• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.89-94
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• 2022

This paper proposes a computationally efficient 2-D direction-of-arrival (DoA) estimation method with a uniform rectangular array (URA). This method is called the direct signal-based method in the sense that it is based directly on the phase relationships among the signals arriving at each antenna of an antenna array rather than their correlation matrix. According to the simulation results, it has be shown that the direct signal-based method, with much less computations than any existing methods, yields the performance comparable to that of the MUSIC (MUltiple SIgnal Classification) method in terms of the root-mean-squared error (RMSE) and the maximum absolute error.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.81-87
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• 2023

With the development of BCI devices, it is now possible to use EEG control technology to move the robot's arms or legs to help with daily life. In this paper, we propose a customized vehicle control model based on BCI. This is a model that collects BCI-based driver EEG signals, determines information according to EEG signal analysis, and then controls the direction of the vehicle based on the determinated information through EEG signal analysis. In this case, in the process of analyzing noisy EEG signals, controlling direction is supplemented by using a camera-based eye tracking method to increase the accuracy of recognized direction . By synthesizing the EEG signal that recognized the direction to be controlled and the result of eye tracking, the vehicle was controlled in five directions: left turn, right turn, forward, backward, and stop. In experimental result, the accuracy of direction recognition of our proposed model is about 75% or higher.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.334-337
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• 2005

The speech intelligibility is one of the most important factors in communication system. The speech intelligibility is related with speech to noise ratio. To enhance the speech to noise ratio, background noise reduction techniques are being developed. As a part of solution to noise reduction, this paper introduces directional microphone using beamforming method and speech filtering method. The directional microphone narrows the spatial range of processing signal into the direction of the target speech signal. The noise signal located in the same direction with speech still remains in the processing signal. To sort this mixed signal into speech and noise, as a following step, a speech-filtering method is applied to pick up only the speech signal from the processed signal. The speech filtering method is based on the characteristics of speech signal itself. The combined directional microphone and speech filtering method gives enhanced performance to speech intelligibility in communication system.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.206-215
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• 2014

Acoustic signal is crucial for the autonomous navigation of underwater vehicles. For this purpose, this paper presents a method of acoustic source localization. The proposed method is based on the probabilistic estimation of time delay of acoustic signals received by two hydrophones. Using Bayesian update process, the proposed method can provide reliable estimation of direction angle of the acoustic source. The acquired direction information is used to estimate the location of the acoustic source. By accumulating direction information from various vehicle locations, the acoustic source localization is achieved using extended Kalman filter. The proposed method can provide a reliable estimation of the direction and location of the acoustic source, even under for a noisy acoustic signal. Experimental results demonstrate the performance of the proposed acoustic source localization method in a real sea environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.45-61
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• 2010

In the communication channel, the received signal is affected by many factors that can cause errors. These effects mean that received signal strength (RSS) based methods incur more errors in measuring distance and consequently result in low precision in the location detection process. As one of the approaches to overcome these problems, we propose using direction calibration to improve the performance of the RSS-based method for distance measurement, and sequentially a weighted least squares (WLS) method using reliability factors in conjunction with a conventional RSS weighting matrix is proposed to solve an over-determined localization process. The proposed scheme focuses on the features of the RSS method to improve the performance, and these effects are proved by the simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.519-527
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• 2014

Adaptive arrays can minimize contributions from interferences incident onto an sensor array while preserving a signal the direction vector of which corresponds to the array steering vector to within a scalar factor. If there exist errors in the steering vector, severe performance degradation can be caused since the desired signal is misunderstood as an interference by the array. This paper presents an adaptive beamforming method which is robust against steering vector errors, exploiting a range of the desired signal direction. In the presented method, an correlation matrix of array response vectors is obtained through integration over the direction range and a minimization problem is formulated using some eigenvectors of the correlation matrix such that a more accurate steering vector than initially given one can be found. The minimization problem is transformed into a relaxed SDP (semidefinite program) problem, which can be effectively solved since it is a sort of convex optimization. Simulation results show that the proposed method outperforms existing ones such as ORM (outside-range-based method) and USM (uncertainty-based method).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.4
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• pp.290-299
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• 2019

Direction-finding equipment with multiple antennas are used to estimate the direction of a signal emitted by a source; they can be used to rescue a victim or locate a specified source. During direction finding, reflection waves are present and signal distortion is observed depending on the external shape and material of a system that incorporates the direction-finding equipment and multiple antennas. Therefore, to accurately estimate the azimuth of the signal source and develop the direction-finding equipment, a calibration should be performed to reflect the influence of the antenna arrangement(layout) and system contour. In this paper, we describe an in-flight calibration method to develop direction-finding equipment to locate communication signals using an aviation system, and we analyze the direction-finding performance when applying phase calibration data obtained through the in-flight calibration.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.119-128
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• 2017

In this paper, the wideband direction finding algorithm and system design method for short duration signal such as frequency hopping or burst signal is presented. The polyphase filterbank that it is possible for the near perfect reconstruction was used as a pre-processing and in each subband power measurement was performed to determine whether the presence of a signal and finally general direction finding algorithm was performed. In addition, various experiments was performed using Matlab Simulink and collected data from wideband receiver to verification of the proposed algorithm.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.