• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.113-118
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• 2009

In this paper, we described the model of noise, target for tracking radar and range tracking, angle tracking, and Doppler frequency tracking for target acquisition and tracking. Target signal as well as the noise signal is modeled as random process varying with elapsed time. This paper addresses three areas of radar target tracking: range tracking, angle tracking, and Doppler frequency tracking. In general, range tracking is prerequisite to and inherent in both angle and Doppler frequency tracking systems. First, we introduced the several range tracking and described techniques for achieving range tracking. Second, we described the radar angle tracking techniques including conical scan, sequential lobing, and monopulse. Finally, we presented concepts and techniques for Doppler frequency tracking for several radar types.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.388-396
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• 2011

Sun tracking system is the most important subsystem in parabolic dish type solar thermal power plant, since it determines the amount of thermal energy to be collected, thus affects the efficiency of solar thermal power plant most significantly. Various types of sun tracking systems are currently used. Among them, use of photo sensors to located the sun(which is called sensor type) and use of astronomical algorithm to compute the sun position(which is called program type) are two of the mostly used methods. Recently some uses CCD sensor, like CCD camera, which is called image processing type sun tracking system. This work is concerned with the analysis of sun tracking performance of various types of sun tracking systems currently used in the parabolic dish type solar thermal power plant. We first developed a sun tracking error measurement system. Then, we evaluate the performance of five different types of sun tracking systems, sensor type, program type, hybrid type(use of sensor and computed sun position simultaneously), tracking error compensated program type and image processing type. Experimentally obtained data shows that the tracking error compensated program type sun tracking system is very effective and could provide a good sun tracking performance. Also the data obtained shows that the performance of sensor type sun tracking system is being affected by the cloud significantly, while the performance of a program type sun tracking system is being affected by the sun tracking system's mechanical and installation errors very much. Finally image processing type sun tracking system can provide accurate sun tracking performance, but costs more and requires more computational time.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.357-370
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• 2014

This study aims to develop a rainfall field tracking method for depth-area-duration (DAD) analysis and assess whether the proposed tracking methods are able to properly estimate the maximum average areal rainfall (MAAR) within the study area during a rainfall period. We proposed three different rainfall field tracking algorithms (Box-tracking, Point-tracking, Advanced point-tracking) and then applied them to the virtual rainfall field with 1hr duration and also compared DAD curves of each method. In addition, we applied the three tracking methods and a traditional GIS-based tool to the typhoon 'Nari' rainfall event of the Yongdam-Dam watershed and then assess applicability of the proposed methods for DAD analysis. The results showed that Box-tracking was much faster than the other two tracking methods in terms of searching for the MAAR but it was impossible to describe rainfall spatial pattern during its tracking processes. On the other hand, both Point-tracking and Advanced point-tracking provided the MAAR by considering the spatial distribution of rainfall fields. In particular, Advanced point-tracking estimated the MAAR more accurately than Point-tracking in the virtual rainfall field, which has two rainfall centers with similar depths. The proposed automatic rainfall field tracking methods can be used as effective tools to analyze DAD relationship and also calculate areal reduction factor.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.5 s.98
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• pp.578-585
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• 2005

In this paper, we present a schematic method estimating the tracking vibration quantity occurring in the track-following system of an optical recording device. A tracking loop gain adjustment algorithm is introduced to estimate accurately the tracking vibration quantity in spite of the uncertainties of the tracking actuator, Accordingly, the tracking vibration quantity can be estimated from the tracking error, the controller output, the nominal actuator model, and a compensated gain. An optimal tracking controller can be designed from a minimum tracking open-loop gain calculated by the estimated tracking vibration quantity The proposed vibration quantity estimation and controller design method are applied to the track-following system of an optical recording device and are evaluated through the experimental result.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.856-860
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• 2007

This paper presents a robust tracking controller design method for the track-following system of an optical recording device. A tracking loop gain adjustment algorithm is introduced to accurately estimate the tracking vibration quantity in spite of the uncertainties of the tracking actuator. A minimum tracking open-loop gain is calculated by the estimated tracking vibration quantity and a tolerable limit of tracking error. A robust tracking controller is designed by considering a robust $H_\infty$ control problem with the weighting function of a slightly larger gain than the minimum tracking open-loop gain. The proposed controller design method is applied to the track-following system of an optical recording device and is evaluated through the experimental result.

• Journal of the Korean Professional Engineers Association
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• v.42 no.6
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• pp.53-57
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• 2009

Antenna Tracking System has been required core technology with special tracking algorithm, and it can be achieved by program tracking, step tracking, optracking, and monopulse tracking as well. Depend on tracking requirement we might be able to apply eligible tracking method in accordance with Geostationary and Inclined Orbit Satellite. Further, we should deeply consider two important factors in order to act up to customer expectation in quality and system performance including competitive price therefore we need maximized endeavor to upgrade not only tracking system performance, but reduction of product through engineering skill and R&D investment.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.85-92
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• 2008

An architecture for multiple radar tracking systems can be broadly categorized according to the methods in which the tracking functions are performed : central-level tracking and distributed tracking. In the central-level tracking, target tracking is performed using observations from all radar systems. This architecture provides optimal solution to target tracking. In distributed tracking, tracking is performed at each radar system and the composite track information is formed through track fusion integrating multiple radar-level tracks. Track-to-track fusion and track-to-track association are required to perform in this architecture. In this paper, issues and recent research on the two tracking architectures are surveyed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.766-770
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• 2010

In this paper, we present an effective covariance tracking algorithm based on adaptive size changing of tracking window. Recent researches have advocated the use of a covariance matrix of object image features for tracking objects instead of the conventional histogram object models used in popular algorithms. But, according to the general covariance tracking algorithm, it can not deal with the scale changes of the moving objects. The scale of the moving object often changes in various tracking environment and the tracking window(or object kernel) has to be adapted accordingly. In addition, the covariance matrix of moving objects should be adaptively updated considering of the tracking window size. We provide a solution to this problem by segmenting the moving object from the background pixels of the tracking window. Therefore, we can improve the tracking performance of the covariance tracking method. Our several simulations prove the effectiveness of the proposed method.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1236-1249
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• 2020

In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.67-75
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• 2008

In this paper, we analyze the performance of Follower Noise Jamming(FNJ) considering three practical tracking parameters such as tracking bandwidth, tracking time and tracking success probability. The performance of FNJ is compared with that of Partial-Band Noise Jamming(PBNJ) in terms of Symbol Error Rate(SER) at the communication receiver under the assumed typical operation model. It is observed that the performance of FNJ is non-linearly dependent on the tracking bandwidth, the tracking time and the tracking success probability. As we can easily expect, it is also observed that the performance of FNJ is better than that of the PBNJ. Finally, it is shown that, for a fixed tracking bandwidth, the combinations of the required tracking time and the tracking success probability which satisfy a certain required SER.