• Title/Summary/Keyword: Cueing Data

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A Precise Trajectory Prediction Method for Target Designation Based on Cueing Data in Lower Tier Missile Defense Systems (큐잉 데이터 기반 하층방어 요격체계의 초고속 표적 탐지 방향 지정을 위한 정밀 궤적예측 기법)

  • Lee, Dong-Gwan;Cho, Kil-Seok;Shin, Jin-Hwa;Kim, Ji-Eun;Kwon, Jae-Woo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.4
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    • pp.523-536
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    • 2013
  • A recent air defense missile system is required to have a capability to intercept short-range super-high speed targets such as tactical ballistic missile(TBMs) by performing engagement control efficiently. Since flight time and distance of TBM are very short, the missile defense system should be ready to engage a TBM as soon as it takes an indication of the TBM launch. As a result, it has to predict TBM trajectory accurately with cueing information received from an early warning system, and designate search direction and volume for own radar to detect/track TBM as fast as it can, and also generate necessary engagement information. In addition, it is needed to engage TBM accurately via transmitting tracked TBM position and velocity data to the corresponding intercept missiles. In this paper, we proposed a method to estimate TBM trajectory based on the Kepler's law for the missile system to detect and track TBM using the cueing information received before the TBM arrives the apogee of the ballistic trajectory, and analyzed the bias of prediction error in terms of the transmission period of cueing data between the missile system and the early warning system.

Implementation of the Aural Cueing System of the Reconfigurable Tactical SFTS for the Rotor Aircraft (회전익 항공기용 가변형 전술용 시뮬레이터의 음향 재생 시스템 제작)

  • Hong, Seung-Beom;Choi, Youn-Chul
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.17 no.4
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    • pp.48-54
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    • 2009
  • We implemented the Aural Cueing System(ACS) system of the reconfigurable tactical trainer(RTT) for th rotor aircraft. RTT provides a collective training system to meet aviation training requirements and supports organizational training for aviations units in combined arms collective training and mission rehearsal. ACS handles the volume, pitch and repetition of the digitally stored sounds based on commands it receives from an UDP/IP. In this paper, we explained and implemented the conceptual and detail design the ACS system for the rotor aircraft such as AH-1H(Iroquios), UH-60(Blackhwak), AH-1(Cobra) etc. The conceptual design composed of the sound cueing data analysis, sound modelling which is inner, outer, weapon and warn environment of rotor aircraft, sound synthesis and replay.

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Physical Features for Way-Finding and Orientation in Specialized Dementia Units (치매노인 특별요양시설내의 길찾기와 방향/현실적응을 위한 물리적 특성)

  • 권오정
    • Journal of the Korean Home Economics Association
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    • v.30 no.4
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    • pp.203-217
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    • 1992
  • From the findings of an exploratory study describing the living environments of segregated Alzheimer/Dementia Units (ADUs), the results relative to environmental cueing reatures, reality orientation aids, and communication/noise control methods are highlighted. Data were collected from a nonrandom, purposive sample of 99 ADUs and their parent long term care facilities in 34 states. Specific recommendations are made about physical features that may assist confused and disoriented residents and contribute to way-finding and orientation in specialized dementia units.

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Motion and Structure Estimation Using Fusion of Inertial and Vision Data for Helmet Tracker

  • Heo, Se-Jong;Shin, Ok-Shik;Park, Chan-Gook
    • International Journal of Aeronautical and Space Sciences
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    • v.11 no.1
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    • pp.31-40
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    • 2010
  • For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.