This is a basic kalman filter library for unidimensional models that you can use with a stream of single values like barometric sensors, temperature sensors or even gyroscope and accelerometers.
- Take a look at this youtube video to see the Kalman Filter working on a stream of values!
Special thanks to Professor Michel van Biezen and his amazing work in http://www.ilectureonline.com/
- /examples - Example sketches for the library (.ino). Run these from the Arduino IDE.
- /src - Source files for the library (.cpp, .h).
- keywords.txt - Keywords from this library that will be highlighted in the Arduino IDE.
- library.properties - General library properties for the Arduino package manager.
- e_mea: Measurement Uncertainty - How much do we expect to our measurement vary
- e_est: Estimation Uncertainty - Can be initilized with the same value as e_mea since the kalman filter will adjust its value.
- q: Process Variance - usually a small number between 0.001 and 1 - how fast your measurement moves. Recommended 0.01. Should be tunned to your needs.
SimpleKalmanFilter kf = SimpleKalmanFilter(e_mea, e_est, q);
while (1) {
float x = analogRead(A0);
float estimated_x = kf.updateEstimate(x);
// ...
}
- BasicKalmanFilterExample - A basic example reading a value from a potentiometer in A0 and SimpleKalmanFilter class to generate estimates.
- AltitudeKalmanFilterExample - Uses a BMP180 barometric sensor and the SimpleKalmanFilter class to estimate the correct altitude.
- Installing Additional Arduino Libraries - Basic information on how to install an Arduino library.
- V 0.1.0 -- Initial commit
This is an open source project!
Please review the LICENSE.md file for license information.
If you have any questions or concerns on licensing, please contact [email protected].