• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.45-52
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• 2001

This paper presents a study on the position tracking control of a robot system on the uncertain elastic base. The elastic bathe is a nonholonomic system but it can be changed into holonomic system, which is much easier to analyze, by modeling an elastic base as a virtual robot that has passive joints. Also, Jacobian operators, which represent the overall robot system including base movement, are defined and applied to the changed model. However, because base movements are not known, the exact Jacobian operators can＇t be estimated. The control algorithm proposed is that uses only Jacobians of a real robot as approximate Jacobian operators. Therefore the approximate Jacobian operators compensate the measured errors from external sensors. The proposed control strategy is evaluated by the simulation and experiment of a single-axis robot system on the elastic base.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.1-7
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• 2011

An attack aircraft such as a fighter needs an accurate location information of a target for the exact air-to-air or air-to-ground attack. In this paper a method is proposed that generates a location information of an air-to-ground target just in use of HMD without the target tracking sensors such as the radar and the FLIR. HMD is an embedded device to induce the seeker header to indicate the direction of a pilot's head. As a simulation result, it is founded that the target location information is able to be generated with a high degree of precision by using of HMD as a passive sensor.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.169-184
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• 2002

In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.6
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• pp.117-126
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• 1994

This paper deals with a robust semi-active control algorithm which is applicable to a semi-active suspension with a multi-state damper. Since the controllable damping rates are discrete in case of a multi-state semi-active damper, the desired damping rate can not be produced exactly even if force-velocity relations of a multi-state semi-active damper is completely known. In addition, damping characteristics of the semi-active dampers are different from damper to damper. A robust nonlinear control law based on sliding control is developed. The main objective of the proposed control strategies is to improve ride quality by tracking the desired active force with a multi-state damper of which the force-velocity relations are "not" completely known. The performance of th proposed semi-active control law is numerically compared to those of the control law based on a bilinear model and a passive suspension. The proposed control algorithm is robust to nonlinear characteristics and uncertainty of the force-Velocity relations of multi-state dampers.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.1-6
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• 2003

It is difficult to detect and to track the moving targets like tanks and diesel vehicles due to the variety of terrain and moving of targets. It is possible to be happened the aliasing conditions as the difficulty of antenna deployment in the complex environment like the battle fields. In this paper, we study the problem of detecting and tracking of moving targets which are emitting wideband signals under severe spatial aliasing conditions because of the sparse arrays. We developed a direction of arrival(DOA) estimation algorithm based on subband MUSIC(Multiple Signal Classification) method which produces high-resolution estimation. In this algorithm, the true bearings are invariant regardless of changes of frequency bands while the aliased false bearings vary. As a result, the proposed algorithm overcomes the aliasing effects and improves the localization performance in sparse passive arrays.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.161-170
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection. especially active shadows resulted from moving vehicles. In this paper a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98(%) in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic information concerning traffic flow is obtained to describe the load of each lane.

• Journal of IKEEE
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• v.26 no.4
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• pp.681-685
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• 2022

Including the COVID-19 crisis, humanity is constantly exposed to viral infections, and efforts are being made to prevent the spread of infection by quickly isolating infected people and tracing contacts. Passive epidemiological investigations that confirm contact with an infected person through contact have limitations in terms of accuracy and speed, so automatic tracking methods using various digital technologies are being proposed. This paper verify contact by utilizing Bluetooth Low Energy (BLE) technology and present an algorithm that identifies close contact through analysis and correction of RSSI (Received Signal Strength Indicator) values. Also, propose a system that can prevent the spread of viruses in a centralized server structure.

• Journal of Radiation Industry
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• v.18 no.3
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• pp.209-215
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• 2024

Radiation work always carries the risk of radiation exposure, so regulatory agencies manage it through licensing when high exposure is expected. However, due to passive management methods using TLD, etc., there are cases where risk management is done after an incident occurs or the incident is covered up. In this study, we developed a system to manage the location of radiation work and the risk of workers in real time through a safety management platform and a location-based personal dosimeter. The safety platform server receives data from the developed personal dosimeter in real time and manages risks in three steps for each worker using location and dose rate, and can predict risks and generate alarms in real time. The personal dosimeter transmits the location and dose rate of the worker in real time using GPS and LTE communication. The developed safety management platform and personal dosimeter were verified through a field test to receive real-time data of the location and dose rate data of the worker, and the risk management function according to the individual dose rate was verified.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.257-268
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• 2023

Sea ice plays an important role in Earth's climate by regulating the amount of solar energy absorbed and controlling the exchange of heat and material across the air-sea interface. Its growth, drift, and melting are monitored on a regular basis by satellite observations. However, low-resolution products with passive microwave radiometer have reduced accuracy during summer to autumn when the ice surface changes rapidly. Synthetic aperture radar (SAR) observations are emerging as a powerful complementary, but previous researches have mainly focused on winter ice. In this study, sea ice drift tracking was evaluated and analyzed using SAR images and tracker with global positioning system (GPS) during late summer-early autumn period when ice surface condition changes a lot. The results showed that observational uncertainty increases compared to winter period, however, the correlation coefficient with GPS measurements was excellent at 0.98, and the performance of the ice tracking algorithm was proportional to the sea ice concentration with a correlation coefficient of 0.59 for ice concentrations above 50%.