Filtering accelerometer data noise

Question

Hi

How do I filter noise of the accelerometer data in Android? I would like to create a high-pass filter for my sample data so that I could eliminate low frequency components and focus on the high frequency components. I have read that Kalman filter might be the best candidate for this, but how do I integrate or use this method in my application which will mostly written in Android Java? or can it be done in the first place? or through Android NDK? Is there by any chance that this can be done in real-time?

Any idea will be much appreciated. Thank you!

Answer 1

I seem to remember this being done in Apple's sample code for the iPhone. Let's see...

Look for AccelerometerFilter.h / .m on Google (or grab Apple's AccelerometerGraph sample) and this link: http://en.wikipedia.org/wiki/High-pass%5Ffilter (that's what Apple's code is based on).

There is some pseudo-code in the Wiki, too. But the math is fairly simple to translate to code.

Answer 2

IMO, designing a Kalman filter as your first attempt is over-complicating what's probably a fairly simple problem. I'd start with a simple FIR filter, and only try something more complex when/if you've tested that and found with reasonable certainty that it can't provide what you want. My guess, however, is that it will be able to do everything you need, and do it much more easily and efficiently.

Answer 3

The samples from Apple's SDK actually implement the filtering in an even simpler way which is by using ramping:

//ramp-speed - play with this value until satisfied
const float kFilteringFactor = 0.1f;

//last result storage - keep definition outside of this function, eg. in wrapping object
float accel[3]; 

//acceleration.x,.y,.z is the input from the sensor

//result.x,.y,.z is the filtered result

//high-pass filter to eleminate gravity
accel[0] = acceleration.x * kFilteringFactor + accel[0] * (1.0f - kFilteringFactor);
accel[1] = acceleration.y * kFilteringFactor + accel[1] * (1.0f - kFilteringFactor);
accel[2] = acceleration.z * kFilteringFactor + accel[2] * (1.0f - kFilteringFactor);
result.x = acceleration.x - accel[0];
result.y = acceleration.y - accel[1];
result.z = acceleration.z - accel[2];

Answer 4

Here is how I've done it in my case http://levonp.blogspot.com/2010/10/how-to-filter-accelerometer-data-from.html