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minidemoKalmanFilter - Minimal Demo. of Kalman Filters (Linear/Extended/Unscented)

Project description

  1. Minimal Kalman Filter classes (Linear, Extended and Unscented).
  2. Interactive demonstration and it’s snapshot.
This package is very simple, and may suitable for educational use.
About 100 executable lines for LKF/EKF/UKF totally.
Demo program will show you the essence (assumption and limitation)
of Kalman Filter.

An implementation of minimal Kalman Filter (LKF/EKF/UKF included).


Interactive demo

Interactive style demo requires numpy and matplotlib. Touch sliders to change the parameter of the filter, and you will find the estimated results updated on your screen. Some snapshots are included in the package directory (snapshot_*.png).


Batch demo

Batch style demo (console version) requires numpy. This demo estimates the position and velocity of 2-dimensinal linear uniform motion, and output results to the console. You can choose the filter class (LKF,EKF,UKF) by comman line.

LKF, EFK and UKF gives almost same reseults for such a linear problem here. Please extend significiant of output to confirm the differences.

python > out_ukf.txt


Uses NumPy and Matplotlib(for interactive demo).


Copyright (c) 2018 Kenich SHIRAKAWA

This is licensed under MIT license. See Licence.txt for more information.


The basic design of unscented transformation class is based on the Sam Burden’s work (see

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