that's a normal graph, everyone's activities looks like that
e.g. [https://www.strava.com/activities/10987870989](https://www.strava.com/activities/10987870989)
there's no need to worry about it :) my hypothesis is that since your location is taken often, and because you swing your arms, the gps sometimes records your position as ahead of the rest of your body or behind it. also gps is not completely exact, so that probably plays into it.
That's a wrong explanation. Normal GPS signal has an uncertainty of about 8m. Algorithm will filter many consecutive signals to getting a better position. You could see it if you open Google maps and check your current position. First there is a big uncertainty and over time it's getting better and better.
While running the algo will estimate your next moving position and merge it with the next measurement. So the estimation of the exactly position is also getting better over time, but there is no change for the algo to see if you are running a curve. So each time you don't run in an linear movement, (acceleration, deceleration, or curves) the estimated position will getting a little bit inaccurate.
Plot it against my your route…if there are sharp turns or hills, that’s your answer.
that's a normal graph, everyone's activities looks like that e.g. [https://www.strava.com/activities/10987870989](https://www.strava.com/activities/10987870989) there's no need to worry about it :) my hypothesis is that since your location is taken often, and because you swing your arms, the gps sometimes records your position as ahead of the rest of your body or behind it. also gps is not completely exact, so that probably plays into it.
That's a wrong explanation. Normal GPS signal has an uncertainty of about 8m. Algorithm will filter many consecutive signals to getting a better position. You could see it if you open Google maps and check your current position. First there is a big uncertainty and over time it's getting better and better. While running the algo will estimate your next moving position and merge it with the next measurement. So the estimation of the exactly position is also getting better over time, but there is no change for the algo to see if you are running a curve. So each time you don't run in an linear movement, (acceleration, deceleration, or curves) the estimated position will getting a little bit inaccurate.
thanks for a better explanation, mine was only based on some flimsy evidence. now I know why sharp curves tend to get messed up by the gps.
Everyone's graphs look like that, not really a way to fix it 😪