IMU Fusion Performance Clarification requirement

[vamshi]

Hi Team,

We are working on BHI160B and also searching for BHI260AB. We learned that BHI160B has a BSX3 algorithm and BHI260AB has a BSX4 algorithm. However, in what way is the BHI260AB better than BHI160B? Could anyone give detailed info on performance improvement of BHI260AB compared to BHI160B (whether it is to reduce Drift or any other)?

Additionally, If we select BHI260AB IMU can we see less drift than BHI160B?


Thanks,
BVK

[leenjas]

Hi @vamshi 👋,

The BHI260AB with BSX4 offers improved performance over the BHI160B's BSX3, particularly in drift reduction, sensor fusion accuracy, and power efficiency. The BSX4 algorithm enhances stabilization and reliability, resulting in less drift and better overall performance in dynamic environments.

[vamshi]

Hi @leenjas ,

Thank you for your reply,

I understand the above information. But I found that the below information is the same in both BHI160B, and BHI260AB IMUs,

Static Accuracy (YPR) (Deg)	2
Dynamic Accuracy (YPR) (Deg)	7
Calibration Time (Sec)	<1
Orientation Stabilization Time (Sec)	0.2

I did not observed the change in drift reduction, sensor fusion accuracy, better overall performance in dynamic environments, etc., in values as you said. 
Could you please confirm the Static, Dynamic Accuracy of BHI260AB, BHI160B IMU? 

Thanks & Regards,
Vamshi.

[vamshi]

Hi

We worked on BHI160B IMU (converting Quaternions to RPY data). IMU is configured with a Sample rate 100Hz, Dynamic Ranges as default. This test was done while the IMU board was in vibration <3Hz. Test was done for 30min and we finally plotted the Accel x, y, z , Gyro x, y, z, Mag x, y, z values and Roll, Pitch, Yaw values can see in the attached image. Now, we are suspecting that Magnetometer and Gyro values are causing the Drift in Yaw. Could you please provide the solution to avoid Yaw Drift.

Thank & Regards,