Estimation#

Estimation using simulated observations#

In the following examples, observations are simulated and then used as input for a covariance analysis and/or estimation.

Covariance Analysis with DELFI-C3
Covariance Propagation Using Starlink-32101
Parameter Estimation with DELFI-C3
Simulation and Estimation Using Different Dynamical Models

Functionality to support estimation#

In the following examples, functionality is showcased that can be used to support (pre- and/or post-processing of observations) estimation

Generating Visibility Plots with Tudat

Estimation using pseudo-observations data#

In the following examples, Cartesian positions of bodies are taken from an external source and used as observations to which a Tudat dynamical model is fit.

Initial State Estimation Using NOE-5 Ephemeris

Estimation using real observations#

In the following examples, real observations are used to fit compute residuals and/or compute dynamics of spacecraft and/or natural bodies.

Retrieving Observations From the Minor Planet Centre
Initial state estimation From Real MPC Observations
Improved state estimation with MPC
Loading and Using Tracking Observations

Estimation using real observations - Python only#

We also have the following examples that showcase the reading of, and estimation from radio tracking data from DSN/ESTRACK. Using these examples requires tudatpy to have been compiled by high-precision time representation (which is not currently available through these conda packages) The examples provide instructions on how to compile your own tudatpy kernel with the required settings.