Attitude Heading Reference System using Kalman Filter

In this project, I have developed an AHRS with Linear Kalman Filter. A clear documentation on how I built it is given as a blog.
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Updated 14 Aug 2022

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This project will help you understand on how to intuitively develop a sensor fusion algorithm using linear kalman filter that estimates Roll, Pitch and Yaw of the vehicle with accelerometer, gyroscope and magnetometer as sensor inputs. The sensor data is used from a smartphone using MATLAB Support Package for Android Sensors. Realtime sensor fusion is also possible using this algorithm.
Check out the complete documentation:

Cite As

Farhan Ahamed (2024). Attitude Heading Reference System using Kalman Filter (https://www.mathworks.com/matlabcentral/fileexchange/116295-attitude-heading-reference-system-using-kalman-filter), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2021b
Compatible with R2017b and later releases
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Smart Phone AHRS

Inspired: TRACKING A TARGET TRAJECTORY USING KALMAN FILTER

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Version Published Release Notes
1.0.1

Updated documentation

1.0.0