A new structure for sequential detection and maximum entropy spectral estimator for characterization of volcanic seismic signals

Abstract

This study proposes a new method to characterize volcanic seismic events based on classic spectral and maximum entropy estimators. Events of interest are detected in the time domains by a new structure of sequential robust detection obtained using autoregressive spectral analysis. Classical power spectral density analysis is then used to define spectral features for each type of seismic events of interest. A data set of seismic events from Cotopaxi volcano was used for the analysis. The proposed method allows near-real time detection of the locations in time where certain volcanic events take place, maximizing the detection probability and maintaining a constant false alarm rate.