Kalman.js - Kalman Filter in JavaScript

Usage

The constructor takes the initial state x and the initial covariance P. For each update cycle you have to provide all necessary vectors and matrices:

let filter = new Kalman(x0, P0)

// loop
filter.update({
  A, // State design matrix
  B, // Input design matrix
  u, // Linear input variable 
  H, // Observation matrix
  R, // Sensor Noise Coviarance
  Q, // Process Noise Covariance (Optional)
  w, // System noise (Optional)
  C, // Measurement design matrix
  y, // new measurement vector
});

Note: Kalman.js is designed to work with the Sylvester Matrix library, but only uses it implicitly. You can use another library as long as it matches the method names of Sylvester.

Installation

Installing Kalman.js is as easy as cloning this repo or use one of the following commands:

bower install kalman

or

npm install kalman

Using Kalman.js with the browser

<script src="kalman.js"></script>
<script>
    var kf = new Kalman.KF;
    ...
</script>

Using Kalman.js with require.js

<script src="require.js"></script>
<script>
requirejs(['kalman.js'],
function(Kalman) {
    var kf = new Kalman.KF;
    ...
});
</script>

Coding Style

As every library I publish, Kalman.js is also built to be as small as possible after compressing it with Google Closure Compiler in advanced mode. Thus the coding style orientates a little on maxing-out the compression rate. Please make sure you keep this style if you plan to extend the library.

Testing

If you plan to enhance the library, make sure you add test cases and all the previous tests are passing. You can test the library with

npm test

Copyright and licensing

Copyright (c) 2016, Robert Eisele Dual licensed under the MIT or GPL Version 2 licenses.