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仿猛禽视顶盖信息中转整合的加油目标跟踪 被引量:2

Aerial refueling target tracking using a falcon visual tectum information integrating like method
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摘要 无人机自主空中加油是当前作战模式下非常重要的军事能力之一。空中加油对接阶段的视觉辅助导引是对接阶段导航的研究重点,而加油目标跟踪则是其中的重要一环。本文通过对猛禽优异的视觉系统与视觉导航能力的研究,发现其视觉通路中视顶盖的信息中转整合能力对于解决跟踪问题具有一定指导作用。通过对这一信息处理模式的模拟,研究了一种仿猛禽交叉通路的神经网络,并针对空中加油视觉任务中可能出现的目标丢失与再入问题,引入猛禽双中央凹扩大搜索策略,设计了一种完整的模拟猛禽视顶盖信息中转整合的目标跟踪网络。仿真实验验证了所提方法的可行性和有效性。 Autonomous aerial refueling is one of the most important military capabilities under current combat situation In docking phase navigation,visual-aid guidance during the docking phase is a main research focus,of which the track-ing of refueling target is an important part and challenge.During researching on the excellent visual system and visual navigation ability of falcon,it was found that the information transfer and integration ability of the visual tectum could help to solve the tracking problem.By simulating information processing mode,constructing a neural network with cross-pathway,and introducing the target out of view and reentry problem that may occur in the aerial refueling visual task,the raptor bifovea based searching strategy is introduced to construct a complete tracking method.Simulation and experiments are done to verify the feasibility and effectiveness of the proposed method.
作者 李晗 段海滨 李淑宇 丁希仑 LI Han;DUAN Haibin;LI Shuyu;DING Xilun(School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,China;School of Biological Science and Medical Engineering,Beihang University,Beijing 100083,China;School of Mechanical Engineering and Automation,Beihang University,Beijing 100083,China)
出处 《智能系统学报》 CSCD 北大核心 2019年第6期1084-1091,共8页 CAAI Transactions on Intelligent Systems
基金 国家自然科学基金项目(91648205) 航空科学基金项目(20185851022)
关键词 自主空中加油 猛禽视觉 视顶盖 双凹结构 目标跟踪 神经网络 autonomous aerial refueling falcon visual system tectum bifovea target tracking neural net work
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  • 1李培华,张田文.主动轮廓线模型(蛇模型)综述[J].软件学报,2000,11(6):751-757. 被引量:125
  • 2唐宗湘,马殷华.鸟类视觉系统的离顶盖通路[J].广西师范大学学报(自然科学版),2004,22(4):78-82. 被引量:6
  • 3LI Shan,LEE M C.Fast visual tracking using motion saliency in video[C]//IEEE International Conference on Acoustics,Speech and Signal Processing(ICASSP 2007).Honolulu,USA,2007:1073-1076.
  • 4WREN C R,AZARBAYEJANI A,DARREL L,PENTLAND A P.Pfinder:real-time tracking of the human body[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(7):780-785.
  • 5YUAN Xiaotong,YANG Shutang,ZHU Hongwen.Region tracking via HMMF in joint feature-spatial space[C]//IEEE Workshop on Motion and Video Computing.(WACV/MOTIONS '05).Breckenridge,CO,USA,2005:72-77.
  • 6NICKELS K,HUTCHINSON S.Model-based tracking of complex articulated objects[J].IEEE Transactions on Robotics and Automation,2001,17(1):28-36.
  • 7LIN W C,LIU Yanxi.A lattice-based MRF model for dynamic near-regular texture tracking[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(5):777-792.
  • 8JANG D,CHOI H.Moving object tracking using active models[C]//International Conference on Image Processing(ICIP 98).Chicago,USA,1998:648-652.
  • 9WEN Zhen,HUANG T S.Enhanced 3-D geometric-model-based face tracking in low resolution with appearance model[C]//IEEE International Conference on Image Processing(ICIP 2005).Genoa,Italy,2005:350-353.
  • 10DOCKSTADER S L,TEKALP A M.Multi-view spatial integration and tracking with Bayesian networks[C]//International Conference on Image Processing.Thessaloniki,2001:630-633.

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