• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1013-1020
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• 2013

In this paper the super-resolution time delay estimation algorithms based on eigen-analysis are developed for spread spectrum signals along with their comparative performance analysis. First, we shall develop super-resolution time delay estimation algorithms using the representative eigen-analysis based AOA (angle-of-arrival) estimation algorithms such as MUSIC, Minimum-Norm, and ESPRIT, and apply them to the ISO/IEC 24730-2.1 real-time locating system (RTLS) employing a direct sequence spread spectrum (DS-SS) technique to compare their performances in RTLS environments. Simulation results illustrate that all the three algorithms can resolve multipath signals whose delay differences are even smaller than the Rayleigh resolution limit. Simulation results also show that MUSIC and Minimum-Norm provide a similar performance while ESPRIT is inferior to both algorithms in RTLS environments.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.617-624
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• 2021

The accurate estimation of the number of signals included in the received signal is required for the AOA(: Angle-of-Arrival) estimation, the interference suppression, the signal reception, etc. AIC(: Akaike Information Criterion) and MDL(: Minimum Description Length) algorithms, which are known as the typical algorithms to estimate the signal number, estimate the number of signals according to the minimum of each criterion. As the number of antenna elements increased, the estimation performance is enhanced, but the computational complexity is increased because values of criteria for entire antenna elements should be calculated for finding their minimum. In order to improve this problem, in this paper, we propose AIC and MDL algorithms based on the beamspace, which efficiently estimate the number of signals while reducing the computational complexity by reducing the dimension of an array antenna through the beamspace processing. In addition, we provide computer simulation results based on various scenarios for evaluating and analysing the estimation performance of the proposed algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.340-346
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• 1996

In this paper, we propose a ne weighted backward covariance matrix method to enhance the resolution for direction-of-arrival(DOA) estimation. The proposed method (MEVM:modified eigenvector method) is an enhanced covariance matrix method which is an extended form of the conventional covariance matrix. We analyze the effect of using the weighted forward-baskward covariance matrix on the performance of the eigenvector method(EVM). By comparing the perturbation angle of the noise-subspace, we show that the spectral estimate obtained using the proposed method is less distorted than the spectral estimate obtained using the conventional EVM. The simulation results show that the new method is more accurate and has better resolution than the conventional EVM under the same noise conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.79-84
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• 2017

This paper is a multi-input multi-path (Multiple-input multiple-output: MIMO) using a space-alternating generalized expectation maximization(SAGE) algorithm in the parameter channel and determine the channel estimation performance. Estimated by the algorithm, SAGE time-varying channel environment, the channel parameters estimated from the parameters of the channel measured in the island region 781 of the band in order to compare the performance and compares the original data. This allows you to check the performance of the algorithm SAGE and is highly stable to delay spread (Delay Spread), the diffusion angle of arrival (Arrive of Angular Spread) performance in terms of accuracy down through the SAGE algorithm for estimating a more general calculation parameters.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.34-42
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• 2010

The DOA(direction of arrival), which is based on parametric and nonparametric estimation algorithm, and adaptive beamforming algorithm for mobile communication environments are researched and analyzed. In parametric estimation algorithm, eigenvalues of the signal component and the noise component are obtained from correlation matrix of received signal by array antenna and power spectrum of the received signal is discriminated from them. Otherwise, in nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Therefore, the improved directional estimation algorithm with regularizing sparsity constraints offers super-resolution and noise suppression compared to other algorithms.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.11
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• pp.886-893
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• 2017

Recently, for detection of low-RCS targets, bistatic radar and multistatic radar have been widely employed. In this paper, we present the process of deriving the received signal modeling of the bistatic MIMO radar system and deals with the performance analysis of applying the bistatic signal to the ML arrival angle estimation algorithm. In case of the ML algorithm, as the number of the targets increases, azimuth search dimension for DOA estimation also increases, which implies that the ML algorithm for multiple targets is computationally very intensive. To solve this problem a closed-form expression of estimation error is presented for performance analysis of the algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2777-2784
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• 2011

In this paper, DOA(direction of arrival) of multiple incident signals received from linear array antenna and circular array antenna, which is based on nonparametric estimation algorithm, and adaptive beam-forming algorithm are studied and analyzed. In nonparametric estimation algorithm, we minimize a regularized objective function for finding a estimate of the signal energy as a function of angle, using nonquadratic norm which leads to supper resolution and noise suppression. And then, DOA is estimated by the signal and noise spatial steering vector, and adaptive beam-forming pattern is improved by weight vectors obtained from the spatial vector. Especially, the discrimination ability of DOA and the adaptive beam-forming ability according to antenna array methods and the number of array elements are compared and considered.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.87-91
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas. However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. The other problem of MUSIC and ESRPIT is to require calibrated antennas with uniform features, and are sensitive to the manufacturing facult and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected hopfield neural model. Computer simulations show the validity of the proposed algorithm. The proposed method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.465-469
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.73.1-73.1
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• 2014

We investigate the influence of the galactic magnetic field (GMF) on the arrival direction (AD) of ultra-high energy cosmic rays (UHECRs) by searching the correlation with the large-scale structure (LSS) of the universe. The deflection angle of UHECRs from sources by the GMF is reflected in a source model by introducing the Gaussian smearing angle as a free parameter. Assuming the deflections by the GMF are mainly dependent on the galactic latitude, b, we divide the regions of sky by b and analyze the correlation between the AD of UHECRs and the LSS of the universe in each region varying the smearing angle. We find the deflection is strongly dependent on the galactic latitude by the maximum likelihood estimation. Specifically, the best-fit smearing angles are $9^{\circ}$ and $84^{\circ}$ in the high galactic latitude (HGL), $-90^{\circ}$ < b < $-60^{\circ}$, and in the low galactic latitude (LGL), $-30^{\circ}$ < b < $30^{\circ}$, respectively. The strength of GMF becomes stronger from the HGL to the LGL. From the results, we can estimate the strength of GMF in each region. In the LGL, for example, if we assume UHECRs are protons, we have the order of $100{\mu}G$ GMF, which is much stronger than the expected value of conventional GMF model. However, if the primaries are heavy nuclei, which is consistent with the observational result of mass composition analysis, the order of GMF strength is a few ${\mu}G$. More data from the future experiments make it possible to study the GMF between the source of UHECRs and Earth more accurately.