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Your search keyword '"Shim, Sang-Wook"' showing total 21 results
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21 results on '"Shim, Sang-Wook"'

5. Long-term tactile hypersensitivity after nerve crush injury in mice is characterized by the persistence of intact sensory axons

Author

Kim, Hyoung Woo, primary, Shim, Sang Wook, additional, Zhao, Anna Mae, additional, Roh, Dahee, additional, Han, Hye Min, additional, Middleton, Steven J., additional, Kim, Wheedong, additional, Chung, Sena, additional, Johnson, Errin, additional, Prentice, John, additional, Tacon, Mike, additional, Koel-Simmelink, Marleen J.A., additional, Wieske, Luuk, additional, Teunissen, Charlotte E., additional, Bae, Yong Chul, additional, Bennett, David L.H., additional, Rinaldi, Simon, additional, Davies, Alexander J., additional, and Oh, Seog Bae, additional

Published
2023
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8. Bezier-curve Navigation Guidance for Impact Time and Angle Control

Author

Shim Sang-Wook, Tahk Min-Jea, and Moon Gun-Hee

Subjects
impact time, Control and Systems Engineering, Computer science, Control theory, anti-ship missiles, lcsh:Motor vehicles. Aeronautics. Astronautics, Control (management), Impact time, Aerospace Engineering, Bézier curve, impact angle, lcsh:TL1-4050, Bézier-curve navigation guidance
Abstract

This paper addresses a novel impact time and angle control guidance law using a Bézier curve. The 2nd order Bézier curve consists of one control point and two boundary points; initial point P0, middle point P1 and end point P2. The curve is tangent to the line P0-P1 and the line P1-P2, respectively, and always exists in the convex hull of the control points. Proposed Bézier curve navigation guidance, makes the missile follow the Bézier curve with the feedback form of guidance command so that the missile hits the target on the desired time in the desired direction. We conducted numerical simulations on several terminal conditions to demonstrate the performance of proposed method.

Published
2018

20. Collision avoidance of Smart UAV in multiple intruders.

Author

Yoo, Chang-Sun, Cho, Am, Park, Bum-Jin, Kang, Young-shin, Shim, Sang-Wook, and Lee, Il-Hyung

Abstract

Collision avoidance of UAV is an important function required from pilots and traffic controller as it intends to fly in the airspace of manned aircraft. It is implemented into Smart UAV which the flight test for automatic take-off, conversion and mission flight was conducted successfully last year. Prior to flight test for collision avoidance, the hardware-in-the-loop simulation (HILS) test is conducted in order to verify system operation and avoidance algorithm. Intruders are simulated through virtual aircraft models on the ground and transmitted to digital flight control computer (DFCC). The detection and avoidance algorithm is implemented to the operational flight program (OFP) in DFCC. This paper gives the description for the configuration of collision avoidance system, HILS system and the result for the simulation test in the case of multiple intruders. [ABSTRACT FROM PUBLISHER]

Published
2012

21. Vision-based long-range target detection using coarse-to-fine particle filter.

Author

Shim, Sang-Wook, Won, Dae-Yeon, Tahk, Min-Jea, Seong, Kiejeong, and Kim, Eung-Tai

Subjects
MONTE Carlo method, MATHEMATICAL models, ALGORITHMS, MATHEMATICAL programming, NOISE
Abstract

In this study, we develop a coarse-to-fine particle filter algorithm for track-before-detect in order to track a subpixel-sized, low signal-to-noise ratio target in sensor data. The proposed algorithm enhances tracking performance in the presence of target motion uncertainty and it also maintains the computational load without increasing the number of particles. This coarse-to-fine particle filter, which is newly applied to track-before-detect, has two recursive stages: a coarse stage for extensive searches of the target’s state space and a fine stage that narrows down the tracking results. During the coarse stage, particles are propagated with uniformly distributed noise to compensate for highly nonlinear target motion. The fine stage disturbs the particles filtered from the coarse stage using Gaussian distributed noise. Monte Carlo simulation results using artificial image sequences indicate improved performance with the proposed algorithm when uncertain large frame-to-frame pixel differences are caused by nonlinear target motions such as jittering effects. The algorithm is also applied to the real camera image frames to verify its detecting performance. [ABSTRACT FROM AUTHOR]

Published
2014
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