In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, the proposed algorithm is effective in reducing the clutter and producing better images. Overall, the methods and procedures registered a signal-to-clutter ratio (SCR) value of 1.54 dB when imaging the most challenging example involving the heterogeneously dense model in 8-antenna geometry. The SCR is slightly increased to 3.12 dB when the number of sensors is increased to 16.
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