Hi all,
I am implementing the numerical propagation following this official tutorial:
examples/Example_numerical_prop.ipynb · master · Orekit Labs / Orekit Python Wrapper · GitLab
Having the matrix process noise Q , I would like to know if in Orekit is possible to implement directly the predicted covariance propagation.
I mean a sort of prediction step of the kalman filter, or simular.
Many thanks for your time and help
Best Regards
MaximeJ
November 8, 2023, 12:51pm
2
Hi @AlessandroV ,
There is a CovariancePropagation tutorial. It uses the StateCovarianceMatrixProvider
to perform a linear propagation of the covariance.
With two limitations with respect to what is available in the Kalman filters:
Only the orbital covariance is propagated (i.e. the propagation and measurements parameters aren’t propagated)
You will have to add the process noise matrix Q by yourself after propagation
Maxime