• Smart Media Journal
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• v.8 no.4
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• pp.85-90
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• 2019

The Ultra-Wide Band sensor is widely used as a wireless indoor localization technology with frequency bands in the GHz range. Meanwhile, in museums, not only the real-time location of visitors but also information on visit route and duration time is required for patrons' behavior analysis. In this paper, the analysis system based Ultra-Wide Band radar for visitor's viewing behavior is introduced and experimented in the real environment. We built the system in National Museum of Korea, and its 22 Ultra-Wide Band radar sensors receive the real-time location of their visitors: this analyzes the visit route and visit time for patrons.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.2
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• pp.183-189
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• 2010

A localization system for indoor robots is an important technology for robot navigation in a building. Our localization system imports the GPS system and consists of more than 3 satellite beacons and a receiver. Each beacon emits both an ultrasonic wave and radio frequency. The receiver in the robot computes the distance from it to the beacon by measuring the flying time difference between ultrasonic wave and radio frequency. It then computes its position with the distance information from more than 3 beacons whose positions are known. However, the distance information includes errors caused from the ultrasonic sensors; we found it to be limited to within one period of a wave (${\pm}2\;cm$ tolerance). This paper presents a method for predicting the maximum position error due to distance information errors by using Taylor expansion and singular value decomposition (SVD). The paper also proposes a measuring parameter such as sensitivity to represent the accuracy of the indoor robot localization system in determining the robot's position with regards to the distance error.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.483-491
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• 2016

Precision of theoretical group velocity of waves in shell structures was discussed for the purpose of source localization of loose parts impact in pressure vessels of nuclear power plants. Estimating exact location of loose parts impact inside a reactor or a steam generator is very important in safety management of a NPP. Evaluation of correct propagation velocity of impact signals in pressure vessels, most of which are shell structures, is essential in impact source localization. Theoretical group velocities of impact signals in a plate and a shell were calculated by wave equations and compared to the velocities measured experimentally in a plate specimen and a scale model of a nuclear reactor. The wave equation applicable to source localization algorithm in shell structures was chosen by the study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.69-76
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• 2020

The sound signal radiated from an underwater source is received by the hydrophone of the system, including multi-path time-delay and multi-path signal by sea surface and bottom reflection. The system using a time-delay between received signals for the source localization shows performance degradation due to incoherence by the multi-path propagation environment and the disturbance of a marine environment. Various types of array and signal processing have been used for robust source range and bearing estimation in this environment. In this paper, we use a line array composed of doublet array and an estimated time-delay correction method for robust localization performance in a multi-path propagation environment. Three doublet arrays are located on the same line, and the time-delay between signals received on each doublet array is estimated in a two-step procedure. The estimated time-delay value is obtained by the cross-correlation function and corrected by the interaction formula between the center-frequency of received signal and the geometry of the array with respect to aperture. By this proposed procedure, the range and bearing of source from array were calculated. In order to confirm the validity of the proposed method and array, we simulated localization and estimation using the Monte-Carlo method.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.670-691
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• 2013

In RSSI-based RFID(Radio Frequency IDentification) indoor localization system, the signal path loss model of each sub-region is different from others in the whole localization area due to the influence of the multi-path phenomenon and other environmental factors. Therefore, this paper divides the localization area into many sub-regions and constructs separately the signal path loss model of each sub-region. Then an improved LANDMARC method is proposed. Firstly, the deployment principle of RFID readers and tags is presented for constructing localization sub-region. Secondly, the virtual reference tags are introduced to create a virtual signal strength space with RFID readers and real reference tags in every sub-region. Lastly, k nearest neighbor (KNN) algorithm is used to locate the target object and an error compensating algorithm is proposed for correcting localization result. The results in real application show that the new method enhances the positioning accuracy to 18.2% and reduces the time cost to 30% of the original LANDMARC method without additional tags and readers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3950-3969
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• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.150-156
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• 2007

Noise is generated by several causes, when signal is processed. Hence, it generates error in the process of data transmission and decreases recognition ratio of image and speech data. Therefore, after eliminating those noises, a variety of methods for reconstructing the signal have been researched. Recently, wavelet transform which has time-frequency localization and is possible for multiresolution analysis is applied to many fields of technology. Then threshold-and correlation-based methods are proposed for removing noise. But, conventional methods accept a lot of noise as an edge and are impossible to remove the additive white Gaussian noise (AWGN) and the impulse noise at the same time. Therefore, in this paper we proposed new wavelet-based algorithm for reconstructing degraded signal by noise and compared it with conventional methods.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.40-43
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• 2015

In this paper, the effects of the leading and the following sounds with single frequency on sound localization are investigated. The sounds with different levels and ISIs(Inter Stimuli Intervals) were used. The width of test sound is 2ms, and those of the leading and the following sounds are 10ms. 1 kHz of the test sound is utilized. The arrival time difference in the subject's ears is set to be 0.5ms. The four kinds of level differences used for one ISI are 0, -10, -15, and -20dB interval. The leading sound is found to have more effect on sound localization than the following sound is. The effect of the leading sound is also found to be dependent on the value of ISI. When the value of the ISI is small, different effects affecting the sound localization are observed.