• 한국정보시스템학회지:정보시스템연구
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• 제17권1호
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• pp.131-153
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• 2008

So many location based service systems, including automobile navigation system logistic management, taxi fleet management, and so on, are being used everywhere. However, these are all outdoors. This paper provides a stepping stone for commercial indoor location based services by developing an integrated system of our indoor positioning and map viewer modules. For the indoor positioning, we propose WLAN (Wireless Local Area Network) based EKF (Extended Kalman Filter) which estimates user's current location and tracts user's trace in the sequence of time. Our map viewer renders a map recorded in an Autocad DXF file and provides functions of map manipulation such as zoom-in, zoom-out, and move. We integrate our indoor positioning and map viewer modules and discuss the experimental results of the integrated system.

• Journal of Information Technology Applications and Management
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• 제13권4호
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• pp.57-70
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• 2006

Location Based Service (LBS) provides high-value added service to users and various works about IBS have been actively performed. The core technology or LBS is positioning of the users. In the field of positioning, outdoor positioning and indoor positioning are developed separately. We are proposing a design of an outdoor-indoor positioning system, implementing a prototype of the system, and verifying the usefulness of the system through experiments. Our experimental results shows that the average error of our system is 4.8 m in the case of out-door positioning and it is 3.3 m in the case of in-door positioning.

• Journal of Positioning, Navigation, and Timing
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• 제11권3호
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.312-314
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• 2005

We have implement indoor positioning system to supply orientation information, We have used ultrasound in indoor positioning system for distance and orientation measurements, then propose a set of methods to calculate orientation from an array of well placed ultrasonic sensors operating in the indoor positioning system, We have design and implement a indoor positioning system using a combination of hardware and software and demonstrate end-to-end functionality of the system, We have implement ZigBee based home automation system using location-aware System.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.286-288
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• 2005

If we are to realize the everyday benefits promised by pervasive computing and context-aware applications, we must first develop the infrastructure to provide contextual location and orientation information through pervasive computing elements. We have implement indoor positioning system to supply orientation information. We have used ultrasound in indoor positioning system for distance and orientation measurements, then propose a set of methods to calculate orientation from an array of well placed ultrasonic sensors operating in the indoor positioning system. We have design and implement a indoor positioning system using a combination of hardware and software and demonstrate end-to-end functionality of the system.

• 한국멀티미디어학회논문지
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• 제18권12호
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• pp.1427-1431
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• 2015

In the salvage area, the location of the incident vessel and diver to rescue the victim are very important. But there are no ways but to rely on the GPS satellites to obtain the location in the salvage sites. Because the positioning using GPS satellites has a measurement error of up to 50 meters caused by the status of the atmosphere, a new positioning method with more accuracy should be devised. So if studies on measuring the position of the ships and divers accurately in the sea are performed, it will be helpful in the field of the salvage positioning. In this paper, a high precision positioning system in salvage using DGPS signal through mobile broadcasting is proposed with positioning error of up to 1 meter.

• 한국컴퓨터정보학회논문지
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• 제26권6호
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• pp.29-35
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• 2021

본 논문에서는 위치 측위의 정확도를 높일 수 있는 방안으로 KNN(K-Nearest Neighbor)과 Local Map Classification 및 Bayes Filter를 융합한 기법을 제안한다. 먼저 이 기법은 Local Map Classification이 실제 지도를 여러 개의 Cluster로 나누고, 다음으로 KNN으로 Cluster들을 분류한다. 그리고 Bayes Filter가 획득한 각 Cluster의 확률을 통하여 Posterior Probability을 계산한다. 이 Posterior Probability으로 로봇이 위치한 Cluster를 검색한다. 성능 평가를 위하여 KNN과 Local Map Classification 및 Bayes Filter을 적용하여서 얻은 위치 측위의 결과를 분석하였다. 분석 결과로 RSSI 신호가 변하더라도 위치 정보는 한 Cluster에 고정되면서 위치 측위의 정확도가 높아진다는 사실을 확인하였다.

• Journal of Positioning, Navigation, and Timing
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• 제9권3호
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• pp.169-173
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• 2020

Location-based services are used as core services in various fields. In particular, in the field of public services such as emergency rescue, accurate location estimation technology is very important. Recently, the technology of tracking the location of self-isolation subjects for COVID-19 has become a major issue. Therefore, location estimation technology using personal smart devices is being studied in various ways, and the most widely used method is to use GPS. Other representative methods are using Wi-Fi, Pedestrian Dead Reckoning (PDR), Bluetooth Low Energy (BLE) beacons, and LTE signals. In this paper, we introduced a positioning technology using deep learning based on LTE Channel State Information-Reference Signal (CSI-RS) data, and confirmed the possibility through an outdoor location estimation experiment using a commercial LTE signal.

• ETRI Journal
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• 제45권6호
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• pp.939-951
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• 2023

It is critical to estimate the location using only Long-Term Evolution (LTE) and Wi-Fi information gathered by the user's smartphone and deployable for emergency rescue, regardless of whether the Global Positioning System is received. In this research, we used a vehicle to gather LTE and Wi-Fi wireless signals over a large area for an extended period of time. After that, we used the learning technique to create a positioning database that included both collection and noncollection points. We presented a two-step positioning algorithm that utilizes coarse localization to discover a rough location in a wide area rapidly and fine localization to estimate a particular location based on the coarse position. We confirmed our technology utilizing different sorts of devices in four regional types that are generally encountered: dense urban, urban, suburban, and rural. Results presented that our algorithm can satisfactorily achieve the target accuracy necessary in emergency rescue circumstances.

• 대한전자공학회논문지TC
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• 제42권1호`
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• pp.61-66
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• 2005

Location Positioning은 유비쿼터스 컴퓨팅에서 주요한 기술이다. 최근에 UWB를 사용한 Location Positioning이 연구되고 있다. 실내 망에 location network을 구성하기 위해서는 base station들의 동기 특성이 매우 중요하다. LAN부터 WAN까지 시간의 동기를 맞추는 프로토콜로 제안되어 사용되고 있는 것이 NTP이다. 또한 실내 망을 동기화시키기 위해 가장 간단한 방법으로 사용할 수 있는 것이 Master-Slave 방식이다. 본 논문에서는 UWB Location Positioning을 위한 실내 망 동기화에 대해 NTP와 Master-Slave 방식을 UWB Channel 모델 특성을 적용하여 비교 분석하였다. 하나의 primary base station을 기준으로 여러 개의 base station을 실내 망에 동기론 맞춰가며 확장시켜 나갈 때, 각 base station이 포함하게 될 오차의 범위론 여러 채널 모델에서 모의 실험하였다. 그 결과, 비교적 간단하게 적용될 수 있는 Master-Slave 방식보다 NTP 방식이 더 적은 오차로 동기를 맞출 수 있는 동기화 방식인 것으로 나타났다.