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I'm looking for an algorithm, that can process an amount of (GPS-) positions and determine, if the actual position gets closer to a way point. What is the "best" way to filter variability in the positions? So far, I've implemented a moving average over the last positions and compare that to the new one.

Does it make sense to use a low-pass filter? Any other ideas?

Thanks.

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Because this is a statistical question (not really a math one) and an adequate answer is going to require some clarification and additional information from you, consider migrating it to the statistics forum at stats.stackexchange.com . –  whuber Oct 9 '10 at 0:52
    
Certainly low pass filters are good at eliminating random noise. –  Ross Millikan Oct 9 '10 at 2:42

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