14:00 〜 14:15
[G06-5-03] Sea level retrieval based on fitting model of GNSS SNR observations
Long-term water level monitoring in coastal regions is important to understand how the local sea level is changing and affects the human life. This paper presents a new altimetric method for retrieving sea surface heights by global navigation satellite signals reflected over the ocean surface. It uses SNR observations from a single geodetic receiver. A detrended SNR fitting model depends on different impact factors of SNR measurements is proposed. The fitting model searching process includes two steps: the coarse parameters of the detrended SNR model for the whole elevation period of different satellites are searched based on optimization method firstly. Then, the fine model parameters for small temporal samples are refined based on the estimated coarse parameters. Ground-based sea level measurements that was conducted at the Onsala Space Observatory from July 1, 2015 to June 30, 2016 demonstrate, that altimetric information about the reflecting water surface can be obtained with a Root Mean Square Error of 9.29 cm with respect to a reference tide gauge dataset. The sea surface changes, derived from our field experiment and the reference tide gauge, are highly correlated with a correlation coefficient of 0.93. Experimental results of the SNR measurements show the proposed method can perform much higher temporal resolution and have higher accuracy when compared to the previously spectral methods.