Recovery of Ultrasonic Impulse Response by Spectral Extrapolation

Further improvement of temporal resolution of seismic data by autoregressive (AR) spectral extrapolation

“…Spectral extrapolation algorithms based on AR techniques have been commonly used for modeling the past values (backward) and future values (forward) of a signal (Lines and Clayton, 1977;Walker and Ulrych, 1983;Oldenburg et al, 1983;Miyashita et al, 1985;Kim et al, 2001Kim et al, , 2003Doğan and Erer, 2004). In applying AR spectral extrapolation, R(ω) is first obtained by Wiener deconvolution.…”

“…This admission is also favorable for the seismic data. Furthermore, frequency window should be selected where the SNR is high so that the extrapolated spectrum will be almost flat (Miyashita et al, 1985;Zala et al, 1988). The reflectivity sequence of layered media consisting of a number of spikes has approximately flat spectrum.…”

“…But, in most cases, this process may not produce meaningful results because of the frequent noise caused by numerical ill-conditions. To overcome this problem, the frequency-dependent alternative version of Wiener filter based on the minimization of a least square error (L2-norm deconvolution) can be generally used as follow (Levy and Fullagar, 1981;Miyashita et al, 1985;Neal et al, 1993;Sin and Chen, 1992).…”

“…The AR technique has been used to predict the missing low and high frequencies and consequently to recover acoustic impedance by inversion of seismic reflection data (Lines and Clayton, 1977;Oldenburg et al, 1983;Walker and Ulrych, 1983). However, the combination of Wiener filtering and autoregressive spectral extrapolation have also been used to improve temporal resolution in analyzing ultrasonic signals which are also used in the discrimination of closely spaced reflectors as well as the detection of the discontinuities in coarse-grained materials, such as austenitic steel welds (Miyashita et al, 1985;Zala et al, 1988;Sin and Chen, 1992;Honarvar et al, 2004). All these studies have shown that Wiener filtering followed by autoregressive spectral extrapolation can produce very good results at a reasonable computational cost.…”

Application of Superresolution Methods for Expert Control of Cylindrical Objects

“…This method has been implemented for extrapolation of acoustic holograms when flaws are located in the far field of the receiving aperture [22,23] or in the Fresnel zone [24] to improve the transverse resolution of the image. It was used also for improvement of the transverse resolution when extrapolating spectra of echo signals [25,26]. Studies [27,28] are concerned with the analysis of the fine structure of pulses scattered from a vertically oriented crack in the bulk of metal.…”