• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.281-291
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• 2019

Depth from defocus estimates the 3D depth by using a phenomenon in which the object in the focal plane of the camera forms a clear image but the object away from the focal plane produces a blurred image. In this paper, algorithms are studied to estimate 3D depth by analyzing the degree of blur of the image taken with a single camera. The optimized object range was obtained by 3D depth estimation derived from depth from defocus using one image of a single camera or two images of different focus of a single camera. For depth estimation using one image, the best performance was achieved using a focal length of 250 mm for both smartphone and DSLR cameras. The depth estimation using two images showed the best 3D depth estimation range when the focal length was set to 150 mm and 250 mm for smartphone camera images and 200 mm and 300 mm for DSLR camera images.

• Korean Journal of Environment and Ecology
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• v.30 no.2
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• pp.165-172
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• 2016

Mallard and Spot-billed ducks that are typical wintering water birds use the wide rice field in the center of the water system as a wintering ground. I try to figure out the daily movement distance from Home-Range to wintering ground for mallard and spot-billed ducks in Mangyunggang, Dongjingang where located in central region. In 2015 wintering period by using a Cannon-net, I attached WT-300 to 5 mallard and 5 spot-billed ducks. Daily movement distance is an overall average 0.89km, the largest distance was 31.09km. Daily movement distance of mallard was 0.97km, the largest distance was 28.78km. Daily movement distance of Spot-billed ducks was 0.80km, the largest distance was 33.39km. Home-Range analysis is used by the SHP files that is compatible with GIS and ArcGIS 9.0 Animal Movement Extension, it was analyzed using the Minimum Convex Polygon Method (MCP) and the Kernel Density Estimation (KDE). The behavior rights of two kinds of ducks was $490.34km^2$ by Minimum Convex Polygon Method (MCP) ($SD=311.20km^2N=10$), an important habitats Kernel Density Estimation (KDE 50%) was $42.24km^2$. Home-Range of Mallard (MCP) was $568.02km^2$, it is wider than home-range(MCP) of spot-billed duck $397.13km^2$ relatively, the core habitats of mallard is $53.05km^2$, it is wider than mallard's core habitats(KDE 50%) $29.26km^2$ relatively.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.481-485
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• 2014

In service robots, a number of human movements are analyzed using a variety of sensors. Vibration signals from walking movements of a human provide useful information about the distance and the movement direction of the human. In this paper, we measure the intensity of vibrations and detect both human walking pace and direction. In our experiments, vibration signals detected by microphone sensors provide good estimation of the distance and direction of a human movement. This can be applied to HRI (Human-Robot Interaction) technology.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.2
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• pp.51-60
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• 2012

An improved method for detecting fault distance in overhead transmission lines is described in this paper. Based on single-ended measurement, propagation theory of traveling waves together with the wavelet transform technique is used. In estimating fault location, a simple, but fundamental method using the time difference between the two consecutive peaks of transient signals is considered; however, a new method to enhance measurement sensitivity and its accuracy is sought. The algorithm is developed based on the lattice diagram for traveling waves. Representing both the ground mode and alpha mode of traveling waves, in a lattice diagram, several relationships to enhance recognition rate or estimation accuracy for fault location can be found. For various cases with fault types, fault locations, and fault inception angles, fault resistances are examined using the proposed algorithm on a typical transmission line configuration. As a result, it is shown that the proposed system can be used effectively to detect fault distance.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.10
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• pp.956-961
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• 2007

We propose a new distance measurement method and local positioning system for the autonomous mobile robots localization. The distance measurement method is able to measure long-range distances with a high accuracy by using ultrasonic sensors. The time of flight of the ultrasonic waves include various noises is calculated accurately by the proposed period detecting method. The proposed local positioning system is composed of four ultrasonic transmitters and one ultrasonic receiver. The ultrasonic transmitter and receiver are separated but they are synchronized by RF (Radio frequency) signal. The proposed system using ultrasonic waves is represented as USAT(Ultrasonic Satellite System). USAT is able to estimate the position using the least square estimation. The experimental results show that the proposed local positioning system enables to estimate the absolute position precisely.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.5
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• pp.708-716
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• 2017

We deal with the target selection in seeker-detection image through network, using the detection information from aerial vehicle and the target information from surveillance and reconnaissance system. Especially, we constrain the sea battle environment, where it is difficult to perform scene-matching rather than land. In this paper, we suggest the target selection algorithm based on the confidence estimation with respect to distance and size. In detail, we propose the generation method of reference point for distance evaluation, and we investigate the effect of pixel margin and target course for size evaluation. Finally, the proposed algorithm is simulated and analyzed through several scenarios.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.554-557
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• 1993

The error analysis for the Time-in-Flight Laser Range Finder with Multiple Tone Amplitude Modulation relevant to the phase detection error is made. The distance can be estimated to solve the formulate which express the relationship between the absolute distance from the range finder to the object and the wavenumbers and the phases of the modulated waves by the optimization technique. The main cause of the estimation error can be considered as the phase detection error induced from the amplitude modulator and the phase detector. To clarify the phase detection error and the optimal amplitude frequency set, the numerical analysis are made.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.26-31
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• 2001

In order to measure the distance from the bottom in the ocean we use ultrasound altitude sonars. The manganese nodule pick-up device developed by KRISO is also using an altitude sonar to control the gap between the pick-up head and sea bottom. This paper describes the performance of the altitude sonar by an experimental method. The experiment was performed with four ground models in a small basin, Manganese nodule models and water-bentonite mixture was used for setting up the ground models. Buttorworth filter was applied to remove the noise caused by a servo motor and its controller. The results show that the altitude sonar gives a good estimation of the types and slopes of the bottom as well as the distance.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1812_1813
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• 2009

This paper presents an accurate indoor localization method of a mobile robot using ultrasonic sensors. The coordinates of mobile robot are calculated by using trilateration which is using the distance between the transmitter and receiver. At this time, the distances can't be accurately calculated by containing noise. We propose Extended Kalman Filter(EKF) to improve estimation accuracy. The performance of proposed EKF is evaluated by simulation program. As a result, we confirm that the errors in estimate of mobile robot's position are eliminated from measured distance.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.149-167
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• 2005

The minimum disparity estimators introduced by Lindsay and Basu (1994) are studied empirically. An extensive simulation in this paper provides a location estimate of the small sample and supplies empirical evidence of the estimator performance for the univariate contaminated normal model. Empirical results show that the minimum generalized negative exponential disparity estimator (MGNEDE) obtains high efficiency for small sample sizes and dominates the maximum likelihood estimator (MLE) and the minimum blended weight Hellinger distance estimator (MBWHDE) with respect to efficiency at the contaminated model.