舒曼谐振的数据处理方法及其应用研究

Study on the data processing methods for Schumann resonance and its application

舒曼谐振(Schumann resonance,SR)信号淹没于非常强的环境噪声数据中,影响了常规处理方法的性能。为了从观测数据中可靠地提取微弱的SR信号,先对实际的SR观测数据进行奇异值分解(singular value decomposition,SVD)滤波,再利用常规算法提取参数,分析了观测站处的闪电源分布、参数日变化规律以及一起太阳耀斑事件对应的参数变化。结果证明,经过SVD滤波后得到的估计结果能更好地反映SR参数的变化规律,极大地提高了常规方法的可靠性。

The Schumann resonance（SR） signal is often buried in the dramatic noise from the surrounding environment,so the performances of the routine methods are affected.In order to extract the weak SR signal reliably,the SR raw data are filtered by a singular value decomposing（SVD） method and the correlative parametars are obtained by regular methods.The actual SR data are filtered by SVD method and are processed by multi-peaks fitting method.The distribution of lighting source around the observatory,the diurnal variation regular of parameters and the frequency variation during a severe solar flare event are analyzed.The analysis results prove that the parameters estimated by the proposed method can manifest the natural law better and greatly improve the performance of the routine methods.