• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.9-18
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• 2013

In this paper, we design and implement an intelligent system for finding objects with RFID(Radio Frequency IDentification) tag in which an mobile robot can do. The system we developed is a learning system of artificial neural network that uses RSSI(Received Signal Strength Indicator) value as input and absolute coordination value as target. Although a passive RFID is used for location estimation, we consider an active RFID for expansion of recognition distance. We design the proposed system and construct the environment for indoor location estimation. The designed system is implemented with software and the result related learning is shown at test bed. We show various experiment results with similar environment of real one from earning data generation to real time location estimation. The accuracy of location estimation is verified by simulating the proposed method with allowable error. We prepare local test bed for indoor experiments and build a mobile robot that can find the objects user want.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.66-77
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• 2002

This paper deals with an implementation of the navigation parameter extraction technique using the TMS320C80 multimedia video processor (MVP). Especially, this Paper focuses on the relative position estimation algorithm which plays an important role in real-time operation of the overall system. Based on the relative position estimation algorithm using the images obtained at two locations, we develop a fast algorithm that can reduce large amount of computation time and fit into fixed-point processors. Then, the algorithm is reconfigured for parallel processing using the 4 parallel processors in the MVP. As a result, we shall demonstrate that the navigation parameter extraction system employing the MVP can operate at full-frame rate, satisfying real-time requirement of the overall system.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.300-301
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• 2007

본 논문에서는 실시간 스펙트럼 추정기에 기반하여 시간-주파수 영역 반사파 계측 시스템에서의 동축케이블 결함을 검출하는 방법을 제안한다. 시간-주파수 영역 반사파 계측 시스템은 가우시안 포락선(Gaussian Envelop)모양의 첩 신호를 기준신호로 하여 도선에 반사파를 분석하는 기법으로써 타 방법에 비하여 높은 정확도를 자랑하는 것으로 알려져 있다. 하지만 결함 위치를 추정하기 위해 Wigner 시간 주파수 분포 함수를 이용하므로 계산량 증가에 따른 실시간 구현이 어렵다는 단점이 있었다. 이러한 단점을 극복하기 위하여 본 논문에서는 LMS 스펙트럼 추정기를 이용한 시간-주파수 영역 반사파 계측 시스템의 구현방법을 새롭게 제안한다. 제안된 기법은 실제 동축케이블에 대한 실험결과를 통하여 그 성능을 입증하도록 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.150-154
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• 2022

The Automatic Ship Identification System(AIS) is importantly used to evaluate the trajectory of ships and the possibility of collision between ships. However, it is difficult to provide real-time information due to the limitation of the transmission intervals. Most of the studies to improve this are conducted based on ideal data, so there is a problem that it is hard to respond to the actual situation. Therefore, in this paper, we propose a discrete Kalman filter-based method that reflects the turning angle according to the type of trajectory, to provide real-time position information on real-time data. In addition, the accuracy evaluation of the proposed algorithm is conducted through experiments using actual data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2056-2063
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• 2012

In a port terminal, containers are stored and transshipped by yard tractors and crane vehicles. For operation efficiency of the terminal, location information of these vehicles is an essential factor. However, most of port terminals try to estimate location of these assets using indirect methods such as event tracking of shipping or unshipping containers. Because these kinds of events are rarely occurred, location of the event includes seriously locating error compared to a real location of vehicle. In this paper, we propose a real-time asset tracking system to obtain accurate and reliable location of terminal assets. The proposed system overcomes a location estimation error caused by container stacks which interrupt wireless communication. In order to mitigate uncertainty and increase accuracy of location estimation, we designed hardwares and multi-step locating system to resolve additional preblems. We implemented system components, and installed these at a port environment for evaluation. The result shows superiority of the system that the accuracy is approximately 5.87 meters (CEP).

