• Title/Summary/Keyword: source localization

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An efficient space dividing method for the two-dimensional sound source localization (2차원 상의 음원위치 추정을 위한 효율적인 영역분할방법)

  • Kim, Hwan-Yong;Choi, Hong-Sub
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.5
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    • pp.358-367
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    • 2016
  • SSL (Sound Source Localization) has been applied to several applications such as man-machine interface, video conference system, smart car and so on. But in the process of sound source localization, angle estimation error is occurred mainly due to the non-linear characteristics of the sine inverse function. So an approach was proposed to decrease the effect of this non-linear characteristics, which divides the microphone's covering space into narrow regions. In this paper, we proposed an optimal space dividing way according to the pattern of microphone array. In addition, sound source's 2-dimensional position is estimated in order to evaluate the performance of this dividing method. In the experiment, GCC-PHAT (Generalized Cross Correlation PHAse Transform) method that is known to be robust with noisy environments is adopted and triangular pattern of 3 microphones and rectangular pattern of 4 microphones are tested with 100 speech data respectively. The experimental results show that triangular pattern can't estimate the correct position due to the lower space area resolution, but performance of rectangular pattern is dramatically improved with correct estimation rate of 67 %.

Influence of Sensor Noise on the Localization Error in Multichannel SQUID Gradiometer System (다채널 스퀴드 미분계에서 센서 잡음이 위치추정 오차에 미치는 영향)

  • 김기웅;이용호;권혁찬;김진목;정용석;강찬석;김인선;박용기;이순걸
    • Progress in Superconductivity
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    • v.5 no.2
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    • pp.98-104
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    • 2004
  • We analyzed a noise-sensitivity profile of a specific SQUID sensor system for the localization of brain activity. The location of a neuromagnetic current source is estimated from the recording of spatially distributed SQUID sensors. According to the specific arrangement of the sensors, each site in the source space has different sensitivity, that is, the difference in the lead field vectors. Conversely, channel noises on each sensor will give a different amount of the estimation error to each of the source sites. e.g., a distant source site from the sensor system has a small lead-field vector in magnitude and low sensitivity. However, when we solve the inverse problem from the recorded sensor data, we use the inverse of the lead-field vector that is rather large, which results in an overestimated noise power on the site. Especially, the spatial sensitivity profile of a gradiometer system measuring tangential fields is much more complex than a radial magnetometer system. This is one of the causes to make the solutions of inverse problems unstable on intervening of the sensor noise. In this study, in order to improve the localization accuracy, we calculated the noise-sensitivity profile of our 40-channel planar SQUID gradiometer system, and applied it as a normalization weight factor to the source localization using synthetic aperture magnetometry.

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Noise source localization using comparison between candidate signal and beamformer output in time domain (시간 영역의 빔출력과 후보 신호 사이의 비교를 통한 소음원의 위치 추정)

  • Kim, Koo-Hwan;Kim, Yang-Hann
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2010.10a
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    • pp.543-543
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    • 2010
  • The objective of this research is estimating the location of interested sound source by using the similarity between a beamformer output in time domain and the candidate signal. The waveform of beamformer output at the location of sound source is similar with the waveform emitted by that source. To estimate the location of sound source by using this feature, we define quantified similarity between candidate signal and beamformer output. The candidate signal describes the signal which is generated by interested source. In this paper, similarity is defined by four methods. The two methods use time vector comparison, and the other two methods use time-frequency map or linear prediction coefficients. To figure out the results and performance of localization by using similarities, we demonstrate two conditions. The one is when two pure tone sources exist and the other condition is when several bird sounds exist. As a consequence, inner product with two time-vectors and structural similarity with spectrograms can estimate the locations of interest sound source.

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Ultrasonic Source Localization and Visualization Technique for Fault Detection of a Power Distribution Equipment (배전설비 결함 검출을 위한 초음파 음원 위치추정 및 시각화 기법)

  • Park, Jin Ha;Jung, Ha Hyoung;Lyou, Joon
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.4
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    • pp.315-320
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    • 2015
  • This paper describes the implemenation of localization and visualization scheme to find out an ultrasonic source caused by defects of a power distribution line equipment. To increase the fault detection performance, $2{\times}4$ sensor array is configured with MEMS ultrasonic sensors, and from the sensor signals aquired, the azimuth and elevation angles of the ultrasonic source is estimated based on the delay-sum beam forming method. Also, to visualize the estimated location, it is marked on the background image. Experimental results show applicability of the present technique.

Closed-form Nonlinear Least-Squares Source Localization from Time-Difference of Arrival Measurements in Planar Space (평면공간에서 다중 센서간 도달 시간차를 이용한 해석적인 최소제곱오차 음원 위치 추정 방법)

  • Shin, Dong-Hoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.4
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    • pp.694-699
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    • 2011
  • A closed-form technique is presented for estimating a single source location from a set of noisy time delay measurements between distributed sensors. The localization formula is derived from nonlinear least squares minimization over the unknowns of target range and bearing in polar coordinates. Computer simulation results are provided for the purpose of performance analysis. Constrained least squares minimization method with prior source location information is also discussed.

