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doi:10.1111/gji.2005.163.issue-1

Cited by 8 publications

(2 citation statements)

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“…In order to investigate the effect of the second-order ionospheric term on GPS positioning in Antarctica, the positioning error should correlate with the ranging error. In addition to simulation, Geiger's (1988) error estimation method proposes analytical or semianalytical solutions in many cases for estimating different disturbances in GPS measurements, and the method has been adopted in some research involving the second-order ionospheric term (Munekane 2005;Liu et al 2010). Let us consider the coordinate system whose axes point toward the east, north, and vertical directions, respectively.…”

Section: Estimation Strategymentioning

confidence: 99%

The effect of the second-order ionospheric term on GPS positioning in Antarctica

Wang

Cui

et al. 2020

Arctic, Antarctic, and Alpine Research

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Global Positioning System (GPS) signals are delayed when passing through the ionosphere due to an ionospheric refraction effect. The ionospheric-free linear combination of GPS signals can eliminate most of the error caused by the first-order ionospheric term. However, the influence of higher-order ionospheric terms remains, and it should be accounted for when conducting highprecision geodetic applications. In this study, we use data from twenty-one GPS continuous operating stations from different observing networks distributed in Antarctica and analyze the effect of the second-order ionospheric term on GPS positioning during the whole year for 2012. Results show that the effect on these stations is at the level of submillimeters to millimeters, and the effect in summer is several times higher than it is in winter. In addition, this effect is found to be positively correlated to the change of the total electron content over the Antarctic continent. On the other hand, all of the stations show the southward and upward movements derived from the effect. The common and seasonal displacement trends displayed in the Antarctic region should not be ignored in future high-precision research or applications but should be brought to attention, especially when total electron content in the ionosphere is high.

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Section: Estimation Strategymentioning

confidence: 99%

The effect of the second-order ionospheric term on GPS positioning in Antarctica

Wang

Cui

et al. 2020

Arctic, Antarctic, and Alpine Research

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“…These electrodes and cables are commonly buried in 20-50-cm depth trenches to secure the acquisition. This procedure is very practical and allows minimization of electrode positioning errors and improves the reliability with which the electrical resistivity distribution can be reconstructed (Zhou and Dahlin, 2003;Oldenborger et al, 2005;Wilkinson et al, 2008). Recently, the British Geological Survey (BGS) has developed a fast geoelectrical imaging system known as automated time-lapse electrical resistivity tomography (ALERT).…”

Section: Introductionmentioning

confidence: 99%

Automated identification of changes in electrode contact properties for long-term permanent ERT monitoring experiments

2013

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Electrical resistivity tomography (ERT) monitoring experiments are being conducted more often to image spatiotemporal changes in soil properties. When conducting long-term ERT monitoring, the identification of suspicious electrodes in a permanent spread is of major importance because changes in electrode contact properties of a single electrode may affect the quality of many measurements on each time-slice. An automated methodology was developed to detect these temporal changes in electrode contact properties, based on a Bayesian approach called "weights of evidence." Contrasts ðC W Þ and studentized contrasts ðC S Þ are estimators of the influence of each electrode in the global data quality. A consolidated studentized contrast ðCC S Þ is introduced to consider the proportion of rejected quadripoles which contain a single electrode. These estimators are computed for each time-slice using Q-factor (coefficient of variation of repeated measurements) threshold values, from 0 to 10%, to discriminate between selected and rejected quadripoles. An automated detection strategy is proposed to identify suspicious electrodes by comparing the CC S to the MEC S (maximum expected C S values when every electrode is good for the given data set). These MEC S are computed using Monte-Carlo simulations of a hundred random draws where the distribution of Q-factor values follows a Weibull cumulative distribution, with k ¼ 0.421 and λ ¼ 1.303, fitted on a background data set filtered using a 5% threshold on absolute reciprocal errors. The efficiency of the methodology and its sensitivity to the selected reciprocal error threshold are assessed on synthetic and field data. Our approach is suitable to detect suspicious electrodes and slowly changing conditions affecting the galvanic contact resistances where classical approaches are shown to be inadequate except when the faulty electrode is disconnected. A data-weighting method is finally proposed to ensure that only good data will be used in the inversion of ERT monitoring data sets.

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