• 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.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.59-68
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• 2019

This paper proposed a method to estimate the vertical delay from the slant delay, which can improve accuracy of the ionospheric correction of SBAS. Proposed method used Chapman profile which is a model for the vertical electron density distribution of the ionosphere. In the proposed method, we assumed that parameters of Chapman profile are given and the vertical ionospheric can be modeled with linear function. We also divided ionosphere into multi-layer. For the verification, we converted slant ionospheric delays to vertical ionospheric delays by using the proposed method and generated the ionospheric correction of SBAS with vertical delays. We used International Reference Ionosphere (IRI) model for the simulation to verification. As a result, the accuracy of ionospheric correction from proposed method has been improved for 17.3% in daytime, 10.2% in evening, 2.1% in nighttime, compared with correction from thin shell model. Finally, we verified the method in the SBAS user domain, by comparing slant ionospheric delays of users. Using the proposed method, root mean square value of slant delay error decreased for 23.6% and max error value decreased for 27.2%.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.651-657
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• 2011

There exists a high correlation between the ionospheric delays and the integer ambiguity in GPS observation equation, so that the sufficient time span is required to revolve the integer ambiguity. This means that the ambiguity resolution plays a key role especially in rapid-static positioning mode. To analyze the effect of ionospheric disturbances on the positioning accuracy, 02/19/2011 day of dataset was selected processed in rapid-static positioning mode. The total of 141 30-minute sessions were processed, i.e., the estimation procedure started every 10 minutes, and the time-to-fix information of each data interval is obtained. In this study, the analysis is performed by comparing the time-to-fix with the magnitudes of ionospheric delays. The computed correlation coefficient between the time-to-fix and the magnitudes of ionospheric delays is 0.31, which indicates the ionospheric disturbances affect the positioning accuracy in rapid-static positioning mode. Therefore, it is required to collect and process sufficient data when the GPS surveying is performed in unfavorable ionospheric conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.575-581
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• 2012

In general, various modeling and estimation techniques have been proposed to extract the tropospheric and ionospheric delays from the GPS CORS. In this study, Kalman filter approach is adopted to estimate the tropospheric and ionospheric delays and the proper modeling for the state vector and the variance-covariance matrix for the process noises are performed. The coordinates of reference stations and the zenith wet delays are estimated with the assumption of random walk stochastic process. Also, the first-order Gauss-Markov stochastic process is applied to compute the ionospheric effects. For the evaluation of the proposed modeling technique, Kalman filter algorithm is implemented and the numerical test is performed with the CORS data. The results show that the atmospheric effects can be estimated successfully and, as a consequence, can be used for the generation of VRS data.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.391-398
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• 2009

Variations of mean ionospheric spatial gradient over Korea are analyzed in order to support GNSS (Global Navigation Satellite System) augmentation systems and integrity monitering systems. A software for analyzing the ionospheric spatial gradient is developed using an ionospheric plate model. Daily and annual variations of ionospheric delay and spatial gradient are analyzed using GPS data in 2003 and 2005 respectively. The ionospheric delays and spatial gradients in 2003 were larger than 2005. Also, the south-north gradient, about -1.0mm/km, is nearly two times larger than the east-west gradient. The annual ionospheric spatial gradients over Korea is varied within 2mm/km.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.64-72
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• 2016

The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.319-325
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• 2007

In case of more than 50km baseline length, the correlation between receivers is reduced. Therefore, there are still some rooms for improvement of its positional accuracy. In this paper, the stochastic modeling of the ionospheric delay is applied and its effects are analyzed. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the medium or long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. The ionospheric delay is stochastically modeled by well-known 1st order Gauss-Markov process. And the correlation time and variation of 1st order Gauss-Markov process are calculated. This paper gives analyzed results of developed algorithm compared with commercial software and Bernese.

• 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 the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.689-699
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• 2013

During extreme ionospheric storms, anomalous ionospheric delays and gradients could cause potential integrity threats to users of GNSS (Global Navigation Satellite System) augmentation systems. GNSS augmentation ground facilities must monitor these ionospheric anomalies defined by a threat model and alarm the users of safely-of-life applications within time-to-alerts. Because the ionospheric anomaly threat model is developed using data collected from GNSS reference stations, the use of poor-quality data can degrade the performance of the threat model. As the total number of stations increases, the number of station with poor GNSS data quality also increases. This paper analyzes the quality of data collected from Korean GPS reference stations using comprehensive GNSS data quality check algorithms. The results show that the range of good and poor qualities varies noticeably for each quality parameter. Especially erroneous ionospheric delay and gradients estimates are produced due to poor quality data. The results obtained in this study should be a basis for determining GPS data quality criteria in the development of ionospheric threat models.