scholarly journals Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China

2018 ◽  
Vol 10 (9) ◽  
pp. 1472 ◽  
Author(s):  
Peng Yuan ◽  
Weiping Jiang ◽  
Kaihua Wang ◽  
Nico Sneeuw
Keyword(s):  
Time Series ◽  
Velocity Field ◽  
Colored Noise ◽  
Environmental Loading ◽  
Movement Observation ◽  
Observation Network ◽  
Uncertainty Estimates ◽  
Position Time Series ◽  
Periodic Signals ◽  
Gps Velocity Field

Analysis of Global Positioning System (GPS) position time series and its common mode components (CMC) is very important for the investigation of GPS technique error, the evaluation of environmental loading effects, and the estimation of a realistic and unbiased GPS velocity field for geodynamic applications. In this paper, we homogeneously processed the daily observations of 231 Crustal Movement Observation Network of China (CMONOC) Continuous GPS stations to obtain their position time series. Then, we filtered out the CMC and evaluated its effects on the periodic signals and noise for the CMONOC time series. Results show that, with CMC filtering, peaks in the stacked power spectra can be reduced at draconitic harmonics up to the 14th, supporting the point that the draconitic signal is spatially correlated. With the colored noise suppressed by CMC filtering, the velocity uncertainty estimates for both of the two subnetworks, CMONOC-I (≈16.5 years) and CMONOC-II (≈4.6 years), are reduced significantly. However, the CMONOC-II stations obtain greater reduction ratios in velocity uncertainty estimates with average values of 33%, 38%, and 54% for the north, east, and up components. These results indicate that CMC filtering can suppress the colored noise amplitudes and improve the precision of velocity estimates. Therefore, a unified, realistic, and three-dimensional CMONOC GPS velocity field estimated with the consideration of colored noise is given. Furthermore, contributions of environmental loading to the vertical CMC are also investigated and discussed. We find that the vertical CMC are reduced at 224 of the 231 CMONOC stations and 170 of them are with a root mean square (RMS) reduction ratio of CMC larger than 10%, confirming that environmental loading is one of the sources of CMC for the CMONOC height time series.

Spatiotemporal noise in GPS position time-series from Crustal Movement Observation Network of China

2018 ◽  
Vol 216 (3) ◽  
pp. 1560-1577 ◽  
Author(s):  
Wei Wang ◽  
Xuejun Qiao ◽  
Dijin Wang ◽  
Zhengsong Chen ◽  
Pengfei Yu ◽  
...  
Keyword(s):  
Time Series ◽  
Crustal Movement ◽  
Movement Observation ◽  
Observation Network ◽  
Position Time Series ◽  
Spatiotemporal Noise

scholarly journals Positioning Performance of BDS Observation of the Crustal Movement Observation Network of China and Its Potential Application on Crustal Deformation

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3353 ◽  
Author(s):  
Xiaoning Su ◽  
Guojie Meng ◽  
Haili Sun ◽  
Weiwei Wu
Keyword(s):  
Time Series ◽  
Crustal Deformation ◽  
Potential Application ◽  
Flicker Noise ◽  
Crustal Movement ◽  
Movement Observation ◽  
North East ◽  
Noise Characteristics ◽  
Observation Network ◽  
Position Time Series

The Crustal Movement Observation Network of China (CMONOC) has begun receiving BeiDou Navigation Satellite System (BDS) observations since 2015, and accumulated more than 2.5 years of data. BDS observations has been widely applied in many fields, and long-term continuous data provide a new strategy for the study of crustal deformation in China. This paper focuses on the evaluation of BDS positioning performance and its potential application on crustal deformation in CMONOC. According to the comparative analysis on multipath delay (MPD) and signal to noise ratio (SNR) between BDS and GPS data, the data quality of BDS is at the same level with GPS measurements in COMONC. The spatial distribution of BDS positioning accuracy evaluated as the root mean square (RMS) of daily residual position time series on horizontal component is latitude-dependent, declining with the increasing of station latitude, while the vertical one is randomly distributed in China. The mean RMS of BDS position residual time series is 7 mm and 22 mm on horizontal and vertical components, respectively, and annual periodicity in position time series can be identified by BDS data. In view of the accuracy of BDS positioning, there are no systematic differences between GPS and BDS results. Based on time series analysis with data volume being 2.5 years, the noise characteristics of BDS daily position time series is time-correlated and corresponding noise is white plus flicker noise model, and the derived mean RMS of the BDS velocities is 1.2, 1.5, and 4.1 mm/year on north, east, and up components, respectively. The imperfect performance of BDS positioning relative to GPS is likely attributed to the relatively low accuracy of BDS ephemeris, and the sparse amount of MEO satellites distribution in the BDS constellation. It is expectable to study crustal deformation in CMONOC by BDS with the gradual maturity of its constellation and the accumulation of observations.

scholarly journals 3-D GPS velocity field and its implications on the present-day post-orogenic deformation of the Western Alps and Pyrenees

