Iterative coherence factor (iCF) beamforming method for ultrasound-based nondestructive testing

This paper proposes a statistical ultrasound beamforming method based on an iterative coherence factor (iCF) to enhance image contrast and signal-to-noise ratio (SNR) with low hardware cost. By leveraging the distribution characteristics of target and noise signals in nondestructive testing (NDT) and structural health monitoring (SHM), the method employs maximum likelihood and enhanced maximum a posteriori (MAP) estimations to iteratively optimize signal distribution parameters. This process continuously strengthens coherent image regions while effectively suppressing background noise, artifacts, and boundary reflections. The effectiveness and robustness of the proposed method are demonstrated through comprehensive experimental validations, including inspections of steel structures, welds, rails guided by longitudinal waves, and carbon fiber-reinforced plate (CFRP) defect detection guided by Lamb waves. Experimental results show that the proposed iCF method significantly outperforms the traditional Delay-and-Sum (DAS) method, achieving over double increase in the imaging contrast and an improvement in SNR greater than 20 dB in both dense and sparse array configurations. In addition, the proposed method has a low computational burden and can easily replace the DAS method. The iterative coherence framework developed in this study has the potential to build up a novel technical route for future optimized signal modeling and parameter estimation in the field of NDT and SHM.