Automatic Detection of Electric Field VLF Electromagnetic Wave Abnormal Disturbance on Zhangheng-1 Satellite

Abstract

Ionosphere disturbances are mainly caused by solar activities and earth surface activities. Different electromagnetic wave disturbances show different shapes on the spectrogram, such as artificial very low frequency transmitting stations, power systems, and satellite platform disturbances which all show a horizontal shape. Due to the electric field coupling or superposition by other electromagnetic disturbances, the horizontal electromagnetic wave clarity on the spectrogram is reduced, interrupted, or disappears. Aiming at this phenomenon, based on computer vision technology, this paper proposes an automatic detection and recognition algorithm for the space electric field abnormal interference. Firstly, the horizontal electromagnetic wave on the spectrogram is detected, and then the detected window density on the horizontal line is counted. We then record and save the density anomaly windows on multiple horizontal lines at the same time, so as to realize the electric field anomaly disturbance automatic detection. The accuracy of the algorithm for detecting continuous electromagnetic wave disturbance with a wide frequency and time interval is up to 98.2%. Through the space electromagnetic disturbances automatic identification from massive data, combined with space events and multi-dimensional information, such as time, space and orbit, it is helpful to further find out the global space-time transformation laws of space events.