Solid Earth ◽  
2016 ◽  
Vol 7 (5) ◽  
pp. 1349-1363 ◽  
Author(s):  
Hai Ninh Nguyen ◽  
Philippe Vernant ◽  
Stephane Mazzotti ◽  
Giorgi Khazaradze ◽  
Eva Asensio
Keyword(s):  
Time Series ◽  
Velocity Field ◽  
Large Scale ◽  
Processing Parameters ◽  
Western Alps ◽  
Southern France ◽  
Ice Cap ◽  
Uplift Rates ◽  
Horizontal Strain ◽  
Gps Velocity Field

Abstract. We present a new 3-D GPS velocity solution for 182 sites for the region encompassing the Western Alps, Pyrenees, and southern France. The velocity field is based on a Precise Point Positioning (PPP) solution, to which we apply a common-mode filter, defined by the 26 longest time series, in order to correct for network-wide biases (reference frame, unmodeled large-scale processes, etc.). We show that processing parameters, such as troposphere delay modeling, can lead to systematic velocity variations of 0.1–0.5 mm yr−1 affecting both accuracy and precision, especially for short (< 5 years) time series. A velocity convergence analysis shows that minimum time-series lengths of  ∼  3 and  ∼  5.5 years are required to reach a velocity stability of 0.5 mm yr−1 in the horizontal and vertical components, respectively. On average, horizontal residual velocities show a stability of  ∼  0.2 mm yr−1 in the Western Alps, Pyrenees, and southern France. The only significant horizontal strain rate signal is in the western Pyrenees with up to 4  ×  10−9 yr−1 NNE–SSW extension, whereas no significant strain rates are detected in the Western Alps (< 1  ×  10−9 yr−1). In contrast, we identify significant uplift rates up to 2 mm yr−1 in the Western Alps but not in the Pyrenees (0.1 ± 0.2 mm yr−1). A correlation between site elevations and fast uplift rates in the northern part of the Western Alps, in the region of the Würmian ice cap, suggests that part of this uplift is induced by postglacial rebound. The very slow uplift rates in the southern Western Alps and in the Pyrenees could be accounted for by erosion-induced rebound.

scholarly journals Signal Extraction from GNSS Position Time Series Using Weighted Wavelet Analysis

2020 ◽  
Vol 12 (6) ◽  
pp. 992 ◽  
Author(s):  
Kunpu Ji ◽  
Yunzhong Shen ◽  
Fengwei Wang
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Satellite System ◽  
Signal Extraction ◽  
Average Error ◽  
North East ◽  
Observation Network ◽  
Position Time Series ◽  
Global Navigation Satellite ◽  
Gnss Position Time Series

The daily position time series derived by Global Navigation Satellite System (GNSS) contain nonlinear signals which are suitably extracted by using wavelet analysis. Considering formal errors are also provided in daily GNSS solutions, a weighted wavelet analysis is proposed in this contribution where the weight factors are constructed via the formal errors. The proposed approach is applied to process the position time series of 27 permanent stations from the Crustal Movement Observation Network of China (CMONOC), compared to traditional wavelet analysis. The results show that the proposed approach can extract more exact signals than traditional wavelet analysis, with the average error reductions are 13.24%, 13.53% and 9.35% in north, east and up coordinate components, respectively. The results from 500 simulations indicate that the signals extracted by proposed approach are closer to true signals than the traditional wavelet analysis.

Preparatory analysis and development for the ITRF2020

2021 ◽  
Author(s):  
Zuheir Altamimi ◽  
Paul Rebischung ◽  
Laurent Metivier ◽  
Xavier Collilieux ◽  
Kristel Chanard ◽  
...  
Keyword(s):  
Time Series ◽  
Input Data ◽  
Parametric Models ◽  
Laser Ranging ◽  
Early Results ◽  
Analysis Strategies ◽  
Position Time Series ◽  
Periodic Signals ◽  
Deformation Models ◽  
Seismic Deformation

&lt;p&gt;In preparation for ITRF2020, we developed a number of software tools and analysis strategies aiming at improving the quality, consistency and accuracy of the new frame. Our target is to enhance the modelling of the nonlinear station motions, including post-seismic deformation models for stations subject to major earthquakes, and periodic signals embedded in the station position time series. In addition to the classical annual and semi-annual signals, we foresee to simultaneously adjust some satellite draconitic harmonics and evaluate their impact on the estimated frame parameters.&amp;#160; The ITRF2020 is expected to be provided in the form of an augmented reference frame so that in addition to station positions and velocities, parametric models for both PSD and periodic signals (expressed in the CM frame of satellite laser ranging) will also be delivered to the users. Depending on the availability of the input data of the four techniques at the time of this presentation, we expect to show and discuss some early results and give some indications regarding the specifications of the final ITRF2020 solution.&lt;/p&gt;

Chameleonic noise in GPS position series: what is the true color of the GPS error spectra?

