• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.564-567
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• 2007

GPS(Global Positioning System) data has a high accuracy at outdoor positioning generally, but its accuracy decreases in the urban areas with dense buildings. Moreover insufficient number of satelllites prevent us GPS positioning at inside of buildings. To complement these shortcomings of GPS, RFID(Radio Frequency IDentification) has been studied on indoor positioning parts. In Ubiquitous environment, LBS(Location Based Service) which can be used anytime and anywhere is an essential component. We use kalman filter to estimate the real location in GPS and RFID handover area. This study's purpose is to make a continuous positioning system using interlocking RFID and GPS.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.169-171
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• 2010

The goal of this study is to evaluate the performance of different solution types(a GPS-only, a GLONASS-only, and a GNSS solution) on GNSS positioning modes which are point positioning and relative positioning(DGNSS-, Static-, and Kinematic-solutions). I started with GNSS sites of seoul metropolitan government's RTK network which providing combined GPS/GLONASS observations : Gangseo(GANS), Dobong(DBON). The positioning accuracy of different solution types on positining modes are compared. Considering the compared results of all cases, can find not only the difference of the performance between the GNSS solution and the GPS-only solution is very small, but also the GLONASS-only solution is not far from the other solution types taking into consideration that GLONASS system is not (yet) a complete system.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.151-156
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• 2020

A technology for calculating the position of a device is very important for users who receive positioning services, regardless of various indoor/outdoor or with/without any positioning infrastructure existence environments. One of the positioning resources widely used at present, LTE, is a typical infrastructure that can overcome the space limitation, however its positioning method based on the position of the LTE base station has low accuracy. A method of constructing a radio wave map of an LTE signal has been proposed as a method for overcoming the accuracy, but it takes a lot of time and cost to perform high-density collection in a wide area. In this paper, we describe a method of creating a high-density DB for the entire region by using vehicle-based partial collection data. To create a positioning database, we applied the idea of Generative Adversarial Network (GAN), which has recently been in the spotlight in the field of deep learning, and learned the collected data. Then, a virtually generated map which having the smallest error from the actual data is selected as the optimum DB. We verified the effectiveness of the positioning DB generation algorithm using the positioning data obtained from un-collected area.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.23-28
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• 2022

The eLoran system is a high-power terrestrial navigation system that is recognized as the most appropriate alternative to complement the GNSS's vulnerability to radio frequency interference. Accordingly, Korea has conducted eLoran technology development projects since 2016. The eLoran system developed in Korea provides 20 m positioning accuracy to maritime user in Incheon and Pyeongtaek harbor. To accurately calculate the position with the eLoran signal, it is necessary to apply a compensation method that mitigates the propagation delay. In this paper, we develop the compensation method to mitigate the eLoran signal propagation delay and evaluate the positioning performance in Incheon harbor. The propagation delay due to the terrain characteristics is pre-surveyed and stored in the user receiver. Real-time fluctuations in propagation delay compared to the pre-stored data are mitigated by the temporal correction generated at a nearby differential Loran station. Finally, two performance evaluation tests were performed to verify the positioning accuracy of the Korean eLoran system. The first test took place in December 2020 and the second in April 2021. As a result, the Korean eLoran service has been confirmed to provide 20 m location accuracy without GPS.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.98-104
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• 1999

As the accuracy of manufactured goods needed high accuracy processing has made the efficiency of NC and measurement technology development, the innovation of machine tools has influence the development of the semi-conductor and optical technology. The movement errors can be expressed in terms of yaw, roll an pitch etc. In the case of expanding the error range, static, dynamic and servo gain errors can be included. Machining center might have twenty-one movement errs including three types of joint errors. Those errors have been measured on the condition of just loading of standard table. Regarding these measuring methods, the mechanical compliance of the structure has not been considered. In this paper, therefor, the influences of the additional load on the positioning accuracy are investigated. The results and the techniques proposed in this study can be considered very effective and useful to compensate more correctly the positioning motion.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.139-142
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• 2020

NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.723-743
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• 2016

