Jason-2近海海面高的最优高斯低通滤波半径选择

Optimal Gaussian Low Pass Filtering Radius Selection for Determining Offshore Sea Surface Height with Jason-2 Data

  • 摘要: 使用测高卫星Jason-2传感器地球物理数据记录(sensor geophysical data record,SGDR)的近海海面高观测数据,基于最大似然估计4参数法,对波形数据进行重跟踪。考虑到星下点沿轨方向前后相邻海面高观测值中高频改正信号具有相关性的特征,提出了确定海面高的最优高斯低通滤波半径选择的技术方法,即对星下点沿轨方向观测值进行差分计算,形成差分数据序列,根据序列的相关系数性来确定滤波半径。对于SGDR数据,若对其进行低通滤波,建议滤波半径选为2 km,既可抑制沿轨海面高数据的高频误差,又可保证该数据没有被过度平滑。研究成果可为充分利用卫星测高数据建立高精度近海海面高模型提供参考,进而促进高精度陆海无缝垂直基准的技术体系建设。

     

    Abstract: The data of sensor geophysical data record(SGDR) of Jason-2 altimeter was collected in China coastal region, and four parameters maximum likelihood estimation method was used for waveform retracking, which can be applied for determinating the mean sea surface.The high frequency correction signals between adjacent observations along the track direction of the altimetry satellite Jason-2 SGDR(sensor geophysical data) record data are correlated near the offshore region. Based on this character, the method for optimal selection Gaussian low pass filter radius is put forward. Firstly, difference calculation is needed between the adjacent observations along the track direction. Secondly, form diffe-rence sequence data sets. Thirdly, determinate the filter radius according to correlation coefficient of the sequences. If the user wants to filter the SGDR data, it is best to select the filter radius of the Gaussian filter equals to 2 km. This method not only can suppress the high frequency error in the SSH(sea surface height), but also can ensure that the data is not excessively smooth. It can be considered as a reference for the establishment of high precision sea surface height model by making full use of satellite altimetry data in offshore region, and also can promote the construction of high precision sea seamless vertical datum.

     

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