Smoothing Sensor Data with a Low-Pass Filter
After some searching, I came to the Wikipedia entry for Low Pass Filter. There's a pseudocode algorithm that I adapted for Java which works splendidly. Not only that, but it's extremely simple. The algorithm essentially requires tracking only two numbers - the prior number and the new number. There's a constant, alpha, which affects the 'weight' or 'momentum' -- basically how drastically does the new value affect the current smoothed value. Here's the full implementation:
/*
* time smoothing constant for low-pass filter
* 0 ≤ alpha ≤ 1 ; a smaller value basically means more smoothing
* See: http://en.wikipedia.org/wiki/Low-pass_filter#Discrete-time_realization
*/
static final float ALPHA = 0.15f;
/**
* @see http://en.wikipedia.org/wiki/Low-pass_filter#Algorithmic_implementation
* @see http://developer.android.com/reference/android/hardware/SensorEvent.html#values
*/
protected float[] lowPass( float[] input, float[] output ) {
if ( output == null ) return input;
for ( int i=0; i<input.length; i++ ) {
output[i] = output[i] + ALPHA * (input[i] - output[i]);
}
return output;
}In my particular case, I used this to normalize raw accelerometer and magetometer sensor readings before calculating a compass bearing. Note that the input and output array elements are not sequential values, but completely separate dimensions (x,y,z) so e.g. each new x value is normalized against the smoothed x value, the new y with the smoothed y, etc.
This smoothing also has the curious effect of actually accelerating and decelerating the resulting visualization, e.g. the compass needle appears to have inertia and momentum if you quickly rotate the device. Just like a physical compass needle would. Neat!
Update: I've posted a follow-up, which explains how to take the low-pass output and get a compass rotation.
10 Comments
Reply
Reply
This works very well, thanks! I'm implementing my own compass using the accelerometer and mag sensors. However, all examples I've found are incomplete in some way. Would you post your sensor handling code? It would be appreciated.
Reply
Dave - finally got around to posting an example which should clarify how the lowPass function is used. See my follow-up post.
Reply
Re: Smoothing Sensor Data with a Low-Pass Filter March 20, 2012 Paweł
Reply
output[i] = output[i-1] + ALPHA * (input[i] - output[i]);
?
Reply
Andrew - So the short answer is, no. See my follow-up post, which should clarify how the function is used.
Reply
Reply
You mean you're getting small numbers from the output of SensorManager.getRotationMatrix(), I presume? I don't remember but I think that value might be in radians.
Reply
Reply