/ImuFusion

EKF IMU Fusion Algorithms

Primary LanguageMATLAB

ImuFusion

EKF IMU Fusion Algorithms

  1. orien.m uses Kalman filter for fusing the gyroscope's and accelerometer's readings to get the IMU's attitude(quaternion).
  2. zupt.m implenments the so called 'zero-velocity-update' algorithm for pedestrian tracking(gait tracking), it's also a ekf filter.

Usage

Example data already included.
Simply run the orien.m or zupt.m. For zupt, set 'CreateVideo' as true if you'd like to save the results as a video.
Note that the datasets and the code for visualizing the results were from: https://github.com/xioTechnologies/Gait-Tracking-With-x-IMU

References:

[1] S. Madgwick. An efficient orientation filter for inertial and inertial/magnetic sensor arrays.
[2] Fischer C, et. Implementing a Pedestrian Tracker Using inertial Sensors.
[3] Isaac Skog, et. Zero-Velocity Detection — An Algorithm Evaluation.