A wavelet-based hybrid approach to remove the flicker noise and the white noise from GPS coordinate time series

摘要

Understanding the destructive interference of noise involved in GPS coordinate time series is crucial for improving the reliability of GPS applications. The majority of the noise consists of both flicker and white noise, both of which are well characterized by a stochastic process following a power-law noise model. To simplify the noise removal for GPS coordinate time series, the noise is usually regarded as pure white noise rather than a mixture of flicker noise and white noise. This work proposes a wavelet-based integrated solution that merges the strengths of Shannon entropy and wavelet thresholding to remove flicker and white noise at the same time. A GPS coordinate time series, spanning 128 days from the GPS monitoring station at the Jinduicheng Mine in Shanxi, China, was selected to test the proposed algorithm. The results demonstrate that both flicker noise and white noise are worthy of attention because they can lead to a seriously misunderstandings about error in a GPS coordinate time series. The utility of our proposed algorithm in removing flicker and white noise is shown to be more comprehensive than the use of wavelet thresholding alone. The findings further reveal that the advance elimination of flicker noise is beneficial for subsequently utilizing wavelet thresholding to delete the white noise in a GPS coordinate time series. This will greatly improve the reliability of GPS coordinate time series, allowing such data to be applied to a wide range of fields.