Take the 2-minute tour ×
Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It's 100% free, no registration required.

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?


share|improve this question
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

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.