• 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.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.115-122
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• 2011

In this paper, we present a method to estimate an accurate real-time sound source direction based on time delay of arrival by using generalized cross correlation with four cross-type microphones. In general, existing systems have two disadvantages such as system embedding limitation due to the necessity of data acquisition for signal processing from microphone input, and real-time processing difficulty because of the increased number of channels for sound direction estimation using DSP processors. To cope with these disadvantages, the system considered in this paper proposes hardware design for enhanced real-time processing using microphone array signal processing. An accurate direction estimation and its design time reduction is achieved by means of an efficient hardware design using spatial segmentation methods and verification techniques. Finally we develop a system which can be used for embedded systems using a sound codec and an FPGA chip. According to experimental results, the system gives much faster real-time processing time compared with either PC-based systems or the case with DSP processors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.3
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• pp.148-151
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• 2013

A new direction of arrival estimation method using effects of model errors and sensitivity analysis is proposed. Since a desired signal is obtained after interference rejection through correction effects of model error, the effect of channel interference on the estimation is significantly reduced. Through simulation, we show that the proposed method offers significantly improved estimation resolution and accuracy relative to existing method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.224-228
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• 2015

In this paper, we study the method for desired signals estimation that array antennas are received signals. We apply sub spatial method of direction of arrival algorithm and adaptive array antennas in order to remove interference and noise signal of received antenna signals. Array response vector of adaptive array antenna is probability, it is correctly estimation of direction of arrival of targets to update weight signal. Desired signals are estimated updating covariance matrix after moving interference and noise signals among received signals. We estimate signals using eigen decomposition and eigen value, high resolution direction of arrival estimation algorithm is devided signal sub spatial and noise sub spatial. Though simulation, we analyze to compare proposed method with general method.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.191-199
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• 2020

Currently, studies on the estimation algorithm based on compressive sensing are actively underway, but to the best of our knowledge, no study on the performance of the Sparse Spectrum Fitting (SpSF) algorithm in nonuniform sensor arrays has been made. This paper deals with the derivation of the compressive sensing based covariance fitting algorithm extended to the frequency domain. In addition, it shows the performance of directon-of-arrival estimation of the frequency domain SpSF algorithm in non-uniform linear sensor array system and the sensor array failure situation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2879-2890
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• 2020

In this paper, we study the estimation of angle, range and polarization parameters of a bistatic polarization sensitive frequency diverse array multiple-input multiple-output (PSFDA-MIMO) radar system. The application of polarization sensitive array in receiver is explored. A signal model of bistatic PSFDA-MIMO radar system is established. In order to utilize the multi-dimensional structure of array signals, the matched filtering radar data can be represented by a third-order tensor model. A joint estimation of the direction-of-departure (DOD), direction-of-arrival (DOA), range and polarization parameters based on parallel factor (PARAFAC) algorithm is proposed. The proposed algorithm does not need to search spectral peaks and singular value decomposition, and can obtain automatic pairing estimation. The method was compared with the existing methods, and the results show that the performance of the method is better. Therefore, the accuracy of the parameter estimation is further improved.

• Convergence Security Journal
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• v.22 no.2
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• pp.105-114
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• 2022

This paper is presents an intelligent control system that visualizes the direction of arrival for hearing impaired using personal mobility, and aims to recognize and prevent dangerous situations caused by sound such as alarm sounds and crack sounds on roads. The position estimation method of sound source uses a machine learning classification model characterized by generalized correlated phase transformation based on time difference of arrival. In the experimental environment reproducing the road situations, four classification models learned after extracting learning data according to wind speeds 0km/h, 5.8km/h, 14.2km/h, and 26.4km/h were compared with grid search cross validation, and the Muti-Layer Perceptron(MLP) model with the best performance was applied as the optimal algorithm. When wind occurred, the proposed algorithm showed an average performance improvement of 7.6-11.5% compared to the previous studies.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.6
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• pp.768-775
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• 2009

In this paper, the sound source localization system in real time which uses the time delay of arrival signal is proposed. This system uses minimum microphones and surveillance camera for estimation of the sound source localization and sound direction. To apply this system to the military field, four models(model1~model4) are derived. Model 1 can be used to evaluate the sound source localization at the long distance. Model2 and model3 can be applied to estimate the sound direction. Model4 is useful for the special purpose and potable device. It is possible for this system to be used for the military guard and surveillance. As a result of experiments, It is shown that this system can estimate the sound source localization and the sound direction using minimum microphones.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.6
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• pp.539-544
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• 2016

This paper improves Sherman's two-pulse method for angle estimation of two unresolved targets in phase comparison monopulse radar. The proposed method provides the angle information with only a single-pulse measurement instead of two pulses. The proposed method can estimate a single-target angle by single-target indicator, in contrast with previous techniques. The accuracy of angle estimation for proposed method is demonstrated by simulations.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.367-373
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• 2016

We propose an improved direction of arrival (DoA) estimation algorithm based on co-prime array and propagator method. The propagator method with co-prime array does not require singular value decomposition (SVD) requiring much less computational complexity but exhibiting somewhat worse performance in comparison with MUSIC based on co-prime array. We notice that one cause of the performance degradation was in the avoidance of the usage of the diagonal elements of the signal autocorrelation matrix that contains the noise power spectral density. So we propose an algorithm with the diagonal elements of the signal autocorrelation matrix based on the fact that the noise power spectral density can be estimated using noise observation over a long period of time. We observe, through simulations, that the proposed scheme in this paper improves the performance, with 4 times more computational requirement, by signal-to-noise ratio of 1.5dB and by DoA resolution of $0.7^{\circ}$ at the detection probability of 95% compared with the previously introduced co-prime array propagator scheme, resulting in performance much closer to that of co-prime array-based MUSIC scheme.