# mherb/kalman

Header-only C++11 Kalman Filtering Library (EKF, UKF) based on Eigen3

Repository: https://github.com/mherb/kalman
Canonical: https://ross.abutalabs.com/products/kalman
Language: C++
License: MIT
License Family: permissive
Last push: 2023-08-24T22:11:18+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": 4030, "days_push": 1105, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1502, forks 415 (observed 2026-08-28T04:04:54.499247+00:00)

## What it is
A header-only C++11 library implementing Kalman filter variants (EKF, SR-EKF, UKF, SR-UKF) built on the Eigen3 linear algebra library. Users define state, control, system, and measurement models as C++ types to perform state estimation.

## Use cases
- estimate robot state from noisy sensor measurements
- implement an extended Kalman filter in C++
- fuse sensor data with an unscented Kalman filter
- add state estimation to an embedded C++ project
- implement square-root Kalman filters for numerical stability
- track object positions with sensor fusion

## When to choose
- you need Kalman filtering in a C++11 or later project
- you want a header-only dependency with no build step
- you need EKF or UKF variants including square-root forms
- you already use Eigen3 for linear algebra

## When to avoid
- you work in Python or another language
- you need particle filters or other Bayesian estimators
- you want a batteries-included robotics framework with sensor drivers
- you need GPU-accelerated filtering for very large state vectors

## Facets
- artifact type: library
- maturity: stable
- function: math, simulation
- domain: robotics, developer-tools
- platform: cpp, cross-platform
- tags: kalman-filter, state-estimation, ekf, ukf, header-only, eigen3, sensor-fusion, algorithms

## Member repositories
- mherb/kalman (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:54.499247+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 2026-08-30T04:32:53.831078+00:00, confidence not recorded.
  - readme: https://github.com/mherb/kalman (fetched 2026-08-28T04:04:54.499247+00:00, sha 10a90b3aca4a)
- Data as of 2026-08-30T08:39:29.467469+00:00.