• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.782-790
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• 2014

In this paper, we apply the 2-D Matrix Pencil Method(MPM) to the estimation of the direction of arrival(DOA) of multiple signals of interest(SOIs) in bistatic MIMO radar. The 2-D MPM shows remarkable performance under a low SNR environment and low computational complexity to estimate the DOA of multiple SOIs. Also, it is possible to estimate the direction of departure(DOD) which is an angle from transmitter to target. To verify the proposed algorithm, we applied the proposed algorithm to a uniformly spaced linear array(ULA) and compared the RMSE(Root Mean Square Error) of DOA and DOD under the various SNR with those of the 2-D Capon algorithm.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.293-301
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• 2022

Direction of arrival (DOA) estimation of space signals is a basic problem in array signal processing. DOA estimation based on the multiple signal classification (MUSIC) algorithm can theoretically overcome the Rayleigh limit and achieve super resolution. However, owing to its inadequate real-time performance and accuracy in practical engineering applications, its applications are limited. To address this problem, in this study, a DOA estimation algorithm with high parallelism and precision based on an analysis of the characteristics of complex matrix eigenvalue decomposition and the coordinate rotation digital computer (CORDIC) algorithm is proposed. For parallel and single precision, floating-point numbers are used to construct an orthogonal identity matrix. Thus, the efficiency and accuracy of the algorithm are guaranteed. Furthermore, the accuracy and computation of the fixed-point algorithm, double-precision floating-point algorithm, and proposed algorithm are compared. Without increasing complexity, the proposed algorithm can achieve remarkably higher accuracy and efficiency than the fixed-point algorithm and double-precision floating-point calculations, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• ETRI Journal
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• v.26 no.1
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• pp.45-47
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• 2004

A resolution enhancement method for estimating the direction-of-arrival (DOA) of signals is presented. The proposed method is by virtually expanding a real array into virtual arrays and then averaging the spatial spectrum of the virtual arrays, each of which has a different aperture size. Superior DOA resolutions are shown in comparison with the standard algorithm, MUltiple SIgnal Classification (MUSIC), for incoherent signals incident on a uniform circular array.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.121-131
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• 2015

Passive emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. Accurate emitter localization can be expected when utilizing continuous measurable parameters and a appropriate combination of theirs. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to choose a appropriate combination of parameters for a better localization performance. And we propose the passive emitter localization method based on Levenberg-Marquardt algorithm with combined TDOA/FDOA and DOA to achieve better accuracy of emitter localization which is located on the ground and stationary. In addition, we present a method for determining the initial emitter position for LM algorithm's input to avoid the divergence of estimation and local minimum.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.219-223
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• 2003

This paper describes an estimation of DOA(Direction Of Arrival) measurement system using DBF receiver with linear array antenna. This DBF receiver is composed of resistive FET mixer using low IF mettled. A radio frequency(RF), a local oscillator(LO) and ail intermediate frequency(IF) considered in this research are 2.09 GHz, 2.08 GHz and 10 MHz, respectively. This receiver is composed of a band-pass filter, a low-pass filter, a DC bias circuit. DOA measurement system is consist of linear array antenna, DBF receiver, AD control box and computer in the anechoic chamber. Receiving antenna is 4-array monopole antenna and DBF receiver is 4-Ch resistive FET mixer without amplifier. DOA algorithm is implemented using MUSIC algorithm with high resolution. We show that the results of DOA is $-30^{\circ},\;0^{\circ}$ and $60^{\circ}$, respectively. And we know that DOA estimation error occur by antenna radiation pattern and fabrication error of antenna array.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.11
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• pp.81-86
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• 2004

Hybrid beamformer composed of Direction-of-Arrival (DOA) based scheme followed by Maximal Ratio Combining (MRC) is proposed to overcome the degradation due to inaccurate channel estimation caused by insufficient pilot power, which happens in conventional Single-Input Multiple-Output (SIMO) Code Division Multiple Access (CDMA) reverse link. The proposed scheme could provide more accurate channel estimation and interference reduction at the expense of diversity gam in the spatially correlated SIMO channel. As a result, hybrid scheme outperforms conventional MRC beamformer for six or more antennas in the channel environment, in which Angle-of-Spread (AOS) is within 30$^{\circ}$.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.759-768
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• 2016

Direction of arrival (DOA) estimation of multiple sources using sensor arrays has been widely studied in the last few decades, particularly, the spherical harmonic analysis utilizing a spherical array. Both the number of sensors on the aperture and size of the sphere can affect the estimation accuracy dramatically. However, those two factors are conflicted to each other in a single spherical array. In this paper, a multiple spherical arrays structure is proposed to provide an alternative design to the traditional single spherical array for the spherical harmonic decomposition, to obtain better localization performance. The new structure consists of several identical spheres in a given area, and the microphones are placed identically on each sphere. The spherical harmonic analysis algorithm using the new multiple array structure for the problem of multiple acoustic sources localization is presented. Simulation results show that the multiple spherical arrays can provide a more accurate direction of arrival (DOA) estimation for the multiple sources than that of a single spherical array, distinguish several adjacent sources more efficiently, and reduce the number of microphones on each sphere without decreasing its’ estimation accuracy.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.103-110
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• 2012

In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. Using the inverse of the eigenvalue-weighted eigen spectra, the algorithm detects the DOAs of multiple sources. To apply the algorithm in target signal detection for GSC-based beamforming, we utilize its spectral response for the DOA of the target source in noisy conditions. The performance of the proposed target signal detection method is compared with those of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics (ROC) curves.

• ETRI Journal
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• v.28 no.6
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• pp.761-769
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• 2006

In this paper, we address the problem of closely spaced source localization using sensor array processing. In particular, the performance efficiency (measured in terms of the root mean square error) of the unconditional maximum likelihood (UML) algorithm for estimating the direction of arrival (DOA) of near-field sources is evaluated. Four parameters are considered in this evaluation: angular separation among sources, signal-to-noise ratio (SNR), number of snapshots, and number of sources (multiple sources). Simulations are conducted to illustrate the UML performance to compute the DOA of sources in the near-field. Finally, results are also presented that compare the performance of the UML DOA estimator with the existing multiple signal classification approach. The results show the capability of the UML estimator for estimating the DOA when the angular separation is taken into account as a critical parameter. These results are consistent in both low SNR and multiple-source scenarios.