Scientific Computation Platform for Geophysical Geodesy

Follow me to model your own geoid quickly using SRBF, then you will be pleasantly surprised!

Issuing time:2024-11-11 18:28Author:Chuanyin ZhangLink:http://www.zcyphygeodesy.com/en/
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From the observed terrestrial, marine and airborne gravity disturbances and GNSS-leveling geoidal heights in orthometric height system (GNSS-leveling height anomalies in normal height system), make the all-element models on gravity field using spherical radial basis functions (SRBFs) in six steps, in which all the terrain effects are not processed, to quickly master the essentials in observation analysis, computation quality control and all-element modelling on regional gravity field.

For the orthometric height system or normal height system,   there is only a slight difference in the processing of the observed GNSS-levelling data, and the other modelling processes are the same.

After the terrain effect processing omitted, SRBF approach process of gravity field is very simple because there is no need for additional continuation reduction, gridding and GNSS leveling fusion process.

PAGravf4.5 recommends a universal multi-source heterogeneous observation deep fusion method by the normalization of the normal equations, which can effectively control the deep fusion of different types of observations using covariance structure to approach gravity field from heterogeneous observation field elements. This method completely separates the contribution of the observation system model (covariance structure) and influences of observation quality (errors or gross errors), so that the fusions are away from the observation errors (gross error), observation types and spatial distribution differences of measurement points. Which is conducive to the fusion of multiple types of observation field elements with extreme differences in spatial distribution (such as very few astronomical vertical deflection or GNSS levelling data included), and is conducive to the exact detection of observation gross errors.

In this case, the normal equation does not also need to be iteratively calculated, which conducive to improve the analytical nature of the SRBF approach algorithm.

The typical technical features of SRBF approach program in PAGrav4.5.

① The analytical function relationships between gravity field elements are strict, and the SRBF approach performance has nothing to do with the observation errors. ② Various heterogeneous observations in the different altitudes, cross-distribution, and land-sea coexisting cases can be directly employed to model the all-element gravity field models on or outisde the geoid without reduction, continuation and griding. ③ Can integrate very few astronomical vertical deflection or GNSS-levelling data, and effectively absorb the edge effect. ④ Has the strong capacity in the detection of observation gross errors, measurement of external accuracy indexes and control of computational performance.



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