Skip to content

Latest commit

 

History

History
29 lines (26 loc) · 1.3 KB

README.md

File metadata and controls

29 lines (26 loc) · 1.3 KB
Raw

kalman

Implementation of the Kalman Filter Algorithm in Julia.

If you only want the implementation, it is the KalmanFilter.jl. Otherwise still feel free to experiment with the data.

  • 00.stochasticMass shows how the filter puts the pdf Function to the ground thruth.
  • 01.sealevel shows the filter in work, applied to the global mean sea level dataset.
  • 02.sinus applies the filter to a non linear system.
  • 03.carposition shows the usage of the filter in motion filtering. First through a simulation ist data created and the filter is applied to smooth the data if only the accelerometer or the GPS is known. After that, there is a data fusion performed with both of these values and the data is applied to real motion data.

To run the examples julia is needed.

$ git clone https://github.com/hydroid7/kalman
$ cd kalman
$ julia
               _
   _       _ _(_)_     |  Documentation: https://docs.julialang.org
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.0.3 (2018-12-18)
 _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
|__/                   |
julia> using IJulia
juila> notebook(dir = pwd())

You will find folders with number prefix. Open them and run the exercises.