期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 60, 期 -, 页码 -出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2022.3219074
关键词
Global navigation satellite system multipath reflectometry (GNSS-MR); ocean tides; sea-level estimation; signal strength indicator (SSI); signal-to-noise ratio (SNR)
类别
资金
- KeyResearch and Development Program of Shandong Province [2021ZDSYS01]
- NaturalScience Foundation of Shandong Province [ZR2022MD046]
- National Natural Science Foundation of China [41704017, 41604003]
In this study, a new method for sea-level estimation using signal strength indicator (SSI) data in GNSS observation files was proposed. It was found that the proposed method could accurately estimate sea levels with a precision similar to the traditional SNR method. Additionally, the sea-level results derived from the proposed method were applied to estimate ocean tides, and the coefficients for several main tides showed good agreement when determined by different data.
Compared with tide gauges, global navigation satellite system multipath reflectometry (GNSS-MR) can provide low-cost, long-term sea-level data that are not susceptible to crustal loading. Signal-to-noise ratio (SNR) observables in GNSS files are commonly used for GNSS-MR; however, these observables are not always present, especially in early GNSS files. Several different combinations of codes and carrier-phases for GNSS-MR as substitutes to extract sea level have been proposed; however, the requirement of these methods for application of cycle slip detection or multifrequency observations to isolate multipath signals reduces their applicability. Here, we propose a new method for sea-level estimation using signal strength indicator (SSI) data in GNSS observation files, which is an alternative to existing methods because SSI data always exist. To verify the proposed method, we used four multiGNSS data from three stations to monitor sea level. Sea-level estimations with root-mean-square errors (RMSEs) of 7-8, 5-9, 12-15 and 9-13 cm relative to in situ data were retrieved, and the correlation coefficients for these stations were bigger than 0.98, 0.98, 0.93 and 0.96, respectively. Moreover, the proposed method measures sea levels with precision similar with the traditional SNR method. In addition, sea-level results derived from the proposed method at these stations were further applied to estimate ocean tides. Ocean-tide coefficients for several main tides determined by different data were in good agreement.
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