• Aerospace Engineering and Technology
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• v.13 no.2
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• pp.66-72
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• 2014

This paper introduces an asynchronous multiple radar fusion algorithm for space object tracking. To estimate orbital motion of space object, a multiple radar scenario which jointly measures single object with different sampling time indices is described. STK/ODTK is utilized to determine realization of orbital motion and joint coverage of multiple radars. Then, asynchronous fusion algorithm is adapted to enhance the estimation performance of orbital motion during which multiple radars measure the same time instances. Monte-Carlo simulation results demonstrate that the proposed asynchronous multi-sensor fusion scheme better than single linearized Kalman filter in an aspect of root mean square error.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.390-394
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• 2007

시간과 장소에 구애받지 않고 실시간으로 정보를 전달받을 수 있는 유비쿼터스 시대가 도래함에 있어서 실시간으로 움직이는 대상물의 위치를 알아내는 기술은 가장 근본적이며 필수적인 요소라 할 수 있다. 추측항법(Dead Reckoning)은 움직이는 대상물에 외부의 도움 없이 자신의 방향각과 가속도, 시간을 관측할 수 있는 관성항법장치(Inertial Navigation System)를 장착하여 이전의 위치 정보를 바탕으로 현재의 위치를 관측하는 방법이다. 또한 RFID(Radio Frequency IDentification)는 이러한 유비쿼터스 근거리무선통신의 핵심 기술로서 본 논문에서는 RFID에 기반한 위치 결정 시스템에 실시간 변화하는 대상물의 위치를 예측하기 위해 추측항법과 칼만필터(Kalman-filter)의 개념을 적용시켰다. 또한 RMSE(Root Mean Square Error)값을 통해 칼만필터의 적용에 따른 정확도의 향상과 각 디자인 요소들의 변화에 따라 위치의 정확도가 어떠한 변화를 갖는지를 분석하였다. 시뮬레이션 결과 칼만필터를 적용했을 때 이전보다 RMSE값이 현저히 작아지는 결과를 통해 위치의 정확도가 크게 향상되는 것을 확인하였다. 또한 RFID의 탐지 범위는 정확도에 큰 영향을 미칠 수 있는 주된 요소가 아니며, RFID 탐지 범위의 표준편차가 작을수록 위치 정확도는 높아지고, RFID 태그의 탐지 확률이 높을수록 RMSE 값의 변동이 작은 안정된 시스템을 갖으며 위치의 정확도 또한 높아진다는 것을 확인하였다.

• Nuclear Engineering and Technology
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• v.31 no.2
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• pp.192-201
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• 1999

This paper proposes an improved signal processing strategy for accurate feedwater flowrate estimation in nuclear power plants. It is generally known that ∼2% thermal power errors occur due to fouling Phenomena in feedwater flowmeters. In the strategy Proposed, the noises included in feedwater flowrate signal are classified into rapidly varying noises and gradually varying noises according to the characteristics in a frequency domain. The estimation precision is enhanced by introducing a low pass filter with the wavelet analysis against rapidly varying noises, and an autoassociative neural network which takes charge of the correction of only gradually varying noises. The modified multivariate stratification sampling using the concept of time stratification and MAXIMIN criteria is developed to overcome the shortcoming of a general random sampling. In addition the multi-stage robust training method is developed to increase the quality and reliability of training signals. Some validations using the simulated data from a micro-simulator were carried out. In the validation tests, the proposed methodology removed both rapidly varying noises and gradually varying noises respectively in each de-noising step, and 5.54% root mean square errors of initial noisy signals were decreased to 0.674% after de-noising. These results indicate that it is possible to estimate the reactor thermal power more elaborately by adopting this strategy.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.70-75
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• 1998

The comparison of Topex/Poseidon sea surface heights and Tide Gauge sea levels was studied in the South Indian Ocean after Topex/Poseidon mission of about 3 years (11- 121 cycles) from January 1993 through December 1995. The user's handbook (AVISO) for sea surface height data process was used in this study Topex/Poseidon sea suface heights ($\zeta$$^{T/P}$), satellite data at the point which is very closed to Tide Gauge station, were chosen in the same latitude of Tide Gauge station. These data were re-sampled by a linear interpolation with the interval of about 10 days, and were filtered by the gaussian filter with a 60 day-window. Tide Gauge sea levels ($\zeta$$^{Argos}$, $\zeta$$^{In-situ}$ and $\zeta$$^{Model}$), were also treated with the same method as satellite data. The main conclusions obtained from the root-mean-square and correlation coefficient were as follows: 1) to Produce Tide Gauge sea levels from bottom pressure, in-situ data of METEO-FRANCE showed very good values against to the model data of ECMWF and 2) to compare Topex/Poseidon sea surface heights of Tide Gauge sea levels, the results of the open sea areas were better than those of the coast and island areas.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.9
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• pp.401-408
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• 2006

In a multi-sensor multi-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). Out-of-sequence measurements can arise at the fusion center due to communication delay and varying preprocessing time for different sensor platforms. In general, the track fusion occurs to enhance the tracking performance of the sensors using the measurements from the sensors at the fusion center. The target informations can wive at the fusion center with the clutter informations in cluttered environment. In this paper, the OOSM update step with MPDA(Most Probable Data Association) is introduced and tested in several cases with the various clutter density through the Monte Carlo simulation. The performance of the MPDA with OOSM update step is compared with the existing NN, PDA, and PDA-AI for the air target tracking in cluttered and out-of-sequence measurement environment. Simulation results show that MPDA with the OOSM has compatible root mean square errors with out-of-sequence PDA-AI filter and the MPDA is sufficient to be used in out-of-sequence environment.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.84-89
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• 2002

In this paper, we present the design method of noise reduction circuit in telephonic system. The circuit consists of compressor, expander and a filter. The basic idea of a proposed method compresses the audible signal in order to mask the channel noise during transmission and then expand at the reverse rate the transmitted signal to naturally recover the original signal. Of course, there should be no distortion or other degradation of the audio itself in passing through companding(compress/expand) cycle. In the compressing process, the gain of compressor is automatically controlled by the envelope level of input signal in order to increase the effective dynamic range of input signal and to improve the signal to noise ratio. The compressed rate is the root time of a audible signal. The compressed signal should be expanded at the square time of the signal to recover a original signal. Simulation shows the proposed method improves the performance of the noise reduction of a channel noise as well as stability. 

