Comparison and Analysis of Three Methods for Dynamic Height Error Correction in GNSS-IR Sea Level Retrievals
Remote Sens(2024)
Changan Univ
Abstract
Sea level monitoring is of great significance to the life safety and daily production activities of coastal residents. In recent years, GNSS interferometric reflectometry (GNSS-IR) has gradually developed into a powerful complementary technique for sea level monitoring, with the advantages of wide signal spatial coverage and lower maintenance cost. However, GNSS-IR-retrieved sea level estimates suffer from a prominent error source, referred to as the dynamic height error due to the nonstationary sea level. In this study, the tidal analysis method, least squares method and cubic spline fitting method are used to correct the dynamic height error, and their performances are analyzed. These three methods are applied to multi-system and multi-frequency data from three coastal GNSS stations, MAYG, SC02 and TPW2, for three years, and the retrievals are compared and analyzed with the in situ measurements from co-located tide gauges to explore the applicability of the three methods. The results show that the three correction methods can effectively correct the sea level dynamic height error and improve the accuracy and reliability of the GNSS-IR sea level retrievals. The tidal analysis method shows the best correction performance, with an average reduction of 39.3% (10.7 cm) and 37.6% (6.7 cm) in RMSE at the MAYG and TPW2 stations, respectively. At station SC02, the cubic spline fitting method performs the best, with the RMSE reduced by an average of 39.3% (5.5 cm) after correction. Furthermore, the iterative process of the tidal analysis method is analyzed for the first time. We found the tidal analysis method could significantly remove the outliers and correct the dynamic height error through iterations, generally superior to the other two correction methods. With the dense preliminary GNSS-IR sea level retrievals, the smaller window length of the least squares method can yield more corrected retrievals and better correction performance. The least squares method and cubic spline fitting method, especially the former, are highly dependent on the amount of daily GNSS-IR sea level retrievals, but they are more suitable for dynamic height correction in storm events than the tidal analysis method.
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Key words
GNSS-IR,sea level,dynamic height error,tidal analysis,least squares,cubic spline fitting
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