Blake C. Eastman, United States Air Force Academy; Audra M. Jensen, United States Air Force Academy; Daniel S. O’Keefe, United States Air Force Academy; Francis K. Chun, United States Air Force Academy; David M. Strong, Strong EO Imaging, Inc.
Keywords: Polarization, GEO Satellites, Space Situational Awareness, Space Domain Awareness
Abstract:
Observations of satellites within the angular resolution of small-aperture telescopes yield unresolved optical point sources, thus requiring different measurement and analysis techniques to characterize these satellites. One type of measurement potentially useful for unresolved satellite characterization is the linear polarization of the reflected satellite optical signature. We investigate this by surveying the polarization signatures of various operational geosynchronous communications satellites, which typically have large solar panel wings. To determine the polarization signature of these satellites, we image them using an Andor Alta U47 CCD camera mounted to a 16-inch f/8.2 telescope. Prior to imaging, the light passes through polarization filters oriented at 0°, 45°, 90°, and 135° with respect to the cameras focal plane. The polarization filters are cycled between images, allowing for near-simultaneous recording of the intensities of light at each of the four orientations. Satellites observed in this manner included DirecTV-10, DirecTV-12, DirecTV-15, XM-4, MEXSAT-3, and SES-3. The intensities of the light at each orientation are extracted using Mira® Pro. Through software developed using MATLAB®, the intensities at each filter orientation were converted into Stokes parameters (S0, S1, S2) as well as angle and degree of linear polarization (AOLP/DOLP). The first Stokes parameter (S0) is the total intensity of the light, whereas the second (S1) and third (S2) parameters are the difference in intensities of light in the 0° and 90° orientations or 45° and 135° orientations, respectively. Additionally, the DOLP quantifies the overall linear polarization of the light, while the AOLP describes the orientation of the polarized light. Though these measures of polarization are best when used with simultaneous observations, a reasonable approximation can be determined using near-simultaneous observations. Aberrations due to the telescope and polarimeter are corrected by a calibration matrix. The accuracy of the polarimeter is verified by measuring stars with known polarizations and comparing the results. Furthermore, data corrupted because of poor atmospheric conditions is identified by analyzing the correlation of Stokes parameters between satellites in the same image frame. A high correlation of the Stokes parameters between satellite pairs suggests the source of the measured polarization is not the satellite but that of the background. Satellites are measured throughout the year, contributing to information on their baseline polarization signatures when the predominant source is due to the spacecraft bus, and glint polarization signatures when the predominant source is due to the solar panels. We present linear polarization signatures of geosynchronous satellites as a function of time and longitudinal phase angle. These signatures clearly show different polarization characteristics of the light reflected off the surface materials associated with the spacecraft. First, a distinct baseline is present in DOLP across the entirety of observations, along with a corresponding AOLP shift, which suggests that a majority of the polarization signature outside a glint is caused by the satellites solar panels. Second, the polarization signature for a given satellite is consistent over different nights, indicating that the polarization signal originates from the satellite spacecraft bus itself. Finally, different, but similarly constructed satellites (which have the same mission set) possess different polarization signatures, hinting that the configuration of the payload and/or orientation of the satellite is influential in the satellites polarization signature.
Date of Conference: September 27-20, 2022
Track: Non-Resolved Object Characterization