Gyro Sensor drift and Correct angle Estimation

Question

I am using LG Optimus 2x smartphone(Gyroscope and Accelerometer sensor) for positioning.

I want to get correct rotation angles from gyroscope that can be used late

Answer 1

I am the author of a compass application that integrates data from magnetic and gyroscope sensors (steady compass). I have tested this application mostly on a LG Optimus black (the device that you can see on the video) running Android 2.2, so I am going to share my experiences:

• Gyroscope readings are very accurate. This sensor is just the opposite to accelerometer and magnetic sensors which give readings with a lot of jitter.
• The readings from the gyroscope (i.e. the angular speed) does not drift at all. You will have a drift in the estimation of the orientation if you just integrate gyroscope readings. Since you are integrating samples in different times, you will obtain just an approach that will degrade after every integration step.
• In order to avoid such a drift in the orientation estimation, you must consider other input sources to correct the results coming from gyroscope data integration. The solution is the integration of data coming from the orientation sensor (magnetic + acceleration) and data coming from the gyroscope.

Be careful with LG phones: According to the Android API, gyroscope will return data in rad/s. The LG Optimus Black with Froyo gives readings in degrees/s. The update to Android 2.3 has just been released for such phone. I have to test whether the new version behaves according to the specifications.

What Android version does your phone have? Have you tested any application using gyroscope? Did you get the expected results?

Answer 2

As far as I know, either the Kalman filter or something similar is implemented in the SensorManager. Check out Sensor Fusion on Android Devices: A Revolution in Motion Processing.

You are trying to solve a problem that is already solved.

Answer 3

Basically gyros drift over long time periods. Whereas accelerometers have no drift but tend to be unstable. By combining information from both sensors using a Kalman filter you can obtain a accurate attitude. For some this less complex you could also use a Complementary Filter.

See this post for more info: Combine Gyroscope and Accelerometer Data