• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.31-37
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• 1999

This paper describes the far-field estimation using the near-field measurement data. Measurement in far-field region gives us the acoustical characteristics of the source but in general measurement is made in near-field such as acoustic water tank or anechoic chamber, so far-field acoustical characteristics of the source should be predicted from near-field data. In this case, the number of measurement points in the near field which relates to the accuracy of the predicted field and the amount of data processing, should be optimized. Existing papers say that measurement points is proportional to kL and depends on geometry and directivity of the source. But they do not give us any definite criterion for the required number of measurement points. Boundary Collocation Method which is one of the far-field prediction methods, is analyzed based on Helmholtz integral equation and Green function and it has been found that the number of measurement points is optimized as 0.54kL which is about one half of the existing results.

• Journal of Korean Society for Atmospheric Environment
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• v.11 no.3
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• pp.279-290
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• 1995

Recently in Korea, due to the significant drop of lead and bromine levels as a marker of autoemission source in the urban areas, the conventional application of receptor methods has many difficulties to properly apportion mass contribution of some sources. It is then needed to urgently develop alternative source profiles and identify new emission markers. Thus, the study has extensively examined the results obtained from using PAHs and elemental data for receptor modeling and has provided an opportunity to identify alternative source compositions and to determine a proper number of the ambient emission sources in Seoul area. The purpose of the study is to identify the sources of PM-10 and to estimate their mass contributions in Seoul area. Thus, a receptor model, target transformation factor analysis(TTFA) has been massively applied. The TTFA offers the possibility of determining the number of sources and their mass contributions. The input data used in this study are composed of two separate sets: fine (d$_{p}$ < 2.5.mu.m) and coarse (2.5.mu.m < d$_{p}$ < 10.mu.m) mode aerosol samples. Each sample was simultaneously collected by a PM-10 dichotomous sampler during the daytime(8 AM to 8 PM) and the nighttime(8 PM to 8 AM) from February to October 1993 on the Sungdong-Gu, Seoul. All the samples were analyzed to determine the levels of 10 inorganic elements by an XRF system as well as 14 PAHs by a HPLC. However, only 8 inorganic elements and 7 PAHs were used for the various statistical analysis.sis.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.129-135
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• 2011

An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.5
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• pp.492-502
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• 2021

In electronic warfare, source enumeration and direction-of-arrival estimation are important. The source enumeration method based on eigenvalues of covariance matrix from received is one of the most used methods. However, there are some drawbacks such as accuracy less than 100 % at high SNR, poor performance at low SNR and reduction of maximum number of estimating sources. We suggested new method based on eigenvalues gaps, which is named AREG(Accumulated Ratio of Eigenvalues Gaps). Meanwhile, FGML(Fast Gridless Maximum Likelihood) which reconstructs the covariance matrix was suggested by Wu et al., and it improves performance of the existing source enumeration methods without modification of algorithms. In this paper, first, we combine AREG with FGML to improve the performance. Second, we compare the performance of source enumeration and direction-of-arrival estimation methods in Rayleigh fading. Third, we suggest new method named REG(Ratio of Eigenvalues Gaps) to reduce performance degradation in Rayleigh Fading environment of AREG.

• ETRI Journal
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• v.34 no.4
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• pp.511-517
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• 2012

The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.97.4-97
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• 2002

1. Introduction Pose estimation of a three dimensional object has been studied in robot vision area, and it is needed in a number of industrial applications such as process monitoring and control, assembly and PCB inspection. In this research, we propose a new pose estimation method based on principal axes analysis. Here, it is assumed that the locations of x-ray source and the image plane are predetermined and the object geometry is known. To this end, we define a dispersion matrix of an object, which is a discrete form of inertia matrix of the object. It can be determined here from a set of x-ray images, at least three images are required. Then, the pose information is obtained fro...

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.109-112
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• 2003

In real time packetized voice applications, missing frames is a major source of voice quality degradation. Thus packet loss concealment(PLC) algorithms are needed to guarantee the QoS of the VoIP. Still current speech codecs for VoIP work poor when consecutive packet losses are issued. In this paper, we proposed a new PLC algorithm for the G.729 codec. Our algorithm works better especially when the consecutive packet loss occurs mainly because it adopts an adaptive gain controller utilizing the number of missing packet information combined with a fixed codebook vector estimation algorithm and LPC bandwidth expansion.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.09a
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• pp.28-34
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• 2002

The b-value in the magnitude-frequency relationship logN(m) = $\alpha$ - bmwhere N(m) is the number of earthquakes exceeding magnitude m, is important seismicity parameter In hazard analysis. Estimation of the b-value for earthquake data observed on KSRS array network is done employing the maximum likelihood technique. Assuming the whole Korea Peninsula as a single seismic source area, the b-value is computed at 0.9. The estimation for KMA earthquake data is also similar to that. Since estimate is a function of minimum magnitude, we can inspect the completeness of earthquake catalog in the fitting process of b-value. KSRS and KMA data lists are probably incomplete for magnitudes less than 2.0 and 3.0, respectively. Examples from probabilistic seismic hazard assessment calculated for a range of b-value show that the small change of b-value has seriously effect on the prediction of ground motion.

• Progress in Medical Physics
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• v.5 no.1
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• pp.41-53
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• 1994

The accurate localization of electrical sources in the brain is one of the most important questions in EEG, especially in the analysis of evoked responses and of epileptiform spike activity. A detailed simulation study of single dipole source estimation based on EEG is given in this paper. The effects of dipole model parameters on single dipole source tracing in EEG are examined in some detail using the Monte Carlo simulation. The error of source localization is found to be greatly influenced by how the electrodes are distributed over the head and the number of them.

• Journal of Korean Society for Atmospheric Environment
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• v.6 no.1
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• pp.11-21
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• 1990

To quantitatively estimate the effect of yellow sand(loess) fromt he Northern China, various soil sources having similar chemical compositions to yellow sands should be separated and identified. After that, mass contribution for yellow sand can be calculated. The study showed that it was impossible to solve this problem by the traditional bulk analyses. However, particle-by-particle analysis by a CCSEM (computer controlled scanning electron microscope) gave enormous potentials to solve it. To perform this study, seven soil source data analyzed by CCSEM were obtained from Texas, U.S.A. Initially, each soil date was classified into two groups, coarse and fine particle groups since the particle number distribution showed a minimum occurring at 5.2$\mu$m of aerodynamic diameter. Particles in each group were then classified into one of the 283 homogeneous particle classes by the universal classification rule which had been built by an expert system in the early study. Further, mass fractions and their uncertainties for each class in each source were calculated by the Jackknife method, and then source profile matrix for the 7 soil sources was created. To use the profile matrix in the study of source contribution, it is necessary to test the degree of collinearity among sources. The profiles were tested by the singular value decomposition method. As a result, each soil source characterized by artificially created variables was totally independent each other and is ready to use in source contribution studies as a receptor model.