skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Transient high frequency signal estimation: A model-based processing approach

Conference ·
OSTI ID:6446237

By utilizing the superposition property of linear systems a method of estimating the incident signal from reflective nondispersive data is developed. One of the basic merits of this approach is that, the reflections were removed by direct application of a Weiner type estimation algorithm, after the appropriate input was synthesized. The structure of the nondispersive signal model is well documented, and thus its' credence is established. The model is stated and more effort is devoted to practical methods of estimating the model parameters. Though a general approach was developed for obtaining the reflection weights, a simpler approach was employed here, since a fairly good reflection model is available. The technique essentially consists of calculating ratios of the autocorrelation function at lag zero and that lag where the incident and first reflection coincide. We initially performed our processing procedure on a measurement of a single signal. Multiple application of the processing procedure was required when we applied the reflection removal technique on a measurement containing information from the interaction of two physical phenomena. All processing was performed using SIG, an interactive signal processing package. One of the many consequences of using SIG was that repetitive operations were, for the most part, automated. A custom menu was designed to perform the deconvolution process.

Research Organization:
Lawrence Livermore National Lab., CA (USA)
DOE Contract Number:
W-7405-ENG-48
OSTI ID:
6446237
Report Number(s):
UCRL-92372; CONF-851209-8; ON: DE87008756
Resource Relation:
Conference: 24. IEEE conference on decision and control, Ft. Lauderdale, FL, USA, 11 Dec 1985; Other Information: Paper copy only, copy does not permit microfiche production
Country of Publication:
United States
Language:
English