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本文详细讨论了重力固体潮观测数据预处理中平均滤波方法、加窗傅里叶变换方法和小波滤波方法。对于M2和S2的调和分析结果,平均滤波方法得到相位延迟误差超过了40°;加窗傅里叶变换得到的振幅因子精度分别为0.00029和0.00068,相位延迟精度分别为0.014°和0.033°;小波滤波方法得到最优的振幅因子精度分别为0.00013和0.00035,最优的相位延迟精度分别为0.006°和0.017°。研究结果表明:小波滤波方法的精度最高,加窗傅里叶变换的精度次之,平均滤波方法的精度最低;基于Daubechies小波基的小波滤波更适合于重力固体潮观测数据的预处理。
This paper discusses in detail the average filtering method, the windowed Fourier transform method and the wavelet filtering method in the gravity tide observation data preprocessing. For the harmonic analysis results of M2 and S2, the average filtering method obtained the phase delay error exceeding 40 °; the precision of the amplitude factor obtained by the windowing Fourier transform was 0.00029 and 0.00068, respectively, and the phase delay accuracy was 0.014 ° and 0.033 ° respectively; The best amplitude factor accuracy of the filtering method is 0.00013 and 0.00035, respectively. The optimal phase delay accuracy is 0.006 ° and 0.017 °, respectively. The results show that wavelet filter has the highest accuracy, the accuracy of windowed Fourier transform is the second, and the average filtering method has the lowest accuracy. The wavelet filter based on Daubechies wavelet is more suitable for the pretreatment of gravity tide observations.