Analytical modeling of optical polarimetric imaging systems

Polarimetric imaging systems have shown promising applications in passive remote sensing. To better understand the effects of various system attributes and help optimize the de sign and use of polarimetric imaging systems, an analytical model is developed to predict the system performance. The model consists of scene, sensor, and processing system components. Some pre-processing procedures such as estimation of the Stokes vector and degree of linear polarization (DoLP) are currently considered in the processing model. Validation with data collected from a division of time polarimeter shows good agreement between model predictions and measurements. It has been shown that the analytical model is able to predict the general polarization behavior and data trends with different scene geometries.