Compressive Sensing for Full Matrix Capture RF Signals Reconstruction in Ultrasonic Array

Abstract

Nondestructive testing and evaluation technology of total focus method (TFM) based on full matrix capture (FMC) is a hot spot in the current array of ultrasonic testing technology. The method has the advantages of high imaging accuracy and strong defect characterization ability, However, the TFM is a data-intensive algorithm, the same logic is used for a large number of calculations at each imaging point, which takes a long time and is difficult to give full play to its advantages in the efficient and automated industrial testing field. To solve the problem of a large amount of data in the acquisition, storage, and transmission of ultrasonic phased array signal, the ultrasonic phased array total focus method based on compressed sensing (CS-TFM) was proposed. The signal sparsity in the fast Fourier transform (FFT) and discrete cosine transform (DCT) sparse domains were compared. The reconstruction accuracy of two reconstruction algorithms, Orthogonal Matching Pursuit (OMP) and L1 norm were analyzed. The optimal sparse basis and the optimal reconstruction algorithm for the full matrix signal of the ultrasonic phased array were obtained. In addition, the effect of the TFM algorithm meshing on image quality and imaging speed was also studied. The experimental verification of the proposed compression sensing (CS) method can accurately reconstruct the ultrasound FMC data at a 60% compression rate, and the root means square error between the reconstructed data and the actual full matrix data is about 6%. CS-TFM method provides a new idea and lays a foundation for reducing the complexity of the detection system and the requirement of hardware.