• Journal of the Microelectronics and Packaging Society
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• v.23 no.4
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• pp.119-123
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• 2016

In this paper, we have fabricated the position detection system with LED and optical sensor to detect a position and trace of robot through visible light communication (VLC). The fabricated position detection system did not have been affected by sunlight in outdoor and a fluorescent light in building. Because 4 LEDs, respectively, transmitted different signals, we have known the position of robot. And we have also observed a trajectory of robot in real time.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.6
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• pp.850-856
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• 2012

Bilateration using two fixed nodes has been used in the field of the real time indoor location system in the narrow space such as building or ship passage. However, as the distance between the fixed nodes increases or any obstructions exist in their zone, it is difficult to detect the location of mobile node(user) due to the degradation of its reception ratio. In order to compensate for these problems, this paper presents, based on IEEE 802.15.4a chirp signal, a new real time indoor location system using stride measurement algorithm which can calculate the location through sensors attached to user. The proposed system consists of an ultrasonic sensor to measure the leg length, a geomagnetic sensor to recognize the user's orientation, and an inertial sensor to obtain the angle between the legs. The experimental results are shown that the proposed system has twice or more accurate output compared with conventional indoor location method in the section which is partially out of communication reachability.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.379-385
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• 2007

관성 센서는 외부 장치의 도움 없이 3차원 공간상에서 움직임 측정이 가능하다. 최근 MEMS 기술의 발달로 소형 저가 관성 센서(가속도 센서 혹은 각속도 센서) 제작이 가능해져 관성 센서를 소형 휴대 기기에 내장하여 사용자의 움직임을 감지하거나 의도 파악하는 연구가 진행되고 있다. 본 연구에서는 관성 센서가 내장된 휴대 기기를 이용하여 3차원 공간상에서 6가지 위치에 따라서 각기 다른 6가지 소리를 발생하는 가상의 멀티 타악기 시스템을 제안한다. 즉, 휴대 기기를 상/하로 흔들면 가상 타악기의 타점 위치에 왔을 때 비트 음을 발생하고, 6개의 다른 위치를 구분하여 다른 타점의 위치에서 휴대 기기를 흔들면 각각 그 위치와 미리 지정된 소리가 발생하도록 하였다. 이러한 가상의 멀티 타악기 시스템을 위해서 3차원 공간상에서 실시간으로 사용자의 움직임을 감지하고 휴대 기기의 위치를 파악하는 것이 필요하다. 저가의 관성 센서를 이용하여 사용자가 휴대 기기를 움직이는 동작이 있는 상황에서 실시간으로 휴대 기기의 위치를 추정하는 것은 쉽지 않지만 본 연구에서는 다양한 사용자의 움직임 동작 분석을 통하여 사용자가 가상의 멀티 타악기를 상/하로 흔드는 동작을 감지하고 다른 위치로 이동하는 동작을 구분하였다. 개발된 동작 감지 알고리즘과 위치 구분 알고리즘을 휴대 기기에 적용되어 실제로 가상의 타악기 시스템을 구현하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2792-2799
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• 2012

Multilateration that consists of three or more fixed nodes has been widely used in the field of indoor real time location system(RTLS). However, when one or two among fixed nodes are partially out of communication reachability due to obstruction and unstable node, it is difficult to obtain an efficient location information. In order to improve the challenges of poor ranging measurements and fluctuations in these environment, this paper presents, based on TOF(Time of Flight), a new algorithm which can reduce the inherent ranging measurements errors in the conventional multilateration using a vector prediction algorithm for the displacement estimation of mobile node and Kalman filter for an efficient distance average. Even if a person moves with mobile node and then it fails ranging measurement from some of fixed nodes, the proposed algorithm using a present and previous measurement value can predict the distance between mobile node and fixed node which fails ranging measurement. The experimental results are shown that the proposed system improves the localization accuracy and efficiency compared with conventional method, respectively.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1022-1030
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• 2006

The location awareness is an important part of many ubiquitous computing systems, but a perfect location system does not exist yet in spite of many researches. Among various location tracking systems, we choose the RFID system due to its wide applications. However, the sensed RSSI signal is too sensitive to the direction of a RFID reader antenna, the orientation of a RFID tag, the human interference, and the propagation media situation. So, the existing location tracking method in spite of using the particle filter is not working well. To overcome this shortcoming, we suggest a robust location tracking method with a double layered structure, where the first layer coarsely estimates a tag's location in the block level using a regression technique or the SVM classifier and the second layer precisely computes the tag's location, velocity and direction using the particle filter technique. Its layered structure improves the location tracking performance by restricting the moving degree of hidden variables. Many extensive experiments show that the proposed location tracking method is so precise and robust to be a good choice for implementing the location estimation of a person or an object in the ubiquitous computing. We also validate the usefulness of the proposed location tracking method by implementing it for a real-time people monitoring system in a noisy and complicate workplace.