西太平洋海域卫星测高重力数据精度分析

Accuracy Analysis of Satellite Altimetry Gravity Data in the Western Pacific Area

  • 摘要: 近年来,海域卫星测高重力数据在大地测量、海域区域构造、海域资源调查、国防安全等方面得到了广泛应用。为评估最新版本卫星测高重力数据在深海区的数据精度,选择西太平洋海域不同来源、不同版本的卫星测高重力数据(SS V24.1、SS V29.1、DTU10、DTU15、GETECH),利用1∶200 000船载重力数据对卫星测高重力数据开展精度评估分析。分析结果表明,5种卫星测高重力数据与船载重力数据高度线性相关,两者之间均存在系统差,船载重力与卫星测高重力数据之间系统差在-8.0×10-5~-7.5×10-5 m/s2之间,其中SS V29.1卫星测高重力数据精度优于其他卫星测高重力数据,标准差为1.51×10-5 m/s2。此外,利用船载重力数据与卫星测高重力数据之间线性相关的特点,引入消除两者之间系统差的一元线性回归分析方法;同时分析了不同来源卫星测高重力数据的噪声分布特征,采用最小曲率方法对卫星测高重力数据进行噪声压制处理,提高了卫星测高重力数据精度。研究结果表明,一元线性回归分析方法能够消除系统差,且最小曲率噪声压制方法能有效地压制船载重力数据和卫星测高重力数据的动态噪声,提高数据精度。两种方法简单实用,计算精度高,可推广应用至全海域使用,并可用于类似的数据精度分析中,具有广阔的推广应用前景。

     

    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 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, root mean square error and standard deviation 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 1.51×10-5 m/s2,1.67×10-5 m/s2 and 1.66×10-5 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, and the root mean square error is greatly 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 0.97×10-5 m/s2 to 1.48×10-5 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.

     

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