• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.167-178
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• 2023

Our society is rapidly changing, and there is a growing demand for various convenience services in our daily lives. Among these services, railway and subway stations require tailored wayfinding services to accommodate individuals with disabilities. Currently, signage and information desks are the primary means of navigation. However, individuals with disabilities often rely on assistance from others due to physical discomfort or cognitive impairments. In this paper, we propose a customized wayfinding system within railway stations to assist individuals with disabilities. This system aims to ensure safe and convenient mobility in complex indoor environments, including transfer facilities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1310-1317
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• 2012

The Global Navigation Satellite System (GNSS) like US Global Positioning System (GPS) and EU Galileo are based on providing precise time and frequency synchronized ranging signals. Because of the exploitation of very precise timing signals these GNSS are used to provide both navigation and time distribution services. Moreover, because the positioning accuracy will improve as more satellites become available, we should expect that a combination of Galileo and GPS will provide better performance than those of both systems separately. However, Galileo will not use the same time reference as GPS and thus, a time difference arises - the GPS-Galileo Time Offset (GGTO). The navigation solution calculated by receivers using signals from both navigation systems will consequently contain a supplementary error if the GGTO is not accounted for. In this paper, we compared GPS Time (GPST) with Galileo Sytem Time (GST) and analyzed the effects of GGTO on positioning accuracy by simulation test. And then we also analyzed the characteristics of two representative GGTO correction methods such as the navigation message based method at system level and the estimation method at user level and propose the conceptual design of the novel correction method being capable of preventing previous method's problems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• The KIPS Transactions:PartC
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• v.17C no.3
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• pp.251-258
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• 2010

In an indoor localization method taking the lateration-based approach, the location of a target is estimated with the location of anchor points (APs) and the approximated distances between the target and APs using received signal strength (RSS) measurements. The accuracy of distance estimation affects the localization accuracy of a lateration-based method. Since a radio propagation environment varies randomly in time and space, the highest RSSs do not necessarily give the best estimation of the distances between a target and APs. Thus, all APs hearing a target have been used for localization. However, the accuracy of a lateration-based method degrades if more APs beyond a certain threshold are used because the area of polygon with the APs increases. In this paper, we focus on reducing the size of the polygon to further increase the localization accuracy. We use the centroid of the polygon as a reference point to estimate the relative location of a target in the polygon. Once the relative location is estimated, only the APs which are closest to the target are used for localization to reduce the area of the polygon with the APs. We validate the proposed method by implementing an indoor localization system and evaluating the accuracy of the proposed method in the various experimental environments.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.173-182
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• 2012

A recent advance in smart phones is increasing utilization of location information. Existing positioning system was using GPS location for positioning. However, the GPS cannot be used indoors, if GPS location has an incorrectly problem. In order to solve indoor positioning problems of indoor location-based positioning techniques have been investigated. There are a variety of techniques based on indoor positioning techniques like as RFID, UWB, WLAN, etc. But WLAN location positioning techniques take advantage the bond in real life. WLAN indoor positioning techniques have a two kind of method that is centroid and fingerprint method. Among them, the fingerprint technique is commonly used because of the high accuracy. In order to use fingerprinting techniques make a WLAN signal map building that is need to lot of resource. In this paper, we try to solve this problem in an Indoor environment for WLAN-based fingerprint of a virtual building technique, which is proposed. Proposed technique is classified Cell environment in existed Indoor environment, all of fingerprint points are shown virtual grid map in each Cell. Its method can make fingerprint grid map very quickly using estimate virtual signal value. Also built signal value can take different value depending of the real estimate value. To solve this problem using a calibration technique for the Splite-tree is proposed. Through calibration technique that improves the accuracy for short period of time. It also is improved overall accuracy using predicted value of around position in cell.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.564-573
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• 2015

GPS is the representative positioning technology for providing the location information. This technique has the disadvantage that does not operate in the shadow areas, such as urban or dense forest and the interior. This paper proposes a hybrid indoor positioning algorithm, which estimates a more accurate location of the terminal using strength of the Wi-Fi signal from the indoor AP. To determine the location of the user, we establish the most appropriate path loss model for the measurement environment. by using the RSSI value measured in a variety of environment such as building structure, person, distance, etc. The path loss exponent obtained by the path loss model is changed according to the environment. REKF, PF estimate the position of the terminal by using measured value from the AP with path loss exponent. For more accurate position estimation, we select positioning system by the value of threshold measured by experiments rather than a single positioning system. Experimental results using the proposed hybrid algorithm show that the performance is improved by about 17% than the conventional single positioning method.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.58-63
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• 2015

