In this paper, we analyze the time series of site coordinates of 27 continuously monitoring GPS sites covered by the Crustal Movement Observation Network of China over the whole country. The data are obtained in the p...In this paper, we analyze the time series of site coordinates of 27 continuously monitoring GPS sites covered by the Crustal Movement Observation Network of China over the whole country. The data are obtained in the period from the beginning of the observation to the November of 2005. On the basis of data processing, we analyze the power spectrum density of coordinate component noise at each site and calculate the spectral indexes manifesting the noise property of each component. The spectral indexes indicate that for most sites, the noise of time series of each coordinate component can be addressed by the model of white noise ＋ flicker noise; and for a small amount of sites, it can be described by the model of white noise ＋ flicker noise ＋ random walk noise. We also quantitatively estimate each noise component in the model by using the criterion of maximum likelihood estimation. The result shows that the white noise in the time series of GPS site coordinates does not constitute the main part of noise. Therefore, the error estimation of site movement parameters is usually too small, or too optimistic if we consider the white noise only. Correspondingly, if this factor is not fully considered in explaining these movement parameters, it might mislead the readers.展开更多
Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the ...Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.展开更多
基金Special project of China Earthquake Administration"Study on the Integrated Observation of Vertical Crustal Move-ment and Deformation of South-North Seismic Zone on the Chinese Mainland".
文摘In this paper, we analyze the time series of site coordinates of 27 continuously monitoring GPS sites covered by the Crustal Movement Observation Network of China over the whole country. The data are obtained in the period from the beginning of the observation to the November of 2005. On the basis of data processing, we analyze the power spectrum density of coordinate component noise at each site and calculate the spectral indexes manifesting the noise property of each component. The spectral indexes indicate that for most sites, the noise of time series of each coordinate component can be addressed by the model of white noise ＋ flicker noise; and for a small amount of sites, it can be described by the model of white noise ＋ flicker noise ＋ random walk noise. We also quantitatively estimate each noise component in the model by using the criterion of maximum likelihood estimation. The result shows that the white noise in the time series of GPS site coordinates does not constitute the main part of noise. Therefore, the error estimation of site movement parameters is usually too small, or too optimistic if we consider the white noise only. Correspondingly, if this factor is not fully considered in explaining these movement parameters, it might mislead the readers.
文摘Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.
