adaptive beamforming for improved ultrasonic imaging in noisy environments

In this paper, we introduce a novel delay-weight-sum (dws) beamforming technique for defect detection in non-destructive testing (ndt). this method offers improved accuracy over traditional total focusing method (tfm) and its weighted variants. the proposed technique enhances defect detection and imaging quality through an advanced dws beamforming approach based on a minimum variance method. the minimum variance approach utilizes the newton-schulz iterative method for efficient matrix inverse approximation. additionally, a new non-linear weighting mechanism, based on a sigmoid function, is introduced to refine the matrix inverse approximation for dws beamforming. this mechanism dynamically adjusts the weighting to enhance reflective points while reducing background noise. comparative analyses demonstrate the superior imaging resolution and reduced background noise achieved by the proposed method compared to existing tfm-based techniques. despite its computational demands, simulation results show that the method significantly improves ultrasonic image quality and contrast, holding promise for advancements in ultrasonic ndt, especially in heterogeneous and noisy environments.