**Built-in bias means your walk tracker over-estimates distances**
People writing GPS software need to re-think their approach to measuring distance, because the system has a built-in bias to over-estimate how far you've moved.

That's the conclusion of a group led by geo-boffin Peter Ranacher of the University of Salzburg, in a paper

published in the

*International Journal of Geographical Information Science*.

If errors were merely random, you'd expect under- and over-estimating measurements to be equally distributed, but that's not what happens according to Ranacher's group. Instead, if geographic points (latitude and longitude) are used to calculate distance, it always results in an over-estimate.*

The too-long-didn't-read version is in the abstract, where they write: “GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points”.

After an awful lot of mathematics that explains the statistical reasons for the over-estimation, the researchers tested the idea by staking out a 10 metre square and undertaking the joyous task of walking around it 25 times, recording their position when passing reference markers every meter.

In a second, less-tedious experiment, the boffins measured the movements of a car with a GPS logger for six days, ending up with around 195 km of the car's trajectories to work on.

For applications where accurate distance measurements are required, the researchers suggest, GPS software should use speed information instead of trying to measure the distance between points: “point speed measurements are calculated from the instantaneous derivative of the GPS signal using the Doppler effect”, they point out, and are therefore highly accurate.

Point speed estimates at high sampling rates would, they write, provide a self-correction mechanism that would correct errors in GPS position estimates, without having to test individual systems to get “ground truth” data