orbdetpy 2.0.4

Orbit determination routines for Python

orbdetpy is a Python library for orbit determination. It is a thin Python wrapper for our Java estimation tools and Orekit http://www.orekit.org/.

Features

Dynamics in orbdetpy can be configured with:

1. EGM96 gravity field up to degree and order 360.
2. Earth solid tides due to the influence of the Sun and Moon.
3. FES 2004 ocean tide model up to degree and order 100.
4. NRL MSISE-00 and exponential atmospheric drag models.
5. Solar radiation pressure.
6. Third body perturbations from the Sun and Moon.
7. Satellite box-wing models and maneuvers.

Range, range-rate, angles, and inertial state measurements are supported. Filtering can be done with our Unscented Kalman Filter or Orekit's Extended Kalman Filter. Dynamic Model Compensation (DMC) can be used with either filter to estimate unmodeled accelerations.

Installation

1. Install the Java Development Kit 8 (1.8) from http://openjdk.java.net/install/index.html. Set the JAVA_HOME environment variable to the JDK installation folder. The java executable must be added to the system path.

2. Install Python 3.7.0 or higher and run pip install orbdetpy to install orbdetpy and other package dependencies.

3. Update the astrodynamics data under orbdetpy/orekit-data periodically by running the following. You will need root privileges on some systems.

   python -c "from orbdetpy.astro_data import update_data; update_data();"

Development

1. Download and extract https://github.com/ut-astria/orbdetpy/releases/download/2.0.4/orekit-data.tar.gz under the orbdetpy/ sub-folder.

2. Developers will need Apache Maven 3+ to build the Java library. Build using the following from the orbdetpy/ sub-folder, where os_cpu_type is linux-x86_64, linux-x86_32, windows-x86_64, windows-x86_32, osx-x86_64, or osx-x86_32 depending on your CPU and OS:

   mvn -e -Dos.detected.classifier=os_cpu_type package

   The command-line is simpler on Intel/AMD 64-bit Linux:

   mvn -e package

Examples

1. fit_radec.py : Run OD with real angles measurements. Also demonstrates the Laplace IOD method for estimating an initial state vector.

2. interpolate_oem.py : Command-line tool for interpolating state vectors from CCSDS OEM ephemeris files. OEM files are available for download at http://astria.tacc.utexas.edu/AstriaGraph.

3. predict_passes.py : Predict satellite passes for ground stations or geographic regions using TLEs. Current elements may be obtained from sites such as http://www.celestrak.com.

4. propagate_tle.py : Propagate TLEs given by command-line arguments.

5. test_conversion.py : Test reference frame and other conversion functions.

6. test_estimation.py : Demonstrates measurement simulation and orbit determination functions.

7. test_interpolation.py : Interpolate state vectors.

Known Issues

1. You might receive warnings from the Windows Defender Firewall on Microsoft Windows. Grant orbdetpy network access permissions.

2. If you use the multiprocessing Python package, imports and calls into orbdetpy must not span multiprocessing function calls. That is, orbdetpy can be used in the parent process or the spawned child processes, but not both. A workaround is to run the orbdetpy RPC server using orbdetpy/start_server.sh in a separate terminal window before running your Python code.