Asynchronous Multi-Sensor Change-Point Detection for Seismic Tremors

TL;DR

This paper introduces an asynchronous multi-sensor change-point detection method tailored for seismic tremors, effectively aligning signals with unknown delays and outperforming existing methods in detecting weak, asynchronous signals.

Contribution

It proposes a novel asynchronous Subspace-CUSUM procedure that jointly estimates signal waveforms and sensor delays, improving detection performance for asynchronous signals.

Findings

The method accurately detects weak, asynchronous seismic signals.

It outperforms traditional one-shot procedures in simulations and real data.

Optimal drift parameters are derived for the proposed detection scheme.

Abstract

We consider the sequential change-point detection for asynchronous multi-sensors, where each sensor observe a signal (due to change-point) at different times. We propose an asynchronous Subspace-CUSUM procedure based on jointly estimating the unknown signal waveform and the unknown relative delays between the sensors. Using the estimated delays, we can align signals and use the subspace to combine the multiple sensor observations. We derive the optimal drift parameter for the proposed procedure, and characterize the relationship between the expected detection delay, average run length (of false alarms), and the energy of the time-varying signal. We demonstrate the good performance of the proposed procedure using simulation and real data. We also demonstrate that the proposed procedure outperforms the well-known `one-shot procedure' in detecting weak and asynchronous signals.