• Journal of Positioning, Navigation, and Timing
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• v.3 no.3
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• pp.123-129
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• 2014

The real-time kinematic (RTK) is one of precise positioning methods using Global Positioning System (GPS) data. In the long baseline GPS RTK, the ionospheric and tropospheric delays are critical factors for the positioning accuracy. In this paper we present RTK algorithms for long baselines more than 100 km with estimating tropospheric delays. The state vector is estimated by the extended Kalman filter. We show the experimental results of GPS RTK for various baselines (162.10, 393.37, 582.29, and 1283.57 km) by using the Korea Astronomy and Space Science Institute GPS data and one International GNSS Service (IGS) reference station located in Japan. As a result, we present that long baseline GPS RTK can provide the accurate positioning for users less than few centimeters.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.87-94
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• 2019

The Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) positioning has been widely used in geodesy, surveying, and navigation fields. RTK can benefit enormously from the integration of multi-GNSS. In this study, we develop a GPS/BeiDou Navigation Satellite System (BDS) RTK integration algorithm for long baselines ranging from 128 km to 335 km in South Korea. The positioning performance with GPS/BDS RTK, GPS-only RTK, and BDS-only RTK is compared in terms of the positioning accuracy. An improvement of positioning accuracy over long baselines can be found with GPS/BDS RTK compared with that of GPS-only RTK and that of BDS-only RTK. The positioning accuracy of GPS/BDS RTK is better than 2 cm in the horizontal direction and better than 5 cm in the vertical direction. A lower Relative Dilution of Precision (RDOP) value with GPS/BDS integration can obtain a better positional precision for long baseline RTK positioning.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.185-190
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• 2006

The correct estimation of the ionospheric delays is very important for the precise kinematic positioning especially in case of the long baseline. In case of triple frequency system, the ionospheric delays can be estimated from the measurements, but, in case of dual frequency system, the situation is not so simple. The precision of those supplied by the external information source such as IONEX is not sufficient. The high frequency component is neglected, and the precision of the low frequency component is not sufficient for the long baseline positioning. On the other hand, the high frequency component can be estimated from the phase range measurements. If the low frequency components are estimated by using the external information source or pseudo range measurements, a more reasonable estimation of the ionospheric delays may be possible. It has already been discussed by the author that the estimation of the low frequency components by using the external information source is not sufficient but fairly effective. The estimation using the pseudo range measurements is discussed in the present paper. The accuracy is not sufficient at present because of the errors in the pseudo range measurements. It is clarified that the bias errors in the pseudo range measurements are responsible for the poor accuracy of the ionospheric delays. However, if the accuracy of the pseudo range measurements is improved in future, the method would become very promising.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.386-389
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• 2007

Currently, fast and accurate long baseline positioning in kinematic mode is a challenging topic, but positional accuracy can be improved with the help of the network-derived external ionospheric corrections. To provide not only ionospheric corrections, but also their variances, satellite-by-satellite interpolation for the ionospheric delays is performed using the least-squares collocation (LSC) method. Satellite-by-satellite interpolation has the advantage in that the vertical projection used in single-layer ionospheric model is not required. Also, more reliable user positioning and the corresponding accuracy assessment can be obtained by providing not only external ionospheric corrections but also their variances. The rover positioning with and without the external ionospheric delays in both rapid-static and kinematic mode was performed and analyzed. The numerical results indicate that the improvement in the positioning quality is achieved using the proposed method. With the TAMDEF network in Antarctica, 18 % improvement in mean time-to-fix in kinematic mode was achieved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.135-143
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• 2009

Integrating the Global Positioning System (GPS) and Inertial Navigation System (INS) sensor technologies using the precise GPS Carrier phase measurements is a methodology that has been widely applied in those application fields requiring accurate and reliable positioning and attitude determination; ranging from 'kinematic geodesy', to mobile mapping and imaging, to precise navigation. However, such integrated system may not fulfil the demanding performance requirements when the baseline length between reference and mobil user GPS receiver is grater than a few tens of kilometers. This is because their positioning/attitude determination is still very dependent on the errors of the GPS observations, so-called "baseline dependent errors". This limitation can be remedied by the integration of GPS and INS sensors, using multiple reference stations. Hence, in order to derive the GPS distance dependent errors, this research proposes measurement processing algorithms for multiple reference stations, such as a reference station ambiguity resolution procedure using linear combination techniques, a error estimation based on Kalman filter and a error interpolation. In addition, all the algorithms are evaluated by processing real observations and results are summarized in this paper.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.12
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• pp.1032-1039
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• 2012

The present paper deals with precise relative positioning of formation satellites with long baseline in low Earth orbit making use of L1/L2 dual frequency GPS carrier phase measurements. Kinematic approach means to describe the motion of objects without taking its mass/dynamics model into consideration. The advantage of the kinematic approach is that information about dynamics of the system is not applied, which gives more flexibility and could improve the scientific interest of the observations made by the mission. The ionosphere terms, which are not canceled by double differenced measurement equation in the case of the long baseline, are explicitly estimated as unknown parameters by extended Kalman filter. The estimated float ambiguities by EKF are solved by existing efficient integer vector search strategy under integer least square condition. For the integer vector search, we employ well known MLAMBDA. Finally, The feasibility and accuracy of processing scheme are demonstrated using the GPS measurements for two satellites in low Earth orbit separated by baselines of 100 km.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.693-700
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• 2009

For real-time precise GPS data processing such as a long baseline network RTK (Real-Time Kinematic) survey, PPP (Precise Point Positioning) and monitoring of ionospheric/tropospheric delays, it is necessary to guarantee accuracy comparable to IGS (International GNSS Service) precise orbit with no latency. As a preliminary study for determining near real-time satellite orbits, the general procedures of satellite orbit determination, especially the dynamic approach, were studied. In addition, the transformation between terrestrial and inertial reference frames was tested to integrate acceleration. The IAU 1976/1980 precession/nutation model showed a consistency of 0.05 mas with IAU 2000A model. Since the IAU 2000A model has a large number of nutation components, it took more time to compute the transformation matrix. The classical method with IAU 2000A model was two times faster than the NRO (non-rotating origin) approach, while there is no practical difference between two transformation matrices.