Abstract
The GRACE team at TU Graz strives to provide high quality gravity field models at high spatial and temporal resolutions. The current release in this series of global gravity field models is ITSG-Grace2014.
One of the team's main efforts is stringent modelling of noise sources and influences. To this end, we analyse the spatial and spectral behaviour of instrument noise and scrutinize the residuals of our estimations. This allows us to identify limiting factors in the overall process, and to develop strategies to minimize their impact. A prominent example is our pioneering use of fused sensor data: We improve the attitude information provided through the star camera by combining it with angular accelerations from accelerometer measurements. The resulting product shows marked improvements in noise behaviour, and leads to improvements in our solutions.
Our investigations go beyond satellite-bound error sources. Inaccuracies in background models contribute a significant amount of noise towards the overall error budget. We mitigate this effect by co-estimating high-frequency temporal variations in the background models through constrained daily gravity field solutions.
In our processing chain, we employ sophisticated noise modelling to estimate covariance functions for our observables, which are used throughout the final adjustment process. To make this knowledge available to other researchers, we publish our gravity field solutions together with complete variance-covariance information.
Noise is not the only focus of our research. We further investigate numerical effects and their impact on the solutions, for example in the integration of the equation of motion.
This contribution will highlight and present some of the points discussed above.
One of the team's main efforts is stringent modelling of noise sources and influences. To this end, we analyse the spatial and spectral behaviour of instrument noise and scrutinize the residuals of our estimations. This allows us to identify limiting factors in the overall process, and to develop strategies to minimize their impact. A prominent example is our pioneering use of fused sensor data: We improve the attitude information provided through the star camera by combining it with angular accelerations from accelerometer measurements. The resulting product shows marked improvements in noise behaviour, and leads to improvements in our solutions.
Our investigations go beyond satellite-bound error sources. Inaccuracies in background models contribute a significant amount of noise towards the overall error budget. We mitigate this effect by co-estimating high-frequency temporal variations in the background models through constrained daily gravity field solutions.
In our processing chain, we employ sophisticated noise modelling to estimate covariance functions for our observables, which are used throughout the final adjustment process. To make this knowledge available to other researchers, we publish our gravity field solutions together with complete variance-covariance information.
Noise is not the only focus of our research. We further investigate numerical effects and their impact on the solutions, for example in the integration of the equation of motion.
This contribution will highlight and present some of the points discussed above.
| Original language | English |
|---|---|
| Publication status | Published - 3 Aug 2016 |
| Event | Asia Oceania Geosciences Society 13th Annual Meeting - Beijing, China Duration: 31 Jul 2016 → 5 Aug 2016 |
Conference
| Conference | Asia Oceania Geosciences Society 13th Annual Meeting |
|---|---|
| Abbreviated title | AOGS |
| Country/Territory | China |
| City | Beijing |
| Period | 31/07/16 → 5/08/16 |
Keywords
- grace
- gravity
- time variable gravity field
- temporal gravity field
Fields of Expertise
- Sustainable Systems