Scaled Coherence Factor Based Beamforming in Microwave Imaging

To solve the restriction of coherence factor (CF)-based beamforming methods in microwave imaging when the signal-to-noise ratio (SNR) is low, which causes the desired signals to be oversuppressed and generates image artifacts. This study proposes an adaptive imaging technique, the SCF-DMAS algorithm, that combines scaled coherence factor (SCF) with delay-multiply-and-sum beamforming algorithm to produce good noise suppression without sacrificing robustness. This technique was tested experimentally in a microwave imaging prototype system with a circular antenna array. The proposed algorithm effectively improves the imaging resolution, contrast, and localization accuracy compared to the other traditional beamformers. The experimental results show that the proposed method can effectively improve the quality of reconstructed images without increasing the computational complexity.