Acceleration plus change in Direction

AI Thread Summary
The discussion focuses on the challenges of accurately calculating acceleration for vessels using GPS data, particularly when the vessel changes direction. The user notes that existing calculations assume straight-line movement, which can lead to inaccuracies with unreliable data. A specific example illustrates how a vessel's speed and direction changes can misrepresent acceleration if not properly accounted for. A suggestion is provided to break down velocity into Cartesian coordinates to calculate average acceleration more accurately. The user plans to implement this advice to improve their calculations.
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I've been working on a hobby site for some time that analyses GPS data, and calculates top speeds etc for sailors.

GPS data is a bit unreliable, so there is necessarily some filtering that occurs, and one filter is on acceleration.

It is unusual for a vessel to accelerate at more than 3m/s^2, for instance.

Recently I've realized that I'm basing all acceleration calculations assuming the vessel is traveling in a straight line. With bad data, this is not necessarily the case. I could have a data point that shows a vessel traveling at 16m/s at 270 degree, then 14m/s at 100 degrees a second later. At the moment, I would be calculating a slight deceleration from this, but in fact this is an invalid point.

I can't seem to find any straightforward reference to how to determine acceleration around a corner. Can someone please point me to a place where I can find this information?

Here's a real example:
data is duration (s), speed (m/s), direction (degrees)
2, 28.9, 155
2, 14.7, 310
2, 18.0, 354
2, 1.02, 270

At the moment, my software doesn't think that the acceleration between points 2 and 3 is unusual, but because of the almost 45 degree turn involved, it should be noticing a big difference.

Dylan.
 
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You have velocity data and an interval of 2 seconds.

You could always componentize the velocity in Cartesian coords then divide by two to get the average acceleration .

for i<max.points;i++
{

velx(i) = speed(i)*cos(direction(i))
vely(i) = speed(i)*sin(direction(i))

accx(i) = (velx(i)-velx(i-1))/data duration
accy(i) = (vely(i)-vely(i-1))/data duration

accmagnitude = sqrt(accx^2+accy^2)
accdirection = arctan(accy/accx)

}
 
Last edited:
Feldoh,

Thanks for that. I will try out this suggestion tonight and see how it goes.
 
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