CODEWITHSUNDEEP
gpscomputational-geometrysmoothing
Dan
Dan

Reputation: 1227

Smoothing aircraft GPS data with realistic turns

I have historical aircraft trajectory data with points varying from 1 second - 1 minute separation. Often these points present sharp turns. I'm looking for suggestions of best methods of resampling the data to generate smooth paths (e.g. point every n seconds) that more realistically represent the path followed. It would be useful to be able to parameterize the function with certain performance characteristics (e.g. rate of change of direction).

I'm aware of algorithms like the Kalman filter, Bezier curve fitting, splines etc. for data smoothing. But what algorithms would you suggest exploring as a starting point for generating smooth turns?

Upvotes: 1

Views: 1040

Answers (1)

nicholaswmin
nicholaswmin

Reputation: 22949

Schneider's Algorithm is an algorithm that approximately fits curves through a series of points.

The resulting curves have a drastically reduced point-count and it's error-tolerance is configurable, so you can adjust it as much as you need to.

In general:

  • Lower error-tolerance: More points, more accurate, less execution
  • Higher error-tolerance: Less points, less accurate, faster execution

Some useful links:

If the resulting curve must pass exactly through your points, you need an interpolation algorithm instead of an approximation algorithm, but keep in mind that those do not reduce point-count.

A really good type of interpolating spline is the Centripetal Catmull-Rom Spline.

Upvotes: 3

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