摘要
针对主被动传感器协同目标跟踪需要,考虑到可扩展性、异构性和动态可重构性等特点,建立了适于不同测量类型和不同测量维数的异构多传感器分散化信息融合算法.以极大化信息融合所得到的信息熵及无人机(UAV,Unmanned Aerial Vehicles)观测信息质量为效能函数,建立了异构多UAV协同目标跟踪的分散化最优控制代价函数以及通信、防撞和控制等约束模型.实现了多UAV协同目标跟踪的分散化模型预测控制,并分析了通讯噪声等因素对分散化信息融合和协同控制的影响.
The decentralized information fusion algorithms for multiple heterogeneous sensors platforms with different types and dimensions was developed to meet the needs of the target tracking with active and passive sensors.The decentralized information fusion algorithm was scalable,heterogeneous and reconfigurable.The performance cost function and constraints model of communication,collision avoiding and control for decentralized optimal control of multiple heterogeneous unmanned aerial vehicles（UAV） in cooperative target tracking were established to maximize the local information entropy obtained by information fusion and the quality of information observed by each UAV.The cooperative target tracking based on multiple heterogeneous UAV was implemented using decentralized model predictive control.The effects of imperfect communication on decentralized information fusion and cooperative control were investigated.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2010年第5期545-549,共5页
Journal of Beijing University of Aeronautics and Astronautics
基金
国家自然科学基金资助项目(60975073)
博士点基金资助项目(20091102110006)
航空科学基金资助项目(2008ZC13011)
关键词
目标跟踪
协同控制
信息融合
模型预测控制
无人机
target tracking
cooperative control
information fusion
model predictive control
unmanned aerial vehicles
