• 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.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.166-171
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• 2022

In this paper, we propose an algorithm to improve DoA(direction of arrival) estimation performance of the subspace-based method by generating high robustness correlation matrix of the signals incident on the uniformly linear array antenna. The existing subspace-based DoA estimation method estimates the DoA by obtaining a correlation matrix and dividing it into a signal subspace and a noise subspace. However, the component of the correlation matrix obtained from the low SNR and small number of snapshots inaccurately estimates the signal subspace due to the noise component of the antenna, thereby degrading the DoA estimation performance. Therefore a robust correlation matrix is generated by arranging virtual signal vectors obtained from the existing correlation matrix in a sliding manner. As a result of simulation using MUSIC and ESPRIT, which are representative subspace-based methods,, the computational complexity increased by less than 2.5% compared to the existing correlation matrix, but both MUSIC and ESPRIT based on RMSE 1° showed superior DoA estimation performance with an SNR of 3dB or more.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.111-114
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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. In the case that 2-D large-sized array antenna is required, however, one of the disadvantages of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. To alleviate the computational complexity, 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.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.204-210
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• 2012

In this paper, we study the method of estimating direction of departure(DOD) and direction of arrival(DOA) using estimation of signal parameters via rotational invariant techniques (ESPRIT) in uniform linear array MIMO radar system. While it is possible to improve the resolution by increasing the numbers of physical antennas and snapshots after matched filtering, such methods generally give rise to increase in complexity. In this paper, we propose to improve the resolution by optimally allocating the number of transmit and receive antennas. In particular, we show that the performance is optimized when the number of the receive antennas is approximately twice that of transmit antennas.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.175-178
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• 2005

In this paper, a carrier frequency offset (CFO) estimator is proposed for the interleaved OFDMA uplink systems. It is based on the estimation of signal parameters via rotational invariance technique (ESPRIT). Compared with the Cao's estimator, the proposed estimator has low computational complexity. Simulation results demonstrate that the proposed estimator performs better than Cao's estimator at the relatively low SNR region. Hence, the proposed estimator is more applicable to the practical environments than the Cao’s estimator.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.251-252
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• 2006

In this paper, we presented an extension of the broadband DOA estimation method using frequency-domain frequency-invariant beamforming (FDFIB). The technique uses FDFIB instead of conventional frequency invariant beamforming (FIB) methods. And different narrowband DOA estimation methods, MUSIC, ESPRIT, and MPM, are used respectively. A comparison is made to demonstrate that the FDFIB-MPM not only offers a better resolution than the FDFIB-MUSIC, FDFIB-ESPRIT, but also it is computationally very efficient.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.78-84
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• 2016

Weapon, command, and communication system have been continually developed in the Korean military since last several decades. However, it is always asked to make a more effort on improving the ability of combat capability through people in order to achieve and maximize military power. In terms of improving the battlefield leadership, this research focused on ROTC(Reserve Officers'Training Corps), because the training junior officers lays a great foundation on basic strength of the military. This study theoretically and empirically examined the ROTC's quality and effectiveness of leadership. The proposed research model and hypotheses are mainly composed of four factors: personality, esprit de corps, and professionalism as independent variables; leadership effectiveness as a dependent variable. The empirical result revealed that esprit de corps, professionalism, and personality have a meaningful influence on leadership effectiveness. It is suggested that an ongoing training and education program of leadership for ROTC should be applied for achieving a better leadership effectiveness on the battlefield.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.984-996
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• 2007

This paper presents techniques of 2-D scattering center extraction and 2-B ISAR(Inverse SAR) image formation for scattering wave which is scattered by a target. In general, 2-D IFFT is widely used to obtain 2-D scattering center and ISAR image of targets. But, this method has drawbacks, that is poor in a resolution aspect. To overcome these shortcomings with the FT(Fourier Transform)-based method, various techniques of high resolution signal processing were developed. In this paper, algorithms of 2-D scattering center extraction and ISAR image formation such as 2-D MEMP(Matrix Enhancement and Matrix Pencil), 2-D ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and F-18 aircraft to estimate 2-D scattering center and abtain 2-D ISAR image.

• 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.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.289-304
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• 2001

◆ 자동차 부품 데이터사전의 작성 ㆍ PLIB Part42의 방법론 적용 ㆍ ESPRIT PLUS Project 방법론의 적용 ㆍ 자동차 부품 데이터사전의 제시 ㆍ 전자상거래를 위한 정보 표준화 방향을 제시 ◆ 데이터사전 방법론의 유용성 확인 ㆍ 검색, 확장, 수정의 유용성 확인