On radar polarization target decomposition theorems with application to target classification, by using neural network method

Abstract

In the first part the authors recall the basic principles of 'radar holography' and high resolution electromagnetic radar imaging construction, and present a real measurement of canonical radar targets. Then they introduce in the second part, the concept of 'radar polarization target decomposition theorems' to separate the Mueller matrix in two parts which are related to a single averaged target and to a residue component. In the last part, they introduce a new polarimetric method of classification based on a neural network modelization, and show how it is possible to identify a scatterer from the knowledge of the four high resolution electromagnetic radar images. >