【作者】 刘建国； 邓鹤； 温同鑫；

【Author】 Jianguo Liu,He Deng,Tongxin Wen (State Lab for Multispectral Information Technique,Institute for Pattern Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074,People’s Republic of China)

【机构】 华中科技大学图像识别与人工智能研究所、多谱信息处理技术国家重点实验室；

【摘要】 现有导航方法都存在一定的不足,开发和研究其它新的导航方法,尤其是借鉴生物视觉机理的导航方法,是未来导航技术研究的重点和趋势。本文在深入研究蜜蜂视觉机理的基础上,根据物理学中熵的概念,提出了一种基于蜜蜂视觉机理的图像熵及图像熵流概念。同时在所提出的熵及熵流概念基础上,提出和建立了一种新的结合Kalman滤波器导航算法。仿真实验结果表明,该算法能够实时校正导弹在三维空间中的飞行轨迹,在降低导弹硬件成本同时也能达到其导航精度要求,为导弹的导航系统研究提供了一个可行的研究方案。更多还原

【Abstract】 Based on the in-depth study of the visual navigation mechanism of flying insects,especially on honeybees,we have proposed a novel navigation algorithm.New concepts of entropy map and entropy flow are presented,which can characterize topographic features and measure changes of the image respectively.And a six-parameter affme motion model to estimate the exterior parameters of the camera is also presented,according to the above two concepts.The new navigation algorithm is based on the entropy flow and Kalman filter.The simulation results show that it can perform excellent and real-time corrections for the missile’s flight path in the three-dimensional space,and meanwhile reduce the cost of the missile’s hardware.更多还原