• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.6
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• pp.38-46
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• 2008

A distributed system for tracking multiple targets with a pair of multifunction radars is proposed and implemented. The system performs track-to-track association and track-to-track fusion at the fusion center to form fused tracks. The association and fusion are performed using target state information linked via communication nodes from a radar at a remote location. Many factors can affect the track-to-track association and fusion performances. They include delays in data transmission buffer of the remote radar, the error in estimating time-stamp of the remote radar, and the gating in track-to-track association. The effects on association and fusion performances due to these factors are investigated through extensive numerical simulations.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.178-183
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• 2012

The design of the integrated quench protection (QP) system for the high current superconducting magnet (SCM) has been fabricated and tested for the toroidal field (TF) coil system of the Korea Superconducting Tokamak Advanced Research (KSTAR) device. The QP system is capable of protecting the TF SCM, which consists of 16 identical coils serially connected with a stored energy of 495 MJ at the design operation level at 35.2 kA per turn. Given that the power supply for the TF coils can only ramp up and maintain the coil current, the design of the QP system includes two features. The first is a basic fast discharge function to protect the TF SCM by a dump resistor circuit with a 7 s time constant in case of coil quench event. The second is a slow discharge function with a time constant of 360 s for a daily TF discharge or for a stop demand from the tokamak control system. The QP system has been successfully tested up to 40 kA with a short circuit and up to 34 kA with TF SCM in the second campaign of KSTAR. This paper describes the characteristics of the TF QP systems and test results of the plasma experiment of KSTAR in 2009.

• Journal of Korean Neurosurgical Society
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• v.30 no.10
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• pp.1170-1176
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• 2001

Objective : The purpose of the study was to evaluate the clinical and radiological results after discectomy and Lubboc bone graft in the surgical management of the cervical diseases with a new titanium interbody implant and integrated screw fixation(PCB) by anterior approach. Methods : The authors retrospectively analyzed 28 cases of anterior cervical fusion with PCB system and Lubboc bone(xeno graft) from september 1998 to december 2000. Twenty-eight patients with cervical diseases underwent decompression cervical lesion and followed from 5 to 27 months with a mean follow-up of 14 months. There patients were evaluated with clinically and radiologically at immediate postoperative period and at 3, 6, 9, and 12 months. Result : The authors investigated the pre- and postoperative intervertebral disc space, clinical outcomes, radiography fusion rate, and Cobb angle in the fixed segments by anterior approach. The lordotic angles and height of disc space were increased after the operation. The clinical outcome of patients follow-up was good or excellent result based on Odom's criteria with improvement of clinical symptom in about 92.9% of the cervical diseases. Two patients showed loosening of the lower and upper cervical screw of PCB instruments, and two patients showed swallowing difficulty and wound infection Conclusion : The PCB system is a new implant for anterior cervical interbody fusion in the degenerative cervical disease and disc herniations. It provides immediate stability and segment distraction. The results of this study indicate that the PCB system is safe, easy handling of hardware, less complications, high fusion rate, and has provide the keeping the intervertebral disc space height and lordotic angles.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.555-567
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• 2014

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.345-353
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• 2015

In this paper, we proposed an information fusion method for enhancement of automatic dependent surveillance - broadcast (ADS-B) system which is one of the next generation navigation system. Although ADS-B provides better performance than traditional radar, ADS-B still has error due to dependence of global navigation satellite system (GNSS) information. In this paper, we improved the ADS-B performance using information fusion of multilateration (MLAT) and wide area multilateration (WAM). Information fusion provides accurate data compared to original data. Mostly, information fusion methods use Kalman filter or IMM(interacting multiple model) filter as a subfilter. However, we used Robust IMM filter as a subfilter to improve the aircraft tracking performance. Also, we use actual ADS-B data not virtual data to increase reliability of our information fusion method.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.423-429
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• 2008

This study was performed to investigate the effects of inertial navigation system (INS) / global positioning system (GPS) sensor fusion for agricultural vehicle navigation. An extended Kalman filter algorithm was adopted for INS/GPS sensor fusion in an integrated mode, and the vehicle dynamic model was used instead of the navigation state error model. The INS/GPS system was consisted of a low-cost gyroscope, an odometer and a GPS receiver, and its performance was tested through computer simulations. When measurement noises of GPS receiver were 10, 1.0, 0.5, and 0.2 m ($1{\sigma}$), RMS position and heading errors of INS/GPS system at 5 m/s straight path were remarkably reduced with 10%, 35%, 40%, and 60% of those obtained from the GPS receiver, respectively. The decrease of position and heading errors by using INS/GPS rather than stand-alone GPS can provide more stable steering of agricultural equipments. Therefore, the low-cost INS/GPS system using the extended Kalman filter algorithm may enable the self-autonomous navigation to meet required performance like stable steering or more less position errors even in slow-speed operation.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.11-19
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• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.3
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.783-789
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• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.9-21
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• 2010

In this paper, optimum design of distributed detection is considered for a parallel sensor network system consisting of a fusion center and multiple passive sonar nodes. Nonrandom fusion rules are employed as the fusion rules of the sensor network. For the nonrandom fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is investigated that maximizes the probability of detection under a constraint on energy consumption due to false alarms. It is also investigated through numerical experiments how signal strength, false alarm probability, and the distance between three sensor nodes affect the system detection performances.