• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.218-223
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• 1993

In this paper, we modify a multiple target angle tracking algorithm presented by Sword et al.. The predicted estimates, instead of the existing estimates, of the target angles are updated by the most recent output of the sensor array to improve the tracking performance of the algorithm for crossing targets. Also, the least square solution is modified to avoid abnormally large angle innovations when the target angles are very close. The improved performance of the proposed algorithm is demonstrated by computer simulations.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1E
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• pp.19-25
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• 2003

Ryu et al. recently proposed a multiple target angle-tracking algorithm without a data association problem. This algorithm, however, shows the degraded performance on evasive maneuvering targets, because the estimated signal subspace is d,:graded in the algorithm. In this Paper, we proposed a new algorithm, in which VFF-PASTd (Variable Forgetting Factor PASTd) algorithm is applied to Ryu's algorithm to effectively handle the evasive target tracking with better time-varying signal subspace.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1E
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• pp.34-37
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• 2005

Ryu et al. proposed a multiple target angle-tracking algorithm without a data association problem using angular innovations. This algorithm, however, needs the computational loads in proportion to the square number of sensors regardless of the number of targets, because it uses a nonlinear equation between the signal subspace and angular innovation. In this Paper, we proposed an efficient algorithm for the multiple target angle-tracking using angular innovations. The proposed algorithm extracts the angular innovations from noise subspace. Also, it is demonstrated by computer simulations dealing with the tracking of crossing targets. The simulation results show that the computational loads of the proposed algorithm are $80\%$ and $60\%$ of those of Ryu's algorithm for 3 targets and 6 targets without degrading the performance of the target tracking.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4
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• pp.230-237
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• 2005

The angle-tracking of maneuvering targets is required to the state estimation and classification of targets in underwater acoustic systems. The Problem of angle-tracking multiple closed and crossing targets has been studied by various authors. Sword et al. Proposed a multiple target an91e-tracking algorithm using angular innovations of the targets during a sampling Period are estimated in the least square sense using the most recent estimate of the sensor output covariance matrix. This algorithm has attractive features of simple structure and avoidance of data association problem. Ryu et al. recently Proposed an effective multiple target angle-tracking algorithm which can obtain the angular innovations of the targets from a signal subspace instead of the sensor output covariance matrix. Hwang et al. improved the computational performance of a multiple target angle-tracking algorithm based on the fact that the steering vector and the noise subspace are orthogonal. These algorithms. however. are ineffective when a subset of the incident sources are coherent. In this Paper, we proposed a new multiple target angle-tracking algorithm for coherent and incoherent sources. The proposed algorithm uses the relationship between source steering vectors and the signal eigenvectors which are multiplied noise covariance matrix. The computer simulation results demonstrate the improved Performance of the Proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.114-120
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• 2011

This paper presents a cooperative standoff tracking of a moving target using multiple unmanned aircraft. To provide guidance commands, vector fields are designed utilizing the Lyapunov stability theory. A roll angle command is generated to keep a constant distance from the target in a circular motion. A speed command and a heading angle command are designed to keep a constant phase angle with respect to the front aircraft and to prevent a collision between aircraft. Numerical simulation is performed to verify the tracking and collision performance of the proposed control laws.

• 전자공학회논문지 IE
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• v.48 no.1
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• pp.25-29
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• 2011

Ryu et al. proposed a multiple target angle-tracking algorithm with efficient equation for angular innovation, and Ryu's algorithm has good feature that it has no data association problem. Ryu's algorithm is only applicable to linear sensor array, because its efficient equation for angular innovation is derived in case of using a linear sensor array. In a many fields studying multiple target angle-tracking, the various shapes of sensor array are used. In sonar, a cylindrical sensor array is as much used as a linear sensor array, a example is hull mounted sonar. In this paper, Ryu's algorithm is modified to be applicable to cylindrical sensor array, and the tracking performance of a modified algorithm is verified by various computer simulations.

• 전자공학회논문지 IE
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• v.43 no.3
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• pp.13-21
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• 2006

Ryu et al. proposed a multiple target angle tracking algorithm using the angular measurement obtained from the signal subspace estimated by the output of sensor array. Ryu's algorithm has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio, and it uses the angular measurement obtained from the signal subspace of sampling time, even though the signal subspace is continuously updated by the output of sensor array. For improving the tracking performance of Ryu's algorithm, a measurement fusion method is derived based on ML(Maximum Likelihood) in this paper, and it admits us to use the angular measurements obtained form the adjacent signal subspaces as well as the signal subspace of sampling time. The new target angle tracking algorithm is proposed using the derived measurement fusion method. The proposed algorithm has a better tracking performance than that of Ryu's algorithm and it sustains the good features of Ryu's algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.20-26
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• 1999

In this paper, a multiple target angle tracking algorithm that can avoid data association problem and has a simple structure is proposed by obtaining the angular innovation of the targets from a signal subspace. The signal subspace is recursively estimated by a signal subspace tracking algorithm, such as PAST. A nonlinear matrix equation which satisfy the estimated signal subspace and the angular innovation is induced and expanded into a Taylor series for linear approximation. The angular innovation is obtained by solving the approximated linear matrix equation in the least square sense. The good performance of the proposed algorithm is demonstrated by various computer simulations.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.362-370
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• 2011

This paper presents a K-band radar system installed on the ground moving vehicle to detect and track a high-speed target. The presented radar is separated into three search regions to satisfy a wide area detection and a limitation of the installing space of the radar, and each region performs detecting the target independently and tracking the detected target automatically. The presented radar radiating K-band FMCW waveform acquires range and velocity information of the target at the every dwell and receiving antenna of the radar is applied the multiple baseline interferometer to extract the precise angle information of the target. 3-dimensional tracking accuracy of the radar is 0.25 m RMSE measured actually through a fire experiment of an imitation target.