• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.94-100
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• 2014

In order to intercept anti-ship missiles, it is important to accurately predict the aiming point. The major factor for degrading the accuracy of the aiming point is the motions of the warships due to waves. Therefore, a stage of correcting the aiming point is required to compensate for such motions of warships. The proposed aiming point correction technique treats the changes in positions and velocity of naval guns by considering changes in the positions and velocities of the anti-ship missiles. In this paper, a ship motion estimation filter was also constructed to predict the motions of warships at the firing time of naval guns. In the simulation part, finally, the distance errors before and after aiming point corrections were compared through 6-DOF simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1130-1141
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• 2015

Conventionally, a pulse radar is used for middle-sized or large-sized ships to detect other ships or obstacles located at a long distance. However, it is hardly equipped for most of the small-sized ships due to mounting and maintenance costs. Therefore, FMCW(frequency modulated continuous wave) radar is suggested as an alternative for the small-sized ships. Since it operates with low power and has good range resolution for relatively close objects, it is eligible for the small-sized ships. In previously proposed FMCW radar system, it only estimates distance and velocity of a target ship placed in the direction of main beam and is hard to detect several ships simultaneously. Thus, we suggest the method for detecting several ships at the same time by applying MUSIC(multiple signal classification) algorithm to FMCW radar signal received by a phased array antenna. In addition, by combining digital beam forming with the MUSIC algorithm, better angle resolution is achievable.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.99-106
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• 2005

Instantaneous Frequency(IF) of Doppler signals is used to get the information of relative velocity and miss distance between a missile and the corresponding target. Though Short-Time Fourier Transform(STFT) is mainly used to estimate IF, it has many errors in wide band signals where frequency changes sharply. Because it has a fixed window in time and frequency axes. This paper deals with IF estimation of Doppler signal using a Continuous Wavelet Transform(CWT) which has adaptive window in time and frequency axes. The proposed method is able to estimate IF regardless of frequency changes because it has a narrow window in high frequency band and a wide window in low frequency band. The experimental results demonstrate that the proposed method outperforms STFT in estimating IF.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1062-1070
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• 2015

This paper presents an application of an optimal smoothing filter for moving target tracking problem based on measured noise source. In order to measure distance and velocity for the moving target, a beamforming method is applied to use the noise source by using microphone array. Also a Kalman filter and an optimal smoothing algorithm are adopted to improve accuracy of trajectory estimation by using a Singer target model. The simulation is conducted with a missile dynamics to verify performance of the optimal smoothing filter, and a model rocket is used for experiment environment to compare the trajectory estimation results between the beamforming, the Kalman filter, and the smoother. The Kalman filter results show better tracking performance than the beamforming technique, and the estimation results of the optimal smoother outperform the Kalman filter in terms of trajectory accuracy in the experiment results.

• Journal of Soil and Groundwater Environment
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• v.11 no.6
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• pp.53-60
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• 2006

Single well injection withdrawal tracer tests with bromide were carried out at two wells developed in a horizontally heterogeneous fractured rock. The hydraulic conductivity of TW-1 well was 5 times larger than TW-2 well, and the average linear velocity of TW-2 well was 1.8 times faster than TW-1 well. The difference of hydrodynamic dispersions of two wells in the fractured rock was studied with the analysis of concentration breakthrough curves and cumulative mass recovery curves of bromide with withdrawal time, and the estimation of average travel distance, pore velocity, longitudinal dispersivity and longitudinal dispersion coefficient. The average travel distances of bromide were estimated to be 3.00 m in TW-1 well and 5.62 m in TW-2 well. The average pore velocities for the injection/withdrawal phase were estimated to be $4.31\;{\times}\;10^{-4}\;m/sec$ in TW-1 well and $8.08\;{\times}\;10^{-4}\;m/sec$ in TW-2 well. Average travel distance and pore velocity were higher in TW-2 well because of small effective porosity. Longitudinal dispersivities were estimated to be 28.73 cm in TW-1 well and 18.49 cm in TW-2 well, and bromide transport was 1.55 times faster in TW-1 well. Longitudinal dispersion coefficients were estimated to be $5.14\;{\times}\;10^{-6}\;m^2/sec$ in TW-1 well and $6.06\;{\times}\;10^{-6}\;m^2/sec$ in TW-2 well, and diffusion area was 1.18 times larger in TW-2 well.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.1-8
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• 2016

