非平稳大地测量信号特征信息小波识别

Feature information identification of non-stationary geodetic signal with wavelet

将小波变换和Fourier变换的谱分析结合起来,在时域中记录大地测量信号序列的突变时间,在频域中提取信号突变的频段,通过序列在小波变换各尺度上的小波能量时谱和能量频谱可以得到大地测量内涵的主要复杂过程的有关尺度层次,进而分析、识别内涵的特征信息.仿真实例表明,该方法既保证了特征信息提取的质量,又降低了计算的时空复杂度.对山东基准站的YATI站和WUDI站的年周期、半年周期、季节周期数据进行实例分析,识别提取了特征信息,效果良好.

Wavelet energy spectrum,combining wavelet transform and Fourier transform can be used to record both the abrupt changing time quantum in time and its frequency band in frequency.So it can be used to determine the relevant scales of the main complex processes which offered the basis for analyzing and identifying the feature information.Simulating results showed that the quality of the extracted information was guaranteed and the time and space complexity was reduced by the mentioned method.this method was also successfully applied to identify and extract feature information from annual period item,semi-annual period item and seasonal period item of YATI and WUDI station in Shandong.