- Imufilter: https://in.mathworks.com/help/fusion/ref/imufilter-system-object.html
- complementaryFilter: https://in.mathworks.com/help/fusion/ref/complementaryfilter-system-object.html
Sensor Fusion using Madgwick/Mahony/kalman filters the MATLAB coding
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Revanth Kumar Adireddy
on 27 Oct 2022
Answered: Amey Waghmare
on 22 Nov 2022
Hi all,
I have 6-DOF raw imu sensor data(only accelerometer and gyroscope). Now , wanted to fuse this data inorder to calculate 'Quaternions' and know the orientation. I am stuck at this point how to build a working algorithm in MATLAB of any of the above mentioned filters.
Any leads,references and already existing matlab scripts?? will be grateful.
Looking Forward.
Thanks.
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Amey Waghmare
on 22 Nov 2022
Hi,
As per my understanding, you have raw accelerometer and gyroscope data and want to obtain the Quaternion orientation estimates using a Sensor Fusion algorithm.
The Sensor Fusion and Tracking Toolbox contains ‘imufilter’ and ‘complementaryFilter’ objects to fuse accelerometer and magnetometer data. The ‘imufilter’ uses an internal error-state Kalman filter and the ‘complementaryFilter’ uses a complementary filter.
More details about the sensor fusion objects are available at the documentation;
You can also refer to the following documentation to align and preprocess the raw sensor data: https://in.mathworks.com/help/fusion/ug/logged-sensor-data-alignment-for-orientation-estimation.html
Hope this resolves the issue.
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