• Title/Summary/Keyword: Source localization

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A Comparative Study of Sound Source Localization Algorithms for Portable Devices (휴대용 단말기에서 음원 위치 추적 기술 비교 연구)

  • Chung Jae-Youn;Yook Dong-Suk
    • Proceedings of the KSPS conference
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    • 2006.05a
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    • pp.49-52
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    • 2006
  • The performance of a sound source localization system degrades severely in reverberant and noisy environments. In addition, restriction on the distance between microphones, which is required by portable devices, also lower the system performance. This paper compares the sound source localization algorithms based on time delay of arrival, which are robust to reverberation and noises considering microphone sensor distance. As well, post filter which outputs maximum count time delay is adopted to increase the accuracy.

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An Efficient Representation of Edge Shapes in Topological Maps

  • Doh, Nakju Lett;Chung, Wan-Kyun
    • ETRI Journal
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    • v.29 no.5
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    • pp.655-666
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    • 2007
  • There are nodes and edges in a topological map. Node data has been used as a main source of information for the localization of mobile robots. In contrast, edge data is regarded as a minor source of information, and it has been used in an intuitive and heuristic way. However, edge data also can be used as a good source of information and provide a way to use edge data efficiently. For that purpose, we define a data format which describes the shape of an edge. This format is called local generalized Voronoi graph's angle (LGA). However, the LGA is constituted of too many samples; therefore, real time localization cannot be performed. To reduce the number of samples, we propose a compression method which utilizes wavelet transformation. This method abstracts the LGA by key factors using far fewer samples than the LGA. Experiments show that the LGA accurately describes the shape of the edges and that the key factors preserve most information of the LGA while reducing the number of samples.

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A method for localization of multiple drones using the acoustic characteristic of the quadcopter (쿼드콥터의 음향 특성을 활용한 다수의 드론 위치 추정법)

  • In-Jee Jung;Wan-Ho Cho;Jeong-Guon Ih
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.3
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    • pp.351-360
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    • 2024
  • With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

Sound Source Localization Method Based on Deep Neural Network (깊은 신경망 기반 음원 추적 기법)

  • Park, Hee-Mun;Jung, Jong-Dae
    • Journal of IKEEE
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    • v.23 no.4
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    • pp.1360-1365
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    • 2019
  • In this paper, we describe a sound source localization(SSL) system which can be applied to mobile robot and automatic control systems. Usually the SSL method finds the Interaural Time Difference, the Interaural Level Difference, and uses the geometrical principle of microphone array. But here we proposed another approach based on the deep neural network to obtain the horizontal directional angle(azimuth) of the sound source. We pick up the sound source signals from the two microphones attached symmetrically on both sides of the robot to imitate the human ears. Here, we use difference of spectral distributions of sounds obtained from two microphones to train the network. We train the network with the data obtained at the multiples of 10 degrees and test with several data obtained at the random degrees. The result shows quite promising validity of our approach.

Implementation of Sound Source Localization Based on Audio-visual Information for Humanoid Robots (휴모노이드 로봇을 위한 시청각 정보 기반 음원 정위 시스템 구현)

  • Park, Jeong-Ok;Na, Seung-You;Kim, Jin-Young
    • Speech Sciences
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    • v.11 no.4
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    • pp.29-42
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    • 2004
  • This paper presents an implementation of real-time speaker localization using audio-visual information. Four channels of microphone signals are processed to detect vertical as well as horizontal speaker positions. At first short-time average magnitude difference function(AMDF) signals are used to determine whether the microphone signals are human voices or not. And then the orientation and distance information of the sound sources can be obtained through interaural time difference. Finally visual information by a camera helps get finer tuning of the angles to speaker. Experimental results of the real-time localization system show that the performance improves to 99.6% compared to the rate of 88.8% when only the audio information is used.

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Sound Source Localization and Separation for Emotional Robot (감성로봇을 위한 음원의 위치측정 및 분리)

  • 김경환;김연훈;곽윤근
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.5
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    • pp.116-123
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    • 2003
  • These days, the researches related with the emotional robots are actively investigated and in progress. And human language, expression, action etc. are merged in the emotional robot to understand the human emotion. However, there are so many sound sources and background noise around the robot, that the robots should be able to separate the mixture of these sound sources into the original sound sources, moreover to understand the meaning of voice of a specific person. Also they should be able to turn or move to the direction of a specific person to observe his expression or action effectively. Until now, the researches on the localization and separation of sound sources have been so theoretical and computative that real-time processing is hardly possible. In this reason for the practical emotional robot, fast computation should be realized by using simple principle. In this paper the methods for detecting the direction of sound sources by using the phase difference between peaks on spectrums, and the separating the sound sources by using fundamental frequency and its overtones of human voice, are proposed. Also by using these methods, it is shown that the effective and real-time localization and separation of sound sources in living room are possible.

