Print Email Facebook Twitter Assessment of noise in GPS coordinate time series: Methodology and results Title Assessment of noise in GPS coordinate time series: Methodology and results Author Amiri-Simkooei, A.R. Tiberius, C.C.J.M. Teunissen, P.J.G. Faculty Aerospace Engineering Department Remote Sensing Date 2007-07-31 Abstract We propose a methodology to assess the noise characteristics in time series of position estimates for permanent Global Positioning System (GPS) stations. Least squares variance component estimation (LS?VCE) is adopted to cope with any type of noise in the data. LS?VCE inherently provides the precision of (co)variance estimators. One can also apply statistical hypothesis testing in conjunction with LS?VCE. Using the w?test statistic, a combination of white noise and flicker noise turns out in general to best characterize the noise in all three position components. An interpretation for the colored noise of the series is given. Unmodelled periodic effects in the data will be captured by a set of harmonic functions for which we rely on the least squares harmonic estimation (LS?HE) method and parameter significance testing developed in the same framework as LS?VCE. Having included harmonic functions into the model, practically only white noise can be shown to remain in the data. Remaining time correlation, present only at very high frequencies (spanning a few days only), is expressed as a first?order autoregressive noise process. It can be caused by common and well?known sources of errors like atmospheric effects as well as satellite orbit errors. The autoregressive noise should be included in the stochastic model to avoid the overestimation (upward bias) of power law noise. The results confirm the presence of annual and semiannual signals in the series. We observed also significant periodic patterns with periods of 350 days and its fractions 350/n, n = 2, , 8 that resemble the repeat time of the GPS constellation. Neglecting these harmonic signals in the functional model can seriously overestimate the rate uncertainty. Subject least squares variance component estimationleast squares harmonic estimationGPS position time series To reference this document use: http://resolver.tudelft.nl/uuid:a3051525-2f00-4e74-a708-4f0aeaa8c99f DOI https://doi.org/10.1029/2006JB004913 Publisher American Geophysical Union ISSN 0148-0227 Source http://europa.agu.org/?view=article&uri=/journals/jb/jb0707/2006JB004913/2006JB004913.xml Source Journal of Geophysical Research, 112, 2007 Part of collection Institutional Repository Document type journal article Rights (c) 2007 The Author(s); American Geophysical Union Files PDF Tiberius_2007.pdf 3.63 MB Close viewer /islandora/object/uuid:a3051525-2f00-4e74-a708-4f0aeaa8c99f/datastream/OBJ/view