3D position tracking based on data from 9 degree of freedom IMU (Accelerometer, Gyroscope and Magnetometer). This can track orientation pretty accurately and position but with significant accumulated errors from double integration of acceleration.
main.py: where the main Extended Kalman Filter(EKF) and other algorithms sit.butter.py: a digital realtime butterworth filter implementation from this repo with minor fixes. But I don't use realtime filtering now.mathlib: contains matrix definitions for the EKF and a filter helper function.plotlib.py: some wrappers for visualization used in prototyping.main.ipynb: almost the same asmain.py, just used for prototyping./Ref: Some paper found on the internet that is helpful./Doc: an Algorithm description (you can view it in html as github doesn't support markdown latex extension) and an API documentation in Chinese.
I use an APP called HyperIMU to pull (uncalibrated) data from my phone. Data is sent through TCP and received using data_receiver.py.