• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.10
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• pp.1012-1019
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• 2010

In this paper, The flight data processing system was designed for multiple target flight test. For flight data processing, multiple target grouping, data fusion processing, and data slaving processing were performed and, as a data fusion filter, centralized, and federated Kalman filters were designed. A centralized kalman filter was modified in order to improve the vehicle's low altitude measurement using radar's SNR and estimation process. From the testing of multiple target missile, it confirmed flight trajectory measurement was improved in low altitude area and the beginning stage of vehicle.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1476-1483
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• 2007

In a multi-sensor target tracking systems, the local sensors have the role of tracking the target and transferring the measurements to the fusion center. The measurements from the same target can arrive out of sequence called, the out-of-sequence measurements(OOSMs). The OOSM can arise in a form of single-lag or multi-lag throughout the transfer at the fusion center. The recursive retrodiction step was proposed to update the current state estimates with the multi-lag OOSM from the several previous papers. The real world has the possible situations that the maneuvering target informations can arrive at the fusion center with the random clutter in the possible OOSMs. In this paper, we incorporate the IMM-MPDA(Interacting Multiple Model - Most Probable Data Association) into the multi-lag OOSM update. The performance of the IMM-MPDA filter with multi-lag OOSM update is analyzed for the various clutter densities, OOSM lag numbers, and target maneuvering indexes. Simulation results show that IMM-MPDA is sufficient to be used in out of sequence environment and it is necessary to correct the current state estimates with OOSM except a very old OOSM.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.438-449
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• 2005

In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor net­works for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.3
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• pp.461-469
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• 2010

In this paper, we have proposed an improved fusion method of detection features which can enhance the detection probability under the given false alarm rate in the prescreening stage of SAR ATR(Synthetic Aperture Radar Automatic Target Recognition) system. Since the detection features have the positive correlation, the detection performance can be improved if the joint probability distribution of detection features is considered in the fusion process. The detection region is designed as a simple piecewise linear function which can be represented by few parameters. The parameters for the detection region can be derived by training the sample SAR images to maximize the detection probability with the given false alarm rate. Simulation result shows that the detection performance of the proposed method is improved for all combinations of detection features.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.372-379
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• 2011

Estimating underwater target state variables(position, velocity, course, etc) is necessary to counteract threatening targets. In passive sonar systems, conventional target motion analysis(TMA) techniques using bearing and frequency measurements of an underwater target are widely introduced. However, it is not clear how conventional TMA techniques can be used if some of frequency measurements are unavailable during parts of the scenario, partially unavailable frequency measurements are common in the ocean with complicated acoustic conditions where frequency measurements often come and go. This paper proposes a new TMA algorithm, which is robust to partially unavailable frequency measurements, using the frequency measurements fusion method.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.487-494
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• 2011

Data Fusion algorithm is essential in Target Detection using radar, and it has more reliability. In this paper, Multi Radar Fusion algorithm using IMM(Interacting Multiple Model) filter is suggested. This well-known IMM filter has better performance than Kalman filter has. In this simulation, Distributed Data Fusion process was applied, and three sub-filters and one main filter were employed. In addition, this simulation was evaluated by virtual radar data which include constant velocity, constant accelerate, turn rate. The result of an evaluation shows better performance in the maneuvering section of aircraft.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.656-658
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• 2022

The purpose of infrared and visible image fusion is to integrate images of different modes with different details into a result image with rich information, which is convenient for high-level computer vision task. Considering many deep networks only work in a single scale, this paper proposes a novel image fusion based on three-scale dense network to preserve the content and key target features from the input images in the fused image. It comprises an encoder, a three-scale block, a fused strategy and a decoder, which can capture incredibly rich background details and prominent target details. The encoder is used to extract three-scale dense features from the source images for the initial image fusion. Then, a fusion strategy called l₁-norm to fuse features of different scales. Finally, the fused image is reconstructed by decoding network. Compared with the existing methods, the proposed method can achieve state-of-the-art fusion performance in subjective observation.

• Proceedings of the Microbiological Society of Korea Conference
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• 2001.11a
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• pp.97-101
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• 2001

The fusion between viral envelope and target cell membrane is a central step of viral infection, and the fusion proteins located at viral envelope mediate such process. Gp41 of HIV is one of the fusion proteins whose structure and mechanism of membrane fusion had been extensively studied. Functionally important motives of gp41 are the N-terminus fusion peptide, the coiled-coil and the membrane proximal C-peptide regions. The role of these regions during the fusion process had been thoroughly examined. Specially, insertion of the fusion peptide into membrane and conformational change of the coiled-coil and C-peptide regions are assumed to be critical for the fusion mechanism. In addition, the coiled-coil region has been shown to interact with membrane, and the C-peptide region regulates the interaction in a dose dependent manner. Furthermore, fusion defective mutations of the coiled-coil region dramatically changed its binding affinity to membrane. These results suggested that the membrane binding property of the coiled-coil region is important for the fusion activity of gp41, and such property could be modulated by the interaction with the C-peptide region.

• Journal of Global Scholars of Marketing Science
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• v.14
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• pp.1-16
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• 2004

This paper explores the impact of banner exposure and clicking on brand-attitude changes and purchase intention changes. It is found that simple exposure to banner ads does not change people's initial brand-attitude and purchase intention, while voluntary exposure to target ads by clicking banner ads results in positive or negative brand attitude and purchase intention changes depending on the likability of the linked target ads from the banner ads. For methodology, this study employed a pretest posttest control group design and used online data collection technology called Cold Fusion. A total of 961 subjects participated in this research.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.569-580
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• 2022

In this study, we investigated the effect of peripheral blur on binocular fusion to resolve binocular fusion failure which is one of the 3D visual fatigues in the perspective of human visual system. With stimulus having discrete disparity change, binocular fusion failure rate for target stimulus having crossed and uncrossed disparity decreased. And target stimulus having continuous disparity also required relatively larger binocular disparity when peripheral blur was presented with target stimulus rather than when peripheral blur was not presented. These results imply that peripheral blur facilitated binocular fusion in the situation of binocular disparity change, and suggest that considering the characteristics of human three-dimensional visual systems, manipulating 3D contents can improve visual discomfort caused by binocular displays at low costs.