20,26,共5页
Fire Control & Command Control
基金
国防预研基金资助项目(3020102020103)
关键词
纯方位
信息融合
数据关联
参数估计
联合优化模型
bearings-only
information fusion
data association
parameter estimation
united optimization model
