Guo Juntian

A lightning motion prediction technology based on spatial clustering method

Lightning warning is an essential means and a key technology for lightning disaster reduction. Passivity is the main drawback of existing lightning warning methods. This paper present a lightning prediction technology based on spatial clustering method to predict lightning motion by utilizing realtime and historical lightning monitoring data of lightning location system. On the contrary to the existing passive lightning prediction and warning methods, this technology initiatively predicts the prospective lighting area. The independent, discrete, random-happen flashes are aggregated to different thunderstorm groups similar to thunderclouds by the spatial clustering method presented in this paper. The position prediction of lightning can be achieved by tracking these thunderstorm groups and calculating the movement direction and speed of them. The lightning prediction method is applied to a certain region of central China. The experiment result shows that the predicted and real positions of lightning are approximately consistent. The average prediction accuracy is around 75%. Important support will be provided for improving the accuracy and reducing the false alarm rate of lightning warning by the presented technology.

Lightning imaging with thunder using broadband direction-of-arrival estimation technique

A single-station-based three-dimensional (3D) acoustic lighting mapping system comprising a microphone array has been developed and used for lightning observations, in which a new broadband direction-of-arrival (DOA) estimation techniques namely incoherent signal-subspace method are proposed for thunder signals in the far-field. Two cloud-to-ground (CG) flashes with highly branch channels recorded by the system are analyzed and presented in this paper. The acoustic mapping results can not only locate on the main channel produced by the return stroke process but also depict the branch channels. Moreover, the located thunder sources by the mapping system and the photography of the high speed camera agree well with each other demonstrating the effectiveness and correctness of the estimation techniques and the mapping system.

The recognition method of thunder based on a noise-estimation algorithm for highly non-stationary environments

A recognition method of the thunder signal based on the end-point detection method with a noise-estimation algorithm for highly non-stationary environments is proposed. To determine the parameter of the algorithm and verify the effectiveness and accuracy of the method we analyze the acoustic signals obtained from two microphone arrays installed at the top platform on a seven-floor building in Wuhan. In this paper, we have chosen two acoustic signals to test the endpoint detection method. It is revealed from the recognition result that the method can find out the accurate beginning and ending time of the thunder signal from the acoustic signals.