Due to GPS signal's vulnerability of jamming attack, various enhancement techniques are needed. Among variety of techniques, we focused on GPS receiver's anti-jamming techniques. There are many anti-jamming methods at GPS receivers which include filtering methods in time domain, frequency domain and space domain. However, these methods are ineffective to signals, which include both jamming and noise. To solve the problem, this paper proposes a jamming separation scheme by using a BSS method in a jamming environment. As separated GPS signals include noise after the jamming separation method, it is difficult to receive accurate GPS signals. For this reason, this paper also proposes a wavelet de-noising method to effectively eliminate noise. Experimental results of this paper are based on a real field test data of an integrated GPS/QZSS/Wi-Fi positioning system. At the end, the simulation result demonstrates its superiority by showing improved positioning accuracy.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.73-78
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• 2005

최근 측위 장치와 모바일 단말 장치, 이동 통신 기술이 발달함에 따라 위치기반서비스에 대한 요구가 증가하고 있다. 그러나 위치기반서비스는 이용자에게 편리하고 유용한 정보를 제공하지만 개인의 프라이버시를 침해할 수 있는 가능성을 함께 가지고 있다. 특히 개인이 깨닫지 못하는 사이에 측위 장치가 탑재되어, 개인의 위치가 제3자에 의해 추적된다면 심각한 프라이버시 침해라 할 수 있다. 이러한 개인 위치정보를 보호하기 위해서는 법적인 규제와 기술적인 장치가 함께 마련되어야 한다. 이 논문에서는 위치정보를 보호하기 위한 위치정보보호시스템을 제시한다. 제시된 위치정보보호시스템은 법적인 규제와 표준 그리고 위치정보를 보호하기 위한 방법들이 설계 및 구현되어 있다.

• Information and Communications Magazine
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• v.20 no.12
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• pp.73-83
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• 2003

정보통신의 발전 및 디지털화에 따라 사람들의 이동성이 증가하고 무선통신망과 위치측위 기술을 바탕으로 차량내외의 이동형 정보서비스를 지원하는 텔레매틱스가 이동통신, 자동차, 시스템, 단말기 컨텐츠 분야를 중심으로 대두되고 있다. 이처럼 텔레매틱스는 다양한 분야의 기술을 통합하고 연계하여 서비스를 제공하는 분야이며, 유무선통신기술, 위치측위기술, 시스템통합기술 등의 기반기술을 토대로 재창출되는 서비스의 집합이다. 본 논문에서는 기존의 기반기술 및 서비스를 바탕으로 효율적으로 텔레매틱스 서비스를 구현하기 위한 텔레배틱스 서비스 서버 구축 방안을 기술한다. 기존의 위치기반서비스 및 지능형 교통시스템 등의 관련 분야의 서비스를 통합 서비스 형태로 제공할 수 있는 통합 서비스 서버 모델을 제안한다. 이 모델은 계층화된 구조를 가지고 있어 관련 분야 기반 기술 및 서비스 기술의 적용을 효율적으로 할 수 있어 향후 시스템 확장성을 용이하게 한다. 또한 본 논문에서는 텔레매틱스 서비스 서버를 활용하여 구축된 위치기반라우팅 서비스의 구현사례를 보여준다. 이는 텔레매틱스 서비스 서버를 활용하여 관련 분야의 기반 기술과 서비스의 기술을 효율적으로 활용할 수 있음을 확인할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.526-528
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• 2013

최근 실내 측위 기술을 이용한 다양한 서비스 제공을 위해 많은 위치 인식 기법이 연구되고 있다. 기존의 실내 위치 인식 기법은 사전에 획득한 맵 정보나 미리 구축한 기반 시설이 필요하거나, 추가 장비를 착용 및 부착해야 하는 단점이 있었다. 이에 본 논문에서는 스마트폰 내부센서를 이용하여 실내에서 사용자의 위치를 측정하는 시스템을 제안하였다. 제안한 시스템은 가속도 센서를 이용하여 이동여부를 파악하고, 사용자의 평균적인 이동속도와 방향센서를 이용하여 획득한 이동방향을 이용하여 위치를 추정한다. 제안한 시스템을 안드로이드 스마트폰에 구현하여 실험한 결과 약 ${\pm}75cm$ 이내의 오차에서 위치 인식이 가능함을 확인하였다.