• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.373-378
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• 2016

Recently, IPS(Indoor Positioning System) Technology has been progressing study and research, It has been studied in the fingerprinting and trilateration continuously. however because Fingerprinting and Trilateration Technology use AP(Access Point) for Positioning Calculation, Fingerprinting and Trilateration are not never had a credit positioning accuracy by using unstable RSSI in large scale. in this paper, to improve the problem about precise positioning in wide area, we introduced a concept of Sector including Cell. Sectors are not involved in each other and only fingerprinting calculation is proceed in a sector. we suggest this fingerprinting system considering efficiency and accuracy and compared to conventional fingerprinting, we demonstrated our system efficiency by mathematical techniques.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.9
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• pp.369-376
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• 2017

Recently, an RSSI-based fingerprinting localization technology has been widely used in indoor location-based services. In the conventional fingerprinting method, as many APs as possible are used to increase the accuracy of location estimation. In another study, a part of APs having the strongest RSSI signal intensity are selected and used to reduce the time spent for positioning. However, it does not reflect the influence of RSSI occurred from the changes of the surrounding environments such as human movement or moving obstacles in a real environment. The environmental changes may cause the difference between the predicted RSSI signal strength value and the measured value, and thus occur an unpredictable error in the position estimation. Therefore, in order to mitigate the error caused by environmental factors, it is necessary to select APs suitable for indoor positioning estimation considering the changes in the surrounding environments. In this paper, we propose a method to select stable APs considering the influence of surrounding environments and derive a suitable positioning algorithm. In addition, we compare and analyze the performance of the proposed method with that of the existing AP selection methods through experiments.

• The Journal of Korean Institute of Information Technology
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• v.17 no.2
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• pp.71-77
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• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

• Smart Media Journal
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• v.4 no.2
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• pp.68-76
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• 2015

Recently, research on indoor locating techniques using smart device sensors has been conducted actively, Owing to the exponential increase in the use of various smart devices. However, in order to develop indoor location techniques, there are limitations due to the requirement that the tracking system has to function without GPS. In this paper, we propose an accurate indoor locating system that does not require additional infrastructure. The proposed scheme is developed based on the idea that the advantages and disadvantages of "Wi-Fi Fingerprinting" and "Step Detection" techniques are complementary. In the proposed scheme, we track users with "Step Detection," and correct errors with "Wi-Fi Fingerprinting." In this paper, we demonstrate the effectiveness and feasibility of our proposed scheme through experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.86-89
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• 2016

실내 위치 인식 기술은 Wi-Fi, Bluetooth Low Energy 등 여러 기술을 통해 시도되어 왔으며, 실내 위치 인식 시스템의 상용화가 급증하는 추세이다. 대표적인 실내 측위 시스템인 Wi-Fi 기반 실내 측위는 고출력으로 넓은 범위에 서비스를 제공해주지만, 각 AP 마다 파워 출력이 다르기 때문에 위치 인식 측면에서의 오차가 발생하고, Bluetooth Low Energy 기반 실내 측위는 10m Cell 내에서는 정확한 인식이 가능하지반, 10m 거리 밖 오차는 매우 크다. UWB(Ultra Wide Band)[1][2][3]는 저전력으로, 3.1~10.6GHz의 대역올 이용하여, Wi-Fi의 10배 이상의 속도로 데이터를 전달한다. 이때, 데이터 전달에 사용되는 전파신호는 레이더 신호와 유사한 특징을 가져 거리측정에 사용될 수 있으며, 실내 측위 시 15cm 이내의 정확도를 가진다. 본 논문에서는 UWB의 광대역을 이용한 핑거프린팅과 정밀 측위를 위한 TDoA 기법을 이용한 정밀 실내 측위 알고리즘을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1197-1209
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• 2016

As Indoor Positioning System demands due to increased penetration and utilization of smart device, Indoor Positioning System using Wi-Fi or BLE(Bluetooth Low Energy) beacon takes center stage. In this paper, a terminal location of the user is calculated through Microscopic Trilateration using RSSI based on BLE. In the next step, a fingerprinting map appling approximate value of Microscopic Trilateration increases an efficiency of computation amount and energy for Indoor Positioning System. I suggest Indoor Positioning Algorithm based on BLE fingerprinting considering efficiency of energy by conducting precise Trilateration that assure user's terminal position by using AP(Access Point) surrounding targeted fingerprinting cells. And This paper shows experiment and result based on An Suggesting Algorithm in comparison with a fingerprinting based on BLE and Wi-Fi that be used for Indoor Positioning System.

• Journal of KIISE
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• v.44 no.6
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• pp.643-648
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• 2017

Among Wi-Fi based indoor positioning systems, fingerprinting localization is the most common technique with high precision. However, construction of the initial radio map and the update process require considerable labor and time effort. To address this problem, we propose an efficient method that constructs the initial radio map at each vertex based on a graph. In addition, we introduce a method to update the radio map automatically by mapping signal data acquired from users to the reference point created on each edge. Since the proposed method collects signal data manually only at the vertex of the graph to build the initial radio map and updates it automatically, our proposed method can dramatically reduce labor and time effort, which are the disadvantages of the conventional fingerprinting method. In our experimental study, we show validity of our radio map update method by comparing with the actual reference point data. We also show that our proposed method is able to construct the radio map with an accuracy of about 3.5m by automatically updating the radio map.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.88-91
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• 2016

최근 스마트 기기의 활용 요구 증가로 인한 실내 위치 인식 시스템 수요가 급증함에 따라, BLE(Bluetooth Low Energy) 비콘을 이용한 실내 측위 시스템이 각광받고 있다. 본 논문은 BLE 비콘 기반에 중심을 두고 RSSI 신호를 이용하여 거시적인 삼변 측량 기법을 이용하여 산출한다. 그 결과값을 근사치 위치에만 Fingerprinting을 적용하여 위치 측위 기본 연산량을 줄임과 동시에 에너지 효율을 증대시킨다. 또한 선정된 Fingerprinting Cell 주위의 노드만을 이용하여 사용자의 단말 위치의 정밀성을 보장하는 정밀 삼변 측량 연산을 수행하여 에너지 효율을 고려한 BLE 핑거프린팅 기반의 정밀 실내 측위 알고리즘을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.763-773
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• 2012

본 논문에서는 Wi-Fi를 이용한 RSSI (Received Signal Strength Indication)기반의 측위 시스템에서 전파환경변화에 민감한 시스템의 문제를 보완하기 위하여 랜드마크 발신기 기반의 측위 시스템을 제안한다. 이를 위하여 핑거프린팅 알고리즘 및 랜드마크 발신기를 구현 하였으며 간단한 측위 정확도 예측모델을 만들어 수신된 전파세기를 기반으로 측위 정확도를 예측하였다. 이를 바탕으로 실내 TEST BED를 구축하였고 주요 지점에 랜드마크 발신기를 부착하여 시스템의 효용성을 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.95-97
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• 2016

실내 위치 인식 기술은 여러 기술을 통해 시도되어 왔으며, 대표적인 기술로는 Wi-Fi 기반 위치 인식과 Bluetooth Low Energy 기반의 위치 인식이 있다. 하지만 Bluetooth Low Energy는 10m 거리 밖에선 오차가 많아지고 정밀도가 낮아지는 특성으로 인해 Wi-Fi가 보편화되었다. 본 논문에서는 핑거프린팅 기법을 이용하였을 때 Wi-Fi와 Bluetooth Low Energy의 위치 인식 기술의 성능 분석을 목적으로 기술되었다.