This Module comes with no guarantee, what so ever.

Filter raw data (often from sensors).

What is the Kalman filter?

In statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe.



This implementation is inspired by Lachlan Blackhall's Python implementation: https://github.com/lblackhall/pyconau2016/blob/master/kalman.py

Watch his Pycon Australia talk for a good, easy-to-digets introduction to the Kalman filter:



Version 1.0 is based on (copy/paste) of Cees de Groot implementation. Thanks for the feedback! https://github.com/cdegroot/palapa/tree/master/kalman


The package can be installed by adding kalman to your list of dependencies in mix.exs:

def deps do
    {:kalman, "~> 1.0.0"}