• The Journal of Information Systems
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• v.17 no.1
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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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• v.13 no.4
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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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• v.11 no.3
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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.

• Proceedings of the KIEE Conference
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• 2005.10b
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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.

• Proceedings of the KIEE Conference
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• 2005.10b
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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.

• Journal of Korea Multimedia Society
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• v.18 no.12
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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.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.29-35
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• 2021

In this paper, we propose a method that combines KNN(K-Nearest Neighbor), Local Map Classification and Bayes Filter as a way to increase the accuracy of location positioning. First, in this technique, Local Map Classification divides the actual map into several clusters, and then classifies the clusters by KNN. And posterior probability is calculated through the probability of each cluster acquired by Bayes Filter. With this posterior probability, the cluster where the robot is located is searched. For performance evaluation, the results of location positioning obtained by applying KNN, Local Map Classification, and Bayes Filter were analyzed. As a result of the analysis, it was confirmed that even if the RSSI signal changes, the location information is fixed to one cluster, and the accuracy of location positioning increases.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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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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• v.45 no.6
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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.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.61-66
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• 2005

Location Positioning is a major technology for ubiquitous computing. Recently the research on Location Positioning using UWB is on going. In order to construct an in-door location network, synchronization of base stations is very important. NTP is Popularly used as clock synchronization protocol ranging from LAN to WAN. Also Master-Slave scheme is the simplest method to synchronize in-door network. We compare and analyze NTP and Master-Slave schemes according to the statistical channel model for indoor multipath propagation environment. In this paper, error ranges are calculated at various circumstances that in-door network expands from one primary base station into several base stations. We compared the correctness of NTP and Master-Slave synchronization methods. NTP is more reasonable synchronization protocol in in-door environment.