Indoor positioning is considered an enabler for a variety of applications, the demand for an indoor positioning service has also been accelerated. That is because that people spend most of their time indoor environment. Meanwhile, the smartphone integrated powerful camera is an efficient platform for navigation and positioning. However, for high accuracy indoor positioning by using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) users' moving in large buildings. To address those issues, this paper uses the TC-OFDM for calculating the coarse positioning information includes horizontal and altitude information for assisting smartphone camera-based positioning. Moreover, a unified representation model of image features under variety of scenarios whose name is FAST-SURF is established for computing the fine location. Finally, an optimization marginalized particle filter is proposed for fusing the positioning information from TC-OFDM and images. The experimental result shows that the wide location detection accuracy is 0.823 m (1σ) at horizontal and 0.5 m at vertical. Comparing to the WiFi-based and ibeacon-based positioning methods, our method is powerful while being easy to be deployed and optimized.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.50-55
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• 2023

Due to the unavailability of global positioning system (GPS) indoors, various indoor pedestrian positioning methods have been designed to estimate the position of the user using received signal strength (RSS) measurements from radio beacons, such as wireless fidelity (WiFi) access points and Bluetooth low energy (BLE) beacons. In indoor environments, radio-frequency (RF) signals are unpredictable and change over space and time because of multipath associated with reflection and refraction, shadow fading caused by obstacles, and interference among different devices using the same frequencies. Therefore, the outliers in the positional information obtained from the indoor positioning method based on RSS measurements occur often. For this reason, the performance of the positioning method can be degraded by the characteristics of the RF signal. To resolve this issue, a map-matching (MM) algorithm based on maximum probability (MP) estimation is applied to the indoor positioning method in this study. The MM algorithm locates the aberrant position of the user estimated by the positioning method within the limits of the adjacent pedestrian passages. Empirical experiments show that the positioning method can achieve higher positioning accuracy by leveraging the MM algorithm.

• Progress in Medical Physics
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• v.24 no.4
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• pp.290-294
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• 2013

Stereotactic Radiosurgery require high accuracy and precision of patient positioning and target localization. We evaluate the real time positioning accuracy of isocenter using optic guided patient positioning system, ExacTrac (BrainLab, Germany), during spinal radiosurgery procedure. The system is based on real time detect multiple body markers attached on the selected patient skin landmarks. And a custom designed patient positioning verification tool (PPVT) was used to check the patient alignment and correct the patient repositioning before radiosurgery. In this study, We investigate the selected 8 metastatic spinal tumor cases. All type of tumors commonly closed to thoracic spinal code. To evaluate the isocenter positioning, real time patient alignment and positioning monitoring was carried out for comparing the current 3-dimensional position of markers with those of an initial reference positions. For a selected patient case, we have check the isocenter positioning per every 20 millisecond for 45 seconds during spinal radiosurgery. In this study, real time average isocenter positioning translation were $0.07{\pm}0.17$ mm, $0.11{\pm}0.18$ mm, $0.13{\pm}0.26$ mm, and $0.20{\pm}0.37$ mm in the x (lateral), y (longitudinal), z (vertical) directions and mean spatial error, respectively. And body rotations were $0.14{\pm}0.07^{\circ}$, $0.11{\pm}0.07^{\circ}$, $0.03{\pm}0.04^{\circ}$ in longitudinal, lateral, table directions and mean body rotation $0.20{\pm}0.11^{\circ}$, respectively. In this study, the maximum mean deviation of real time isocenter positioning translation during spinal radiosurgery was acceptable accuracy clinically.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.1
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• pp.9-17
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• 2013

In this paper, a pseudorange correction regeneration algorithm was developed to improve the positioning accuracy of DGPS using multi-reference stations, and the optimal minimum number of reference sites was determined by trying out different numbers of reference. This research was conducted using from two to five sites, and positioning errors of less than 1 m were obtained when pseudorange corrections are collected from at least four reference stations and interpolated as the pseudorange correction at the rover. After determining the optimal minimum number of reference stations, the pseudorange correction regeneration algorithm developed was tested by comparison with the performance of other algorithms. Our approach was developed based on an exponential model. If pseudorange corrections are regenerated using an exponential model, the effect of a small difference in the baseline distance can be enlarged. Therefore, weights can be applied sensitively even when the baseline distance differs by a small amount. Also weights on the baseline distance were applied differently by assigning weights depending on the difference of the longest and shortest baselines. Through this method, the positioning accuracy improved by 19% compared to the result of previous studies.