Modeling and simulating of accelerometers and gradiometers concepts
- authored by
- Arthur Reis, Alexey Kupriyanov, Vitali Müller, Jürgen Müller, Manuel Schilling
- Abstract
Geosciences have benefited greatly from the GOCE, GRACE and GRACE-FO missions, especially regarding how the observations of terrestrial mass variations is used to understand and track climate change processes. Furthermore, future gravimetry missions are planned to keep monitoring the static and time variable Earth gravitational field. A limiting factor in gravity field recovery resolution is the sensitivity of the spacecraft's accelerometers, responsible for distinguishing the non-gravitational accelerations from the gravitational signal. Novel accelerometer designs with enhanced sensitivity would therefore be valuable for gravimetry. To facilitate this venture, we built a tool to model and simulate accelerometers and gradiometers. ACME (Accelerometer Modeling Extended) is a MATLAB/Simulink toolbox that numerically simulates parametrically generated accelerometers and gradiometers, including the dynamics of test mass, capacitances and actuation forces from the electrodes, system frequency response and noise budget (with noise sources such as gas thermal, capacitance sensor, contact potential difference, actuation, and so on). It also includes different sensor models, such as capacitive sensing and laser interferometric readout. In order to simulate the in-flight behaviour of the instrument, it can be integrated with an orbital dynamics simulator with high-fidelity gravitational field model (XHPS). The generated amplitude spectral densities and mock data series are passed onto gravity field recovery software to evaluate the possible science return. Additionally, simulating legacy instruments allow us to validate the workflow. We'll present the development progress of the toolbox and some illustrative results of what it can achieve.
- Organisation(s)
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Institute of Geodesy
- External Organisation(s)
-
Max Planck Institute for Gravitational Physics (Albert Einstein Institute)
- Type
- Abstract
- Publication date
- 17.07.2023
- Publication status
- Published
- Sustainable Development Goals
- SDG 13 - Climate Action
- Electronic version(s)
-
https://doi.org/10.57757/IUGG23-0583 (Access:
Closed)
-
Details in the research portal "Research@Leibniz University"