A Pseudo-Fourier Series Method and its Application in Tilt Data Processing

The basic principle of a new pseudo-Fourier series method is derived in detail in this paper. Simulation experiments show that the algorithm can effectively remove the noise and preserve signal's original energy effectively compared with the filtering results based on adaptive LMS algorithm. In addition, the experiment shows that the filtering speed of like Fourier methods is about 25 times the speed of adaptive LMS algorithm. The four types of ground tides are successfully filtered for picking-up the long-term trend of the tilt observation.

Application of a Pseudo-Fourier Series Method in Tilt Data Processing

A new pseudo-Fourier series (PFS) method to suppress single-frequency noise is proposed in this paper. The basic principle is derived in detail. Numerical experiments show that the PFS method is highly effective in extracting harmonic signal and when the frequency of the extracted composition is very close to that of the noise composition, the filtering effect will be slightly decreased, and the close range is about 1e-4. Four types of ground tides are successfully filtered out for picking-up the long-term trend of the tilt observation and the mutational abnormality.