基于异质传感器的空间目标融合识别系统设计  

Design of Fusion Recognition System for Space Objects Based Heterogeneous Sensors

作　　者：刘慧敏[1] 王宏强[1] 黎湘[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院空间电子信息技术研究所,长沙410073

出　　处：《信号处理》2010年第2期203-207,共5页Journal of Signal Processing

基　　金：国家高技术863项目;国防预研项目(No.41303040203)资助

摘　　要：在空间目标识别中有电磁、光度、红外、无线电等多种传感器信息可以利用,不同类型的传感器获得的信息在时域、频域和特征域上的冗余和互补,可以提高识别的正确率,扩展识别的时间和空间覆盖范围,而对于复杂的空间目标识别问题,不可避免的要用到多种分类方法,这些分类器的自动优化组合是融合识别获得良好性能的关键。本文分析了空间目标分布式传感器信息处理系统中的单传感器优缺点,并设计了基于多级增强融合结构的空间目标融合识别方案,给出了其系统级融合的软件设计。该方案能根据不同传感器和分类器的性质自动的对其进行优化组合,充分开发多分类器系统的潜力、提高异质多传感器融合识别的效率和稳健性。There are diverse kinds of sensors can be used for space objects recognition,such as radar,radio,IR sensors and electro-optical sensors.The information acquired by them is redundant and complemental in time domain,frequency domain or characteristic domain.The redundant information can improve the recognition reliability of fusion method and the complemental information can span the time or space range that the objects can be recognized.Various kinds of classifiers are designed to the complex space objects recognition problem,the automatic optimization and assemble of them is the key factor for the good performance of the whole fusion system.In this paper,the traits of each kind of sensors in the distributed heterogeneous sensor information process system are analyzed specially,and then a multilevel enhanced fusion scheme for space objects recognition is brought out to exploit latent abilities of various kinds of classifiers and the software design of systematical level is presented.The scheme assembles different sensors and fusion classifiers automatically so as to exploit the latent abilities of various kinds of classifiers and to improve the efficiency and robustness of the system.

关 键 词：异质多传感器 融合识别 空间目标 多级增强融合 

分 类 号：V19[航空宇航科学与技术—人机与环境工程] TP391.4[自动化与计算机技术—计算机应用技术]