Tutorials
The goal of this library is to easily interact with standard GNSS datasets and file types and run baseline algorithms on measurements in these datasets/data types.
The gnss_lib_py library is divided into submodles, as
described here and the tutorials are similarly
organized.
These tutorials are in interactive Jupyter notebooks and have been rendered as part of the documentation. You can run the code yourself by running the notebooks in the ‘tutorials’ directory here. The notebooks can also be run in Google Colab without downloading the repository by selecting the ‘Open in Colab’ option at the top of each notebook.
The tutorials below show you how to load datasets, interact with our
standard NavData class, run baseline algorithms, generate metrics
for the resultant estimates, and visualize results and data.
All of this can be accomplished with a few lines of code and modularly.
Parser Tutorials
These tutorials explain existing parsers and how to create a new
parser that inherits from NavData to handle new measurement types
and/or files.
Algorithm Tutorials
These tutorials demonstrate existing algorithms for state estimation and fault detection and estimation.
Utility Tutorials
These tutorials illustrate some of the utility functions available in
the utils directory.
- GNSS Constants
- Coordinate Conversions
- DOP
- Ephemeris Downloader
- File Operations
- Filters
- GNSS Models
- SV (Space Vehicle) Models
- Adding SV States with Precise Ephemerides (SP3 & CLK)
- Adding SV states to
NavDatawith received measurements using broadcast ephemeris - Add SV states for visible satellites given a series of times and positions
- Finding PRNs and states for visible SVs for a given position and time
- Finding SV states at given time and for specific PRNs
- Simulating SV positions given elevation and azimuth
- Time Conversions
Visualization Tutorials
These tutorials illustrate most commonly used plotting functions
available in the visualizations directory.