zhongpeixiang / kalmanjs

Javascript based Kalman filter for 1D data

KalmanJS

Javascript based Kalman filter for 1D data. Sometimes you need a simple noise filter without any dependencies; for those cases Kalman.js is perfect.

Background

I wrote two blog posts on explaining Kalman filters in general and applying them on noisy data in particular:

• KalmanJS, Lightweight Javascript Library for Noise filtering
• Kalman filters explained: Removing noise from RSSI signals

Installation

The KalmanJS library is a small javascript library and can easily be integrated in to your project manually. Alternatively, the library can be included using npm.

Node (es6)

npm install kalmanjs

import KalmanFilter from 'kalmanjs';

const kf = new KalmanFilter();
kf.filter(2);

Node (es5)

npm install kalmanjs

var KalmanFilter = require('kalmanjs').default;

var kf = new KalmanFilter();
kf.filter(2);

Applying the filter on a dataset

Using the filter is simple. First we create a simple dataset with random noise:

//Generate a simple static dataset
var dataConstant = Array.apply(null, {length: dataSetSize}).map(function() {
  return 4;
});
//Add noise to data
var noisyDataConstant = dataConstant.map(function(v) {
  return v + randn(0, 3);
});

Then we apply the filter iteratively on each data element:

//Apply kalman filter
var kalmanFilter = new KalmanFilter({R: 0.01, Q: 3});

var dataConstantKalman = noisyDataConstant.map(function(v) {
  return kalmanFilter.filter(v);
});

See this blog post for screenshots and more examples.

Copyright

Copyright (C) 2015 Wouter Bulten

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with this program. If not, see http://www.gnu.org/licenses/.