tim.coddington

07-27-2012, 01:23 AM

Hi,

I want to estimate the bias of the x, y, and z acceleration data from my IMU. I would appreciate help guiding me toward this goal. I'd like to take this one step at a time since the process is more involved that one would have thought.

First, here are steps I've take so far in my test software:

1) I read the IMU accel data and attitude (pitch, yaw, and roll) at approx 10hz.

If I don't watch the waveforms using a graphing tool I developed using Qt

open source library then I can sample as high as 500hz.

2) I convert from gravities to m/s^2

3) After transforming accel vector in sensor frame to local tangent plane navitgation frame, I add gravity vector (0,0,9.81m/s^s) to cancel out gravity.

As seen from the attached screen shot, I'm left with accel in navigation frame and each component has a bias.

Red, Green, Blue lines correspond with x, y, and z. Dashed lines correspond to resultant accel and solid lines correspond to accel after using a low pass butterworth 2 pole filter.

IMU is sitting stationary on a level counter. Yaw some heading but pitch and roll are <1deg.

Ultimately, I'd like some guidance on best way to estimate and remove the bias, but at this point it makes sense to get some feedback. I would appreciate your constructive comments.

Thanks

4078

I want to estimate the bias of the x, y, and z acceleration data from my IMU. I would appreciate help guiding me toward this goal. I'd like to take this one step at a time since the process is more involved that one would have thought.

First, here are steps I've take so far in my test software:

1) I read the IMU accel data and attitude (pitch, yaw, and roll) at approx 10hz.

If I don't watch the waveforms using a graphing tool I developed using Qt

open source library then I can sample as high as 500hz.

2) I convert from gravities to m/s^2

3) After transforming accel vector in sensor frame to local tangent plane navitgation frame, I add gravity vector (0,0,9.81m/s^s) to cancel out gravity.

As seen from the attached screen shot, I'm left with accel in navigation frame and each component has a bias.

Red, Green, Blue lines correspond with x, y, and z. Dashed lines correspond to resultant accel and solid lines correspond to accel after using a low pass butterworth 2 pole filter.

IMU is sitting stationary on a level counter. Yaw some heading but pitch and roll are <1deg.

Ultimately, I'd like some guidance on best way to estimate and remove the bias, but at this point it makes sense to get some feedback. I would appreciate your constructive comments.

Thanks

4078