Regularizes a trajectory onto a uniform time grid, linearly interpolating
missing observations (with added noise matched to the observed
increment scale) and replacing implausible jumps.
Usage
fill_missing_data(t, x, y, track_id)
Arguments
- t, x, y
observed times and coordinates (may have gaps/dropped frames).
- track_id
an identifier carried through to the output.
Value
a list with the regularized `t`, `x`, `y`, indices that were
`filled` vs. `replaced` for each coordinate, and `track_id`.