Improving Time Estimation by Blind Deconvolution: with Applications to TOFD and Backscatter Sizing

TL;DR

This paper introduces a blind deconvolution method using statistical wavelet estimation to improve time resolution in ultrasound-based diffraction techniques, applicable to TOFD and backscatter sizing.

Contribution

It presents a novel blind deconvolution scheme that estimates the wavelet without prior knowledge, enhancing time resolution in ultrasonic signal analysis.

Findings

Robustness demonstrated on synthetic data

Effective wavelet estimation from signals

Improved time resolution in diffraction techniques

Abstract

In this paper we present a blind deconvolution scheme based on statistical wavelet estimation. We assume no prior knowledge of the wavelet, and do not select a reflector from the signal. Instead, the wavelet (ultrasound pulse) is statistically estimated from the signal itself by a kurtosis-based metric. This wavelet is then used to deconvolve the RF (radiofrequency) signal through Wiener filtering, and the resultant zero phase trace is subjected to spectral broadening by Autoregressive Spectral Extrapolation (ASE). These steps increase the time resolution of diffraction techniques. Results on synthetic and real cases show the robustness of the proposed method.