• Journal of the Society of Naval Architects of Korea
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• v.42 no.4 s.142
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• pp.299-306
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• 2005

To determine a guidance law which is suitable for Target Tracking System(TTS) of an underwater vehicle, the performance (hitting probability) of TTS were calculated with four different guidance schemes, considering underwater vehicle's manoeuvrability and characteristics of seeking equipment such as sonar To evaluate the performance of TTS with each guidance law, numerous target-tracking simulations of underwater vehicle were performed under the condition of target's various motion scenario. Furthermore, the effect of sonar characteristics to the performance of guidance law in TTS was studied by changing parameters of sonar such as frequency of ping and detecting error of target. The pursuit-tail guidance law showed the best performance among four different guidance laws. Complex motion of target from straight line to turning circle and zigzag movement, low frequency of sonar ping and large detecting error of target decreased the hitting probability.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.852-862
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• 2013

This paper proposes a target tracking control method for wheeled mobile robots with nonholonomic constraints by using a backstepping-like feedback linearization. For the target tracking, we apply a vision system to mobile robots to obtain the relative posture information between the mobile robot and the target. The robots do not use the sensors to obtain the velocity information in this paper and therefore assumed the unknown velocities of both mobile robot and target. Instead, the proposed method uses only the maximum velocity information of the mobile robot and target. First, the pseudo command for the forward linear velocity and the heading direction angle are designed based on the kinematics by using the obtained image information. Then, the actual control inputs are designed to make the actual forward linear velocity and the heading direction angle follow the pseudo commands. Through simulations and experiments for the mobile robot we have confirmed that the proposed control method is able to track target even when the velocity sensors are not used at all.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.54-60
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• 2013

In this paper, a novel method called location-based delivery (LBD), which combines the short message service (SMS) and global position system (GPS), is proposed, and further, a realistic system for tracking a target's movement is developed. LBD reduces the number of short message transmissions while maintaining the location tracking accuracy within the acceptable range. The proposed approach, LBD, consists of three primary features: Short message format, location prediction, and dynamic threshold. The defined short message format is proprietary. Location prediction is performed by using the current location, moving speed, and bearing of the target to predict its next location. When the distance between the predicted location and the actual location exceeds a certain threshold, the target transmits a short message to the tracker to update its current location. The threshold is dynamically adjusted to maintain the location tracking accuracy and the number of short messages on the basis of the moving speed of the target. The experimental results show that LBD, indeed, outperforms other methods because it satisfactorily maintains the location tracking accuracy with relatively fewer messages.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.759-762
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• 1996

In previous work Kwon and Yoo [5] have shown that the FIR tracking algorithm using the input estimation technique. However, it has not solved the problem of systems with parameter uncertainties. Therefore, in this paper we propose a new robust $H_{\infty}$ FIR tracking filter to solve the target tracking problems under systems with parameter uncertainties. Also, we use here the input estimation approach to account for the possibility of maneuver. Simulation results show that the robust $H_{\infty}$ FIR tracking filter proposed here still has good tracking performance for a maneuvering target tracking problem even under all system parameter uncertainties.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.693-698
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• 2016

A decentralized control method is proposed to enable a group of robots to achieve maximum performance in multisensory target tracking while avoiding collision with the target. The decentralized control was designed based on navigation function formalism. The study showed that the multiple agent system converged to the positions providing the maximum performance by the decentralized controller, based on Lyapunov and Hessian theory. An exemplary simulation was given for a multiple agent system tracking a stationary target.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.139-144
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• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.359-365
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion(FBFE) based on virus evolutionary genetic algorithm (VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter(EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FDFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by idenLifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.6
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• pp.1166-1191
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• 2011

This paper presents an adaptive active tracking system with sector based scanning for a single PTZ camera. Dividing sectors on an image reduces the search space to shorten selection time so that the system can cover many targets. Upon the selection of a target, the system estimates the target trajectory to predict the zooming location with a finite amount of time for camera movement. Advanced estimation techniques using probabilistic reason suffer from the unknown object dynamics and the inaccurate estimation compromises the zooming level to prevent tracking failure. The proposed system uses the simple piecewise estimation with a few frames to cope with fast moving objects and/or slow camera movements. The target is tracked in multiple steps and the zooming time for each step is determined by maximizing the zooming level within the expected variation of object velocity and detection. The number of zooming steps is adaptively determined according to target speed. In addition, the iterative estimation of a zooming location with camera movement time compensates for the target prediction error due to the difference between speeds of a target and a camera. The effectiveness of the proposed method is validated by simulations and real time experiments.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.163-163
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• 2000

The tracking system on the moving vehicle is made up of two parts. One is a stabilizer which is flatting the system against the moving vehicle, the other is a tracker which is tracking the target. This makes use of the geometric information of the tracking target and that utilizes the dynamic information of the moving vehicle equipping the tracking system. Especially the stabilizer is very important for an ocean vehicle affected by wave, wind, and current. In this paper, the stabilizer of sun tracking system for a ship is developed.