Weirdly enough, my robot platform which has an official ROS package supported by a manufacturer doesn't provide any covariance matrices of its sensors. So, I'm basically trying to estimate these values for odometery and IMU using collected raw sensor readings to use the Kalman filter. For odometer, I feel like putting the robot into a static position (i.e., initial position) and collecting sensor readings will be enough to estimate its covariance.
What I'm a bit confused about is the way to calculate the covariance for IMU. So far, sensor readings collected in a static position show some random oscillation only in angular velocity and linear acceleration. Orientation never shows any noise in this situation. Would it be enough to follow the exactly same way I did for the odometer or should I do something else?