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光流/惯导多传感器信息融合方法
引用本文:刘小明,陈万春,邢晓岚,殷兴良.光流/惯导多传感器信息融合方法[J].北京航空航天大学学报,2012,38(5):620-624.
作者姓名:刘小明  陈万春  邢晓岚  殷兴良
作者单位:北京航空航天大学宇航学院,北京,100191;空军装备研究院总体所,北京,100076;中国航天科工集团公司,北京,100830
摘    要:将光流传感器多点布置在弹体上,建立了纵向平面内的弹体运动学模型和光流传感器量测模型,利用离散卡尔曼滤波器对光流信息和速率陀螺信息进行融合,估计弹体的高度、姿态和速度信息,并利用估计信息进行了超低空飞行的高度控制仿真,仿真结果表明:利用多个光流传感器和一个速率陀螺,可以准确地、实时地估计出弹体的高度、垂直速度、俯仰角、俯仰角速度和攻角等信息,并可利用这些信息实现导弹的超低空突防任务.

关 键 词:光流  光流传感器  信息融合  卡尔曼滤波器  超低空突防
收稿时间:2011-01-26

Optical flow/INS multi-sensor information fusion
Liu Xiaoming Chen WanchunSchool of Astronautics,Beijing University of Aeronautics and Astronautics,Beijing,China Xing XiaolanSystem Analysis Institute,Air Force Armament Research Academy,Beijing,China Yin Xingliang.Optical flow/INS multi-sensor information fusion[J].Journal of Beijing University of Aeronautics and Astronautics,2012,38(5):620-624.
Authors:Liu Xiaoming Chen WanchunSchool of Astronautics  Beijing University of Aeronautics and Astronautics  Beijing  China Xing XiaolanSystem Analysis Institute  Air Force Armament Research Academy  Beijing  China Yin Xingliang
Institution:1. School of Astronautics, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;2. System Analysis Institute, Air Force Armament Research Academy, Beijing 100076, China;3. China Aerospace Science & Industry Corp, Beijing 100830, China
Abstract:Several optical flow sensors were mounted dispersedly on a missile airframe.The airframe kinematics model in the vertical plane and the optical flow sensor measurement model were established.Discrete-time Kalman filters were used to fuse the optical flow data and rate gyroscope data,and estimate the altitude,attitude and velocity of the airframe.A very-low altitude-holding flight simulation was then implemented based on these estimations.The simulation results indicate that several optical flow sensors and a rate gyroscope can be used to estimate the altitude,vertical velocity,pitching angle,pitching angular velocity and attack angle exactly and real-time.These estimations can help to implement very-low penetration missions.
Keywords:optical flow  optical flow sensor  information fusion  Kalman filter  very-low penetration
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