Inverse estimation of bi-directional reflectivity in long-wave infrared region by using RPSO algorithm

The Infrared signature is used in the fields of remote sensing, military defense and auto navigation system by detecting objects against the background. Infrared signature of objects depends on many factors, including the shape of objects, surface temperature, emissivity, bidirectional reflectivity and radiation sources such as solar irradiation and sky shine. It is essential to procure radiative surface properties in predicting the infrared signature of objects. Especially the bidirectional reflectivity is difficult to obtain due to the limited data in the literature. In this study, we develop a software which estimates radiative properties of painted surfaces inversely from the measured temperature and radiance variations with time by using the Repulsive particle swarm optimization (RPSO) algorithm. In this study surface radiative reflection properties in the LWIR region are estimated for 3 different paints by using the pre-determined radiance in LWIR region and surface temperature. The results obtained from this study show fairly good agreement with the original BRDF data used to estimate the LWIR radiance and temperature as the input data.