• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.854-859
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• 2002

Location Based Services, or LBS refers to value-added service by processing information utilizing mobile user location. With the rapidly increasing wireless internet subscribers and world LBS market, the various location based applications are introduced such as buddy finder, proximity and security services. As the killer application of the wireless internet, the LBS has preconsidered technology about location determination technology, LBS middleware server for various application, and diverse contents processing technology. This paper describes the open architecture for LBS platform ensuring interoperability among the wireless networks and various location-based application services and the functional requirements for the LBS platform. The LBS platform in a narrow sense provides a standard interfaces for location management and network management for location services as follows, positioning (location acquisition through network or/and handset), location managing, location based functions, profile management, authentication and security, location based billing, information roaming between carriers and the system monitoring independent to specific network or ISP/CPs(Content Providers).

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.684-690
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• 2015

This paper presents a modified residual-based EKF (Extended Kalman Filter) for performance improvement of indoor positioning using WiFi RSSI (Received Signal Strength Indicator) measurement. Radio signal strength in indoor environments may have irregular attenuation characteristics due to obstacles such as walls, furniture, etc. Therefore, the performance of the RSSI-based positioning with the conventional trilateration method or Kalman filter is insufficient to provide location-based accurate information services. In order to enhance the performance of indoor positioning, in this paper, error analysis of the distance calculated by using the WiFi RSSI measurement is performed based on the radio propagation model. Then, an IARM (Irregularly Attenuated RSSI Measurement) error is defined. Also, it shows that the IARM error is included in the residual of the positioning filter. The IARM error is always positive. So, it is presented that the IARM error can be estimated by taking the absolute value of the residual. Consequently, accurate positioning can be achieved based on the IEM (IARM Error Mitigated) EKF with the residual modified by using the estimated IARM error. The performance of the presented IEM EKF is verified experimentally.

• 한국측량학회지
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• 제37권5호
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• pp.397-402
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• 2019

Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

• Journal of Positioning, Navigation, and Timing
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• 제12권3호
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• pp.323-332
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• 2023

Today, services using Positioning, Navigation, and Timing (PNT) technology are provided in various fields, such as smartphone Location-Based Service (LBS) and autonomous driving. Generally, outdoor positioning techniques depend on the Global Navigation Satellite System (GNSS), and the need for positioning techniques that guarantee positioning accuracy, availability, and continuity is emerging with advances in service. In particular, continuity is not guaranteed in urban canyons where it is challenging to secure visible satellites with standalone GNSS, and even if more than four satellites are visible, the positioning accuracy and stability are reduced due to multipath channels. Research using Low Earth Orbit (LEO) satellites is already underway to overcome these limitations. In this study, we conducted a trend analysis of LEO-PNT research, an LEO satellite-based navigation and augmentation system. Through comparison with GNSS, the differentiation of LEO-PNT was confirmed, and the system design and receiver processing were analyzed according to LEO-PNT classification. Lastly, the current status of LEO-PNT development by country and institution was confirmed.

• 한국정보통신학회논문지
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• 제24권3호
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• pp.448-458
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• 2020

공통현을 이용한 삼변측량 기반 실내 측위의 경우 각 AP로부터 이동체까지의 거리를 구하여, 각 AP별로 해당 거리를 반지름으로 하는 원을 이용하여 원들의 둘레가 교차 되는 접점들을 이용하여 이동체의 위치를 예상한다. 거리 오차로 인하여 원 간의 접점이 생성되지 않는 경우, 위치 예상에 실패하게 된다. 본 논문에서는 이를 개선하기 위한 알고리즘을 제안하였는데, 거리에 따라 반지름의 크기에 비례한 값을 임의로 추가하여 강제로 접점을 생성하여 예상 위치를 생성한 뒤, 해당 원의 반지름에 추가된 임의 값과 원점으로부터, 거리에 따른 보정을 하였다. 기존 삼변측량의 거리 오차로 인한 좌표 생성 실패 비율과 좌표 측위 오차를 최소화하는 발전된 알고리즘을 제안하고 시스템을 제작하여 성능을 분석하였다.

• 한국컴퓨터정보학회논문지
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• 제28권3호
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• pp.11-16
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• 2023

실내 측위를 위한 기법으로 Fingerprinting, 삼변 측량을 이용한 실내 위치 측위 방법, Wi-Fi / Bluetooth 등 장비로 얻은 정보를 활용하여 사용자의 실내 위치를 특정 하는 것이 일반적이고 대표적인 방법이다. 하지만 이러한 방법들은 실내 공간이 다수의 장비(AP, Beacon)를 설치할 수 있을 만큼의 장소가 마련되어야 한다. 본 논문에서는 폭이 좁은 건물 등 기존 방식을 적용할 수 없는 건물 구조에서 GPS 신호와 비콘 으로부터 전달된 신호를 동시에 이용하여 건물 내 사용자의 위치를 표현할 수 있는 기법을 제안한다. 또한 최단 경로 탐색을 위해 가장 대표적이고 효율적인 최단 경로 탐색 알고리즘 중의 하나인 다익스트라 알고리즘(Dijkstra Algorithm)를 적용하여 최단 경로 탐색 시스템을 설계 구현했다. 제안된 기법은 향후 건물 구조 특성을 고려한 사용자 실내 위치 측정 방법 중 하나로 고려될 수 있을 것이다.

• 한국전자거래학회지
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• 제13권4호
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• pp.1-16
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• 2008

위치기반서비스에서 사용자의 위치를 확인하고 추적하는 것이 필수적이다. 특히 옥내에서 위치기반서비스를 제공하기 위해 많은 연구자들은 무선 근거리통신망 환경에서 사용자의 옥내 위치추적에 대해 연구를 수행해 오고 있다. 한편, GPS를 이용하는 옥외에서의 위치추 적에는 칼만필터(Kalman filter)가 이용되기도 하였다. 본 연구에서는 오늘날 널리 보급되어 있는 무선 근거리통신망 환경에서 옥내 위치추적에 적용될 수 있는 확장칼만필터 방법을 제안한다. 기존 연구와 본 제안방법을 비교 실험한 결과, 칼만 필터를 사용함으로써 궤적 측정치의 정확도를 제고할 수 있으며, 나아가서 지도정보를 이용함으로써 정확도를 더욱 제고할 수 있음을 보인다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 추계학술대회
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• pp.122-124
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• 2010

WPS(Wifi Positioning System)은 실세계에 산재해 있는 AP의 정보를 활용한 측위 기법이다. WPS에서 사용되는 측위 연산은 일반적으로 핑거 프린트 기법을 사용한다. 핑거 프린트 기법은 평균값을 활용한 측위 기법으로 측위 정확도의 문제와 수식 연산을 사용함으로써 발생하는 성능 저하의 문제가 있다. 본 논문에서는 이러한 기존의 핑거프린트 문제점을 해결하기 위한 MSS(Max Signal Strength) 기법을 설명하고 동일한 조건에서 연산시간 감소와 정확도 향상 방안을 제안한다. 이를 검증하기 위한 테스트 환경에 대하여 제시하며, 성능을 분석한다.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.41-46
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• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.