Improved vessel squat modeling for hydrographic and navigation applications using kinematic GNSS positioning

Ardalan, Alireza A.; Rezvani, Mohammad-Hadi

doi:10.1007/s10291-013-0326-8

Cited by 6 publications

(3 citation statements)

References 10 publications

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“…According to the definition of the carrier attitude angle, the GNSS antenna wobble on the buoy is mainly caused by the attitude changes in the roll and pitch directions [ 33 ], and the correction of the GNSS buoy can be simply expressed as

where

denotes the value of the pole arm of the GNSS antenna relative to the center of the buoy, and

and

denote the instantaneous roll and pitch.…”

Section: Methodsmentioning

confidence: 99%

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Sea Surface Height Measurements Based on Multi-Antenna GNSS Buoys

Xue,

Yang,

Zhao

et al. 2024

Sensors

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Sea level monitoring is an essential foundational project for studying global climate change and the rise in sea levels. Satellite radar altimeters, which can sometimes provide inaccurate sea surface height data near the coast, are affected by both the instrument itself and geophysical factors. Buoys equipped with GNSS receivers offer a relatively flexible deployment at sea, allowing for long-term, high-precision measurements of sea surface heights. When operating at sea, GNSS buoys undergo complex movements with multiple degrees of freedom. Attitude measurements are a crucial source of information for understanding the motion state of the buoy at sea, which is related to the buoy’s stability and reliability during its development. In this study, we designed and deployed a four-antenna GNSS buoy with both position and attitude measurement capabilities near Jimiya Wharf in Qingdao, China, to conduct offshore sea surface monitoring activities. The GNSS data were processed using the Precise Point Positioning (PPK) method to obtain a time series of sea surface heights, and the accuracy was evaluated using synchronous observation data from a small sea surface height radar. The difference between the GNSS buoy and the full-time radar was calculated, resulting in a root-mean-square error (RMSE) of 1.15 cm. Concurrently, the attitude of the GNSS buoy was calculated using multi-antenna technology, and the vertical elevation of the GNSS buoy antenna was corrected using the obtained attitude data. The RMSE between the corrected GNSS buoy data and the high ground radar was 1.12 cm, indicating that the four-antenna GNSS buoy can not only acquire high-precision coastal sea level data but also achieve synchronous measurement of the buoy’s attitude. Furthermore, the data accuracy was also improved after the sea level attitude correction.

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where

denotes the value of the pole arm of the GNSS antenna relative to the center of the buoy, and

and

denote the instantaneous roll and pitch.…”

Section: Methodsmentioning

confidence: 99%

“…According to the definition of the carrier attitude angle, the GNSS antenna wobble on the buoy is mainly caused by the attitude changes in the roll and pitch directions [33], and the correction of the GNSS buoy can be simply expressed as…”

Section: Gnss Data Processingmentioning

confidence: 99%

Sea Surface Height Measurements Based on Multi-Antenna GNSS Buoys

Xue,

Yang,

Zhao

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…The effects of bathymetric data are generally a comprehensive process. The real-time navigation positioning information, posture and sound velocity data, and echo signals of vessels should be edited or corrected to recognize and reject false signals and to recover and retain real information for improving the sounding accuracy and ensuring the drawing quality of seafloor topographic map [8][9]. These steps are essential preparations to the subsequent data processing and mapping control.…”

Section: Introductionmentioning

confidence: 99%

Detection and Elimination of Bathymetric Outliers in Multibeam Echosounder System Based on Robust Multi - quadric Method and Median Parameter Model

Wang¹,

Zhou²,

Wu³

et al. 2018

JESTR

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Multibeam echosounder system is a dynamic measurement under the continuous motion of measurement platform. Contaminated sporadic outliers are inevitably generated during bathymetric data acquisition due to the interference of underwater environmental effects, such as ocean waves, wind, and tides. A filtering model of robust multi-quadric method based on median parameter was proposed in this study to detect and eliminate the outliers in bathymetric datasets. The submarine topography trend surface model was constructed by the multi-quadric function. Known node parameters in the function were obtained by the threshold extraction method of joining angle, chord with dispersion. The robust iterations of residual error initials and the weight-weakening process of outliers were studied by median parameters and IGGIII equivalent weight function. The validity of the proposed filtering model was verified by experimental datasets of offshore waters, which were collected by BV5000 multibeam side scan sonar. Results demonstrate that the known node selection strategy in this study can remove redundancy information in point set and extract regional characteristic points to the maximum extent. The fitting errors at normal bathymetric points are all below 0.06 m, which are decreased compared with the corresponding magnitude of other schemes (0.16 m, 0.12 m). The residual initial value of robust iteration based on median parameters exhibites relatively high estimation accuracy and detection efficiency. The errors of bathymetric points are relatively small (0.019 m), and the detection number of outliers (150) is efficient in the entire detection region. This work can improve the accuracy and efficiency of underwater terrain detection and lay a foundation for later scientific research and marine exploration.

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