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Adele, a fast suboptimal estimator for real-time deconvolution

Adele, a fast suboptimal estimator for real-time deconvolution

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© The Institution of Electrical Engineers
Published

It is shown how a Kalman filter approach can solve an orthogonalisation problem that occurs when accelerating the convergence of the Kaczmarz algorithm for real-time deconvolution. A new suboptimal estimator is developed in the case of noise and input stationary statistics. Simulation results in reflection seismology are presented.

Inspec keywords: seismology; signal processing; Kalman filters; filtering and prediction theory

Other keywords: reflection seismology; suboptimal estimator; Kaczmarz algorithm; Kalman filter; orthogonalisation problem; real-time deconvolution

Subjects: Information theory; Signal processing and detection; Filters and other networks

References

    1. 1)
      • Demoment, G.: `Déconvolution discrète en temps réel', Proc. 8th Colloque GRETSI, 1981, Nice, p. 275–280.
    2. 2)
      • N.D. Crump . A Kalman filter approach to the deconvolution of seismic signals. Geophysics , 1 - 13
    3. 3)
      • M.Z. Nashed , M.Z. Nashed . (1976) Aspects of generalized inverses in analysis and regularization, Generalized inverses and applications.
    4. 4)
      • J.M. Mendel . White-noise estimator for seismic data processing in oil exploration. IEEE Trans. , 694 - 706
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