// the find
pms67/Attitude-Estimation
MatLAB and Python implementations for 6-DOF IMU attitude estimation using Kalman Filters, Complementary Filters, etc.
A companion code repo for a blog post on IMU attitude estimation, covering complementary and Kalman filter approaches in both MATLAB and Python. It's a learning resource, not a library — the value is in reading the code alongside the article at philsal.co.uk. Useful for someone working through the math for the first time.
Clean, minimal implementations that map closely to the filter equations — no abstraction layers obscuring what's actually happening. Having both MATLAB and Python lets you cross-check results between environments. The included CSV of real IMU data means you can run it immediately without hardware. Good starting point for understanding gyro drift compensation.
Abandoned since 2018 and it shows — no packaging, no tests, not pip-installable, and the Python files are scripts rather than importable modules. A single CSV dataset limits validation; you can't easily swap in your own sensor data without editing the scripts. The MATLAB code is essentially undocumented and assumes you already know what you're looking at. 'Complimentary' is misspelled as 'complimentary' in the filename, which is a minor but telling sign of the project's polish level.