Overview and classification of a priori information used in microwave tomography

Different kinds of a priori information used to enhance microwave tomography are introduced and classified into two main categories. The first main category of a priori information is about features of target, these can introduce some information of the target to the tomography algorithm. This type of a priori information can lead to a better initial guess and an appropriate regularization as well. The second category is about the imaging system, these can enhance the imaging though loading system configuration information, such as the boundary condition, background and so on. This type of a priori information changes the field which inquires the target, thus it can enhance the system's ability of acquiring the information of target. Both the categories are aimed to improve the quality and quantity of available information, and help the algorithm seeking an accuracy solution stably.