RESIDENT SPACE OBJECT CHARACTERIZATION BY FUSING POLARIZED AND UNPOLARIZED LIGHT CURVES
Abstract
Space situational awareness (SSA) involves knowing a resident space object s (RSO s) information, usually orbital position, and assessing how this information can affect its future state in relation to other RSOs. One of the main challenges in SSA is the characterization of RSOs. Characterization typically involves estimating a range of attributes, including RSO shape, mass, albedo area and material composition. Previous work has shown that polarized light information can be used to determine the material properties of an RSO, and unpolarized light can be used to determine an RSO s shape. The specular reflection of unpolarized light off a flat surface creates a reflection that is partially polarized. This polarization depends on the index of refraction and on the extinction coefficient of the reflecting material. Thus, the degree of polarization contains information about the surface material that is not contained in the unpolarized light curve. An initial polarized bidirectional reflectance distribution function (BRDF) has been developed to generate polarized light curves. Several BRDF models exist to generate unpolarized light curves. Methods will be assessed to fuse both polarized and unpolarized light curves to simultaneously estimate material properties and shapes. The current proposed work significantly extends previous work by 1) providing theoretical analyses in "Flatland" space, which will provide deeper insights on the usefulness of using polarized light curves, 2) investigating multispectral polarized light curves to assess any performance gains for characterization, 3) incorporating more detailed and realistic BRDF polarized models, 4) performing a thorough analysis of the observability of the to-be-estimated attributes, and 5) incorporating the results to assess the performance of an overall approach to simultaneously estimate multiple attributes.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 20, 2023
- Source ID
- FA95502210440
Entities
People
- John Crassidis
Organizations
- Air Force Office of Scientific Research
- Research Foundation for the State University of New York
- United States Air Force