• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.173-176
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• 2008

긴급 SOS 시스템을 구축하기 위하여 빠르고 정확한 위치추적 기술의 개발이 필요하다. 본 논문에서는 긴급한 상황에 처한 사람의 위치를 빠르고 정확하게 추적하기 위하여 핸드폰기지국 망을 이용한 광역위치추적 기술과 근거리 위치추적 기술로 제안된 능동형 위치추적 기술이 융합된 신개념의 긴급 SOS 시스템을 제안하고, 근거리 위치추적 기술인 능동형 위치추적 기술에 Zigbee 통신 방식을 적용하여 링크 버짓과 채널 모델을 이용한 근거리 위치추적 성능을 분석 하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.186-201
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• 2021

As autonomous driving technology advances, the accuracy of the vehicle position is important for recognizing the environments around driving. Map-matching localization techniques based on high definition (HD) maps have been studied to improve localization accuracy. Because conventional map-matching techniques estimate the vehicle position based on an HD map reference dataset representing the center of the lane, the estimated position does not reflect the deviation of the lateral distance within the lane. Therefore, this paper proposes a localization system based on the reference lateral position dataset extracted using image processing and HD maps. Image processing extracts the driving lane number using inverse perspective mapping, multi-lane detection, and yellow central lane detection. The lane departure method estimates the lateral distance within the lane. To collect the lateral position reference dataset, this approach involves two processes: (i) the link and lane node is extracted based on the lane number obtained from image processing and position from GNSS/INS, and (ii) the lateral position is matched with the extracted link and lane node. Finally, the vehicle position is estimated by matching the GNSS/INS local trajectory and the reference lateral position dataset. The performance of the proposed method was evaluated by experiments carried out on a highway environment. It was confirmed that the proposed method improves accuracy by about 1.0m compared to GNSS / INS, and improves accuracy by about 0.04m~0.21m (7~30%) for each section when compared with the existing lane-level map matching method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.124-131
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• 2015

In this paper, we proposed indoor positioning system using RSS(Received Signal Strength) positioning method and TSS(Transmission Signal Strength). The main point in the paper is to improve reliability of accuracy positioning with the area recognition algorithm and probabilistic algorithm, which can be effectively used indoor. In the test in 1-dimensional or 2-dimensional spaces, also we checked effective positioning system considered environment of propagation that is changed by reflection, refraction and multipath in according to space form. It is necessary to find place where urgent situation happen and quickly to respond the situation for patients or the weak. Therefore, we expect the positioning system proposed can apply to the field of traffic IT.

• Information and Communications Magazine
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• v.28 no.7
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• pp.3-14
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• 2011

본고에서는 무선 이동통신 및 무선 데이터 통신의 기술적인 급성장과 함께 스마트폰 사용자의 급증으로 인하여 새롭게 떠오르고 있는 위치 기반 서비스 (Location Based Service; LBS)의 국내외 최근 동향을 알아보고자 한다. 이를 위하여 위치정보를 추정하기 위한 무선측위 기술동향에 대해 알아보고, LBS의 플랫폼 구성 기술 및 응용 동향에 대해 알아본다. 그리고 마지막으로 국내외 기술 개발 동향을 알아본 후에 결론을 맺는다.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.790-798
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• 2021

In this paper, we propose a method to improve the accuracy of positioning by adding angle and distance validation to the existing Bluetooth-based positioning method using the angle of arrival. In the existing positioning method, an error occurs in the positioning value due to a multipath phenomenon induced in a non-visible distance environment. The proposed method derives the maximum and minimum angles of arrival that can be measured in consideration of the moving speed of the positioned device, and then examines whether the measured angle of arrival exceeds the range of the maximum and minimum angles of arrival. The accuracy of positioning is improved by conducting a distance validation check to see if the location of the device to be positioned and the distance to the positioning device exceed the effective distance. A simulation was conducted to analyze the positioning performance between the proposed method and the existing method, and it was confirmed that the positioning performance was improved through angle and distance validation compared to the existing method in a situation where the positioning error increased through the simulation results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.14-19
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• 2020

This paper proposes a precise drone-positioning technique using a differential global positioning system (DGPS). The proposed system consists of a reference station for error correction data production, and a mobile station (a drone), which is the target for real-time positioning. The precise coordinates of the reference station were acquired by post-processing of received satellite data together with the reference station location data provided by government infrastructure. For the system's implementation, low-cost commercial GPS receivers were used. Furthermore, a Zigbee transmitter/receiver pair was used to wirelessly send control signals and error correction data, making the whole system affordable for personal use. To validate the system, a drone-tracking experiment was conducted. The results show that the average real-time position error is less than 0.8 m.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.352-354
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• 2016

Recent with the progress of smart devices, there is an increasing demand for indoor location-based services. For this reason, research on indoor positioning system using a iBeacon techniques added to BLE(Bluetooth Low Energy) specifications of Bluetooth4.0 has been actively. However, RSSI signal used for the measurement of the distance between the iBeacon and the receiving terminal has the problems of inaccurate distance measurement to environmental factors such as obstacles. In this paper, we propose an implemented indoor positioning technique to use filtering technology enhance the reliability of the RSSI signal and the broadcasting signal of the terminal access point function.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.155-158
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• 2017

WiFi Fingerprinting기술의 측위 정확도에 가장 큰 영향을 주는 요인은 수신되는 신호세기(RSS)의 안정성이다. 하지만 실내 환경의 높은 복잡도로 인해 같은 위치에서도 RSS가 시간에 따라 변화하며 불안정하다. 이러한 RSS variance 문제를 해결 하기위한 다양한 연구들이 수행되었다. 하지만 기존 연구들의 경우 시스템의 복잡도가 증가하며, RSS가 급격히 변하는 경우에는 측위 성능을 보장 할 수 없다. 본 논문에서는 특수한 구조를 갖는 Neural Network설계하고 이에 최적화된 입력 Feature고안하며 이를 통해 급격한 RSS 변화에서도 성능을 보장하는 WiFi Fingerprinting 알고리즘 제안한다. 제안하는 알고리즘과 기존 알고리즘을 동일한 조건에서 시뮬레이션을 통해 비교한 결과 제안하는 알고리즘이 급격한 RSS 변화에서 상대적으로 높은 측위 정확도 보여줌을 확인 할 수 있었다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.601-608
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• 2023

Mobile robots are widely used in industries because mobile robots perform tasks in various environments. In order to carry out tasks, determining the precise location of the robot in real-time is important due to the need for path generation and obstacle detection. In particular, when mobile robots autonomously navigate in indoor environments and carry out assigned tasks within pre-determined areas, highly precise positioning performance is required. However, mobile robots frequently experience data missing in wireless communication environments. The robots need to rely on predictive techniques to autonomously determine the mobile robot positions and continue performing mobile robot tasks. In this paper, we propose an extended Kalman filter-based algorithm to enhance the accuracy of mobile robot localization and address the issue of data missing. Trilateration algorithm relies on measurements taken at that moment, resulting in inaccurate localization performance. In contrast, the proposed algorithm uses residual values of predicted measurements in data missing environments, making precise mobile robot position estimation. We conducted simulations in terms of data missing to verify the superior performance of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.550-551
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• 2021

Positioning technology is performing important functions in augmented reality, smart factory, and autonomous driving. Among the positioning techniques, the positioning method using beacons has been considered a challenging task due to the deviation of the RSSI value. In this study, the position of a moving object is predicted by training a neural network that takes the RSSI value of the receiver as an input and the distance as the target value. To do this, the measured distance versus RSSI was collected.