• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.333-333
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• 2023

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.229-236
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• 2023

As the importance and dependency of the positioning, navigation, and timing (PNT) information provided by the radio navigation satellite service (RNSS) increases, the vulnerability of RNSS to jamming can lead to significant risks. The signal design under the consideration of anti-jamming performance helps to provide service which is robust to jamming environment. Therefore, it is necessary to evaluate the jamming robustness performance during the design of new signals. In this paper, we introduce figures-of-merit (FoMs) that can be used for an anti-jamming performance analysis of designed signals of interest. We then calculate the FoMs, such as the quality factor (Q factor), tolerable jamming-to-signal ratio (tolerable J/S), and range to jammer (d) for legacy RNSS signals and analyze the results. Finally, based on the results of the analysis, we derive waveform design conditions to obtain good anti-jamming performance. As a result, this paper shows that the waveforms with wide bandwidth leading to good spectral efficiency provide strong anti-jamming performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1951-1972
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• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.583-591
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• 2018

With the development of ICT(Information and Communication Technology), the number of smart devices is rapidly increasing. LBS(Location Based Service) applications that provide user's location based service are used in various fields. There is also a growing demand for indoor precision positioning technology to provide seamless services. In this paper, we propose an indoor positioning system that estimates the location of a smartphone user. The proposed algorithm determines whether the received signal is LOS(Line-of-Sight) or NLOS(Non-Line of-Sight) in order to decrease multipath effect by the indoor environment. The proposed positioning algorithm is very simple and requires only the AP(Access Point) coordinates. In addition, it requires only two APs for estimating the location of a smartphone user. The proposed algorithm is a practically applicable technology without any additional hardware and kernel modification in the smartphone. In the experiment results, the reliability of the positioning system was found to be within 0.83 m.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.9
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• pp.954-960
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• 2009

In this paper, Indoor Positioning System based on Wi-Fi system which is one of the key technology in LBS(Location Based Service) is proposed. The proposed system estimates distance between MS(Mobile Station) and AP(Access Point) using RSSI(Received Signal Strength Indicator). RSSI is affected by outlier that originate from indoor environment complexity and obstacle. In this paper, we introduce a Robust outlier Extended Kalman Filter that can ignore, real-time outlier in the observations. To demonstrate performance of proposed indoor positioning system, we used a PDA as the MS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.3
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• pp.87-94
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• 2017

GNSS modernization and development is in progress throughout the globe, and it is focused on the addition of a new navigation signal. Accordingly, for the next-generation GNSS signals that have been developed or are under development, various combinations that are different from the existing GNSS signal structures can be introduced. In this regard, to design an advanced signal, it is essential to clearly understand the effects of the signal structure and design variables. In the present study, the effects of the GNSS spreading code period and GNSS data bit duration (i.e., signal design variables) on the signal processing performance were analyzed when the data bit transition was considered, based on selected GNSS signal design scenarios. In addition, a method of utilizing the obtained result for the design of a new GNSS signal was investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2382-2386
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• 2003

The Global Positioning System(GPS) is a satellite based precise positioning system avaliable worldwide. The GPS have many error sources. The earth's ionosphere and atmosphere cause delays in the GPS signal that translate into position errors. Some errors can be factored out using mathematics and modeling. The configuration of the satellites in the sky can magnify other errors. The problem of accuracy on GPS measurement data can be meaningful. In this study, we propose the method for GPS positioning accuracy improvement. The FUZZY set theory on PDOP(Position Dilution of Precision) and SNR(Signal to Noise Ratio) provide improved for measured positioning data. The accuracy of positioning has been improved by selecting data from original using the FUZZY set theory on PDOP and SNR.