Hybrid Resolvent Kernel Calibration Technique for Microwave Imaging Systems

This work assesses a hybrid calibration technique that uses together measured and simulated data to compensate modeling errors such as fabrication tolerances and positioning inaccuracies. Here, as a proof-of-concept, it is considered a virtual microwave imaging experiment of a human brain stroke condition. The test involves a full-wave software based on the finite element method and 3-D highly realistic system models, including a set of 24 monopoles immersed in a solid brick-shaped matching medium and a single-cavity anthropomorphic head phantom. The studied case shows that under favorable assumptions, the calibration procedure improves the quality of the retrieved images compared to the non-calibrated-kernel approach.