• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.1028-1032
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• 1996

Stabilization performance of a sight stabilization system can be improved by proper selection of control algorithm and mechanism. In that aspect, in this paper, effects of an inertia balancer are studied. Parameters of the inertia balancer were obtained from the governing equation by assuming there is no external force and friction. Simulation and experimental results show that the inertia balancer contributes significantly to the stabilization of the line of sight(LOS). In particular, it was found that the inertia balancer is more effective as frequency of the disturbance increases.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.533-539
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• 2012

The performance analysis of wireless geolocation in a non-line-of-sight (NLOS) environment is a very important issue. Since Cramer-Rao lower bound (CRLB) determines the physical impossibility of the variance of an unbiased estimator being less than the bound, many studies presented the performance analysis in terms of CRLB. Several CRLBs for time-of-arrival (TOA), pseudo-range TOA, angle-of-arrival (AOA), and signal strength (SS) based positioning methods have been derived for NLOS environment. However, the performance analysis of time difference of arrival (TDOA) and TDOA/SS based geolocation techniques in a NLOS environment is still an opening issue. This paper derives the CRLBs of TDOA and TDOA/SS based positioning methods for NLOS environment. In addition, theoretical analysis proves that the derived CRLB for TDOA is the same as that of pseudo-range TOA and the TDOA/SS scheme has a lower CRLB than the TDOA (or SS) scheme.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.3
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• pp.152-156
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• 2010

Non-line-of-sight (NLOS) propagation is one of the challenges in radio positioning. Distinguishing the transmission status of the communication as line-of-sight (LOS) or NLOS is of great importance for the wireless communication systems. This paper focuses on the identification of NLOS based on time-of-arrival (TOA) distance estimates and the received signal strength (RSS) measurements. We set a path loss threshold based on the joint TOA and RSS based NLOS detection method to determine LOS or NLOS. Simulation results show that the proposed method ensures the correct of detection for the LOS condition and can improve the NLOS identification for the weak noise and long distance.

• Journal of electromagnetic engineering and science
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• v.13 no.2
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• pp.86-92
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• 2013

The present paper defines diversity gain for stationary users. This deals in particular with gathering the received signal statistics over possible user positions and orientations in space rather than over time, and to define a meaningful diversity gain related to the cumulative improvement of the performances of the 1% users with the worst receiving conditions. The definition is used to evaluate diversity gain for some typical small antennas in an extreme environment with only line-of-sight (LOS). The LOS environment is regarded as user-distributed 3D-random LOS caused by the statistics of an ensemble of stationary users with arbitrary orientations in the horizontal plane (2D), and with arbitrary orientations of their wireless devices in the vertical plane. Thus, an overall 3D-random distribution of user orientation is assumed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.600-603
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• 2004

UAV (Unmanned Aerial Vehicle) is an aerial vehicle that can accomplish the mission without pilot. UAV was developed for a military purpose such as a reconnaissance in an early stage. Nowadays usage of UAV expands into a various field of civil industry such as a drawing a map, broadcasting, observation of environment. These UAV, need vision system to offer accurate information to person who manages on ground and to control the UAV itself. Especially LOS(Line-of-Sight) system wants to precisely control direction of system which wants to tracking object using vision sensor like an CCD camera, so it is very important in vision system. In this paper, we propose a method to recognize object from image which is acquired from camera mounted on gimbals and offer information of displacement between center of monitor and center of object.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1986-1993
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• 2003

The spatially resolved spray volume fractions from both line-of-sight data of direct measuring cells and a laser diffraction particle analyzer (LDPA) are tomographically reconstructed by the Convolution Fourier transformation, respectively. Asymmetric sprays generated from a twin-hole injector are tested with 12 equiangular projections of measurements. For each projection angle, a line-of-sight integrated injection rate was measured using a direct sampling method and also a liquid volume fraction from a set of line-of-sight Fraunhofer diffraction measurements was measured using a light extinction method. Interpolated data between the projection angles effectively increase the number of projections, significantly enhancing the signal-to-noise level in the reconstructed data. The reconstructed volume fractions from the direct sampling cells were used as reference data for evaluating the accuracy of the volume fractions from the LDPA.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1155-1161
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• 2001

We propose an adaptive nonlinear control algorithm for high precision tracking and stabilization of LOS(Line-of-Sight). The friction parameters of the LOS gimbal are estimated by off-line evolutionary strategy and the friction is compensated by estimated friction compensator. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Lyapunov stability theory, and its convergence is guaranteed under the limited modeling error or torque disturbance. The performance of the pro-posed algorithm is verified by computer simulation on the LOS gimbal model of a moving vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.186-190
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• 2011

The Line-Of-Sight stabilization system is designed to minimize the error of Line-Of-Sight under the disturbing circumstances. In order to control this system more accurately and reduce the level of the disturbance, adding an isolator is mostly considered. However, it is difficult to predict the exact the behavior of the isolator and the effect of a stabilization Error. Therefore, the simulation model of the control system using co-simulation with Adams and matlab simulink is presented and the effects of the isolation properties are reviewed.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.92-100
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• 1999

In the microcell mobile communication, we propose algorithms processing operational disposition to exactly analysis propagation environments from the base station to mobile stations. Algorithms are developed by the triangle analysis method can operate variable propagation paths and reflect numbers. For simulation, we suppose that mobile stations are located in the shadow region of the line of sight and the area of the non-line of sight sloping against the line of sight area at variable angles. By analyzing the results of simulation using proposed algorithms, we can be applied to the optimal position selection of the base station in the microcell mobile communication.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.7
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• pp.72-78
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• 2008

The line-of-sight(LOS) stabilization system is a precision electro-mechanical gimbals assembly for suppressing vibration due to its environment and tracking the target in a desired direction. This paper describes the design of gimbals system to reject the disturbance and to improve stabilization. The controller consists of a DSP with transducer and actuator interfaces. Unknown parameters of the gimbals are estimated by the signal compression method. The cross-correlation coefficient between the impulse response from the assumed model and the one from model of the gimbals is used to obtain the better estimation. The quasi-impulse response through linear element included in the gimbals could be obtained by the signal compression method. The unknown parameter of the linear element could be estimated as comparing the bode plots for impulse response from gimbals with them from model's response.