<p>I'm using GPS units and mobile computers to track individual pedestrians' travels. I'd like to in real time "clean" the incoming GPS signal to improve its accuracy. Also, after the fact, not necessarily in real time, I would like to "lock" individuals' GPS fixes to positions along a road network. Have any techniques, resources, algorithms, or existing software to suggest on either front?</p>

<p>A few things I am already considering in terms of signal cleaning:
- drop fixes for which num. of satellites = 0
- drop fixes for which speed is unnaturally high (say, 600 mph)</p>

<p>And in terms of "locking" to the street network (which I hear is called "map matching"):
- lock to the nearest network edge based on root mean squared error
- when fixes are far away from road network, highlight those points and allow user to use a GUI (OpenLayers in a Web browser, say) to drag, snap, and drop on to the road network</p>

<p>Thanks for your ideas!</p>

I assume you want to "clean" your data to remove erroneous spikes caused by dodgy readings. This is a basic dsp process. There are several approaches you could take to this, it depends how clever you want it to be.
At a basic level yes, you can just look for really large figures, but what is a really large figure? Yeah 600mph is fast, but not if you're in concorde. Whilst you are looking for a value which is "out of the ordinary", you are effectively hard-coding "ordinary". A better approach is to examine past data to determine what "ordinary" is, and then look for deviations. You might want to consider calculating the variance of the data over a small local window and then see if the z-score of your current data is greater than some threshold, and if so, exclude it.