How to implement a LowPass Filter?

I'm doing some math on both gyroscope and accelerometer data combined and I'd li开发者_如何转开发ke to low pass filter the resulting data. So could someone post some generic code for a Low Pass filter?

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A 1st order IIR low-pass filter can be of the form:

output_value = rate * input_value + (1.0 - rate) * previous_output_value;

which is pretty much what's inside Apple's AccelerometerGraph example. You select the rate parameter depending on what frequency (very very roughly shakes per second) you want to roll-off or start to attenuate to get a smoother resulting output, and the sample rate of the input data.

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A low pass filter is simply smoothing of the results to remove the high frequencies. The simplest low pass filter is a box filter which is done by averaging n samples together.

For averaging 2 samples together this is as simple as doing:

sample[n] (sample[n] + sample[n + 1]) / 2;

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If Apple's AccelerometerGraph example is too complex for you to understand, I created a simpler accelerometer example for my class which you can download here. This implements a simple low-pass and high-pass filter for raw accelerometer values, then logs the results to the screen.

As hotpaw2 and Goz describe, this uses a very simple weighted rolling average for the filter calculation:

UIAccelerationValue lowPassFilteredXAcceleration = (currentXAcceleration * kLowPassFilteringFactor) + (previousLowPassFilteredXAcceleration * (1.0 - kLowPassFilteringFactor));