Skip to main content

Modular Python tool for parsing, analyzing, and visualizing Global Navigation Satellite Systems (GNSS) data and state estimates

Project description

build codecov Documentation Status

gnss_lib_py

gnss_lib_py is a modular Python tool for parsing, analyzing, and visualizing Global Navigation Satellite Systems (GNSS) data and state estimates. It also provides an intuitive and modular framework allowing users to quickly prototype, implement, and visualize GNSS algorithms. gnss_lib_py is modular in the sense that multiple types of algorithms can be easily exchanged for each other and extendable in facilitating user-specific extensions of existing implementations.

satellite skyplot

gnss_lib_py contains parsers for common file types used for storing GNSS measurements, benchmark algorithms for processing measurements into state estimates and visualization tools for measurements and state estimates. The modularity of gnss_lib_py is made possibly by the unifying NavData class, which contains methods to add, remove and modify numeric and string data consistently. We provide standard row names for NavData elements on the reference page. These names ensure cross compatibility between different datasets and algorithms.

Documentation

Full documentation is available on our readthedocs website.

Code Organization

gnss_lib_py is organized as:

   ├── data/                          # Location for data files
      └── unit_test/                  # Data files for unit testing
   ├── dev/                           # Code users do not wish to commit
   ├── docs/                          # Documentation files
   ├── gnss_lib_py/                   # gnss_lib_py source files
        ├── algorithms/               # Navigation algorithms
        ├── parsers/                  # Data parsers
        ├── utils/                    # GNSS and common utilities
        └── __init__.py
   ├── notebooks/                     # Interactive Jupyter notebooks
        ├── tutorials/                # Notebooks with tutorial code
   ├── results/                       # Location for result images/files
   ├── tests/                         # Tests for source files
      ├── algorithms/                 # Tests for files in algorithms
      ├── parsers/                    # Tests for files in parsers
      ├── utils/                      # Tests for files in utils
      └── test_gnss_lib_py.py         # High level checks for repository
   ├── CONTRIBUTORS.md                # List of contributors
   ├── build_docs.sh                  # Bash script to build docs
   ├── poetry.lock                    # Poetry specific Lock file
   ├── pyproject.toml                 # List of package dependencies
   └── requirements.txt               # List of packages for pip install

In the directory organization above:

  • The algorithms directory contains localization algorithms that work by passing in a NavData class. Currently, the following algorithms are implemented in the algorithms:

    • Weighted Least Squares
    • Extended Kalman Filter
    • Calculating pseudorange residuals
    • Calculating multi-GNSS satellite PVT information
  • The data parsers in the parsers directory allow for either loading GNSS data into gnss_lib_py's unifying NavData class or parsing precise ephemerides data. Currently, the following datasets and types are supported:

  • The utils directory contains utilities used to handle GNSS measurements, time conversions, visualizations, satellite simulation, file operations, etc.

Installation

gnss_lib_py is available through pip installation with:

pip install gnss-lib-py

For directions on how to install an editable or developer installation of gnss_lib_py on Linux, MacOS, and Windows, please see the install instructions.

Tutorials

We have a range of tutorials on how to easily use this project. They can all be found in the tutorials section.

Reference

References on the package contents, explanation of the benefits of our custom NavData class, and function-level documentation can all be found in the reference section.

Contributing

If you have a bug report or would like to contribute to our repository, please follow the guide on the contributing page.

Troubleshooting

Answers to common questions can be found in the troubleshooting section.

Attribution

This project is a product of the Stanford NAV Lab and currently maintained by Ashwin Kanhere and Derek Knowles. If using this project in your own work please cite the following:


   @inproceedings{knowlesmodular2022,
      title = {A Modular and Extendable GNSS Python Library},
      author={Knowles, Derek and Kanhere, Ashwin V and Bhamidipati, Sriramya and Gao, Grace},
      booktitle={Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022)},
      institution = {Stanford University},
      year = {2022 [Online]},
      url = {https://github.com/Stanford-NavLab/gnss_lib_py},
   }

Additionally, we would like to thank all contributors to this project.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gnss_lib_py-0.2.0.tar.gz (84.5 kB view details)

Uploaded Source

Built Distribution

gnss_lib_py-0.2.0-py3-none-any.whl (94.6 kB view details)

Uploaded Python 3

File details

Details for the file gnss_lib_py-0.2.0.tar.gz.

File metadata

  • Download URL: gnss_lib_py-0.2.0.tar.gz
  • Upload date:
  • Size: 84.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for gnss_lib_py-0.2.0.tar.gz
Algorithm Hash digest
SHA256 2de2b1037c929602c9a248cc7db1c9077deaaf8f4940b5ad5c4fe7fdb4f694f5
MD5 24f4c5536d14b0498034f249a4d18f46
BLAKE2b-256 c09dfab8f32c6c3ceca3c6b6349cb6b8ba7602f542f1dd991802426872745611

See more details on using hashes here.

File details

Details for the file gnss_lib_py-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: gnss_lib_py-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 94.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for gnss_lib_py-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8e8d38612d0250b1c746c1947aafee4b4b5853b21a46b6831f3068994159f5aa
MD5 f27bfa0ea6e7048c132ca595c55c076b
BLAKE2b-256 d515f0d612e96803218734bb89f3f94cb585cfc6d456b7c66ae3292feb13d00f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page