• Journal of Internet Computing and Services
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• v.11 no.2
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• pp.61-72
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• 2010

This paper addresses the problem of moving object localization using Ultra-Wide-Band(UWB) range measurement and the method of location accuracy improvement of the indoor moving object. Unlike outdoor environment, it is difficult to track moving object position due to various noises in indoor. UWB is a radio technology that has attention for localization applications recently. UWB's ranging technique offer the cm accuracy. Its capabilities for data transmission, range accurate estimation and material penetration are suitable technology for indoor positioning application. This paper propose a positioning algorithm of an moving object using UWB ranging technique and particle filter. Existing positioning algorithms eliminate estimation errors and bias after location estimation of mobile object. But in this paper, the proposed algorithm is that eliminate predictable UWB range distance error first and then estimate the moving object's position. This paper shows that the proposed positioning algorithm is more accurate than existing location algorithms through experiments. In this study, the position of moving object is estimated after the triangulation and eliminating the bias and the ranging error from estimation range between three fixed known anchors and a mobile object using UWB. Finally, a particle filter is used to improve on accuracy of mobile object positioning. The results of experiment show that the proposed localization scheme is more precise under the indoor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.889-900
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• 2012

In wireless sensor networks, the positioning scheme using received signal strength (RSS) has been widely considered. Appropriate estimation of path-loss exponent (PLE) between a sensor node and an anchor node plays a key role in reducing position error in this RSS-based positioning scheme. In the conventional researches, a sensor node directly uses the PLEs measured by its nearest anchor node to calculate its position. However, the actual PLE between a sensor node and the anchor node can be different from the PLE measured by its nearest anchor node. Thus, if a sensor node directly uses the PLEs measured by its nearest anchor node, the estimated position is different from the actual position of the sensor node with a high probability. In this paper, we describe the method how a sensor node estimates PLEs from the anchor nodes of interest by itself and calculates its position based on these self-estimated PLEs. Especially, our proposal suggests the mechanism to iteratively calculate the PLEs depending on the estimated distances between a sensor node and anchor nodes. Based on the recalculated PLEs, the sensor node reproduces its position. Through simulations, we show that our proposed positioning scheme outperforms the traditional scheme in terms of position error.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.38-44
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• 2007

This paper presented a location and attitude estimation scheme of a capsule endoscope based on ultrasonic ranging. The scheme comprised eight on-capsule ultrasonic sensors to alleviate measurement errors due to irregularities in human body ultrasonic characteristics. It calculated the coordinate values and angles in a Cartesian coordinate system. The Matlab simulation reflecting random errors yielded the average deviations of 0.8mm in the location and $0.2^{\circ}$ in the attitude angle. These values are far smaller than normal intestine movement ranges inside human body, and will contribute accurate diagnosis of intestine.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• Journal of Korea Ship Safrty Technology Authority
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• s.21
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• pp.66-77
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• 2006

Stainless steel has been stably used closed by passivity oxidation films(Cr₂O₃) is made by neutral atmospheric environment. However, passivity oxidaton films of the surface of stainless steel occasionally comes to be destroyed in seawater which is influenced by an environment having galogen ion like Cl‾, then, localization corrosion comes to occur Stainless steel 304 for shaft system material of the small-size FRP fishing boat on seawater environments made an experiment on simulation of sacrifical anode(Al, Zn). Through these experiment and study, following results have been obtained ; According to the field inspection and corrosion simulation, the corrosion on the 2nd class stainless steel shaft(STS304) in FRP fishing boat has been verified to occur by crevice corrosion and galvanic corrosion etc., According to the comparison and analysis of Stainless steel 304 was severely corroded, but, protected shaft specimen was not totallay corroded. This result is assumed to be made by the facts that anodic reaction, Fe → fe²+＋ 2e¯, has been restricted by the cathodic protection current of sacrificial anode material.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1226-1232
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• 2010

A door can serve as a feature for place classification and localization for navigation of a mobile robot in indoor environments. This paper proposes a door detection method based on the recognition of various door handles using the general Hough transform (GHT) and support vector machine (SVM). The contour and color histogram of a door handle extracted from the database are used in GHT and SVM, respectively. The door recognition scheme consists of four steps. The first step determines the region of interest (ROI) images defined by the color information and the environment around the door handle for stable recognition. In the second step, the door handle is recognized using the GHT method from the ROI image and the image patches are extracted from the position of the recognized door handle. In the third step, the extracted patch is classified whether it is the image patch of a door handle or not using the SVM classifier. The door position is probabilistically determined by the recognized door handle. Experimental results show that the proposed method can recognize various door handles and detect doors in a robust manner.

• Smart Structures and Systems
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• v.20 no.2
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• pp.219-229
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• 2017

Outlier detection is an imperative task to identify the occurrence of abnormal events before the structures are suffered from sudden failure during their service lives. This paper proposes a two-phase method for the outlier detection of Global Positioning System (GPS) monitoring data. Prompt judgment of the occurrence of abnormal data is firstly carried out by use of the relational analysis as the relationship among the data obtained from the adjacent locations following a certain rule. Then, a negative selection algorithm (NSA) is adopted for further accurate localization of the abnormal data. To reduce the computation cost in the NSA, an improved scheme by integrating the adjustable radius into the training stage is designed and implemented. Numerical simulations and experimental verifications demonstrate that the proposed method is encouraging compared with the original method in the aspects of efficiency and reliability. This method is only based on the monitoring data without the requirement of the engineer expertise on the structural operational characteristics, which can be easily embedded in a software system for the continuous and reliable monitoring of civil infrastructure.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.225-235
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• 2006

Not a few nations have tried to copy the success of Silicon Valley since 1980's. Research of information communication industry cluster has emerged in Korea since 1990. In this background this paper thoroughly reviewed scholarly literature related to industry cluster with an attempt to extract dominant factors for cluster formation, and designed a survey instrument to measure the status-quo of cluster formation of software industry in Chungbuk Province Korea, as an example. Based on the results from statistical analysis a strategic scheme was proposed to propel software industry cluster formation in the region.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1162-1179
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• 2017

In this paper, we propose indoor location tracking method using RSSI(Received Signal Strength Indicator) value received from BLE(Bluetooth Low Energy) beacon. Due to the influence of various external environmental factors, it is very difficult to improve the accuracy in indoor location tracking. In order to solve this problem, we propose a novel method of reducing the noise generated in the external environment by using a double Gaussian filter. In addition, the value of the RSSI signal generated in the BLE beacon is different for each device. In this study, we propose a method to allocate additional weights in order to compensate the intensity of signal generated in each device. This makes it possible to improve the accuracy of indoor location tracking using beacons. The experiment results show that the proposed method effectively decrease the RSSI deviation and increase location accuracy. In order to verify the usefulness of this study, we compared the Kalman filter algorithm which is widely used in signal processing. We further performed additional experiments for application area for indoor location service and find that the proposed scheme is useful for BLE-based indoor location service.