Updated material identification from remote sensing of polarized self-emission

An important application for remote sensing is the detection and discrimination of targets of interest. The detection and discrimination problem is not trivial, especially if the target blends with its background or when decoys are deployed. Remote sensing systems can utilize imaging polarimetry to identify the materials from which targets are made. A fundamental property of a material is its complex index of refraction, which can be calculated from the material’s degree of linear polarization (DoLP). Previously, we reported on a technique for estimation of the complex index of refraction (CIR) using measurements of the polarized radiance from a material’s self-emission. The materials were measured with an imaging polarimeter that operates in the mid-wave infrared spectral region. Several improvements to our processes have been implemented since the earlier work and these improved processes have led to improved results, which are detailed in this paper. A larger set of materials was measured and analyzed, including measurements with a new imaging polarimeter, which operates in the long-wave infrared spectral region. We also made improvements to our model for the degree of linear polarization of a material. This model is used in conjunction with the DoLP calculated from the measured data to estimate the CIR, which is a fundamental property of materials and can therefore be used to identify a material. An initial goal of this work is to use the technique to discriminate between metals and dielectrics. We demonstrate the ability to discriminate between metals and dielectrics with the estimated CIR results. There is a clear difference for the estimated index of refraction values, and an even more significant difference for the coefficient of extinction values, obtained for metals versus the values obtained for dielectrics. These differences in estimated values provide a means of discriminating metals from dielectrics.