Abstract: Objective:  Since the 1970s, the advent of satellite altimetry has provided an effective database for determining the marine gravity field, effectively filling the gaps of shipborne gravity data. In recent years, the accuracy of satellite altimetry gravity data has improved significantly with the continuous improvement of satellite altimetry techniques. In order to evaluate the quality of the latest satellite altimetry gravity data in deep sea area, the download satellite altimetry gravity data in versions SS V24.1, SS V29.1, DTU10, DUT15, GETECH are comparative analyzed with the shipborne gravity data with the scale of 1:200 000 in the Western Pacific Area.   Methods:  The accuracies of the five different versions of satellite altimetry gravity data are externally checked by using shipborne gravity line-type data and the corresponding grid data separately. The correlation coefficient, mean deviation (md), root mean squared (rms) error and standard deviation (std) between every satellite altimetry gravity data and the shipborne gravity data are calculated to compare and analyze. Based on comparative analysis results, the linear regression method is used to remove the system deviation between the satellite altimetry gravity data and the shipborne gravity data, and the minimum curvature filtering method is used to suppress the noise in the satellite altimetry gravity data to improve the data accuracy.   Results:  The results show that:(1) Five versions of satellite altimetry gravity data are highly linearly correlated with shipborne gravity data, but there are system deviation between them. The accuracies of SS V29.1, V24.1 and DTU15 are high, and the standard deviation between them and shipborne gravity data are 1.509×10^-5 m/s², 1.665×10^-5 m/s² and 1.657×10^-5 m/s² respectively, which is better than the comparison results obtained by previous scholars. (2) The linear regression method can help to figure out the relationship between the satellite altimetry gravity data and the shipborne gravity data, which can eliminate system deviation between the satellite altimetry gravity data and shipborne gravity data. After regression calculation, the average difference beteween the satellite altimetry gravity and the shipborne gravity data decreased to 0×10^-5 m/s², and the root mean square error isgreatly reduced, ranging from 1.50×10^-5 m/s² to 2.20×10^-5 m/s².(3) The minimum curvature filtering method can effectively suppress the noise of shipborne gravity data and altimetry gravity data, and make the distribution features of satellite altimetry gravity data more clear and improve the accuracy of satellite altimetry gravity data. After noise suppression, the root mean square error and standard deviation are equal, ranging from 0.90×10^-5 m/s² to 1.50×10^-5 m/s², among which the standard deviation between SS V29.1 and shipborne gravity data is the smallest,0.97×10^-5 m/s².   Conclusions:  According to the comparative analysis, the accuracy of the latest five versions of satellite altimetry gravity data are better than their former versions and can meet the needs of marine gravity research on scales around 1:500 000 to 1:1 000 000. The linear regression method and minimum curvature filtering method can be used efficiently and easily in improving the accuracy analysis of satellite altimetry gravity data in the Western Pacific area, which can lead to better applications of the satellite altimetry gravity data and deserve to be promoted.