Entropy description of measured information in microwave imaging

For the reconstruction of permittivity distribution in microwave imaging, the information quantity of measured data plays an important role for the reconstruction precision. And the information quantity depends greatly on the number of measurement points. So it is necessary to determine the number of measurement points in analysis and evaluation of a large number of measured data. In this paper, a mathematical methodology based on information entropy is proposed to describe the measured information and determine the required number of measurement points in microwave imaging. Moreover Bayesian theory is used to calculate the information entropy. Numerical tests show that the methodology proposed can describe the measured information effectively. As a result, this methodology can be applied to instruct how to determine the number of measurement points in microwave imaging.