• Title/Summary/Keyword: Strapdown Image Seeker

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Terminal Homing Guidance of Tactical Missiles with Strapdown Seekers Based on an Unscented Kalman Filter (스트랩다운 탐색기를 장착한 전술유도탄의 UKF 기반 종말호밍 유도)

  • Oh, Seung-Min
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.3
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    • pp.221-227
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    • 2010
  • Recent development in seeker technology explores a new seeker design in which, with larger field-of-view (FOV), optical parts are strapped down to a body (hence, called as a body-fixed seeker or a strapdown seeker). This design has several advantages such as comparatively easier maintenance and calibration by removing complex mechanical moving parts, increasing reliability, and cost savings. On the other hand, the strapdown seeker involves difficulties in implementing guidance laws since it does not directly provide inertial LOS rates. Instead, information for generating guidance commands should be extracted by estimating missile/target relative motion utilizing target images on the image plane of a strapdown seeker. In this research, a new framework based on an unscented Kalman filter is developed for estimating missile/target relative motion on the simplified assumption of a point source target. Performance of a terminal guidance algorithm, in which guidance command is generated based on the estimated relative motion, is demonstrated by a missile/target engagement simulation.

Inertial Sensor Aided Motion Deblurring for Strapdown Image Seekers (관성센서를 이용한 스트랩다운 탐색기 훼손영상 복원기법)

  • Kim, Ki-Seung;Ra, Sung-Woong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.40 no.1
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    • pp.43-48
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    • 2012
  • This paper proposes a practical linear recursive robust motion deblurring filter using the inertial sensor measurements for strapdown image seekers. The angular rate information obtained from the gyro mounted on the missile is used to define the PSF(point spread function). Since the gyro output contains a unknown but bounded bias error. the motion blur image model can be expressed as the linear uncertain system. In consequence, the motion deblurring problem can be cast into the robust Kalman filtering which provides reliable state estimates even in the presence of the parametric uncertainty due to the gyro bias. Through the computer simulations using the actual IR scenes, it is verified that the proposed algorithm guarantees the robust motion deblurring performance.