• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.108-114
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• 2014

This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

• 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.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.413-423
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• 2008

The template matching method is used as a simple method to track objects or patterns that we want to search for in the input image data from image sensors. It recognizes a segment with the highest correlation as a target. The concept of this method is similar to that of SNF (Strongest Neighbor Filter) that regards the measurement with the highest signal intensity as target-originated among other measurements. The SNF assumes that the strongest neighbor (SN) measurement in the validation gate originates from the target of interest and the SNF utilizes the SN in the update step of a standard Kalman filter (SKF). The SNF is widely used along with the nearest neighbor filter (NNF), due to computational simplicity in spite of its inconsistency of handling the SN as if it is the true target. Probabilistic Strongest Neighbor Filter for m validated measurements (PSNF-m) accounts for the probability that the SN in the validation gate originates from the target while the SNF assumes at any time that the SN measurement is target-originated. It is known that the PSNF-m is superior to the SNF in performance at a cost of increased computational load. In this paper, we suggest an image tracking algorithm that combines the template matching and the PSNF-m to estimate the states of a tracked target. Computer simulation results are included to demonstrate the performance of the proposed algorithm in comparison with other algorithms.

• The Korea Genome Conference
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• 2004.07a
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• pp.49.2-49.2
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• 2004

• The Korea Genome Conference
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• 2005.09a
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• pp.52-52
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• 2005

• The Korea Genome Conference
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• 2003.09a
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• pp.49.2-49.2
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• 2003

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2339-2355
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• 2021

In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.255-259
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• 2004

본 논문에서는 다목적 위성 2호의 주 탑재체인 MSC (Multi-Spectral Camera)의 영상자료 검보정을 위한 검보정 target 준비 작업에 대해 설명한다. MSC 영상 자료에 대한 검보정 작업은 다목적 위성 2호의 발사 후 초기 운영 기간 (LEOP: Launch and Early Operation Phase)인 3개월 동안 수행될 예정이다. 위성 발사 전까지 MSC 영상 자료에 대한 검보정을 수행하기 위해 필요한 준비 작업들이 현재 한국항공우주연구원에서 진행중이다. LEOP 기간 동안 MSC 영상 자료를 검보정하기 위해서, MSC의 센서 특성에 따라 7가지 정도의 검보정 target에 대한 설계 초안이 완성되었으며, 향후 target에 대한 설계를 완성한 후에 2004년 중에 한 두 부지에 몇 가지 target들을 건설하고, 다목적 위성 2호의 궤도 특성을 고려하여 일부 target은 운반이 가능하도록 제작할 예정이다. 검보정 target이 촬영된 MSC 영상 자료의 분석을 통해, GSD (Ground Sample Distance), Aliasing, Linearity, Edge Slope & Response, MTF (Modulation Transfer Function), FOV & IFOV, Absolute radiometric validation, Position Accuracy 등의 MSC 검보정 요소 값들을 측정할 계획이다.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.3
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• pp.36-43
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• 2003

Multi-target away signal simulator which can simulate the radiated noises of maneuvering targets in a specified ocean range is an essential equipment for the validation of developed towed array sonar system. This simulator should provide realistic multi-channel signals those are required for beamforming on the signal processing unit of towed away system. This paper describes the overall system configuration and signal synthesis techniques for the target radiated noise. And this paper considers why the time delays between target and individual sensors are caused and how to compensate these time delays to individual sensors output. This multi-purpose target simulator could be used for the training of TASS operators.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.614-622
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• 2018

As multiple weapons are fired simultaneously in multi-target and multi-weapon environments, a possibility always exists in the collision occurred by the intersection between weapon trajectories. The collision between weapons not only hinders the rapid reaction but also causes the loss of the asset of weapons of friendly force to weaken the responsive power against the threat by an enemy. In this paper, we propose an intersection validation and interference elimination algorithm between weapon trajectories in multi-target and multi-weapon environments. The core points of our algorithm are to confirm the possible interference through the analysis on the intersections between weapon trajectories and to eliminate the mutual interference. To show the superiority of our algorithm, we implement the evaluation and verification of performances through the simulation and visualization of our algorithm. Our experimental results show that the proposed algorithm performs effectively the interference elimination regardless of the number of targets and weapon groups by showing that no cross point exists.