A MATLAB‑based Kriged Kalman Filter software for interpolating missing data in GNSS coordinate time series

Authors: Liu, Ning; Dai, Wujiao; Santerre, Rock; Kuang, Cuilin
Abstract: GNSS coordinate time series data for permanent reference stations often suffer from random, or even continuous, missing data. Missing data interpolation is necessary due to the fact that some data processing methods require evenly spaced data. Traditional missing data interpolation methods usually use single point time series, without considering spatial correlations between points. We present a MATLAB software for dynamic spatiotemporal interpolation of GNSS missing data based on the Kriged Kalman Filter model. With the graphical user interface, users can load source GNSS data, set parameters, view the interpolated series and save the final results. The SCIGN GPS data indicate that the software is an effective tool for GNSS coordinate time series missing data interpolation.
Document Type: Article de recherche
Issue Date: 9 December 2017
Open Access Date: Restricted access
Document version: VoR
Permalink: http://hdl.handle.net/20.500.11794/16883
This document was published in: GPS Solutions, Vol. 22 (1), 1–8 (2018)
Alternative version: 10.1007/s10291-017-0689-3
Collection:Articles publiés dans des revues avec comité de lecture

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