In this section you find MATLAB functions and documentation related to the challenges.
We provide some MATLAB m-files which may be helpful to get started with the challenges.
- readACC.m - Reads GRACE like Accelerometer data (asc format)
- readGNV.m - Reads GRACE like GNV data (asc format)
- readKBR.m - Reads GRACE like KBR data (asc format)
- readLRI.m - Reads LRI data (asc format)
- readSCA.m - Reads GRACE like star camera data (asc format)
- Ri2e.m - Returns the rotations matrix from a (pseudo) inertial frame to an Earth-fixed Earth-centred coordinate system.
- Ri2srf.m - Computes the rotation matrix from inertial frame to satellite reference frame (SRF) based on given quaternions (Q)
If you would like to contribute or want to share your m-files, just let us know by sending an email to axel.schnitgeraei.mpg.de.
Don't hesitate to contact us, if you find errors or other ways to improve something.
There are several different techniques that have been used to recover gravity field from SST data.
There is a comprehensive mathematical review of these methods by Keller (2014). Some of these techniques are:
- The acceleration approach: The main observable is the range acceleration. This approach has been implemented by Liu (2008) and Sharifi (2005).
- The energy balance approach: The main observable is the range rate. The theory has been developed by Jekeli (1999) and has been used by Han et al. (2006) for GRACE data.
- The integral equation approach: This approach has been implemented by Mayer-Gürr et al. (2005)
- The variational (classical) approach: Standard method that CSR, GFZ and JPL use to estimate GRACE level 2 data.
Also have a look at:
- Naeimi, M. and Flury, J. (Editors) (2017): Global Gravity Field Modeling from Satellite-to-Satellite Tracking Data, Lecture Notes in Earth System Sciences, Springer, DOI: 10.1007/978-3-319-49941-3, ISBN: 978-3-319-49941-3