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.1
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• pp.73-80
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• 2004

In this paper, the implementation and embedding method of the existing air-filled waveguide-filters at millimeter-wave on general PCB substrate is introduced by systematically inserting the vias inside waveguide and mathematically manipulating the simple equations obtained ken the classical circular-post waveguide filter design. All the metal structures placed vertically such as side wall fur perfect ground plane and circular-post for signal control in the air-filled WR-22 waveguide are replaced with several types of via for constructing the bandpass-filter. Side wall and poles inside waveguide are realized by placing a series array of via and tuning the via diameter. The lengths of x, y, z axis are reduced in proportion to root square of employed substrate dielectric constant and especially the length of z axis can be more reduced due to the characteristics of the wave propagation. Because the mass production on PCB is possible without fabricating a large-scaled metal waveguide of WR-22 as input/output ports at millimeter-wave regime, the manufacturing cost is reduced considerably. Finally, when using multilayer process like LTCC for small-sized module, it is one of advantages to use only one layer f3r the filter fabrication. To evaluate the validity of this novel technique, order-3 Chebyshev BPF(Bandpass-Filter) centered at 40 GHz-band with a 2.5 ％ FBW (Fractional Bandwidth) were used. The employed substrate has relative dielectric constant of 2.2 and thickness of 10 mil of Rogers RT/Duroid 5880. Accroding to design and measurement results, a good performance of insertion loss of 2 ㏈ and return loss of -30 ㏈ is achieved at full input/output ports.

• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.413-420
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• 2012

Spectroscopic measurement method based on visible and near-infrared wavelengths was prominent technology for rapid and non-destructive evaluation of internal quality of fruits. Reflectance measurement was performed to evaluate firmness, soluble solid content, and acid content of truss tomatoes by hyperspectral reflectance imaging system. The Vis/NIR reflectance spectra was acquired from truss tomatoes sorted by 6 ripening stages. The multivariable analysis based on partial least square (PLS) was used to develop regression models with several preporcessing methods, such as smoothing, normalization, multiplicative scatter correction (MSC), and standard normal variate (SNV). The best model was selected in terms of coefficient of determination of calibration ($R_c^2$) and full cross validation ($R_{cv}^2$), and root mean standard error of calibration (RMSEC) and full cross validation (RMSECV). The results of selected models were 0.8976 ($R_p^2$), 6.0207 kgf (RMSEP) with gaussian filter of smoothing, 0.8379 ($R_p^2$), $0.2674^{\circ}Bx$ (RMSEP) with the mean of normalization, and 0.7779 ($R_p^2$), 0.1033% (RMSEP) with median filter of smoothing for firmness, soluble solid content (SSC), and acid content, respectively. Results show that Vis / NIR hyperspectral reflectance imaging technique has good potential for the measurement of internal quality of truss tomato.

• Water for future
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• v.28 no.5
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• pp.219-233
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• 1995

A non-stationary multivariate model is selected in which the mean and variance of rainfall are not temporally or spatially constant. And the rainfall prediction system is constructed which uses the recursive estimation algorithm, Kalman filter, to estimate system states and parameters of rainfall model simulataneously. The on-line, real-time, multivariate short-term, rainfall prediction for multi-stations and lead-times is carried out through the estimation of non-stationary mean and variance by the storm counter method, the normalized residual covariance and rainfall speed. The results of rainfall prediction system model agree with those generated by non-stationary multivariate model. The longer the lead time is, the larger the root mean square error becomes and the further the model efficiency decreases form 1. Thus, the accuracy of the rainfall prediction decreases as the lead time gets longer. Also it shows that the mean obtained by storm counter method constitutes the most significant part of the rainfall structure.

• Journal of Navigation and Port Research
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• v.40 no.2
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• pp.83-87
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• 2016

The maritime industry is expanding at an alarming rate hence there is a perpetual need to improve situation awareness in the maritime environment using new and emerging technology. Tracking is one of the numerous ways of enhancing situation awareness by providing information that may be useful to the operator. The tracking module designed herein comprises determining existing states of high dynamic target warship, state prediction and state compensation due to random noise. This is achieved by first analyzing the process of tracking followed by design of a tracking algorithm that uses ${\alpha}-{\beta}-{\gamma}$ tracking filter under a random noise. The algorithm involves initializing the state parameters which include position, velocity, acceleration and the course. This is then followed by state prediction at each time interval. A weighted difference of the observed and predicted state values at the $n^{th}$ observation is added to the predicted state to obtain the smoothed (filtered) state. This estimation is subsequently employed to determine the predicted state in the next radar scan. The filtering coefficients ${\alpha}$, ${\beta}$ and ${\gamma}$ are determined from a pre-determined value of the damping parameter, ${\xi}$. The smoothed, predicted and the observed positions are used to compute the twice distance root mean square (2drms) error as a measure of the ability of the tracking module to manage the noise to acceptable levels.