• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.33-41
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• 2004

Accuracy of registration between images acquired from various medical image modalities is one of the critical issues in radiation treatment planing. In this study, a method of accuracy evaluation of image registration using a homemade brain phantom was investigated. Chamfer matching of CT-MR and CT-SPECT imaging was applied for the multimodal image registration. The accuracy of image correlation was evaluated by comparing the center points of the inserted targets of the phantom. The three dimensional root-mean-square translation deviations of the CT-MR and CT-SPECT registration were 2.1${\pm}$0.8 mm and 2.8${\pm}$1.4 mm, respectively. The rotational errors were ＜ 2$^{\circ}$ for the three orthogonal axes. These errors were within a reasonable margin compared with the previous phantom studies. A visual inspection of the superimposed CT-MR and CT- SPECT images also showed good matching results.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.333-340
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• 2003

Doppler processing is the heart of pulsed Doppler radar. It gives a clutter elimination and coherent integration. With the improvement of digital signal processors (DPSs), the implementation using them is more widely used in radar systems. Generally, so as for Doppler processor to process the input data in real time, a parallel processing concept using multiple DSPs should be used. This paper implements a programmable Doppler processor, which consists of MTI filter, DFB and square-law detector, using 8 ADSP21060s. Formulating the distribution time of the input data, the transfer time of the output data and the time required to compute each algorithm, it estimates total processing time and the number of required DSP. Finally, using the TSG that provides radar control pulses and simulated target signals, performances of the implemented Doppler processor are evaluated.

• Journal of Apiculture
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• v.32 no.2
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• pp.99-109
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• 2017

The multiple real-time PCRs against pathogens of Bombus species including DWV, IAPV, KBV, SBV, BQCV, kSBV, SBPV and Paenibacillus larvae, Mellisococcus plutonius, Lysinibacillus fusiformis, and Klebsiella oxytoca have been developed. One extracted nucleic acid from Beesample could be applied to 11 different PCRs in same time and condition. Specific PCR-products were amplified qualitative and quantitative manner inner 20 minutes successfully, when each 1000 molecules of pathogen-specific target DNA is existed as template, respectively. The multiple PCR detection that we propose would be expected to apply to quarantine test for international exchange of Bombus species.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.445-453
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• 2001

The multiple targets tracking problem has been one of the main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimen-sion filter, input estimation filter, interacting multiple model(IMM) filter, dederated variable dimension filter with input estimation, etc., have proposed to address the tracking and sensor fusion issues. In this pa- per, two existing tracking algorithm, i.e, the IMM filter and the variable dimension filter with input estima-tion(VDIE), are combined for the purpose of improving the tracking performance for maneuvering targets. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns, i.e., waver, pop-up, and high-diver motions, are defined and are applied to the modified IMM filter as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMM filter than the standard IMM filter are demonstrated though computer simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.314-324
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• 2018

This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

• Journal of IKEEE
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• v.8 no.1 s.14
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• pp.39-46
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• 2004

This paper presents the realization schemes for a multipurpose coherent mono-pulse radar Simulator with extendable features. We developed and installed the TSG(Timing Signal Generator) board which can simulate a mechanically rotate signal of antenna, an operation timing signal of pulse radar and target signal, to operate the simulator without real target in the indoor environment. Also, with the insertion of the radar signal processor, it came to be easy to achieve the addition of radar function algorithms, to rebuild or extend the multi-DSP Architecture into the simulator. Throughout the simulation results, we verified that the designed coherent mono-pulse radar simulator can exactly display a moving target on the realistic monitor(RD 9800).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1304-1311
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• 2003

Target tracking in a real world situation is difficult problem because of continuous variations in images, huge amounts of data, and high processing speed demands. The problem becomes even harder in the case of sea background. This paper presents an initial study of neural network based method for target detection and tracking in cluttering environment. The approach uses a combination of differential motion analysis, Kohonen self-organizing network and region growing method. The network is capable of detecting the mass-centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment showed promising results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2739-2749
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• 1996

This aper introduces the multiple Neocognitron module approach for the effective target reognition. The Neocognitron which is designed to classify a pattern by extracting the local features from it, seems to be an unique method that can perform a pattern recognition using the neural networks. But due to its rigid structure, the Neocognitron must be reconstructed whenever there exists a variation on the number of classes. This is a quite difficult problem for the target recognition application that needs huge amount of computation and numerous classes to be classified. In this paper, we construct several smaller Necognitrom modules and train each module to adapt each class. After construction of the mulules, we integrate them in parallel so as to adaopt input at the same time and to produce each score that shold be matched to be learned class. This approach can reduce the sizes of the networks and is adaptive to the increase of classes as well as the authentic distortion, shift, scale variation and slight rotation invariant properties of general Neocognitron. This paper show the effectiveness of the proposed approach through some experience and performs analysis of the inhibitory interconnections in the architecture of the multiple module structure.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.210-217
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• 2003

We introduced a scheme for finding an optimal data association matrix that represents the relationships between the measurements and tracks in multi-target tracking (MIT). We considered the relationships between targets and measurements as Markov Random Field and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space that may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation in closed form. By introducing Lagrange multiplier, we derived a compact equation for parameters updating. In this manner, a pair of equations that consist of tracking and parameters updating can track the targets adaptively in a very variable environments. For measurements and targets, this algorithm needs only multiplications for each radar scan. Through the experiments, we analyzed and compared this algorithm with other representative algorithm. The result shows that the proposed method is stable, robust, fast enough for real time computation, as well as more accurate than other method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.737-743
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• 2015

This paper are mainly focusing on the facts influencing on RCS reductions, appling radar absorbing materials by using RCS contributions of elements and appling a metamaterials which is high-tech radar absorbing materials. RCS analysis results are given for a simplified ship model, with radar absorbing materials and metamaterials cause RCS reduction in terms of mean values.