• Title/Summary/Keyword: Spotlight Mode

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Modified WLS Autofocus Algorithm for a Spotlight Mode SAR Image Formation (스포트라이트 모드 SAR 영상 형성에서의 수정된 가중치 최소 자승기법에 의한 자동 초점 알고리즘)

  • Hwang, Jeonghun;Shin, Hyun-Ik;Kim, Whan-Woo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.28 no.11
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    • pp.894-901
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    • 2017
  • In the existence of motion, azimuth phase error due to accuracy limitation of GPS/IMU and system delay is unavoidable and it is essential to apply autofocus to estimate and compensate the azimuth phase error. In this paper, autofocus algorithm using MWLS(Modified WLS) is proposed. It shows the robust performance compared with original WLS using new target selection/sorting metric and iterative azimuth phase estimation technique. SAR raw data obtained in a captive flight test is used to validate the performance of the proposed algorithm.

Development of Ring Right for Medical Purpose (메디컬 링 라이트의 개발)

  • Cheon, Min-Woo;Park, Yong-Pil
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.766-767
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    • 2010
  • By using LED which is a light source which has been in the spotlight recently, the ring light for medical purposes was developed for shadowless shooting of local site in the affected area. The developed ring light was designed to be able to control the various quantity of light by using PWM (pulse width modulation) method, and by controlling each LED (light emitting diode) independently the regulation of color temperature and color rendering are possible. Also, the persistent light for continuous shooting of affected area and flash mode action for snap shooting are possible. In this study the response speed of momentary flash function was checked using interface circuit configured for momentary shadowless shooting of affected area.

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Development of AI-Based Condition Monitoring System for Failure Diagnosis of Excavator's Travel Device (굴착기 주행디바이스의 고장 진단을 위한 AI기반 상태 모니터링 시스템 개발)

  • Baek, Hee Seung;Shin, Jong Ho;Kim, Seong Joon
    • Journal of Drive and Control
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    • v.18 no.1
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    • pp.24-30
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    • 2021
  • There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

Analysis of SAR Image Quality Degradation due to Pointing and Stability Error of Synthetic Aperture Radar Satellite (위성체 지향 및 안정화 오차로 인한 영상레이더 위성 영상 품질 저하 해석)

  • Chun, Yong-Sik;Ra, Sung-Woong
    • Journal of Astronomy and Space Sciences
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    • v.25 no.4
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    • pp.445-458
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    • 2008
  • Image chain analysis of synthetic aperture radar (SAR) satellite is one of the primary activities for satellite design because SAR image quality depends on spacecraft bus performance as well as SAR payload. Especially, satellite pointing and stability error make worst effect on the original SAR image quality which is implemented by SAR payload design. In this research, Image chain analysis S/W was developed in order to analyze the SAR image quality degradation due to satellite pointing and stability error. This S/W consists of orbit model, attitude control model, SAR payload model, clutter model, and SAR processor. SAR raw data, which includes total 25 point targets in the scene of $5km{\times}5km$ swath width, was generated and then processed for analysis. High resolution mode (spotlight), of which resolution is 1m, was applied. The results of image chain analysis show that radiometric accuracy is the most degraded due to the pointing error. Therefore, the successful design of attitude control subsystem in spacecraft bus for enhancing the pointing accuracy is most important for image quality.

Urban Area Building Reconstruction Using High Resolution SAR Image (고해상도 SAR 영상을 이용한 도심지 건물 재구성)

  • Kang, Ah-Reum;Lee, Seung-Kuk;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.29 no.4
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    • pp.361-373
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    • 2013
  • The monitoring of urban area, target detection and building reconstruction have been actively studied and investigated since high resolution X-band SAR images could be acquired by airborne and/or satellite SAR systems. This paper describes an efficient approach to reconstruct artificial structures (e.g. apartment, building and house) in urban area using high resolution X-band SAR images. Building footprint was first extracted from 1:25,000 digital topographic map and then a corner line of building was detected by an automatic detecting algorithm. With SAR amplitude images, an initial building height was calculated by the length of layover estimated using KS-test (Kolmogorov-Smirnov test) from the corner line. The interferometric SAR phases were simulated depending on SAR geometry and changable building heights ranging from -10 m to +10 m of the initial building height. With an interferogram from real SAR data set, the simulation results were compared using the method of the phase consistency. One of results can be finally defined as the reconstructed building height. The developed algorithm was applied to repeat-pass TerraSAR-X spotlight mode data set over an apartment complex in Daejeon city, Korea. The final building heights were validated against reference heights extracted from LiDAR DSM, with an RMSE (Root Mean Square Error) of about 1~2m.