• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.1083-1094
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• 2012

Commercialized location estimation System with high accuracy is widely used for various services. However, if the systems aren't completely installed in an indoor, location estimation accuracy tend to be very poor. In this paper, indoor location estimation algorithm to improve the accuracy of object location, by correcting the location information obtained from a system that does not fully install, is proposed. In this paper, UWB-based Ubisense system that provides high position accuracy in an indoor environment was utilized. In conclusion, this paper was able to improve the positioning accuracy, by correcting that information about the location of the measured object in position estimation system.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.19-28
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• 2011

Recently, ubiquitous computing and related technologies is more and more growing concern about. Depending on the trend, the moving object recognition and tracking research have been required in order to meet the diverse needs of the user. In the location-based services, one of the most important issues in the indoor environment is to provide location-aware services. In this paper, the effective algorithm to help estimate the position of moving objects in an indoor environment is proposed. We propose an algorithm that combined the existing trilateration measurement and the improved measurement of environmental adaptation scene analysis. The proposed indoor location estimation algorithm use the trilateration measurement when we have enough anchor in the line-of-sight environment. Otherwise that use measurement of environmental adaptation scene analysis. Consequently, the proposed algorithm has been improved the localization accuracy of a moving object as well as was able to reduce complexity of the algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.863-865
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• 2015

A method for estimating position is AOA, TOA, TDOA, Wi-Fi, Beacon etc. A method for estimating the location in indoor environment is used mainly Wi-Fi, Beacon. The reason is that AOA, TOA and TDOA are unfit to estimate position in indoor environment. To address this problem, this paper presents a AOA algorithm based on AP having a four directional antenna. The algorithm uses only the angle received from the four antennas. This can draw linear equations for signal. And calculate the intersections of the lines. Intersections means the position of user.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.875-878
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• 2010

In this paper, we proposed a RSSI based cooperative localization algorithm considering wireless propagation characteristics in indoor environment for wireless sensor networks, which can estimate the BN position. The conventional RSSI based estimation scheme has low precision ranging according to time variable propagation characteristics. Hence, we implemented ray-launching simulator for analysis of propagation characteristics in $13.65m{\times}8.7m$, and performed proposed localization scheme with 4 RN and 1 to 5 BN. From the results, if we can consider channal characteristic in proposed ranging scheme, the cooperative localization algorithm with propagation characteristics provides higher localization accuracy than RSSI based conventional one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1463-1471
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• 2016

The indoor localization algorithm using the Difference Means based on Fingerprint (DMFPA) to improve the performance of indoor localization in moving Wi-Fi environment is proposed in this paper. In addition to this, the performance of the proposed algorithm is also compared with the Original Fingerprint Algorithm (OFPA) and the Gaussian Distribution Fingerprint Algorithm (GDFPA) by our developed indoor localization simulator. The performance metrics are defined as the accuracy of the average localization accuracy; the average/maximum cumulative distance of the occurred errors and the average measurement time in each reference point.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.482-484
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• 2015

대표적인 위치기반 기술인 GPS는 건물 내부와 같이 실내에서의 위치추정이 거의 불가능하다. 따라서 실내 측위의 방안으로 BlueTooth 4.0LE 기반의 장치인 비콘(Beacon)을 활용하여 실내 GPS의 역할을 수행하도록 하는 기법이 활용되고 있다. 그러나, 비콘의 거리측정에 사용되는 RSSI의 문제점으로 인해, 위치추정의 정확도가 급격히 저하되는 문제점을 가지고 있다. 본 논문에서는 개선된 위치선정 알고리즘을 통하여 오차율을 줄여, 정밀한 위치 추정이 가능한 알고리즘을 제안하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.113-120
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• 2017

In recent years, indoor localization has been researched for the improvement of its localization accuracy capability in Wi-Fi environment. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs in the 3rd case had the lowest average error of 3.99 among its 4 scenarios.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1926-1933
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• 2013

Many localization algorithms have been proposed for Wireless Sensor Networks (WSNs). The IEEE 802.15.4a-based location-aware-system can provide precise ranging distance between two mobile nodes. The mobile nodes can obtain their exact locations by using accurate ranging distances. However, the indoor environments contain various obstacles which cause non-line-of-sight (NLOS) conditions. In NLOS condition, the IEEE 802.15.4a-based location-aware system has a large scale location error. To solve the problem, we propose location error compensation in indoor environment by using MST-based topology control. Experimental and simulation results show that the proposed algorithm improves location accuracy in NLOS conditions.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.558-563
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• 2015

There have recently been various services that use indoor location estimation technologies. Representative methods of location estimation include fingerprinting and triangulation, but they lack accuracy. Various kinds of research which apply existing location estimation methods like AOA, TOA, and TDOA are being done to solve this problem. In this paper, we study the location estimation algorithm based on AOA using a RSSI difference in indoor environments. We assume that there is a single AP with four antennas, and estimate the angle of arrival based on the RSSI value to apply the AOA algorithm. To compensate for RSSI, we use a recursive averaging filter, and use the corrected RSSI and the Pythagorean theorem to estimate the angle of arrival. The results of the experiment, show an error of 18% because of the radiation pattern of the four non-directional antennas arranged at narrow intervals.