• Journal of the Korean Society of Safety
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• v.11 no.1
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• pp.60-66
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• 1996

As the recently proposed JTC has been proven to be effective for implementation of real-time target tracking system, the interest on the electronic support system for the real-time JTC tracker has been increased. Accordingly, we proposed a tracking system which is based on BPEJTC and adaptive the fixed site. But because the EOTS is generally needed in the moving site such as aircraft and vehicles, and there are many different tracking algorithm to adopt the BPEJTC, we present an advanced version of BPEJTC dniver which has synchronization input so as to be used for the target pointer. In addition to the designed system architecture, some experimental results conducted by this system are illustrated.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.119-127
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• 2010

In this paper, we propose a new automatic surveillance tracking system that can extract the target from the complex background and foreground noises by using the image-based SAD algorithm and control the servo motor of cameras by using kanatani algorithm. From the experimental results the proposed stereo tracking system is found to track the target adaptively under the circumstance of complex and changing background noises and the possibility of real-time implementation of the proposed system by using the optical system is also suggested.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.44-53
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• 2008

An interacting multiple model (IMM) estimation algorithm based on the mixing of the predicted state estimates is proposed in this paper for a right continuous jump-linear system model different from the left-continuous system model used to develop the existing IMM algorithm. The difference lies in the modeling of the mode switching time. Performance of the proposed algorithm is compared numerically with that of the existing IMM algorithm for noisy system identification. Based on the numerical analysis, the proposed algorithm is applied to target tracking with a large sampling period for performance comparison with the existing IMM.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.22-28
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• 2007

The STIR(Signal Tracking & Illumination Radar) in KDX(Korean Destroyer Experimental) combat system acquires target from designating 3-D target information of surveillance radar (MW-08), and The performance of radar is decided by target acquisition time and accuracy of tracking loop because the STIR tracks automatically in accordance with tracking algorithm. In the view of ship, elements related with target acquisition time of the STIR can be various. In this paper the target acquisition time of the STIR is reduced by identifying the elements and suggesting the performance improvement method. The way of performance improvement is suggested through analysing main affecting factors. First, tracking algorism is required for analysis. Second, fitness of parameters that control elements related with acquisition distance is analyzed. And the third, accuracy of ship based sensors is analyzed. In conclusion, acquisition time against ship target can be advanced to 3 seconds from 10 seconds.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2346-2351
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• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.108-118
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• 2009

In this paper we develop an indoor location tracking system and its 3D tracking monitoring viewer, viz., 3D Navigation Viewer (3DNV). We focus on the integration of an indoor location tracking system with the Virtual Reality Modeling Language (VRML), to facilitate a representation of the user's spatial information in virtual indoor environments that is synchronized with the physical location environment. The developed indoor location tracking system employs beacons as active transmitters, and a listener as a passive receiver. The distance information calculated from the difference speeds of RF and Ultrasonic signals is exploited, to determine the user's physical location. This is essential in supporting third parties like doctors and caregivers in identifying the activities and status of a particular individual via 3DNV. 3DNV serves as a unified user interface for an indoor location tracking system, showing the viewpoint and position of the target in virtual indoor environments. It was implemented using VRML, to provide an actual real time visualization of the target's spatial information.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.369-377
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• 2005

This paper describes the realization of a coordinates tracking algorithm for an EOTS (Electro-Optical Tracking System). The EOTS stabilizes the image sensors, tracks targets automatically, and provides navigation capability for vehicles. The coordinates tracking algorithm calculates the azimuth and the elevation angle of an EOTS using the inertial navigation system and the attitude sensors of the vehicle, so that LOS designates the target coordinates which are generated by a Radar. In the error analysis, the unexpected behaviors of an EOTS due to the time delay and deadbeat of the digital signals of the vehicle equipments are anticipated and the countermeasures are suggested. The application of this algorithm to an EOTS will improve the operational capability by reducing the time which is required to find the target and support flight especially in the night time flight and the poor weather condition.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.490-498
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• 2010

This paper presents an autonomous target tracking approach and technique for transmitting ground control station image periodically for an unmanned aerial vehicle using onboard gimbaled(pan-tilt) camera system. The miniature rotary UAV which was used in this study has a small, high-performance camera, improved target acquisition technique, and autonomous target tracking algorithm. Also in order to stabilize real-time image sequences, image stabilization algorithm was adopted. Finally the target tracking performance was verified through a real flight test.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.217-226
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• 2003

Recently Lim has proposed a linear, recursive, unbiased minimum variance filter for a maneuvering target based on the maneuver dynamics modeled as a jump process of Poisson-type. In the proposed filter it was assumed that the state transition parameters of the jump used for target maneuver modeling are a priori known to the filter. However, in most cases they are not known in practice. In this paper, we consider the influence of system (target) modeling error on the performance of the proposed tracking filter arising from the maneuver tracking. For qualitative analysis Monte-Carlo simulations are carried out against employing the maneuver model with different state transition parameters from the actual values.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.54-62
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• 2006

In this paper, a new stereo object tracking system using the disparity motion vector is proposed. In the proposed method, the time-sequential disparity motion vector can be estimated from the disparity vectors which are extracted from the sequence of the stereo input image pair and then using these disparity motion vectors, the area where the target object is located and its location coordinate are detected from the input stereo image. Basing on this location data of the target object, the pan/tilt embedded in the stereo camera system can be controlled and as a result, stereo tracking of the target object can be possible. From some experiments with the 2 frames of the stereo image pairs having $256\times256$ pixels, it is shown that the proposed stereo tracking system can adaptively track the target object with a low error ratio of about 3.05 % on average between the detected and actual location coordinates of the target object.