Abstract
SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed
and accuracy in mind and offers the following capabilities:
- A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc.
- Customizable force propagation models, including a variety of Earth gravity models, lunar gravity,
radiation pressure, etc.
- Multiple-hypothesis tracking (MHT) UCT linker
- Vectorized computations
- Short arc probabilistic orbit determination
- Conjunction probability estimation
- Uncertainty quantification
- Monte Carlo data fusion
- Support for multiple coordinate frames (with coordinate frame conversions)
- Developers:
-
Schlafly, Edward [1] ; Yeager, Travis [1] ; Pruett, Kerianne [1] ; Schneider, Michael [1] ; Ebert, Julia [1] ; Merl, Daniel [1] ; Lifset, Noah [1] ; Armstrong, Robert [1] ; Dawson, William [1] ; Meyers, Joshua [1] ; Perloff, Alexx [1] ; Golovich, Nathan
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Release Date:
- 2023-11-08
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Version:
- 1.0
- Licenses:
-
MIT License
- Sponsoring Org.:
-
USDOE National Nuclear Security Administration (NNSA)Primary Award/Contract Number:AC52-07NA27344
- Code ID:
- 126106
- Site Accession Number:
- LLNL-CODE-862420
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Country of Origin:
- United States
Citation Formats
Schlafly, Edward, Yeager, Travis, Pruett, Kerianne, Schneider, Michael, Ebert, Julia, Merl, Daniel, Lifset, Noah, Armstrong, Robert, Dawson, William, Meyers, Joshua, Perloff, Alexx, and Golovich, Nathan.
Space Situational Awareness for Python.
Computer Software.
https://github.com/LLNL/SSAPy.
USDOE National Nuclear Security Administration (NNSA).
08 Nov. 2023.
Web.
doi:10.11578/dc.20240417.1.
Schlafly, Edward, Yeager, Travis, Pruett, Kerianne, Schneider, Michael, Ebert, Julia, Merl, Daniel, Lifset, Noah, Armstrong, Robert, Dawson, William, Meyers, Joshua, Perloff, Alexx, & Golovich, Nathan.
(2023, November 08).
Space Situational Awareness for Python.
[Computer software].
https://github.com/LLNL/SSAPy.
https://doi.org/10.11578/dc.20240417.1.
Schlafly, Edward, Yeager, Travis, Pruett, Kerianne, Schneider, Michael, Ebert, Julia, Merl, Daniel, Lifset, Noah, Armstrong, Robert, Dawson, William, Meyers, Joshua, Perloff, Alexx, and Golovich, Nathan.
"Space Situational Awareness for Python." Computer software.
November 08, 2023.
https://github.com/LLNL/SSAPy.
https://doi.org/10.11578/dc.20240417.1.
@misc{
doecode_126106,
title = {Space Situational Awareness for Python},
author = {Schlafly, Edward and Yeager, Travis and Pruett, Kerianne and Schneider, Michael and Ebert, Julia and Merl, Daniel and Lifset, Noah and Armstrong, Robert and Dawson, William and Meyers, Joshua and Perloff, Alexx and Golovich, Nathan},
abstractNote = {SSAPy is a python package allowing for fast and precise orbital modeling. SSAPy is designed with speed
and accuracy in mind and offers the following capabilities:
- A variety of integrators, including Runge-Kutta, SciPy, SGP4, etc.
- Customizable force propagation models, including a variety of Earth gravity models, lunar gravity,
radiation pressure, etc.
- Multiple-hypothesis tracking (MHT) UCT linker
- Vectorized computations
- Short arc probabilistic orbit determination
- Conjunction probability estimation
- Uncertainty quantification
- Monte Carlo data fusion
- Support for multiple coordinate frames (with coordinate frame conversions)},
doi = {10.11578/dc.20240417.1},
url = {https://doi.org/10.11578/dc.20240417.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240417.1}},
year = {2023},
month = {nov}
}