8,152
edits
Changes
From Fellrnr.com, Running tips
no edit summary
Simply taking a GPS watch on a single run does not provide sufficient data to reasonably evaluate its accuracy. To gather the data for this test I ran the same route repeatedly, recording laps every quarter mile. The course is challenging for GPS, with lots of twists, tree cover, power lines, turn arounds and goes under a bridge. However, I believe that it's reasonably representative of real-world conditions, and probably less challenging than running in the city with skyscrapers.
=Accuracy, Trueness and Precision (plus Repeatability)=
For this evaluation I'll use the ISO 5725 definition of [http://en.wikipedia.org/wiki/Accuracy_and_precision Accuracy as the combination of trueness and precision].
{| class="wikitable"
|- valign="top"
** Note that I'm intentionally using an uncalibrated Footpod (factor = 1.000) to gather data for a comparison of Foodpod and GPS.
* The older Garmin 205 does remarkably well.
=Footpod Accuracy=
The accuracy of a Footpod is far higher than GPS, as well as more consistent and quicker to react to changes in pace. For any given run, the average pace error from the Footpod is only 7 seconds/mile (at a 9:00 min/mile pace) or 5 seconds/Km (at a 5:30 min/Km pace). In practical terms, I've found that I always have to use a Footpod to pace a marathon or for critical speedwork. For details of how the Footpod calibration was done, see [[GPS Testing Methodology]].
|}
=GPS Short and long measurements=
As you can see from the images below, the GPS track tends to take shortcuts around bends, reducing the length of the measured track. This cutting of the corners indicates the devices are doing some post-hoc smoothing to try to overcome the GPS errors. The more smoothing they do, the better the accuracy is likely to be in a straight line and the worse it is around corners or twisty courses. In my discussions with engineers working on GPS systems, this type of smoothing is often performed with a [http://en.wikipedia.org/wiki/Kalman_filter Kalman filter]. (When I tested using software without smoothing I found the measurements were long on my course rather than short, which is almost always the case.)
[[File:GPS Shortcuts.jpg|none|thumb|500px|The GPS tracks in red showing the tendency to cut the corners on the curves.]]
Often GPS measurements of races, especially marathons record a longer distance than the race. This is partly because the USATF technique for measuring the distance takes a path that is no more than 12 inches away from the tangent (corner), and few runners are able to run that close. In a large marathon you can be forced to take a line that is a long way from the tangent. The other factor is that on a straight line, the GPS error tends to give a slightly longer measurement.
|[[File:Fenix2 Getting Lost6.jpg|none|thumb|x400px|This GPS track looks reasonable until marker #54, and then the track gets offset, but strangely it stays offset until the last marker.]]
|}
=GPS Accuracy and Weather=
GPS Accuracy is slightly better with clear skies than with cloud cover. The difference between completely clear and fully overcast is generally less than 0.1% and my testing includes a similar mix of cloud cover for each watch, so I ignore this difference. However, rain can degrade accuracy by 0.3-3.1%, with the better watches being impacted the least. Because it does not rain that frequently where I test, this has created some potential bias in my testing so I now ignore measurements taken during the rain. This has only made a slight difference to the results, but it ensures consistence.
=GPS Accuracy and Seasons=
I run in a wooded area with mostly deciduous trees, so the foliage varies by season. This foliage can have a noticeable impact on GPS accuracy, with better accuracy during the bare winter months than the rest of the year. This difference is mostly 0.1-1.5%, but in some cases can be as large as 2.5%. Because of this, my testing now ignores data from the winter months when the trees are bare. The short winter here in the south of the US means that the impact on the overall results are small, but like the weather impacts noted above, this does ensure greater consistency.
=GPS Accuracy and Pace=
[[File:AccuracyAndPace.jpg|none|thumb|500px| A plot of GPS precision against pace. The red line is the correlation.]]