Microwave imaging is a science which has been evolved from older detecting/locating techniques (e.g., radar) in order to evaluate hidden or embedded objects in a structure (or media) using electromagnetic (EM) waves in microwave regime (i.e., ~300 MHz-300 GHz).[1] Engineering and application oriented microwave imaging for non-destructive testing is called microwave testing, see below.
Microwave imaging techniques can be classified as either quantitative or qualitative. Quantitative imaging techniques (are also known as inverse scattering methods) give the electrical (i.e., electrical and magnetic property distribution) and geometrical parameters (i.e., shape, size and location) of an imaged object by solving a nonlinear inverse problem. The nonlinear inverse problem is converted into a linear inverse problem (i.e., Ax=b where A and b are known and x (or image) is unknown) by using Born or distorted Born approximations. Despite the fact that direct matrix inversion methods can be invoked to solve the inversion problem, this will be so costly when the size of the problem is so big (i.e., when A is a very dense and big matrix). To overcome this problem, direct inversion is replaced with iterative solvers. Techniques in this class are called forward iterative methods which are usually time consuming. On the other hand, qualitative microwave imaging methods calculate a qualitative profile (which is called as reflectivity function or qualitative image) to represent the hidden object. These techniques use approximations to simplify the imaging problem and then they use back-propagation (also called time reversal, phase compensation, or back-migration) to reconstruct the unknown image profile. Synthetic aperture radar (SAR), ground-penetrating radar (GPR), and frequency-wave number migration algorithm are some of the most popular qualitative microwave imaging methods[1].