• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.335-342
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• 2023

Lunar Navigation Satellite System refers to a constellation of satellite providing PNT services on the moon. LNSS consists of main satellite and navigation satellites. Navigation satellites orbiting around the moon and a main satellite moves the area between the moon and the L2 point. The navigation satellite performs the same role as the Earth's GNSS satellite, and the main satellite communicates with the Earth for time synchronization. Due to the effect of the non-uniform shape of the moon, it is necessary to focus on the influence of the lunar gravitational field when designing the orbit simulation for navigation satellite. Since the main satellite is farther away from the moon than the navigation satellite, both the earth's gravity and the moon's gravity must be considered simultaneously when designing the orbit simulation for main satellite. Therefore, the main satellite orbit simulation must be designed through the three-body problem between the Earth, the moon, and the main satellite. In this paper, the orbit simulation tool for main satellite and navigation satellite required for LNSS was designed. The orbit simulation considers the environment characteristics of the moon. As a result of comparing long-term data (180 days) with the commercial program GMAT, it was confirmed that there was an error of about 1 m.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.63-73
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• 2024

NeQuick G is the ionosphere model utilized by Galileo single-frequency users to estimate the ionospheric delay on each user-satellite link. The model is characterized by the effective ionization level (Az) index, determined by a modified dip latitude (MODIP) and broadcast coefficients derived from daily global space weather observations. However, globally fitted Az coefficients may not accurately represent ionosphere within local area. This study introduces a method for regional ionospheric modeling that searches for locally optimized Az coefficients. This approach involves fitting TEC output from NeQuick G to TEC data collected from GNSS stations around Korea under various ionospheric conditions including different seasons and both low and high solar activity phases. The optimized Az coefficients enable calculation of the Az index at any position within a region of interest, accounting for the spatial variability of the Az index in a polynomial function of MODIP. The results reveal reduced TEC estimation errors, particularly during high solar activity, with a maximum reduction in the RMS error by 85.95%. This indicates that the proposed method for NeQuick G can effectively model various ionospheric conditions in local areas, offering potential applications in GNSS performance analyses for local areas by generating various ionospheric scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2481-2486
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• 2013

It requires a lot of time and effort for general users who do not have enough understanding of GPS to properly processing GPS data. However, the GPS data processing field heavily relies on foreign-produced software and there is almost no development of user-oriented technology. Therefore, in this study, it was attempted to build an expert service that enables non-experts to use high-precision GPS data processing. As a result, an expert service that can maximize user convenience simply by entering the minimum required information for GPS data processing was developed, and the expert service was verified by relative positioning processing of the observation data of satellite control point provided by National Geographic Information Institute and observation data obtained by GPS survey. The expert service significantly reduces the effort and time for processing GPS data, which will contribute to precise positioning and other various studies.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.58-63
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• 2015

Due to GPS signal's vulnerability of jamming attack, various enhancement techniques are needed. Among variety of techniques, we focused on GPS receiver's anti-jamming techniques. There are many anti-jamming methods at GPS receivers which include filtering methods in time domain, frequency domain and space domain. However, these methods are ineffective to signals, which include both jamming and noise. To solve the problem, this paper proposes a jamming separation scheme by using a BSS method in a jamming environment. As separated GPS signals include noise after the jamming separation method, it is difficult to receive accurate GPS signals. For this reason, this paper also proposes a wavelet de-noising method to effectively eliminate noise. Experimental results of this paper are based on a real field test data of an integrated GPS/QZSS/Wi-Fi positioning system. At the end, the simulation result demonstrates its superiority by showing improved positioning accuracy.

• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.37-44
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• 2016

Republic of Korea has established its performance-based navigation (PBN) implementation plan in 2010 for ensuring a smooth transition to PBN operations and relevant new flight procedures are being developed in accordance with the roadmap. Various Navigation aids (NAVAIDs) like global navigation satellite systems (GNSS), distance measuring equipment (DME), VHF omnidirectional range (VOR), inertial navigation system (INS) are used to support PBN procedures. Among them, GNSS would play a central role in PBN implementation. However, vulnerability of satellite navigation signals to artificial and natural interferences has been discovered and various alternative positioning, navigation and timing (APNT) technologies are under development in many countries. In this paper, we study whether continuous PBN operations can be achievable without GNSS signals. As a result, it shows that some of the domestic airports require the construction of APNT in the approach area.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.417-425
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• 2012

It is well known that GPS cannot provide positioning results if sufficient number of visible satellites are not available. To overcome this weak point, attentions have been recently moved to hybrid positioning methods that augments GPS with other sensors. As an extension of hybrid positiong methods, this paper proposes a new method that combines GPS and vision sensor to improve availability and accuracy of land vehicle positioning. The proposed method does not require any external map information and can provide position solutions if more than 2 navigation satellites are visible. To evaluate the performance of the proposed method, an experiment result with real measurements is provided and a result shows that accumulated error of n-axis is almost 2.5meters and that of e-axis is almost 3meters in test section.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.479-484
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• 2017

A Neustrelitz TEC model (NTCM) developed by Deutsches Zentrum $f{\ddot{u}}r$ Luft- und Raumfahrt (DLR) provides a better accuracy than the global positioning system (GPS) Klobuchar model for predicting ionospheric delay. The NTCM model accuracy is comparable to Galileo NeQuick model, and it has less computation time. The NTCM model uses F10.7 values as a parameter of solar activity function, while a NTCM-Broadcast (NTCM-BC) uses TEC values from a Klobuchar model. For this reason, a NTCM-BC model can be used for real-time ionosphere correction. In this paper, vertical ionospheric delay and GPS positioning errors in Korea by using a NTCM-BC ionosphere model from 2009 to 2014 are analyzed and compared with those of a Klobuchar model. In the 6-year statistics, the vertical ionospheric delay is reduced by 17.7 %, and horizontal and vertical positioning accuracies by the NTCM-BC model are improved by 25.6 % and 6.7 %, respectively, over the Klobuchar model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2321-2330
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• 2015

A variety of studies for indoor positioning are now being in progress due to the limit of GPS that becomes obsolete in the room. However, most of them are based on private wireless networks and the situation is difficult to commercialize them since they are expensive in terms of installation and maintenance costs, non-real-time, and not accurate. This paper applies the mark recognition algorithm used in existing augmented reality applications to the indoor vehicle positioning application. It installs floor marks on the ground, performs the perspective transformation on it and decodes the internal data of the mark and, as a result, it obtains an absolute coordinate. Through the geometric analysis, it obtains current position (relative coordinates) of a vehicle away from the mark and the heading direction of the vehicle. The experiment results show that when installing the marks every 5 meter, an error under about 30 cm occurred. In addition, it is also shown that the mark recognition rate is 43.2% of 20 frames per second at the vehicle speed of 20km/h. Thus, it is thought that this idea is commercially valuable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1950-1956
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• 2017

In food-printing field, precise positioning technique for a printing object is very important. In this paper, we propose cup positioning method for a latte-art printer through image processing. A camera sensor is installed on the upper side of the printer, and the image obtained from this is projected and converted into a top-view image. Then, the edge lines of the image is detected first, and then the coordinate of the center and the radius of the cup are detected through a Circular Hough transformation. The performance evaluation results show that the image processing time is 0.1 ~ 0.125 sec and the cup detection rate is 92.26%. This means that a cup is detected almost perfectly without affecting the whole latte-art printing time. The center point coordinates and radius values of cups detected by the proposed method show very small errors less than an average of 1.5 mm. Therefore, it seems that the problem of the printing position error is solved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.75-80
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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. A neural network was introduced to create synthetic data from the collected actual data. Based on this neural network, the RSSI value versus distance was predicted. The real value of RSSI was obtained as a neural network for generating synthetic data, and based on this value, the coordinates of the object were estimated by learning a neural network that tracks the location of a terminal in a virtual environment.