Polarization characteristics motivating target detection in different polarization spaces

Coated target detection has attracted lots of attention due to its great potentials in applications. However, there is still a huge challenge to precisely detect coated targets due to scattering and modulations caused by coats. In this paper, the multi-angle reflective polarization information, together with multi-dimensional representation formats, has been explored for an excellent solution for the aforementioned challenge. Specifically, we construct a real-scenario multi-layer scatterer to represent coated targets based on the Monte Carlo algorithm, and realistic interactions between the scatterer and light are modeled and simulated considering multiple scattering effects. These interactions change the polarization state of incident light, causing scattering light to carry target information. Afterwards, the scattering lights leaving the scatterer are captured in the whole upper hemisphere to obtain multi-angle reflective information. Based on it, the polarization indexes are explored to measure the changes of polarization property of targets with different roughness at different incident angles. Moreover, the Indexes of Polarization Purity (IPPs) space and Components of Purity (CP) space are used to distinguish target characteristics. In addition, we have also constructed a new determinant-trace (DET-TRA) space for distinguishing target characteristics more effectively. The results demonstrate the targets' changing characteristics with different targets' indexes and unique distributions in proposed representation spaces, indicating a practical method for detecting and inverting coated targets.