• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.9
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• pp.1027-1032
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• 2015

Using the radio wave, RFID(: Radio Frequency IDentification) wirelessly transmits the unique information saved in a tag attached on the specific object. In the construction area, the trend in using RFID for managing the input and inventory of the construction materials is upward. General management systems for the construction materials have only a function of identifying the tag attached on the construction materials, but the management system with a function of identifying and managing the location information of the construction materials employing RFID, for reusing it, is not actively developed. For the efficient reuse of the construction materials, in this paper, we propose the RFID system with a function of estimating and saving the location information of the specific construction materials, based on the estimated distances between the particular subs and reader. The proposed system consists of RFID reader, distance estimate, communication, and memory units.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.494-500
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• 2020

This paper proposes a new distance estimation technique for indoor localization in ultra wideband (UWB) systems. The proposed technique is based on recurrent neural network (RNN), one of the deep learning methods. The RNN is known to be useful to deal with time series data, and since UWB signals can be seen as a time series data, RNN is employed in this paper. Specifically, the transmitted UWB signal passes through IEEE802.15.4a indoor channel model, and from the received signal, the RNN regressor is trained to estimate the distance from the transmitter to the receiver. To verify the performance of the trained RNN regressor, new received UWB signals are used and the conventional threshold based technique is also compared. For the performance measure, root mean square error (RMSE) is assessed. According to the computer simulation results, the proposed distance estimator is always much better than the conventional technique in all signal-to-noise ratios and distances between the transmitter and the receiver.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1930-1931
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• 2007

본 논문에서는 Zigbee와 초음파 센서를 이용한 실내 항법 시스템을 제안한 시스템 Zigbee라는 단거리 무선 통신 망을 이용하여 수집한 후 이동체의 위치를 추정한다. 제안한 시스템에서는 여러 곳에 초음파 센서를 설치하고 이동체까지 측정한 거리는 실내 항법에 적합한 위치 추정 기법을 결정하기 위하여 최소자승법과 직접풀이법의 성능을 모의실험을 통하여 비교하였고, 두 기법 모두 충분히 작은 오차를 가지는 것을 확인하였는데 최소자승법은 선형화 기준점 설정에 따라 발산하는 경우가 나타나는 것을 볼 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.577-582
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• 2004

This paper describes position estimation algorithm using neural network for the navigation of the vision-based Wheeled Mobile Robot (WMR) in a corridor with taking ceiling lamps as landmark. From images of a corridor the lamp's line on the ceiling in corridor has a specific slope to the lateral position of the WMR. The vanishing point produced by the lamp's line also has a specific position to the orientation of WMR. The ceiling lamps has a limited size and shape like a circle in image. Simple image processing algorithms are used to extract lamps from the corridor image. Then the lamp's line and vanishing point's position are defined and calculated at known position of WMR in a corridor To estimate the lateral position and orientation of WMR from an image, the relationship between the position of WMR and the features of ceiling lamps have to be defined. Data set between position of WMR and features of lamps are configured. Neural network are composed and teamed with data set. Back propagation algorithm(BPN) is used for learning. And it is applied in navigation of WMR in a corridor.

• 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 the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.211-217
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• 2019

Location positioning systems are available in applications such as mobile, robotic tracking systems and Wireless location-based service (LBS) applications. The GPS system is the most well-known location tracking system, but it is not easy to use indoors. The method of radio frequency identification (RFID) location tracking was studied in terms of cost-effectiveness for indoor location tracking systems. Most RFID systems use active RFID tags using expendable batteries, but in this paper, an inexpensive indoor location tracking system using passive RFID tags has been developed. A pattern matching method and a system for tracing location by generating regression curves were studied to use precision tracking algorithms. The system was tested by verifying the level of error caused by noise. The three-dimensional curves are produced by the regression equation estimated the statistically meaningful coordinates by the differential equation. The proposed system could also be applied to mobile robot systems, AGVs and mobile phone LBSs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1055-1062
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• 2015

A GPS based wave height meter system is proposed in this paper. The proposed system uses a dual-frequency measurements, a precise GPS satellite information and a PPP-based navigation algorithm to estimate the position with high accuracy. This method does not need to receive corrections from the reference stations. Therefore, unlike RTK based wave meter, regardless of the distance to the reference stations, it is possible to estimate position with high accuracy. This system is very simple and accurate system, but accelerometer-based system requires the other sensors such as GPS. Because position error is accumulated in the accelerometer system and must be removed periodically for high accuracy. In order to get the measurements and test the proposed wave height meter system, a buoy equipped with the test platform is installed on the sea near by Jukbyeon habor in Uljin, Korea. Then, to evaluate the performance, compares built-in commercial wave height meter with proposed system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.199-205
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• 2015

Indoor positioning technology has been developed very actively for the smart phone handheld by most users. Especially, many TDOA positioning systems using acoustic signal have been studied, and it estimates the smart phone position by measuring the distance between the smart phone speaker and the microphones which is installed to receive the acoustic signal from the smart phone, and by calculating the hyperbolic equations. But there are always errors for the distance measurements, and furthermore the microphone installation error produces huge position estimation error. In this paper, the position estimation error due to the position error of acoustic sensor in the 3 dimensional TDOA positioning system, is analyzed by PDOP simulation and experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.332-340
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• 2013

This paper reports a programming toolkit for implementing localization and navigation of a mobile robot both in real world and simulation. Many of the previous function libraries are difficult to use because of their complexity or lack of usability. The proposed toolkit consist of functions for dead reckoning, motion model, measurement model, and operations on directions or heading angles. The dead reckoning and motion model deals with differential drive robot and bicycle type robot driven by front wheel or rear wheel. The functions can be used for navigation in both real environment and simulation. To prove the feasibility of the toolkit, simulation results are shown along with the results in real environment. It is expected the proposed toolkit is used for test of algorithms for mobile robot navigation such as localization, map building, and obstacle avoidance.