• Title/Summary/Keyword: 레이저 관성항법장치

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Study of ARS using Ring Laser Gyro (Ring Laser Gyro를 이용한 ARS에 관한 연구)

  • Jeong, Sang-Ki;Choi, Hyeung-Sik;Ji, Dae-Hyeong;Jung, Dong-Wook;Kwon, O-Soon;Shin, Chang-Joo;Seo, Jung-Min
    • Journal of Ocean Engineering and Technology
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    • v.31 no.2
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    • pp.164-169
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    • 2017
  • Studies were performed on an ARS using SDINS's RLG and the geomatic sensor. To develop the ARS, experiments were performed to determine the characteristics of the RLG and geomatic sensor. Based on the results, to reduce the angular position errors of the RLG, which accumulate from the angular velocity data, an algorithm was studied that uses the Extended Kalman filter (EKF) to compensate the RLG data and geomatic sensor data. To verify the performance of the developed algorithm for reducing the cumulative angular errors, experiments that included the developed EKF were performed. Through these, it was shown that a drastic reduction in the angular errors of the RLG were achieved.

Design of Multi-Sensor Data Processing System for Real-Time Aerial Monitoring (실시간 공중 모니터링을 위한 다중센서 데이터 처리 컴퓨터의 설계)

  • Joe, Hyun-Woo;Lee, Jong-Hyuk;Kim, Hyung-Shin
    • Proceedings of the Korean Information Science Society Conference
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    • 2008.06b
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    • pp.400-404
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    • 2008
  • 무인항공기를 이용한 실시간 공중 모니터링은 재난 재해, 테러 등의 위기상황을 사전에 대비하고, 사고 발생 시 피해상황을 신속하게 파악할 수 있는 효율적인 관리 시스템이다. 실시간 공중 모니터링을 위해 무인항공부문에서는 고성능의 카메라, 관성항법장치, 레이저 스캐너, GPS 수신기 등의 다중 센서들을 장착하고, 제어하며 각 센서들로부터 입력받은 데이터 처리 및 지상국으로 데이터 전송이 실시간으로 가능해야 한다. 기존 무인 모니터링 시스템들은 카메라와 같이 단일 센서의 운용을 목적으로 설계되었으나, 본 연구에서는 레이져 스캐너, 적외선카메라를 포함하는 다중센서를 위한 컴퓨터를 설계하였다. 최근 다중센서를 장착한 관측시스템에 관한 연구가 미국 및 유럽에서 수행되고 있으나, 아직 개발이 완료되지 않은 상태이다. 본 논문에서는 고성능 다중 센서 데이터 처리를 위해 실시간 소프트웨어, 고속 대용량 데이터처리 기술, 고속 압축 기술, 이기종 다중 센서들 간의 시각 동기화 기능을 제공하는 탑재컴퓨터의 설계결과를 소개하였다.

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A Comparison on the Positioning Accuracy from Different Filtering Strategies in IMU/Ranging System (IMU/Range 시스템의 필터링기법별 위치정확도 비교 연구)

  • Kwon, Jay-Hyoun;Lee, Jong-Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.3
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    • pp.263-273
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    • 2008
  • The precision of sensors' position is particularly important in the application of road extraction or digital map generation. In general, the various ranging solution systems such as GPS, Total Station, and Laser Ranger have been employed for the position of the sensor. Basically, the ranging solution system has problems that the signal may be blocked or degraded by various environmental circumstances and has low temporal resolution. To overcome those limitations a IMU/range integrated system could be introduced. In this paper, after pointing out the limitation of extended Kalman filter which has been used for workhorse in navigation and geodetic community, the two sampling based nonlinear filters which are sigma point Kalman filter using nonlinear transformation and carefully chosen sigma points and particle filter using the non-gaussian assumption are implemented and compared with extended Kalman filter in a simulation test. For the ranging solution system, the GPS and Total station was selected and the three levels of IMUs(IMU400C, HG1700, LN100) are chosen for the simulation. For all ranging solution system and IMUs the sampling based nonlinear filter yield improved position result and it is more noticeable that the superiority of nonlinear filter in low temporal resolution such as 5 sec. Therefore, it is recommended to apply non-linear filter to determine the sensor's position with low degree position sensors.