Advances in Mixed Signal Processing for Regional and Teleseismic Arrays
Abstract
In this subject, we have considered a number of possible approaches to resolving mixtures of propagating signals and noises over seismic arrays. The problem is important because there will often be interfering noise sources, extraneous signals, or mixtures of phases that will be organized as plane waves. Analyzing such mixtures using conventional beam-forming and other methods will produce distorted velocities and azimuths and may even give incorrect magnitudes. One interesting result of this study is that beam-forming, single-signal F-Statistics as well as typical high resolution multiple-signal estimators from engineering literature, such as the Multiple Signal Characteristic (MUSIC) algorithm all suffer from the above problems for some very common situations involving regional and teleseismic data. We have approached the problem by showing that the multiple-signal plane-wave model is essentially in the form of a nonlinear regression in the frequency domain so that a sequential approach to isolating component signals analogous to stepwise linear regression can be applied. This approach provides a sequence of tests showing the power contribution of each component of a mixture and yields estimators for velocities and azimuths and their uncertainties. In the first year, we used this regression model, coupled with a corrected form of Akaike's Information Criterion (AICC) to setfie on a final mixture. Applying the AICC as a model selection criterion yielded three signals known to have occurred on this long-period mixture and a decomposition of a regional earthquake into a known signal and a propagating noise.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2006
- Accession Number
- ADA468795
Entities
People
- Robert H. Shumway
Organizations
- University of California, Davis