  A comprehensive methodology is provided for smoothing noisy, irregularly
sampled data with non-Gaussian noise using smoothing splines. We demonstrate
how the spline order and tension parameter can be chosen a priori from physical
reasoning. We also show how to allow for non-Gaussian noise and outliers which
are typical in GPS signals. We demonstrate the effectiveness of our methods on
GPS trajectory data obtained from oceanographic floating instruments known as
drifters.
