# balzer82/Kalman

Some Python Implementations of the Kalman Filter

Repository: https://github.com/balzer82/Kalman
Canonical: https://ross.abutalabs.com/products/balzer82-kalman
Language: Jupyter Notebook
License Family: other
Topics: kalman-filter, python, kalman
Last push: 2024-04-01T18:18:34+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4587, "days_push": 884, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1142, forks 371 (observed 2026-08-28T04:03:44.704214+00:00)

## What it is
A collection of Jupyter Notebook implementations of Kalman Filters (constant velocity, constant acceleration, 2D/3D, adaptive, extended) in Python, with explanatory blog posts and videos. It serves as an educational resource for learning state estimation and sensor fusion rather than a production library.

## Use cases
- learn how a kalman filter works with python examples
- sensor fusion of gps and accelerometer data
- track a ball in 3d space with a kalman filter
- implement an extended kalman filter tutorial
- estimate position when gps signal is lost in a tunnel
- adaptive measurement covariance kalman filter example

## When to choose
- you want to learn or teach Kalman filtering with runnable notebooks
- you need reference implementations to adapt for sensor fusion prototypes

## When to avoid
- you need a production-grade, maintained filtering library with an API
- you need a package with a license for commercial redistribution

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: simulation, data-science, math
- domain: tutorials, data-science
- platform: python, cross-platform
- tags: kalman-filter, jupyter-notebooks, sensor-fusion, state-estimation, educational, algorithms

## Member repositories
- balzer82/Kalman (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:44.704214+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:35:04.546237+00:00, confidence not recorded.
  - readme: https://github.com/balzer82/Kalman (fetched 2026-08-28T04:03:44.704214+00:00, sha f4149f8b6cb3)
- Data as of 2026-08-30T08:39:29.467469+00:00.