• 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.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2212-2219
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• 2018

This paper describes extended fault location algorithm using estimated remote source impedance. The method uses data only at the local end and the sequence current distribution factors for more accurate estimation. The proposed algorithm can respond to variation of the local and remote source impedance. Therefore, this method is especially useful for transmission lines interconnected to a wind farm that the source impedance varies continuously. The proposed algorithm is very insensitive to the variation in fault distance and fault resistance. The simulation results have shown the accuracy and effectiveness of the proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.885-890
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• 2009

A fault location algorithm using estimated local source impedance after a fault is proposed in this paper. The method uses after fault data only at the local end. It uses the negative sequence current distribution factor for more accurate estimation. The proposed algorithm can keep up with the variation of the local source impedance. Therefore, the proposed algorithm especially is valid for a transmission line interconnected to a wind farm that the equivalent source impedance changes continuously. The performance of the proposed algorithm was verified under various fault conditions using the Simpowersystem of MATLAB Simulink. The proposed algorithm is largely insensitive to the variation in fault distance and fault resistance. The test results show a very high accurate performance.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4E
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• pp.52-60
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• 2001

This paper describes real time implementation of subband sound localization system on a floating-point DSP TI TMS320C31. The system determines two dimensional location of an active speaker in a closed room environment with real noise presents. The system consists of an two microphone array connected to TI DSP hosted by PC. The implemented sound localization algorithm is Subband CPSP which is an improved version of traditional CPSP (Cross-Power Spectrum Phase) method. The algorithm first split the input speech signal into arbitrary number of subband using subband filter banks and calculate the CPSP in each subband. It then averages out the CPSP results on each subband and compute a source location estimate. The proposed algorithm has an advantage over CPSP such that it minimize the overall estimation error in source location by limiting the specific band dominant noise to that subband. As a result, it makes possible to set up a robust real time sound localization system. For real time simulation, the input speech is captured using two microphone and digitized by the DSP at sampling rate 8192 hz, 16 bit/sample. The source location is then estimated at once per second to satisfy real-time computational constraints. The performance of the proposed system is confirmed by several real time simulation of the speech at a distance of 1m, 2m, 3m with various speech source locations and it shows over 5% accuracy improvement for the source location estimation.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.467-469
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• 2001

This paper presents an efficient location estimation methodology for a partial discharge(PD) source in the power transformer. The methodology previously proposed is not suitable for locating a PD source because the ultrasonic signal with medium attenuated through the inner structure. In general, the propagation characteristic of ultrasonic signal with medium is different. Therefore, using this propagation characteristic, we can detect the location of PD source. In this paper, the proposal algorithm finds the PD source using three sensors attached to one side of the transformer without attenuation of the ultrasonic signal and applying the neural network based geometrical method. The proposed methodology demonstrates the effectiveness and validity on an experimental transformer.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1436-1443
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• 1989

In this paper, we propose a maximum-likelihood estimation(MLE) method to obtain the location and the amplitude of the pulses in MPE( multi-pulse excitation)-LPC speech synthesis using multi-pulses as excitation source. This MLE method computes the value maximizing the likelihood function with respect to unknown parameters(amplitude and position of the pulses) for the observed data sequence. Thus in the case of overlapped pulses, the method is equivalent to Ozawa's crosscorrelation method, resulting in equal amount of computation and sound quality with the cross-correlation method. We show by computer simulation: the multi-pulses obtained by MLE method are(1) pseudo-periodic in pitch in the case of voicde sound, (2) the pulses are random for unvoiced sound, (3) the pulses change from random to periodic in the interval where the original speech signal changes from unvoiced to voiced. Short time power specta of original speech and syunthesized speech obtained by using multi-pulses as excitation source are quite similar to each other at the formants.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.35-41
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• 2016

Based on correlation and least square method, a closed-form algorithm for estimating the location of mixed far-field and near-field source is presented using the Uniform Circular Array (UCA). Recently, for a homogeneous circular arrangement case, a correlation based closed-form algorithm is proposed to estimate 2-D angle (azimuth, elevation) and the extended algorithm is proposed to 3-D location (azimuth, elevation, range). These algorithms assume the far-field source or near-field source only. Therefore, for mixed source localization, the proposed algorithm estimates source location with the assumption of far-field source, and then estimates the range to distinguish the far-field from the near-field source. For both cases, numerical experiments have been performed, which confirmed the validity of the proposed algorithm.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.15-21
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• 2020

This paper presents the outlier detection algorithm in the estimation method of a source location and velocity based on two-step weighted least-squares method using time difference of arrival(TDOA) and frequency difference of arrival(FDOA) data. Since the accuracy of the estimated location and velocity of a moving source can be reduced by the outliers of TDOA and FDOA data, it is important to detect and remove the outliers. In this paper, the method to find the minimum inlier data and the method to determine whether TDOA and FDOA data are included in inliers or outliers are presented. The results of numerical simulations show that the accuracy of the estimated location and velocity is improved by removing the outliers of TDOA and FDOA data.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.53-59
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• 2020

This paper relates to an IoT device system that detects sound source and estimates the sound source location. More specifically, it is a system using a sound source direction detection device that can accurately detect the direction of a sound source by analyzing the difference of arrival time of a sound source signal collected from microphone sensors, and track the generation direction of a sound source using an IoT sensor. As a result of a performance test by generating a sound source, it was confirmed that it operates very accurately within 140dB of the acoustic detection area, within 1 second of response time, and within 1° of directional angle resolution. In the future, based on this design plan, we plan to commercialize it by improving the reliability by reflecting the artificial intelligence algorithm through big data analysis.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.129-135
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• 2011

An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.