Comprehensive Space-Object Characterization using Spectrally Compressive Polarimetric Sensing.

摘要

Among the most important accomplishments of the project are 1. Development of physical models that predict how surface roughness, texture, and shape alter the state of polarization of solar illumination scattered/reflected by a space object and their use to determine surface shape, material composition, and texture; 2. Derivation and application of a number of approximate, task-based theoretical performance-assessment tools based on statistical information and Bayesian error analysis that are numerically efficient and generally applicable to image analysis, recovery, and reconstruction tasks; 3. Design, fabrication, and testing of two polarimetrically enhanced versions of the CASSI instrument using polarization sensitive elements; 4. Development and benchmarking of new algorithms for highly resolved spatial segmentation, material identification, shape determination, surface characterization, and extraction of rigid-body kinematics from polarimetric CASSI data; and 5. Recovery of 3D shape, rigid-body kinematics, and surface characterization from a time series of 2D compressive spectral-polarimetric images.