In this study, an WiFi fingerprinting method based on the k-nn algorithm was applied to improve the accuracy of location tracking of a moving train on a platform and evaluate the performance to minimize the estimation error of location tracking. The data related to the position of the moving train are monitored by the control center for trains and used widely for the safety and comfort of passengers. The train location tracking methods based on WiFi installed by telecom companies were evaluated. In this study, a simulator was developed to consider the environments of two cases; in already installed WiFi devices and new installed WiFi devices. The developed simulator can simulate the localized estimation of the position under a variety of conditions, such as the number of WiFi devices, the area of platform and entry velocity of train. To apply location tracking algorithms, a k-nn algorithm and fuzzy k-nn algorithm were applied selectively according to the underlying condition and also four distance measurement algorithms were applied to compare the error of location tracking. In conclusion, the best method to estimate train location tracking is a combination of the k-nn algorithm and Minkoski distance measurement at a 0.5m grid unit and 8 WiFi AP installed.

• Journal of Navigation and Port Research
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• v.40 no.2
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• pp.83-87
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• 2016

The maritime industry is expanding at an alarming rate hence there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking module designed herein comprises determining existing states of high dynamic target warship, state prediction and state compensation due to random noise. This is achieved by first analyzing the process of tracking followed by design of a tracking algorithm that uses ${\alpha}-{\beta}-{\gamma}$ tracking filter under a random noise. The algorithm involves initializing the state parameters which include position, velocity, acceleration and the course. This is then followed by state prediction at each time interval. A weighted difference of the observed and predicted state values at the $n^{th}$ observation is added to the predicted state to obtain the smoothed (filtered) state. This estimation is subsequently employed to determine the predicted state in the next radar scan. The filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from a pre-determined value of the damping parameter, ${\xi}$. The smoothed, predicted and the observed positions are used to compute the twice distance root mean square (2drms) error as a measure of the ability of the tracking module to manage the noise to acceptable levels.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.313-319
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• 2009

The blasting has a lot of economic efficiency and speediness but it can damage to a neighbor structure, a domestic animal and a cultured fish due to the blasting vibration, then the public grievance is increased. Therefore, we need to manage the blasting vibration efficiently. The prediction of the correct vibration velocity is not easy because there are lots of different kinds of the scale of blasting vibration and it has a number of a variable effect. So we figure the optimum line through the least-squares regression by using the vibration data measured in hard rock blasting and compared with the design vibration prediction equation. As a result, we confirm that the vibration estimated in this paper is bigger than the design vibration prediction equation in the same charge and distance. If there is a Gaussian normal distribution data on the left-right side of the least squares regression, then we can estimate the vibration prediction equation on reliability 50%(${\beta}=0$), 90%(${\beta}=1.28$), 95%(${\beta}=1.64$). 99.9%(${\beta}=3.09$). As a result, it appears to be suitable that the reliability is 99% at the transverse component, the reliability 95% is at the vertical component, the reliability 90% is at the longitudinal component and the reliability is 95% at the peak vector sum component.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.174-180
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• 2015

In this paper, we propose the passive sonar signal processing technique for estimating target information using proximity sensor. This algorithm is performed by single sensor which is constituted underwater sensor network and has a hierarchical structure. The estimated parameter is the velocity, the depth, the distance and bearing at CPA situations and we can improve the accuracy of signal processing techniques through having a hierarchical structure. We verify the performance of the proposed method by computer simulation and then we check the result that 20% error can be occurred in maximum detectable range. We also confirm that proposed method has the reliability in the actual sea environment through the sea experiment.