• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• Smart Structures and Systems
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• v.8 no.2
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• pp.219-237
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• 2011

This paper presents novel research into the source localization of multiple impacts. Source localization technology for single impact loads in a plate structure has been used for health monitoring. Most of research on source localization has been focused only on the localization of single impacts. Overlapping of dispersive waves induced by multiple impacts and reflection of those waves from the edge of the plate make it difficult to localize the sources of multiple impacts using traditional source localization technology. The method solving the overlapping problem and the reflection problem is presented in the paper. The suggested method is based on pre-signal processing technology using band pass filter and optimal filter. Results from numerical simulation and from experimentation are presented, and these verify the capability of the proposed method.

• 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.

• MALSORI
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• no.67
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• pp.135-147
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• 2008

In this paper, we propose a method for source localization in reverberant environments based on an adaptive eigenvalue decomposition (AED) algorithm which directly estimates channel impulse responses from a speaker to microphones. Unfortunately, the AED algorithm may suffer from whitening effects on channels estimated from temporally correlated natural sounds. The proposed method which applies sparse priors to the estimated channels can avoid the temporal whitening and improve the performance of source localization in reverberant environments. Experimental results show the effectiveness of the proposed method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.3
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• pp.220-226
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• 2011

This paper presents the novel work for source localization of serial multiple impacts in a plate sructure. It is difficult to identify the source of serial multiple impacts with the current source localization techenology(SLT) because of the overlapping of dispersive wave induced by multiple impacts and the reflaction from the edge of the plate. In this paper, the new method is suggested for source localization. The method is developed based on the SLT with pre-signal processing such as some limitation for the selection of three sensors, the frequency range for TFA and impact time interval. Results from numerical simulation and experiment in isotropic plate structure are presented, which show the capability of the proposed method.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.237-244
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• 2008

Nowadays, research on human-robot interaction has been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report a speaker localization system with six microphones for a humanoid robot called MAHRU from KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. The proposed method, using the TDOA-based feature matrix and its algorithm based on MSAE, effortlessly localizes a sound source without any requirement for calculating approximate nonlinear equations. To verify the solid performance of our speaker localization system for a humanoid robot, we present various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.155-160
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• 2011

In distributed source localization where sensors transmit measurements to a fusion node, we address the sensor selection problem where the goal is to find the best set of sensors that maximizes localization accuracy when quantization of sensor measurements is taken into account. Since sensor selection depends heavily upon rate assigned to each sensor, joint optimization of rate allocation and sensor selection is required to achieve the best solution. We show that this task could be accomplished by solving the problem of allocating rates to each sensor so as to minimize the error in estimating the position of a source. Then we solve this rate allocation problem by using the generalized BFOS algorithm. Our experiments demonstrate that the best set of sensors obtained from the proposed sensor selection algorithm leads to significant improvements in localization performance with respect to the set of sensors determined from a sensor selection process based on unquantized measurements.

• Investigative Magnetic Resonance Imaging
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• v.7 no.2
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• pp.108-115
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• 2003

Purpose : To evaluate the effect of the gradient switching noise on the ECD source localization with the EEG data recorded during the MRI scan. Materials and Methods : We have fabricated a spherical EEG phantom that emulates a human head on which multiple electrodes are attached. Inside the phantom, electric current dipole(ECD) sources are located to evaluate the source localization error. The EEG phantom was placed in the center of the whole-body 3.0 Tesla MRI magnet, and a sinusoidal current was fed to the ECD sources. With an MRI-compatible EEG measurement system, we recorded the multi channel electric potential signals during gradient echo single-shot EPI scans. To evaluate the effect of the gradient switching noise on the ECD source localization, we controlled the gradient noise level by changing the FOV of the EPI scan. With the measured potential signals, we have performed the ECD source localization. Results : The source localization error depends on the gradient switching noise level and the ECD source position. The gradient switching noise has much bigger negative effects on the source localization than the Gaussian noise. We have found that the ECD source localization works reasonably when the gradient switching noise power is smaller than $10\%$ of the EEG signal power. Conclusion : We think that the results of the present study can be used as a guideline to determine the degree of gradient switching noise suppression in EEG when the EEG data are to be used to enhance the performance of fMRI.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.270-274
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• 2007

In this paper, we present a Sound Source Localization (SSL) based GCC (Generalized Cross Correlation)-PHAT (Phase Transform) and new measurement method of angle with robot auditory system for a network-based intelligent service robot. The main goal of this paper is to analysis performance of TDOA and GCC-PHAT sound source localization method and new angle measurement method is compared. We use GCC-PHAT for measuring time delays between several microphones. And sound source location is calculated by using time delays and new measurement method of angle. The robot platform used in this work is wever-R2, which is a network-based intelligent service robot developed at Intelligent Robot Research Division in ETRI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.434-439
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• 2013

It is very difficult to monitor the blind spots that are not recognized by traditional surveillance camera (CCTV) systems, and the surveillance efficiencies are very low though many accidents/events can be solved by the systems. In this paper, the fuzzy logic based sound source localization system using sound strength in the underground parking lot is suggested and the performance of the system is analyzed in order to enhance the stabilization and the accuracy of the localization algorithm in the suggested system. It is confirmed that the localization stabilization of the localization algorithm (SLA_fuzzy) using the fuzzy logic in the suggested system is 4 times higher than that of the conventional localization algorithm (SLA). In addition to this, the localization accuracy of the SLA_fuzzy in the suggested system is 29% higher than that of the SLA.