• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.562-565
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• 1987

This paper addresses the development of the estimation algorithm to acquire target position, velocity and course using bearing-only measurements in two dimensional environment. System state equations are derived from modified polar coordinates instead of existing Cartesian coordinates system. The Extended Kalman Filter is used to constitute the estimation algorithm because of state equation's nonlinearity. The computer simulation is done to verify the performance of derived algorithm. Simulation result showed that estimated state value of filter was converged to the true value in 10 minutes.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.496-499
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• 1995

In this paper, a new detection scheme, the detectable maneuver set (DMS) scheme, is proposed by incorporating the trade-off property between target maneuver magnitude and detection time delay. With this new detection scheme, small maneuvers can be effectively detected without enlarging window size. Simulation results show that the proposed DMS scheme gives better tracking performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.172-181
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• 2019

This paper deals with the problem of generating the energy optimal trajectory which is intended to enhance the target tracking performance of a passive homing missile. Noticing that the essence of passive target tracking is the range estimation problem, the target information gathered by passive measurements can be readily analyzed by introducing the range estimator designed in line-of-sight(LOS) frame. Moreover, for the linear filter structure of the suggested range estimator, the cost function associated with the target information is clearly expressed as a function of the line-of-sight rate. Based on this idea, the optimal missile trajectory maximizing the target information is obtained by solving the saddle point problem for an indefinite quadratic cost which consists of the target information and the energy. It is shown that, different from the previous heuristic approaches, the guidance command producing the optimal passive homing trajectory is produced by the modified proportional navigation guidance law whose navigation constant is determined by the weighting coefficient for target information cost.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.77-84
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• 2005

In most vision applications, we are frequently confronted with determining the position of object continuously. Generally, intertwined processes ire needed for target tracking, composed with tracking and control process. Each of these processes can be studied independently. In case of actual implementation we must consider the interaction between them to achieve robust performance. In this paper, the robust real time visual tracking in complex background is considered. A common approach to increase robustness of a tracking system is to use known geometric models (CAD model etc.) or to attach the marker. In case an object has arbitrary shape or it is difficult to attach the marker to object, we present a method to track the target easily as we set up the color and shape for a part of object previously. Robust detection can be achieved by integrating voting-based visual cues. Kalman filter is used to estimate the motion of moving object in 3D space, and this algorithm is tested in a pan/tilt robot system. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.11
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• pp.1013-1020
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• 2011

This paper deals with the tracking problem of a moving target using multiple unmanned aerial vehicles. A decentralized extended information filter is designed to cooperatively estimate the position and the velocity of the moving target. The extended information filter is adopted to consider the range and the line-of-sight angle as measurement data. The decentralized scheme is applied to enhance the estimation performance using the information provided by other vehicles. Numerical simulation is performed to verify the tracking performance of the proposed decentralized filters.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.177-187
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• 2010

A MTG (Multimode Tracking and Guidance) system is employed to compensate for the limitations of individual seekers such as RF (Radio frequency) or IIR (Imaging Infra-red) and to improve the overall tracking and guidance performance in jamming, clutter, and adverse weather environments. In the MTG system, tracking filter, data association, and data fusion methods are important elements to maximize the effectiveness of precision homing missile guidance. This paper proposes the formulation of a Kalman filter for the estimation of line-of-sight rate from seeker measurements in missiles guided by proportional navigation. Also, we suggest the HPDA (Highest Probability Data Association) and data fusion methods of the MTG system for target tracking in the adverse environments. Mont-Carlo simulation is employed to evaluate the overall tracking performance and guidance accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.2
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• pp.75-82
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• 2002

It is useful to detect the tracking error with an optimal view in the presence of measurement origin uncertainty. In this paper, after the investigation of the targer error dependent on the detection threshold as well as the detection and false alarm probabilities in a clutter environment, a new algorothm that optimizes the threshold of validation region for target trackinf is proposed. The performance of the algorithm is demonstrated through computer simulations.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.297-302
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• 2017

The tracking filter plays a key role in accurate estimation and prediction of maneuvering the vessel's position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The ${\alpha}-{\beta}-{\gamma}$ filter is one of the special cases of the general solution provided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity, and acceleration for the nth observation, and predicts the next position and velocity. Although found to track a maneuvering target with good accuracy than the constant velocity ${\alpha}-{\beta}$ filter, the ${\alpha}-{\beta}-{\gamma}$ filter does not perform impressively under high maneuvers, such as when the target is undergoing changing accelerations. This study aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The ${\alpha}-{\beta}-{\gamma}$ filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration to improve the filter's performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, ${\alpha}-{\beta}-{\gamma}-{\eta}$ algorithm as compared to the constant acceleration model, ${\alpha}-{\beta}-{\gamma}$ in terms of error reduction and stability of the filter during target maneuver.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.121-130
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• 2000

A practical method is proposed to improve hit probability of the digital gun fire control system, when the measured rate of the tracking sensor becomes biased under some operational situation. For ground moving target it is shown that the well-known Kalman filter which uses position measurement only can be optimally used to eliminate the rate bias error. On the other hand, for 3D moving aircraft we present a new algorithm which incorporate FIR-type filter, which uses position and rate measurement at the same time, and the fixed-lag smoother using position measurement only, and show that it has the optimal performance in terms of both estimation accuracy and response time.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.497-502
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• 2002

The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the state of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, a DNA coding-based interacting multiple model (DNA coding-based W) method is proposed. The proposed method can overcome the mathematical limits of conventional methods by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive IMM algorithm and the GA-based IMM method in computer simulations.