I'm trying to create a classifier to distinguish different boats by their trajectories. I have training data of the longitude and latitude of a boat and time in seconds.
Vessels like a ferry will have a straight predictable trajectory between two points, whereas fishing vessels can have zig-zag like trajectories for example.
My initial approach is to create features for example the mean speed, standard deviation of the speed, standard deviation on the course, such that each trajectory table is distilled into 1 row of features. Then I can train something like a random forest classifier on these rows.
Is this a good approach, any other suggestions that could account for the characteristic trajectory shapes.