• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.09a
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• pp.97-100
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• 2004

Multivariate Newton Raphson method is developed to perform the particle tracking in the three dimensional area using four objective functions. In this method, three variables are solved to compute target point and actual and real tracking time. The simulated pathlines in various types of three dimensional elements are well matched with exact pathline.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1261-1271
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• 2013

Zoom tracking involves the automatic adjustment of the focus motor in response to the zoom motor movements for the purpose of keeping an object of interest in focus, and is typically achieved by moving the zoom and focus motors in a zoom lens module so as to follow the so-called "trace curve", which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. Thus, one can simply implement zoom tracking by following the most closest trace curve after all the trace curve data are stored in memory. However, this approach is often prohibitive in practical implementation because of its large memory requirement. Many other zoom tracking methods such as GZT, AZT and etc. have been proposed to avoid large memory requirement but with a deteriorated performance. In this paper, we propose a new zoom tracking method called 'Approximate Feedback Zoom Tracking method (AFZT)' on DM36x-based IP network camera, which does not need large memory by approximating nearby trace curves, but generates better zoom tracking accuracy than GZT or AZT by utilizing focus value as feedback information. Experiments through real implementation shows the proposed zoom tracking method improves the tracking performance and works in real-time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.158-166
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• 2011

Generally, moving object tracking used Lucas-Kanade feature tracking method which is strong in movement, rotation and size. But this method is very weak of occlusion by background or another object and so on. In this case, this method tracks backgrounds or another objects instead a moving object, or a tracking is finished. In order to solve this problem, we proposes Lucas-Kanade feature tracking method which introduce a destimation function and prediction function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1711-1725
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• 2014

Multi-target tracking is the main purpose of many video surveillance applications. Recently, multi-target tracking based on the particle filter method has achieved robust results by using the data association process. However, this method requires many calculations and it is inadequate for real time applications, because the number of associations exponentially increases with the number of measurements and targets. In this paper, to reduce the computational cost of the data association process, we propose a novel multi-target tracking method that excludes particle samples in the overlapped predictive region between the target to track and marginal targets. Moreover, to resolve the occlusion problem, we define an occlusion mode with the normal dynamic mode. When the targets are occluded, the mode is switched to the occlusion mode and the samples are propagated by Gaussian noise without the sampling process of the particle filter. Experimental results demonstrate the robustness of the proposed multi-target tracking method even in occlusion.

• ETRI Journal
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• v.37 no.3
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• pp.617-625
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• 2015

In this paper, a steering control system for the path tracking of autonomous vehicles is described. The steering control system consists of a path tracker and primitive driver. The path tracker generates the desired steering angle by using the look-ahead distance, vehicle heading, and a lateral offset. A method for applying an autonomous vehicle to path tracking is an advanced pure pursuit method that can reduce cutting corners, which is a weakness of the pure pursuit method. The steering controller controls the steering actuator to follow the desired steering angle. A servo motor is installed to control the steering handle, and it can transmit the steering force using a belt and pulley. We designed a steering controller that is applied to a proportional integral differential controller. However, because of a dead band, the path tracking performance and stability of autonomous vehicles are reduced. To overcome the dead band, a dead band compensator was developed. As a result of the compensator, the path tracking performance and stability are improved.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.5
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• pp.31-38
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• 2014

Maximum power point tracking method is very important to enhance efficiency of photovoltaic system. Meanwhile a lot of research about MPPT has been studied and developed new one better than a method of the past. This paper deals with Perturb and Observation that are most commonly used. Tracking parameter changed PV voltage for PV current and it was simulated with P-SIM program. The P&O tracking method to use current for parameter lows ripple rate of output and enhances response rate of tracking. Through this study, it has been demonstrated that method using current for tracking parameter is effective.

• 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.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.77-86
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• 2006

Usually, a tracking-gate of the tracker is used to track the target radar signal in the active ECM system. In this paper, we propose the feed-back tracking-gate filtering method. The designed method applies a tracking-gate of the tacker to the ECM system's receiver as a rejection or pass filter selected by the receiver's purpose, and the specific target signals can be passed or rejected though this tracking-gate filter. Thus, the number of input signals within the receiver's search band is minimized owing to this filter except the target signals. In conclusion, the EW equipment's reaction time can be reduced and the error value about the target signals can be lower than the previous methods'.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.22-30
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• 2023

When tracking small UAVs and drone targets in cloud clutter environments, MWIR sensors are often unable to track targets continuously. To overcome this problem, the SWIR sensor is mounted on the same gimbal. Target tracking uses sensor information fusion or selectively applies information from each sensor. In this case, parallax correction using the target distance is often used. However, it is difficult to apply the existing method to small UAVs and drone targets because the laser rangefinder's beam divergence angle is small, making it difficult to measure the distance. We propose a tracking method which needs not parallax correction of sensors. In the method, images from MWIR and SWIR sensors are captured simultaneously and a tracking error for gimbal driving is chosen by effectiveness measure. In order to prove the method, tracking performance was demonstrated for UAVs and drone targets in the real sky background using MWIR and SWIR image sensors.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.93-100
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• 2003

Accuracy in maneuvering target tracking using multiple models relies upon the suit-ability of each target motion model to be used. To construct multiple models, the interacting multiple model (IMM) algorithm and the adaptive IMM (AIMM) algorithm require predefined sub-models and predetermined acceleration intervals, respectively, in consideration of the properties of maneuvers. To solve these problems, this paper proposes the GA-based IMM method as an intelligent tracking method for a maneuvering target. In the proposed method, the acceleration input is regarded as an additive process noise, a sub-model is represented as a fuzzy system to compute the time-varying variance of the overall process noise, and, to optimize the employed fuzzy system, the genetic algorithm (GA) is utilized. The simulation results show that the proposed method has a better tracking performance than the AIMM algorithm.