基于BP神经网络技术的电离层VTEC融合

随着电离层探测技术的不断发展，电离层观测资料也越来越多，只使用单一的观测资料会出现电离层反演精度不高的问题。为了提高电离层的反演精度，使用BP神经网络技术将地基反演和国际参考电离层(international reference ionosphere，IRI)模型的垂直总电子含量（vertical total electron content，VTEC）数据进行有效融合。在温带地区\35°(N)~45°(N)，60°(E)~80°(E)\]进行电离层反演试验，结果表明基于BP神经网络技术的电离层数据融合和地基反演获得的电离层VTEC精度都比较高，但是基于BP神经网络的电离层数据融合反演精度比地基反演更高，所以基于BP神经网络技术的数据融合能够提高电离层的反演精度。

Ionospheric VTEC fusion based on BP neural network technology

With the continuous development of ionospheric detection technology, there are more ionospheric observation data. Using only a single observation datum will cause the problem of low accuracy of ionospheric inversion. In order to improve the inversion accuracy of the ionosphere, the BP neural network technology is used to effectively fuse the vertical total electron content (VTEC) data of ground-based inversion and international reference ionosphere (IRI) model inversion. Ionospheric inversion experiments were performed in temperate regions 35°(N)--45°(N)，60°(E)--80°(E)\]. The results show that the data fusion based on BP neural network technology and ground-based inversion can both achieve high accuracy of ionospheric VTEC. The data fusion method based on BP neural network has higher ionospheric inversion accuracy than ground-based inversion, so data fusion based on BP neural network technology can improve the ionospheric inversion accuracy.