Ultrasonic imaging is widely used because of its non-invasive,low cost and good real-time performance.A large number of acquisition channel data and high sampling rate are needed by ultrasound system to improve the quality of image reconstruction,resulting in time-consuming imaging and complex system.Compressed sensing (CS) algorithm only needs a small number of measurements to reconstruct the original signal under the condition of under sampling.In order to solve the problem of high sampling rate and large data volume faced by the system,DWT-IRLS algorithm in compressed sensing theory is applied to ultrasonic imaging in this paper.The ultrasonic data are sparse transformed through discrete wavelet transformation (DWT),the high and low frequency coefficients are sampled and measured,and the iterative reweighted least squares (IRLS) method is introduced to reconstruct the measurement coefficients.Finally,the reconstructed image is obtained by DWT inverse transformation. Through experimental analysis, the image reconstruction effect with 50% of the original data gradually tends to be stable.Compared with the reconstruction algorithms such as DWT-OMP,DWT-CoSamp and DCT-IRLS,DWT-IRLS algorithm has higher imaging quality and more obvious detail features.