Localization of Underwater Noise Sources Using TDOA (Time Difference of Arrival) Method (도달지연시간 기법을 이용한 수중 소음원의 위치추적)

  • Ahn, Byoung-Kwon;Go, Yeong-Ju;Rhee, Wook;Choi, Jong-Soo;Lee, Chang-Sup
    • Journal of the Society of Naval Architects of Korea
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    • v.48 no.2
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    • pp.121-127
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    • 2011
  • As considerable interests in noise emission from a ship have been increased, the need for localization of noise sources of the marine propeller generating cavitation and singing noise is looming large. In many practical cases, cavitation and singing noise occur on a particular position of the certain blade of the propeller. It is so important to know the position of noise source correctly in order to eliminate or suppress unwanted noise. In this study, we develop "noise source localization technology" using TDOA method. Experimental measurements carried out at the circulating water channel and towing tank show that noise source can be clearly identified and localized using TDOA method.

Ground-Platform Sensor Position Optimization Based Hybrid Time Difference of Arrival Method for Airborne Emitter (Hybrid TDOA 알고리즘 기반의 Airborne Emitter 위치탐지를 위한 Ground-Platform 센서의 위치 최적화)

  • Park, Jin-Oh;Lee, Woo-Seok;You, Byung-Sek;Kook, Chan-Ho;Chung, Jae-Woo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.5
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    • pp.886-893
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    • 2010
  • This paper considers the problem of time difference-of-arrival(TDOA) source localization when the TDOA and angle of arrival(AOA) measurements from an airborne emitter source are subject to ground-platform sensor position. The optimization of sensors' position is a challenging problem and a solution with good localization accuracy has yet to be found. This paper proposes an estimator that can achieve these purposes and provides optimized sensor position for good localization accuracy using the proposed estimator. The developed algorithm and sensor position are then examined under the special case of a single airborne source. The theoretical developments are supported by simulations.

A Study on 3-Dimensional Near-Field Source Localization Using Interference Pattern Matching in Shallow Water Environments (천해에서 간섭패턴 정합을 이용한 근거리 음원의 3차원 위치추정 기법연구)

  • Kim, Se-Young;Chun, Seung-Yong;Son, Yoon-Jun;Kim, Ki-Man
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.4
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    • pp.318-327
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    • 2009
  • In this paper, we propose a 3-D geometric localization method for near-field broadband source in shallow water environments. According to the waveguide invariant theory, slope of the interference pattern which is seen in a sensor spectrogram directly proportional to a range of the source. The relative ratio of the range between source and sensors was estimated by matching of two interference patterns in spectrogram. Then this ratio is applied to the Apollonius's circle which shows the locus of a source whose range ratio from two sensors is constant. Two Apollonius's circles from three sensors make the intersection point that means the horizontal range and the azimuth angle of the source. And this intersection point is constant with source depth. Therefore the source depth can be estimated using 3-D hyperboloid equation whose range difference from two sensors is constant. To evaluate a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program and analysis of localization error is demonstrated. From simulation results, error estimate for range and depth is described within 50 m and 15 m respectively.

Performance enhancement of underwater acoustic source localization by nonlinear optimization of multiple parameters (다수 정보들의 비선형 최적화에 의한 수중 음원 위치 추정 성능 향상)

  • Yang, In-Sik;Kwon, Taek-Ik;Kang, Tae-Woong;Kim, Ki-Man
    • The Journal of the Acoustical Society of Korea
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    • v.36 no.6
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    • pp.419-424
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    • 2017
  • TDoA (Time Difference-of Arrival) or DoA (Direction-of-Arrival) can be used for source localization. However, the localizing performance is dependent on relative position between source and receivers, receivers' geometric structure, sound speed, and so on. In this paper we propose a source localization method with enhanced performance that combines multiple information. The proposed method uses the time TDoA, DoA and sound speed as variables. LM (Levenberg-Marquardt) method which is one of nonlinear optimizations is applied. The performances of the proposed method was evaluated by simulation. As result of simulation, the proposed method has the lower average localizing error performance than the previous method.