2020 ◽  
Author(s):  
Alvaro Santamaría-Gómez ◽  
Jim Ray
Keyword(s):  
Time Series ◽  
Skin Color ◽  
Colored Noise ◽  
Flicker Noise ◽  
Linear Trend ◽  
Pink Noise ◽  
Noise Levels ◽  
Color Noise ◽  
Position Time Series ◽  
True Color

&lt;p&gt;&lt;em&gt;Chameleonic: readily changing color or other attributes.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Chameleon: a lizard that changes skin color to match what surrounds it so that it cannot be seen.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;The error spectrum of decadal long GPS position time series is typically represented by a combination of flicker (pink) noise at long periods and white noise at short periods. It is known that when fitting a linear trend to the series, part of the flicker noise at the longest observed period will be absorbed by the trend. Here, using real and synthetic GPS position series, we show how the error spectrum is even more altered by the position discontinuities that populate the series. The fitted position offsets at the discontinuity epochs absorb a significant portion of the power spectrum at periods longer than the separation between the discontinuity epochs. The resulting error spectrum is flattened at long periods and this implies that:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;the estimated content of colored noise is biased low and can even apparently change its color towards whiter noise, i.e. the true noise color is not observable due to the discontinuities,&lt;/li&gt; &lt;li&gt;the red (random walk) noise , most probably present in the series in small quantity, becomes undetectable even if long series are used,&lt;/li&gt; &lt;li&gt;the pink (flicker) noise is not the best color noise to represent the error spectrum in long series containing discontinuities,&lt;/li&gt; &lt;li&gt;the colored noise content cannot be compared between series with different sets of discontinuities.&lt;/li&gt; &lt;/ul&gt;&lt;p&gt;These findings need to be considered when comparing the noise levels between series from different solutions, networks or monuments.&amp;#160;In particular, and contrary to a recently published recommendation, station operators should make every effort to avoid adding new discontinuities into their station time series if reliable velocity estimates are expected.&lt;/p&gt;

scholarly journals 3D GPS velocity field and its implications on the present-day postorogenic deformation of the Western Alps and Pyrenees

2016 ◽  
Author(s):  
Hai Ninh Nguyen ◽  
Philippe Vernant ◽  
Stephane Mazzotti ◽  
Giorgi Khazaradze ◽  
Eva Asensio
Keyword(s):  
Time Series ◽  
Velocity Field ◽  
Reference Frame ◽  
Precise Point Positioning ◽  
Environmental Noise ◽  
Western Alps ◽  
Common Mode ◽  
Southern France ◽  
Accuracy And Precision ◽  
Gps Velocity Field

Abstract. We present a new 3D GPS velocity solution for 182 sites for the region encompassing the Western Alps, Pyrenees, and southern France. The velocity field is based on a Precise Point Positioning (PPP) solution, to which we apply a common-mode filter, defined by the 26 longest time series, in order to correct for network-wide biases (reference frame, environmental noise, ...). We show that processing options, such as troposphere delay, can lead to systematic velocity variations of 0.1–0.5 mm yr−1 affecting both accuracy and precision, especially for short (

scholarly journals The interseismic velocity field of the central Apennines from a dense GPS network

2013 ◽  
Vol 55 (5) ◽  
Author(s):  
Alessandro Galvani ◽  
Marco Anzidei ◽  
Roberto Devoti ◽  
Alessandra Esposito ◽  
Grazia Pietrantonio ◽  
...  
Keyword(s):  
Velocity Field ◽  
Geodetic Network ◽  
Central Apennines ◽  
Position Time Series ◽  
Seismogenic Structures ◽  
Adriatic Coast ◽  
Continuous Gps ◽  
Interseismic Velocity ◽  
Strain Rate Field ◽  
Gps Velocity Field

<p>Since 1999, we have repeatedly surveyed the central Apennines through a dense survey-style geodetic network, the Central Apennines Geodetic Network (CAGeoNet). CAGeoNet consists of 123 benchmarks distributed over an area of ca. 180 km × 130 km, from the Tyrrhenian coast to the Adriatic coast, with an average inter-site distance of 3 km to 5 km. The network is positioned across the main seismogenic structures of the region that are capable of generating destructive earthquakes. Here, we show the horizontal GPS velocity field of both CAGeoNet and continuous GPS stations in this region, as estimated from the position–time series in the time span from 1999 to 2007. We analyzed the data using both the Bernese and GAMIT software, rigorously combining the two solutions to obtain a validated result. Then, we analyzed the strain-rate field, which shows a region of extension along the axis of the Apennine chain, with values from 2 × 10<span><sup>–9</sup></span> yr<span><sup>–1</sup></span> to 66·× 10<span><sup>–9</sup></span> yr<span><sup>–1</sup></span>, and a relative minimum of ca. 20 × 10<span><sup>–9</sup></span> yr<span><sup>–1</sup></span> located in the L'Aquila basin area. Our velocity field represents an improved estimation of the ongoing elastic interseismic deformation of the central Apennines, and in particular relating to the area of the L'Aquila earthquake of April 6, 2009.</p>

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