一种电离层周期探测新方法

A Method Based on the Combination of Wavelet Multi-scale Decomposition and Fast Fourier Transform to Detect the Ionosphere Cycle

近年来,电离层时空变化的研究已经成为了研究热点之一,提出一种基于小波多尺度分解和快速傅里叶变换相结合的方法来探测太阳活动和电离层周期,此方法探测效果好、速度快、准确率高,可以探测出较弱的周期。通过总电子含量、太阳黑子数及沃尔夫黑子数数据序列分析,并就电离层模型和影响电离层影响因子层面,可以得出三者高度线性相关;作为影响电离层变化的因素,太阳黑子数及沃尔夫黑子数可以相互替代;在电离层模型中引入参数沃尔夫黑子数更为合理等结论。

In recent years, temporal and spatial variation of the ionosphere has become one of the hotspots. A method which combines the wavelet multi-scale decomposition and fast Fourier transform is proposed to detect the cycle of solar activity and the ionosphere. This method has the advantages of good results, fast and high accuracy, and it can detect the weak cycle. By analyzing the data sequence of TEC, SSN and F10.7, the following conclusions were got： TEC. SSN and F10.7 are high linear correlated; As the factor that influences the changes in the ionosphere, F10.7 and SSN can replace each others the parameter of F10.7 should be quoted to the ionosphere model.