Estimation of seismic-wave parameters and signal detection using maximum-likelihood methods

A broad-band maximum likelihood method is presented for the detection of an d parameter extraction from seismic events using wideband data recorded by an array of seismic stations. The statistical characteristics of finite Fou rier-transformed data motivate the use of approximate maximum-likelihood (M L) methods which allow simultaneous detection and wave-parameter estimation . The detection strategy based on the likelihood ratio indicates the presen ce of a seismic event and resolves different phases of seismic events arriv ing within a time interval of interest. The corresponding slowness vectors of the phases are simultaneously estimated by optimization of the likelihoo d function over parameters of interest. The potential of the wideband ML me thod is demonstrated on GERESS data and compared to conventional f-k analys is showing advantages of the former in detection and resolution. (C) 2001 E lsevier Science Ltd. All rights reserved.