论文标题
通过连续分段结构检测嘈杂的GPS时间序列中的变化点
Detecting change-points in noisy GPS time series with continuous piecewise structures
论文作者
论文摘要
用潜在的连续分段结构在嘈杂的数据序列中检测变更点是一个具有挑战性的问题，尤其是当对结构变化的确切性质的先验知识未知时。一种重要的应用是在地面变形的GPS测量中自动检测慢速事件（SSE），一种慢速地震。我们提出了一种基于奇异频谱分析的新方法，以掩盖与分段线性结构的偏差，从而使我们能够使用分离株 - 使用分段 - 非线性结构在SSE数据中检测变更点。我们在模拟和真实的SSE数据中证明了它的有效性。
Detecting change-points in noisy data sequences with an underlying continuous piecewise structure is a challenging problem, especially when prior knowledge of the exact nature of the structural changes is unknown. One important application is the automatic detection of slow slip events (SSEs), a type of slow earthquakes, in GPS measurements of ground deformation. We propose a new method based on Singular Spectrum Analysis to obscure the deviation from the piecewise-linear structure, allowing us to apply Isolate-Detect to detect change-points in SSE data with piecewise-non-linear structures. We demonstrate its effectiveness in both simulated and real SSE data.
