Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Experimental Verification of Multi-Sensor Geolocation Algorithm using Sequential Kalman Filter

순차적 칼만 필터를 적용한 다중센서 위치추정 알고리즘 실험적 검증

  • Lee, Seongheon (Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology) ;
  • Kim, Youngjoo (Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology) ;
  • Bang, Hyochoong (Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology)
  • 이성민 (한국과학기술원 항공우주공학과) ;
  • 김영주 (한국과학기술원 항공우주공학과) ;
  • 방효충 (한국과학기술원 항공우주공학과)
  • Received : 2014.08.30
  • Accepted : 2014.09.22
  • Published : 2015.01.01
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Abstract

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

Keywords

References

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