• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.130-137
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• 2010

An uplink indoor positioning system is proposed in the present work, where the acoustic signals are solely used for positioning. The underlying acoustic signals include whistle, finger snap, and hands-clapping. In the proposed method, positioning is achieved by finding the time-difference-of-arrivals using several self-generating sounds. To evaluate the feasibility of the signals and their positioning accuracies, the database of 100 persons about self-generating acoustic signals is built up. The results show that the hands-clapping sound is the most suitable for acoustic-based indoor positioning.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.2
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• pp.139-144
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• 2021

In this paper, we described configuration and construction of infrastructure for the KASS Reference Station (KRS), subsystem of Korea Augmentation Satellite System (KASS). KASS system consists of three subsystems(KRS, Mission Control Center (MCC), KASS Uplink Station (KUS)). One of these subsystems, KRS receives GNSS data for generating range error and integrity verification and sends to MCC. It is needed to antenna facilities for mounting GNSS antenna and shelter for operating KRS and infra equipment(power and network system, lightning and grounding system, fire extinguish) for operating KRS. For this reason, we have established the requirements for KRS infrastructure and constructed infrastructure for KRS to meet the requirements of KRS infrastructure.

• The Journal of Korean Institute of Information Technology
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• v.17 no.2
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• pp.71-77
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• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.