• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.197-200
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• 2008

A GNSS augmentation system provides precise position information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (Ionospheric and Tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common errors (noise errors) of ionosphere and troposphere wet vapor.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.2
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• pp.11-18
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• 2016

Global Positioning System (GPS) is currently widely used for aviation applications. Single-frequency GPS receivers are highly affected by the ionospheric delay error, and the ionospheric delay should be corrected for accurate positioning. Single-frequency GPS receivers use the Klobuchar model, whose model parameters are transmitted from GPS satellites. In this paper, the long-term accuracy of the Klobuchar model from 2002 to 2014 is analyzed. The IGS global ionosphere map is considered as true ionospheric delay, and hourly, seasonal, and geographical error variations are analyzed. Histogram of the ionospheric delay error is also analyzed. The influence of solar and geomagnetic activity on the Klobuchar model error is analyzed, and the Klobuchar model error is highly correlated with solar activity. The results show that the Klobuchar model estimates 8 total electron content unit (TECU) over the true ionosphere delay in average. The Klobuchar model error is greater than 12 TECU within $20^{\circ}$ latitude, and the error is less than 6 TECU at high latitude.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1045-1050
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• 2008

A GNSS augmentation system provides precision information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (ionospheric and tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common error (noise errors) of ionosphere and troposphere wet vapor.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.49-54
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• 2013

This paper describes the progress and results of 'Wide Area Differetial GNSS (WA-DGNSS) Development' project which is supported by Korea Ministry of Land, Transport and Maritime Affairs. This project develops the main algorithm of the WA-DGNSS which can guarantee the improved accuracy, availability and integrity all over the Korean peninsula. After the establishment of WA-DGNSS ground system, a real time demonstration using pseudolite will be conducted. Product of this project will be directly utilized in Korean Satellite Based Augmentation System(SBAS) development project which is planned to be started from 2014.

• Journal of Navigation and Port Research
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• v.37 no.3
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• pp.263-267
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• 2013

This paper describes the progress and the plan of 'Wide Area Differential GPS (WA-DGPS) Development' project supported by Korean Ministry of Oceans and Fisheries. The project develops the main algorithms of the WA-DGPS which guarantees the improved accuracy, availability, and integrity all over the Korean peninsula. After the establishment of WA-DGPS ground infrastructure system, a real-time demonstration using pseudolite installed on the ground will be conducted in the final year. Also, the development of Korean Satellite-based Augmentation System (SBAS) is expected to be started from 2014, and the algorithms and the results in the WA-DGPS project will be used in the SBAS development.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.247-252
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• 2004

It's important to develop Metadata standard to manage a large of marine geospatial data such as observation, ocean survey, satellite image more effectively. If we use metadata in Marine GIS we can make sense marine geospatial data, make the most of marine dataset. International standard organization's work and NGIS's standard are a good example to illustrate metadata standard's importance. But we don't have metadata standard for marine dataset, so it's difficult to search and use geospatial data In this paper, we presented common marine metadata element, and composited metadata implementation schema. Finally we constructed marine GIS metadata editing tool..

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.205-215
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• 2012

A GPS sensor is widely used in many areas such as navigation, or air traffic control. Particularly, the car navigation system is equipped with GPS sensor for locational information. However, when a car goes through a tunnel, forest, or built-up area, GPS receiver cannot get the enough number of satellite signals. In these situations, a GPS receiver does not reliably work. A GPS error can be formulated by sum of bias error and sensor noise. The bias error is generated by the geometric arrangement of satellites and sensor noise error is generated by the corrupted signal noise of receiver. To enhance GPS sensor accuracy, these two kinds of errors have to be removed. In this research, we make the road database which includes Road Database File (RDF). RDF includes road information such as road connection, road condition, coordinates of roads, lanes, and stop lines. Among the information, we use the stop line coordinates as a feature point to correct the GPS bias error. If the relative distance and angle of a stop line from a car are detected and the detected stop line can be associated with one of the stop lines in the database, we can measure the bias error and correct the car's location. To remove the other GPS error, sensor noise, the Kalman filter algorithm is used. Additionally, using the RDF, we can get the information of the road where the car belongs. It can be used to help the GPS correction algorithm or to give useful information to users.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1349-1359
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• 2021

Acquisition of precise position and velocity information of GNSS-INS (Global Navigation Satellite System; Inertial Navigation System) sensors in obtaining SAR SLC (Single Look Complex) images from raw data using BPA (Backprojection Algorithm) was regarded decisive. Several studies on BPA were accompanied by Kalman Filter for sensor noise oppression, but often implemented once where insufficient information was given to determine whether the filtering was effectively applied. Multiple operation of Kalman Filter on GNSS-INS sensor was presented in order to assess the effective order of sensor noise calibration. FMCW (Frequency Modulated Continuous Wave)-SAR raw data was collected from twice airborne experiments whose GNSS-INS information was practically and repeatedly filtered via Kalman Filter. It was driven that the FMCW-SAR raw data with diverse path information could derive different order of Kalman Filter with optimum operation of BPA image restoration.