A Robust Estimation Method of the Wall Parameters Based on Machine Learning

In through-wall radar imaging, the wall parameters, including permittivity, wall thickness and conductivity, are of crucial importance for locating targets precisely and obtaining a well-focused image. There are usually ambiguities in practice. To obtain a quick and accurate estimation of wall parameters, a robust approach based on machine learning is introduced. The measurement results demonstrate that the estimation approach has the advantages of high precision and low computational time.