| Abstrakt: |
One of the challenges on the characterization of geosynchronous satellites is the estimation of the attitude, rotation rate, and shape of geosynchronous satellites from the solar illumination reflected off the solar panels and bus towards the observer from non-resolved photometric signatures of object. It has been observed from measured light curves, that a specific pattern in the light curve may give an indication of the evolution of the orientation of the largest components on a satellite, i.e. the solar panels, during the time of the acquisition of measurements. This paper presents results on the simulation of DirecTV-10 satellite from 04:30 to 8:00 (UTC), which was observed during the glint season from 04:00 to 8:00 (UTC) on 23 February 2021 with U.S. Air Force Academy’s USAFA-16 and CMU-Falcon’s telescopes. We use a physics-based simulator; Digital Imaging and Remote Sensing Image Generator (DIRSIG™) to help us understand the temporal and spectral variability of the light curves in terms of the orientation of the solar panels. To accomplish this optical parameters, lat/lon of the telescopes, the characteristics of the photometric filters, the two-line element of the satellite, and a standard atmospheric condition model, are all input into the simulator to carry out the simulations. We use a high-fidelity CAD model of the satellite, materials, and BRDF measurements provided by the Air Force Research Laboratory Satellite Assesment Center (AFRL- SatAC). We describe a generate-and-test method we use to simulate the angular position (E-W) of the solar panels, such that the L 2 norm error between measured and simulated line curves is minimized. The results presented in this paper show that DIRSIG™ is able to accurately match, up to some accuracy, specific patterns observed on calibrated magnitude measurements of the USAFA-16 and CMU-Falcon telescopes. This study will help us develop and understanding of the behavior of unresolved space objects (RSOs) and guide the design, development, and testing of exploitation algorithms. [ABSTRACT FROM AUTHOR] |
Full text from SpringerLink