Abstract--In this paper, a merged dataset of collinearlyprocessed sea surface height (SSH) derived from more than 200 repetition periods of Geophysical Data Record (GDR) data of T/P, Jason-1 and Jason-2 satellites is achieve. A directestimation method based on the merged dataset with a resolution of 0.25 × × × × 0.25 is proposed. Compared with the previous non-parametric or parametric models, our directestimation method is with a better accuracy owing to the high spatial resolution of the merged dataset from various satellites. By applying the direct-estimation method in HY-2 satellite, we get the sea state bias (SSB) of HY-2 and demonstrate that this method is with a high accuracy, a good data extension and a wide applicability. Hence, the direct-estimation model can be effectively used for the SSB correction in the current and the subsequent in-orbit satellites.Keywords-satellite altimeter; sea state bias; direct-estimation method; significant wave height I INTRODUCTIONThe Sea State bias (SSB) consisting of the electromagnetic bias, the skewness bias and the tracker bias is one of the fundamental error sources in the measurement of the sea surface height in altimetry [1,2]. Due to the improved orbital technology in recent years, SSB has replaced the orbit errors and became the largest source of error [3]. The empirical models are previously used to correct the SSB: the parametric model, the nonparametric model and the direct-estimation method [4]. Although the parametric model is simple and straightforward, it fails to effectively estimate the true SSB due to the existed errors in the model [5]. Compared with the parametric model, the nonparametric model is with a better accuracy, however, this approach is very complicated and lacks a good extension [6].The direct estimation SSB value through the merged dataset can be applicable to a wider range of sea conditions [7] and especially out of modeling using altimeter, the SSB application like in HY-2 or other subsequent altimeters. The previous direct-estimation method which is based on a single altimeter dataset only can be used for the single altimeter. The future trend of the sea state bias correction is the optimized data set and using more parameters. Guizhong Wang [8] has built a merged dataset for the parametric model. HaoRan Ren [9] has studied on the altimeter-based inversion model of mean wave period. In this paper the directestimation is based on the collinear data that in the same location at different time. Statistical analysis was performed by numerous multiple satellite altimeter sea surface height difference to reveal the inherent dependent variable relationship among SSB and significant wave height (SWH), wind speed (U). This paper integrates more than 200 cycles Geophysical Data Record (GDR) data of T/P, Jason-1 and Jason-2 satellites, collinear the sea surface height, and gets the collinear dataset. Then build the direct estimation SSB table by the dataset and apply the table to HY-2. Finally analyze and evaluates the effectiveness of the method...