Smoothing and interpolating noisy gps data with smoothing splines

被引：0
|
作者：
Early, Jeffrey J. [1 ]
Sykulski, Adam M. [2 ]
机构：
[1] NorthWest Research Associates, Redmond,WA, United States
[2] Data Science Institute, and Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom
来源：
Journal of Atmospheric and Oceanic Technology | 2020年 / 37卷 / 03期
关键词：
A comprehensive method 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 that are typical in global positioning system (GPS) signals. We demonstrate the effectiveness of our methods on GPS trajectory data obtained from oceanographic floating instruments known as drifters. © 2020 American Meteorological Society;
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页码：449 / 465
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