Starman is a library which implements algorithms of use when trying to track the true state of one or more systems over time in the presence of noisy observations.
Full documentation is available on readthedocs.
Currently starman supports the following algorithms:
- Kalman filtering for state estimation.
- Rauch-Tung-Striebel smoothing for the Kalman filter.
- Scott and Longuet-Higgins feature association for matching measurments to tracked states.
See the LICENCE.txt file in the repository root for details. tl;dr: MIT-style.
Starman implements the Kalman filter. The Kalman filter was used for trajectory estimation in the Apollo spaceflight programme. Starman is thus a blend of "star", signifying space, and "Kalman". That and "kalman" was already taken as a package name on the PyPI.