• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.708-717
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• 2017

Tracking of sound-location is widely used in various area such as intelligent CCTV, video conference and voice commander. In this paper we introduce the real-time sound-location tracking method for smart lecture system using TDoA(Time Difference of Arrival) with orthogonal microphone array on the ceiling. Through discussion on some models of TDoA detection, cross correlation method using linear microphone array is proposed. Orthogonal array with 5 microphone could detect omni direction of sound-location. For real-time detection we adopt the threshold of received energy for eliminating no-voice interval, signed cross correlation for reducing computational complexity. The detected azimuth angles are processed using median filter for lowering the angle deviation. The proposed system is implemented with high performance MCU of TMS320F379D and MEMs microphone module and shows the accuracy of 0.5 and 6.5 in degree for white noise and lectured voice, respectively.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.11-16
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• 2021

This study developed a design to estimate the location of rescue demander using the sound system at disaster site, in the conditions of indoor positioning cannot be performed properly. It is a location tracing system through smart phone application. It generates sound wave information of rescuer at the rescue site, and it can be used as assistant means for indoor location tracing at the disaster site using sound wave receiving measurement technology.

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.393-407
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• 2020

In order to reduce the threat by illegal unmanned aerial vehicles, a tracking system based on sound was implemented. There are three main points to the drone acoustic tracking method. First, it scans the space through variable beam formation to find a sound source and records the sound using a microphone array. Second, it classifies it into a hidden Markov model (HMM) to find out whether the sound source exists or not, and finally, the sound source is In the case of a drone, a sound source recorded and stored as a tracking reference signal based on an adaptive beam pattern is used. The simulation was performed in both the ideal condition without background noise and interference sound and the non-ideal condition with background noise and interference sound, and evaluated the tracking performance of illegal drones. The drone tracking system designed the criteria for determining the presence or absence of a drone according to the improvement of the search distance performance according to the microphone array performance and the degree of sound pattern matching, and reflected in the design of the speech reading circuit.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.343-352
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• 2012

To follow a sound source by a mobile robot, the relative position and orientation of the sound source from the mobile robot have been estimated using a microphone array. In this research, the difference among the traveling times of the sound source to each of three microphones has been used to calculate the distance and orientation of the sound source from the mobile robot which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference comparing to the conventional methods. To generate the tracking direction to the sound source, fuzzy rules are applied and the results are used to control the mobile robot in a real-time. The efficiency of the proposed algorithm has been demonstrated through the real experiments comparing to the conventional approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.1017-1025
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• 2000

The human auditory system has been shown to posses remarkable abilities in the localization and tracking of sound sources. The localization is the result of processing two primary acoustics cues. These are the interaural time difference(ITD) cues and interaural intensity difference(IID) cues at the two ears. In this paper, we propose TEPILD(Time Energy Previous Integration Location Detector) model. TEPILD model is constructed with time function generator, energy function generator, previous location generator and azimuth detector. Time function generator is to process ITD and energy function generator is to process IID. Total average accuracy rate is 99.2%. These result are encouraging and show that proposed model can be applied to the sound source location detector.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.759-766
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• 2016

This paper is on a system design of recognizing sound sources and tracing locations from detecting a section of sound sources which is strong in surrounding environmental sounds about sound sources occurring in an abnormal situation by using signals within the section. In detection of the section with strong sound sources, weighted average delta energy of a short section is calculated from audio signals received. After inputting it into a low-pass filter, through comparison of values of the output result, a section strong in background sound is defined. In recognition of sound sources, from data of the detected section, using an HMM(: Hidden Markov Model) as a traditional recognition method, learning and recognition are realized from creating information to recognize sound sources. About signals of sound sources that surrounding background sounds are included, by using energy of existing signals, after detecting the section, compared with the recognition through the HMM, a recognition rate of 3.94% increase is shown. Also, based on the recognition result, location grasping by using TDOA(: Time Delay of Arrival) between signals in the section accords with 97.44% of angles of a real occurrence location.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.200-210
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• 2014

An active virtual impedance algorithm is newly proposed to track a sound source and to avoid obstacles while a mobile robot is following the sound source. The tracking velocity of a mobile robot to the sound source is determined by virtual repulsive and attraction forces to avoid obstacles and to follow the sound source, respectively. Active virtual impedance is defined as a function of distances and relative velocities to the sound source and obstacles from the mobile robot, which is used to generate the tracking velocity of the mobile robot. Conventional virtual impedance methods have fixed coefficients for the relative distances and velocities. However, in this research the coefficients are dynamically adjusted to elaborate the obstacle avoidance performance in multiple obstacle environments. The relative distances and velocities are obtained using a microphone array consisting of three microphones in a row. The geometrical relationships of the microphones are utilized to estimate the relative position and orientation of the sound source against the mobile robot which carries the microphone array. Effectiveness of the proposed algorithm has been demonstrated by real experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.5
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• pp.25-37
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• 2010

This study is aimed at enhancing mobility rights for the transportation underprivileged that has been made light of relatively compared to normal people. In order to do this, we've suggested having ITS (Intelligent Traffic System) built and improving satisfaction through the test operation of its main system. The existing sound signal device for the visually handicapped has one problem with managing it. Because, the people in charge of it had to visit each problematic site directly to maintain and fix some problems every time it was out of order. Moreover, it couldn't provide sustainable services about voice guidance and the visually handicapped had to control it by either confirming the location of buttons that were installed on the pillar of traffic light and then pressing one of them or using a remote controller on their own. In order to improve such inconveniences, we have created a new typed sound signal device for the visually handicapped by applying the cutting-edge wireless technology based on ergonomics considering actual road situations. Such technology enables it report the status of signal device and light to them by using its voice guidance system automatically every time they have access to it. Additionally, we've already introduced it to a couple of test areas and then known the fact that they recognized traffic situation more conveniently and safely compared to the existing sound signal device. That is above average in terms of satisfaction. In addition to that, we've provided LTS (Location Tracking System - Location-based service intended for elementary students) by utilizing the existing wireless infrastructure and founded the fact that about 87% of their parents were satisfied with the service based on LTS.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.4
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• pp.423-430
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• 2011

The most satisfactory split-beam transducer for fish sizing maintains a wide bearing angle region for correct fish tracking without interference from side lobes and lower sensitivity to fish echoes outside of the main lobe region to correctly measure the angular location of free-swimming fishes in the sound beam. To evaluate the performance of an experimentally developed 50 kHz split-beam transducer, the angular location of a target was derived from the electrical phase difference between the resultant signals for the pair of transducer quadrants in the horizontal and vertical planes consisting of 32 transducer elements. The electrical phase difference was calculated by cross-spectral density analysis for the signals from the pair of receiving transducer quadrants, and the directivity correction factor for a developed split-beam transducer was estimated as the fourth-order polynomial of the off-axis beam angle for the angular location of the target. The experimental results demonstrate that the distance between the acoustic centers for the pair of receiving transducer quadrants can be controlled to less than one wavelength by optimization with amplitude-weighting transformers, and a smaller center spacing provides a range of greater angular location for tracking of a fish target. In particular, a side lobe level of -25.2 dB and an intercenter spacing of $0.96\lambda$($\lambda$= wavelength) obtained in this study suggest that the angular location of fish targets distributing within a range of approximately ${\pm}28^{\circ}$ without interference from side lobes can be measured.