A Multiple Algorithm Approach to the Analysis of GNSS Coordinate Time Series for Detecting Geohazards and Anomalies

Habboub, Mohammed; Psimoulis, Panos; Bingley, R. M.; Rothacher, M.

doi:10.1029/2019jb018104

Cited by 7 publications

(7 citation statements)

References 83 publications

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“…The precision enhancement is significant especially when Galileo is added in GPS-only solution. Also, the precision is the highest in E component due to the geometric restriction of the DD solution since the baseline direction is constrained to EW orientation (Habboub et al 2020). Finally, the U component has the lower precision (i.e.…”

Section: Resultsmentioning

confidence: 99%

Assessment of the accuracy of low-cost multi-GNSS receivers in monitoring dynamic response of structures

et al. 2022

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The monitoring of bridges is a crucial operation for their structural health examination and maintenance. GNSS technology is one of the methods which are applied with the main advantage that the direct measurement of the bridge displacement is conducted in an independent global coordinate system. However, the high cost of the GNSS stations, which are consisted of dual-frequency receivers and geodetic GNSS antennas, is the main reason of the limited application of GNSS for bridge monitoring. In this study, we assessed the performance of low-cost multi-GNSS receivers in monitoring dynamic motion, similar to that of bridge response. The performance of the low-cost GNSS receivers was assessed based on controlled experiments of horizontal and vertical motion. For the horizontal motion, controlled experiments of circular motion of various predefined radius between 5 and 50 cm were executed where the low-cost GNSS receivers were assessed against dual-frequency geodetic receivers. For the vertical motion, manually controlled experiments of vertical oscillations of amplitude 8 and 15 mm were executed where the low-cost GNSS receivers were assessed against the Robotic Total Station (RTS). Finally, a low-cost monitoring system formed by two closely spaced low-cost GNSS receivers was applied in dynamic displacement monitoring of the Wilford Suspension Bridge. The analysis of the low-cost GNSS data revealed the beneficial contribution of (i) the multi-constellation on the accuracy and precision of the GNSS solution and (ii) the combination of closely spaced low-cost GNSS receivers, to limit potential cycle slips and the low-cost GNSS noise level and reach accuracy and precision similar to that of geodetic-grade GNSS receivers. This was confirmed in the bridge monitoring application, where the main modal frequency and the response amplitude of the bridge were identified successfully by the low-cost GNSS receivers’ data analysis.

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Section: Resultsmentioning

confidence: 99%

Assessment of the accuracy of low-cost multi-GNSS receivers in monitoring dynamic response of structures

et al. 2022

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“…may enhance even further the precision by using multi-GNSS solution and not only GPS-only solution (Msaewe et al 2017). Finally, a more advanced modified version of CME, potential application of spatial analysis techniques (Habboub et al 2020), and the geometric constrain of the short-baseline between the two closely spaced low-cost receivers may lead to more efficient modelling of the common mode error (Zhang et al 2019).…”

Section: Discussionmentioning

confidence: 99%

“…However, the main advantage of CME against the SDF is that, it does not require multiple days of recording to apply the CME method and it is applied on coordinates time-series, making it applicable for multi-GNSS data. The CME method has been applied successfully for geodetic grade receivers in GNSS networks (Habboub et al 2020), as it is unlikely to have closely spaced (in m-range) geodetic-grade receivers due to their high cost. Hence, the application of CME in closely spaced GNSS receivers, as examined in this study, is practically feasible only for lowcost GNSS receivers.…”

Section: Gnss Data Processing and Methodology Of Time-series Analysismentioning

confidence: 99%

Analysis of the performance of closely spaced low-cost multi-GNSS receivers

et al. 2021

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The recent advances of low-cost GNSS receivers have broadened their application field not only in positioning and navigation, but also in deformation monitoring of civil engineering structures and geohazards. Even though some consumer-grade low-cost GNSS receivers can achieve cm-level accuracy, their lower performance compared to the dual-frequency high-end GNSS receivers restricts its systematic application of GNSS technology in monitoring projects. In this study, the noise level and performance of the low-cost GNSS receivers are assessed against geodetic receivers in terms of precision and availability when subjected to different measurements conditions, such as antenna grade, satellite constellation, and base station (antenna-receiver), based on zero- and short-baseline measurements. Furthermore, a new method is developed where a dual low-cost GNSS rover-system is formed by deploying two closely spaced low-cost GNSS receivers (30 cm apart), aiming to model their common error (multipath, satellite constellation, etc.) and reduce their noise level. The analysis of the zero- and short-baseline measurements reveals the potential improvement of the precision of the low-cost receiver by using multi-GNSS measurements and the importance of using a GNSS base station with geodetic antenna. However, development of a methodology which is based on adopting the sidereal filtering and the common mode error technique for the two closely spaced low-cost GNSS receivers may lead to precision of mm-level. The proposed methodology may broaden the application of low-cost GNSS receivers in monitoring networks and mainly for slowly developed deformations.

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“…Habboub et al. (2020) applied a neural network to coordinate time series anomaly detection applicable to specific regional datasets well above the noise floor. Dybing et al.…”

Section: Methodsmentioning

confidence: 99%

Supervised Machine Learning of High Rate GNSS Velocities for Earthquake Strong Motion Signals

et al. 2022

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High rate Global Navigation Satellite System (GNSS) processed time series capture a broad spectrum of earthquake strong motion signals, but experience regular sporadic noise that can be difficult to distinguish from true seismic signals. The range of possible seismic signal frequencies amidst a high, location‐varying noise floor makes filtering difficult to generalize. Existing methods for automatic detection rely on external inputs to mitigate false alerts, which limit their usefulness. For these reasons, geodetic seismic signal detection makes for a compelling candidate for data‐driven machine learning classification. In this study we generated high rate GNSS time differenced carrier phase (TDCP) velocity time series concurrent in space and time with expected signals from 77 earthquakes occurring over nearly 20 years. TDCP velocity processing has increased sensitivity relative to traditional geodetic displacement processing without requiring sophisticated corrections. We trained, validated and tested a random forest classifier to differentiate seismic events from noise. We find our supervised random forest classifier outperforms the existing detection methods in stand‐alone mode by combining frequency and time domain features into decision criteria. The classifier achieves a 90% true positive rate of seismic event detection within the data set of events ranging from MW4.8–8.2, with typical detection latencies seconds behind S‐wave arrivals. We conclude the performance of this model provides sufficient confidence to enable these valuable ground motion measurements to run in stand‐alone mode for development of edge processing, geodetic infrastructure monitoring and inclusion in operational ground motion observations and models.

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A Multiple Algorithm Approach to the Analysis of GNSS Coordinate Time Series for Detecting Geohazards and Anomalies

Cited by 7 publications

References 83 publications

Assessment of the accuracy of low-cost multi-GNSS receivers in monitoring dynamic response of structures

Assessment of the accuracy of low-cost multi-GNSS receivers in monitoring dynamic response of structures

Analysis of the performance of closely spaced low-cost multi-GNSS receivers

Supervised Machine Learning of High Rate GNSS Velocities for Earthquake Strong Motion Signals

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