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Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tightly-coupled GNSS/INS integration has been shown to provide better performance than loosely-coupled approach in GNSS degraded environments. However， it is difficult to achieve reliable ambiguity resolution (AR) when the number of satellites is below four. In this case, ambiguity search in the ambiguity domain is not possible，which means other AR method should be considered. Also, it is likely to wrongly fix the ambiguities，which will lead to biased state estimate or even filter divergence. In this paper，a tightly-coupled RTK/INS algorithm based on centralized Kalman Filter (KF) is implemented， in which ambiguity parameters are augmented into the state vector. Ambiguity-fixed or -float carrier phase observables can be used to update the filter even if the number of satellites is less than four，and this improves the accuracy of the integrated system in complex environments. A field vehicular test was conducted to evaluate the performance of the tightly-coupled algorithm in terms of the position drift error during GNSS signal outages and ambiguity recovery time after outages. Test results indicate that by utilizing tactical-grade inertial measurement units (IMUs)，the horizontal position drift error is about 0.3m during 30-second partial outage and the average time for reliable ambiguity recovery is 1 to 2 seconds when the number of satellites in view is three. Besides, the performance of float solution is only slightly worse than the fixed solution for shout-time (e.g. 60 seconds) partial outages, but both of them are much better than the case of full GNSS outages. [ABSTRACT FROM AUTHOR]

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For real-time regional VTEC(vertical total electron content) modeling over China, ionospheric modeling is realized based on spherical cap harmonic functions, low-degree spherical harmonic functions, polynomial models and Kriging interpolation techniques. This paper focuses on the spatial variability and relevance of VTEC and Kriging interpolation methodology to achieve real-time regional VTEC modeling using China regional GPS data. Results indicate that fitting accuracy in the high latitude areas is better than in lower latitude areas, Kriging interpolation and polynomial modeling show better performance than the spherical cap harmonic function and low-degree spherical harmonic function. But polynomial modeling has a marginal effect as fitting precision decreases rapidly while the distance to the center of the modeling region is increased. The variance of grid VTEC estimated using Kriging algorithm, in contrast conforms closely to the actual situation, with shows higher precision when the number of IPPs increases over the region. [ABSTRACT FROM AUTHOR]