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Volume 38 Issue 5
May  2012
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Journal of Beijing University of Aeronautics and Astronautics  > 2012  >  38(5): 620-624.
Liu Yun, Tang Fagen, Lin Guangyanet al. Robust proximal support vector machine[J]. Journal of Beijing University of Aeronautics and Astronautics, 2007, 33(09): 1090-1093. (in Chinese)
Citation: Liu Xiaoming, Chen Wanchun, Xing Xiaolan, et al. Optical flow/INS multi-sensor information fusion[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(5): 620-624. (in Chinese)
shu

Optical flow/INS multi-sensor information fusion

  • 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

  • Received Date: 26 Jan 2011
  • Publish Date: 30 May 2012
    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.

     

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    • References(13)
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