I have a similar problem with a GPS where the CPU sometimes takes too long to get out of idle / sleep mode when the data is arriving.
So I implemented an algorithm that looks for the largest subset of points that does not contain any jumps or faults. So for example if samples 2, 7, 8 and 9 are timestamped 1970-01-01 while the remaining 5 samples are timestamped correctly, the algorithm will be smart enough to drop all 4 incorrect samples, even though sample 8 matches up with its neighbours. The algorithm is based on the shortest path algorithm. Instructions for filtering NMEA through it is here : http://wiki.openstreetmap.org/wiki/Converting_NMEA_to_GPX#Gosmore_NMEA_to_GPX_conversion Regards, Nic On Wed, Mar 11, 2009 at 6:16 AM, Simon Wood <[email protected]> wrote: > Hi all, > I was wondering how to filter out 'obviously wrong' points from a GPX track > log, which was recorded in heavy tree coverage. The track log was mostly > good, but had a few outlying (individual) points, which would have been hard > to find by hand given 1s data for 1 1/2 hours. > > As it took me a while to work out I thought I would document it here, as it > might be of use to someone else. I did this by using GPSBabel to compute the > speed for each point and then used awk to filter out (drop) points which > exceeded a threshold. > > $ gpsbabel -t -i gpx -f track.gpx -x track,speed -o unicsv -F temp.unicsv > $ head -n 1 temp.unicsv > new.unicsv > $ head -n -1 temp.unicsv | awk -F ',' '{if ($5<20) print $0;}' >> > new.unicsv > $ gpsbabel -t -i unicsv -f new.unicsv -x transform,trk=wpt -o gpx -F > new.gpx > > The awk script could be made more complicated (ie. calculate acceleration > over several samples) to give an even better result. > > The difference is clear: > $ ./wherewasi.py track.gpx --summary > > > WhereWasI Output > ================= > > Filename=track.gpx > Number of Track Segments = 1 > --------------------------------------------- > Start Segment / Point = 0/0 > End Segment / Point = 0/5365 > Start Time = 07/03/2009 17:35:20 > End Time = 07/03/2009 19:04:51 > Number of Track Points = 5366 > --------------------------------------------- > Total Time = 01:29 > Total Distance = 12.03 km > Total Climb = 4761 m > --------------------------------------------- > Average Speed = 8.06 km/hr > Maximum Speed = 1239.35 km/hr > --------------------------------------------- > > > $ ./wherewasi.py new.gpx --summary > > > WhereWasI Output > ================= > > Filename=new.gpx > Number of Track Segments = 1 > --------------------------------------------- > Start Segment / Point = 0/0 > End Segment / Point = 0/5316 > Start Time = 07/03/2009 17:35:20 > End Time = 07/03/2009 19:04:50 > Number of Track Points = 5317 > --------------------------------------------- > Total Time = 01:29 > Total Distance = 9.86 km > Total Climb = 3469 m > --------------------------------------------- > Average Speed = 6.61 km/hr > Maximum Speed = 66.82 km/hr > --------------------------------------------- > > Cheers, > Mungewell. > > PS. Wherewasi can be found here: > http://code.google.com/p/wherewasi/ > > _______________________________________________ > talk mailing list > [email protected] > http://lists.openstreetmap.org/listinfo/talk >
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