• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1343-1346
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• 2005

위치기반서비스 시스템에서 가장 기본이 되는 요소는 사용자의 위치를 정확히 측정하는 것이다. 측위 시스템은 옥외용과 옥내용으로 구분될 수 있고, 옥외용은 GPS 기반 시스템이 가장 일반적이다. 본 논문은 SiRF StarⅡ chipset을 이용하여 전자캠퍼스를 위한 옥외용 측위시스템 구현 사례를 소개한다. 전자캠퍼스의 특징으로 적용 영역이 비교적 협소하다는 것과 따라서 좀 더 정확한 측정 방법이 필요하다는 것을 들 수 있다. 본 논문은 RADAR 방식을 사용하여 오차를 줄일 수 있다는 것과 사용자 추적 방법 구현 사례를 보인다.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1059-1068
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• 2021

In urban areas, GPS(Global Positioning System)/GNSS(Global Navigation Satellite System) signals are blocked or distorted by structures such as buildings, which limits positioning. To compensate for this problem, in this paper, fingerprinting-based positioning using RSRP(: Reference Signal Received Power) information of LTE signals is performed. The W-KNN(Weighted - K Nearest Neighbors) technique, which is widely used in the positioning step of fingerprinting, yields different positioning performance results depending on the similarity distance calculation method and weighting method used in correlation. In this paper, the performance of the fingerprinting positioning according to the techniques used in correlation is comparatively analyzed experimentally.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.9-14
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• 2014

Recently, precision guided munition systems and missile defense systems based on GPS have been taking a key role in modern warfare. In warfare however, unexpected interferences cause by large/small scale fading, radio frequency interferences, etc. These interferences result in a severe GPS positioning error, which could occur late supports and friendly fires. To solve the problems, this paper proposes an interference mitigation positioning method by adopting a wavelet denoising filter algorithm. The algorithm is applied to a GPS/QZSS/Wi-Fi combined positioning system which was performed by this laboratory. Experimental results of this paper are based on a real field test data of a GPS/QZSS/Wi-Fi combined positioning system and a simulation data of a wavelet denoising filter algorithm. At the end, the simulation result demonstrates its superiority by showing a 21.6% improved result in comparison to a conventional GPS system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1549-1556
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• 2016

By increased moving speed of aircraft, estimating location of itself becomes more important than ever. This requirement is satisfied by appearance of GPS, however it is useless when signal reception from satellite is not good enough by interruption, for example, traffic jamming. Applying link for communication to additional positioning system is capable of providing relative position of aircraft. Estimating location with link for communication is done without additional equipment but with signal processing based on correlation of received signal. ESPRIT is one of the representative algorithm among them. Estimating correlation matrix is possible to have error since it includes average operation needs enough number of samples not impractical. Therefore we propose algorithm that defines, estimates and removes error matrix of correlation. Proposing algorithm shows better performance than previous one when transmitters are close.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.580-585
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• 2009

Real Time Locating Systems (RTLS) are used to track and identify the location of objects in real time using simple, inexpensive tags attached to or embedded in objects and readers that receive the wireless signals from these tags to determine their locations. A tag is powered an internal source such as a battery. The blink frequency of a tag affects the energy efficiency and the locating accuracy of RTLS. The mobility of a tag also affects the locating accuracy. In this paper, we introduce a RTLS tag design which improves the locating accuracy and the power efficiency. We propose an adaptive transmission-rate control algorithm using a motion sensor. By analyzing the signal pattern of the motion sensor, we can build a model to estimate the speed of the motion. Using this model, our algorithm can achieve better locating accuracy and lower power consumption than those of the conventional method. In our experiments, the number of transmission reduced as 40%, keeping similar locating accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.101-108
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• 2005

Inertial Navigation System has been used extensively to determine the position, velocity and attitude of the body. An INS is very expensive, however, heavy, power intensive, requires long setting times and the accuracy of the system is degraded as time passed due to the accumulated error. Global Positioning System(GPS) receivers can compensate for the Inertial Navigation System with the ability to provide both absolute position and attitude. This study describes a method to improve both the accuracy of a body positioning and the precision of an attitude determination using GPS antenna array. Existing attitude determination methods using low-cost GPS receivers focused on the relative vectors between the master and the slave antennas. Then the positioning of the master antenna is determined in meter-level because the single point positioning with pseudorange measurements is used. To obtain a better positioning accuracy of the body in this research, a wireless internet is used as an alternative data link for the real-time differential corrections and dual-frequency GPS receivers which is expected to be inexpensive was used. The numerical results show that this system has the centimeter level accuracy in positioning and the degree level accuracy in attitude.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.25-30
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• 2024

Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.1-9
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• 2006

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the techniques for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase. Off-line phase is not a time critical procedure, but on-line phase is indeed a time-critical procedure. If it is too slow then the user's location can be changed while it is calculating and the positioning method would never be accurate. Even so there is no research of improving efficiency of on-line phase of wireless fingerprinting. This paper proposes a decision-tree method for wireless fingerprinting and performs comparative analysis of the fingerprinting techniques including K-NN, Bayesian and our decision-tree.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.287-295
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• 2010

RTLS used to track the location of object or person in real time. However, if there are a lot of tags and readers, the conventional single RTLS server may fail to estimate location of tags. And if the server cannot receive the tags signal due to pass-loss or NLOS from more than three readers, the server fail to estimate location of tags. In this paper, we propose a special reader which embeds RTLS location engine for distributed RTLS. And by using multi-directional antenna, alleviating multi-path effect and allowing estimate tag's location only using two readers. We also implement the system, we can reduce server packet 16times and get the all results of location estimate in single second. We achieved the location error within 1m.