An Analytical Model for Optical Polarimetric Imaging Systems
Optical polarization has shown promising applications in passive remote sensing. However, the combined effects of the scene characteristics, the sensor configurations, and the different processing algorithm implementations on the overall system performance have not been systematically studied. To better understand the effects of various system attributes and help optimize the design and use of polarimetric imaging systems, an analytical model has been developed to predict the system performance. The model propagates the first- and second-order statistics of radiance from a scene model to a sensor model and, finally, to a processing model. Validations with data collected from a division of time polarimeter are presented. Based on the analytical model, we then define a signal-to-noise ratio of the degree of linear polarization and receiver operating characteristic curves as two different system performance metrics to evaluate the polarimetic signatures of different objects, as well as the target detection performance. Several examples are presented to show the potential applications of the analytical model for system analysis.