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In this paper, which is based on the data of the HY-2 altimeter, the parametric models of estimating the sea state bias (SSB) were studied. The segmented fitting method of track was adopted to extract the crossing points dataset from the HY-2 geophysical data records (GDR). According to the Taylor expansion, 36 parametric models of estimating SSB as the function of the significant wave height and wind speed were established, and then the coefficients of each parametric model can be calculated by the method of linear regression. After evaluation and selection, the optimal model was obtained. The efficiency of this model can be verified by explained variance, determination coefficient and residual. By comparing with the original SSB estimated model used in the HY-2 GDR, the model formulated in this paper was better than the latter. The results showed this model can improve the correction of SSB in the HY-2 altimeter effectively.