高铁震源地震信号的稀疏化建模

In China, there are thousands of high-speed trains running on over twenty thousand kilometers railways every day. These running high-speed trains not only cause vibration of railway roadbed but also stimulate seismic waves. The data recorded by seismic receivers to these events contain multi-narrow-band waves by high-speed trains as well as wide-band background noise. Therefore, the key step to use these signals is to divide the complex data into the real high-speed train induced seismic signals and the background noise. Considering the morphological difference between the high-speed train induced seismic signals and the background noise, we firstly introduce the morphological component analysis to the processing of the high-speed train induced seismic signals, and realize the separation between these signals and the background noise by sparse modeling. We applied this approach to the dataset collected by Peking University in South China. The results show that the acquired dataset can be successfully divided to the multi-narrow-band high-speed train induced seismic signals and the wide-band background noise by using the morphological component analysis and block-coordinate relaxation.