基于多台站高频GPS的地震预警优化算法研究  

Optimization algorithm of earthquake early warning based on multi-station high frequency GPS

作　　者：张文浩 尹玲 胡文博 ZHANG Wenhao;YIN Ling;HU Wenbo(College of Electronic and Electric Engineering,Shanghai University of Engineering Science,Shanghai 201620,China;Institute of Geology,China Earthquake Administration,Beijing 100029,China;Shanghai University,School of Communication&Information Engineering,Shanghai 200444,China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620 [2]中国地震局地质研究所,北京100029 [3]上海大学通信与信息工程学院,上海200444

出　　处：《全球定位系统》2022年第3期56-64,共9页Gnss World of China

基　　金：中国地震局地质研究所博士后项目“基于深度学习的震级综合快速判定研究”;国家自然科学基金委员会青年基金(61802251)。

摘　　要：随着精密定位技术的发展,高频GPS已能够精确记录地表位移数据,研究高频GPS能为地震预警工作做出一定补充.针对目前地震预警中单站预警误报率高的问题引入深度学习技术,利用长短期记忆网络(LSTM)联合周边区域台站对单台站进行预警以达到减少误报的目的.首先通过对新西兰南部地区1 Hz高频GPS数据进行解算得到多个台站无震时间序列,再利用该数据训练网络得到融合区域特征的高精度模型.该模型可以对无震时间序列进行预测并动态制定阈值区间,当实际观测值超出置信区间则判定异常.通过与传统短时窗平均/长时窗平均算法(STA/LTA)及未融合区域特征的单站模型进行对比,结果表明:融合区域特征的单站模型可有效减少误报,在多个台站的无震长序列上较传统方法表现优异,具有一定的应用价值.With the development of precision positioning technology,high-frequency GPS has been able to accurately record surface displacement data.Research on high frequency GPS can make a certain supplement to earthquake early warning.In view of the high false alarm rate of single station in earthquake early warning,we introduce deep learning technology and use the long short-term memory(LSTM)neural network to combine with surrounding stations to give early warning to single station.First,the seismic-free time series of multiple stations are obtained by solving the 1 Hz high-frequency GPS data in the southern region of New Zealand Then the data is used to train the network to obtain a high-precision model that integrates regional features.The model can predict the seismic-free time series and dynamically formulate a threshold interval.When the actual observation value exceeds the confidence interval,an abnormality is determined.By comparing with the traditional short-time window averaging/long-time window averaging algorithm(STA/LTA)and the single station model without regional features,the results show that the single station model fusing regional features can effectively reduce false alarms.It performs better than traditional methods on seismic-free long sequences of multiple stations and has certain application values.

关 键 词：GPS 长短期记忆网络(LSTM) 时间序列 误报 新西兰地震 地震预警 

分 类 号：P228.49[天文地球—大地测量学与测量工程]