Source Localization of Single Impact Based on Higher Order Time Frequency (고차-시간 주파수 기술을 이용한 평판에서의 충격 위치추적)

  • Moon, Yoo-Sung;Lee, Sang-Kwon;Yang, Hong-Goon
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.2
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    • pp.129-136
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    • 2011
  • The aim of this paper is to present the method of identifying the impact location on the plate. This basic research has the future purpose to achieve the human-interaction technology based on the signal processing, piezoelectric materials, and wave propagation. The present work concerning the location identification of a single impact on the plate simulated the waveform numerically generated by impact force and applied the SWFOM(sliced Wigner higher fourth order moment) to the waveform to get the arrival time differences due to impact force between three sensors attached to the plate. The simulated signal is useful to get the information for time interval for the only direct wave. This information is used the source localization by using experimental work. The measured signal is also used for source localization of a single impact based on the higher order time frequency as a novel work.

AE source on-line localization on material with unknown acoustic wave propagation velocity (전파속도를 알수 없는 재료에서의 AE 발생위치 온라인 측정)

  • Jhang, Kyung-Young;Lee, Weon-Heum;Kim, Dal-jung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.22 no.3
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    • pp.688-694
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    • 1998
  • The ability to locate the defects in materials is one of the major attrations of the acoustic emission(AE) technique. The most conventional method for planar AE source localization is to place three or more AE sensors on the plate and to determine the source position by measuring the differences in the arrival times of the AE wave at the sensors, which is called as triangulation method. But this method can not be applied in the material of which elastic wave propagtion velocity is not known. In this paper, we propose two methods, vector method and error minimization method, for AE source location on the material with unknown AE wave velocity. In this method, it is not needed to know the propagation velocity previously, that is, we can apply this method to arbitrary material of which properties are not known exactly. Also, in this paper, the robustness to the error in the measurement of time differences are discussed for both methods. Finally, in order to evaluate the actual performances, experiments using a pencil lead break as the AE source were carried out on the aluminum plate.

The effect of model parameters on single dipole source tracing in EEG (모델 변수가 EEG의 Single Dipole Source 추정에 끼치는 영향에 관한 연구)

  • 박기범;박인호;김동우;배병훈;김수용;박찬영;김신태
    • Progress in Medical Physics
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    • v.5 no.1
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    • pp.41-53
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    • 1994
  • The accurate localization of electrical sources in the brain is one of the most important questions in EEG, especially in the analysis of evoked responses and of epileptiform spike activity. A detailed simulation study of single dipole source estimation based on EEG is given in this paper. The effects of dipole model parameters on single dipole source tracing in EEG are examined in some detail using the Monte Carlo simulation. The error of source localization is found to be greatly influenced by how the electrodes are distributed over the head and the number of them.

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Sound Source Localization using HRTF database

  • Hwang, Sung-Mok;Park, Young-Jin;Park, Youn-Sik
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.751-755
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    • 2005
  • We propose a sound source localization method using the Head-Related-Transfer-Function (HRTF) to be implemented in a robot platform. In conventional localization methods, the location of a sound source is estimated from the time delays of wave fronts arriving in each microphone standing in an array formation in free-field. In case of a human head this corresponds to Interaural-Time-Delay (ITD) which is simply the time delay of incoming sound waves between the two ears. Although ITD is an excellent sound cue in stimulating a lateral perception on the horizontal plane, confusion is often raised when tracking the sound location from ITD alone because each sound source and its mirror image about the interaural axis share the same ITD. On the other hand, HRTFs associated with a dummy head microphone system or a robot platform with several microphones contain not only the information regarding proper time delays but also phase and magnitude distortions due to diffraction and scattering by the shading object such as the head and body of the platform. As a result, a set of HRTFs for any given platform provides a substantial amount of information as to the whereabouts of the source once proper analysis can be performed. In this study, we introduce new phase and magnitude criteria to be satisfied by a set of output signals from the microphones in order to find the sound source location in accordance with the HRTF database empirically obtained in an anechoic chamber with the given platform. The suggested method is verified through an experiment in a household environment and compared against the conventional method in performance.

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Model-based Clustering of DOA Data Using von Mises Mixture Model for Sound Source Localization

  • Dinh, Quang Nguyen;Lee, Chang-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.59-66
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    • 2013
  • In this paper, we propose a probabilistic framework for model-based clustering of direction of arrival (DOA) data to obtain stable sound source localization (SSL) estimates. Model-based clustering has been shown capable of handling highly overlapped and noisy datasets, such as those involved in DOA detection. Although the Gaussian mixture model is commonly used for model-based clustering, we propose use of the von Mises mixture model as more befitting circular DOA data than a Gaussian distribution. The EM framework for the von Mises mixture model in a unit hyper sphere is degenerated for the 2D case and used as such in the proposed method. We also use a histogram of the dataset to initialize the number of clusters and the initial values of parameters, thereby saving calculation time and improving the efficiency. Experiments using simulated and real-world datasets demonstrate the performance of the proposed method.