Microstructures and mechanical properties after spheroidizing annealing (SA) of GCr15 bearing steel with and without an alternating magnetic field (AMF) were investigated. It was found that the application of the AMF at the austenitizing stage promoted the dissolution of carbides, accelerated the austenitizing process and increased the hardness of the quenched sample. After isothermal annealing, the carbides in the sample with an AMF more uniformly distributed and became finer in comparison with those without an AMF. The average hardness of the sample treated in the AMF was lower than that without an AMF. The phenomena could be attributed to the enhanced diffusivity in the AMF.

Traditional near-field synthetic aperture radar (SAR) imaging algorithms reveal target features by exploiting signal amplitude and phase information. However, electromagnetic wave propagation is constrained by short distance. Therefore, the spherical wave approximation needs to be considered. In addition, it is also limited by equipment ambient noise, azimuth-distance coupling, wave scattering, and transmission power. Both the amplitude and phase of the signal suffer from the interference of multiple clutter, so they cannot be effectively utilized. To address these issues, this paper introduces a covering penetration detection system based on an improved Range Migration Algorithm (IMRMA) imaging method. Firstly, the proposed method minimizes interferences from the front end of the system using an optimized window to balance denoising and information preservation. Next, interval non-uniform interpolation, instead of Stolt interpolation decoupling, is employed to reduce the computational overhead significantly. To minimize the effects due to wave scattering and propagation loss, distance information is enhanced using amplitude and phase compensation. This reduces scattering effects and enhances image quality. An experimental system is constructed based on a vector network analyzer (VNA) to image the target. The proposed method takes about half the time of traditional RMA. The PSNR in the chunky bowl experiment is higher than 14 dB, which is higher than all the compared methods in the paper. The test results show that the designed system and the reported method can effectively achieve high-resolution images by strengthening the target intensity and suppressing the environmental artifacts.

In the medical field, microwave imaging technology has experienced rapid development due to its non-invasive and non-radioactive nature. The confocal algorithm is a method commonly used for microwave breast cancer imaging, with the key objective of removing clutter in images to achieve high-quality results. However, the current methods are facing challenges in removing clutter. In order to reduce the clutter in images, a multiplicative improved coherence factor delay multiply and sum algorithm based on the maximum interclass differencing method is proposed. The algorithm compares the starting and ending moments of tumor signals in different channels to determine whether the tumor-scattered signals in different channels overlap in time. An improved coherence coefficient is obtained by summing the non-overlapping signals and multiplying the time window. The multiplicative improved coherence factor, which is obtained by multiplying the coherence coefficients of the improved multi-pair signals, is then multiplied by the focal point intensity obtained using the delay multiply and sum algorithm to reduce clutter in an image. To evaluate the performance of the proposed algorithm, several low-cost uniform and non-uniform models of human breast and tumor tissue with dielectric properties were prepared for testing. The experimental results show that, compared to the existing algorithm, the proposed algorithm can greatly reduce the clutter in images, with a signal-to-clutter ratio of at least 4 dB higher as well as contrast at least six-fold higher.