Deconvolution of ultrasonic nondestructive evaluation signals using higher-order statistics

In ultrasonic nondestructive evaluation (NDE) of materials, pulse echo measurements are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic pulses, and are corrupted by additive noise. Deconvolution operation seeks to undo these masking effects and extract the defect impulse response which is essential for identification. In this contribution, we show that the use of higher-order statistics (H0S)-based deconvolution methods is more suitable to unravel the aforementioned effects. Synthetic and real ultrasonic data obtained from artificial defects is used to show the improved performance of the proposed technique over conventional ones, based on second-order statistics (SOS), commonly used in ultrasonic NDE.