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Results from an Experiment that Collected Visible-Light Polarization Data Using Unresolved Imagery for Classification of Geosynchronous Satellites

机译:使用未解析图像收集地球同步卫星分类的可见光偏振数据的实验结果

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In order to protect critical military and commercial space assets, the United States Space Surveillance Network must have the ability to positively identify and characterize all space objects. Unfortunately, positive identification and characterization of space objects is a manual and labor intensive process today since even large telescopes cannot provide resolved images of most space objects. The objective of this study was to collect and analyze visible-spectrum polarization data from unresolved images of geosynchronous satellites taken over various solar phase angles. Different collection geometries were used to evaluate the polarization contribution of solar arrays, thermal control materials, antennas, and the satellite bus as the solar phase angle changed. Since materials on space objects age due to the space environment, their polarization signature may change enough to allow discrimination of identical satellites launched at different times. Preliminary data suggests this optical signature may lead to positive identification or classification of each satellite by an automated process on a shorter timeline. The instrumentation used in this experiment was a United States Air Force Academy (USAFA) Department of Physics system that consists of a 20-inch Ritchey-Chretien telescope and a dual focal plane optical train fed with a polarizing beam splitter. Following a rigorous calibration, polarization data was collected during two nights on eight geosynchronous satellites built by various manufacturers and launched several years apart. When Stokes parameters were plotted against time and solar phase angle, the data indicates that a polarization signature from unresolved images may have promise in classifying specific satellites.
机译:为了保护重要的军事和商业空间资产,美国太空监视网络必须具有积极识别和表征所有空间物体的能力。不幸的是,由于即使是大型望远镜也无法提供大多数空间物体的可分辨图像,因此,对空间物体的正确识别和表征是当今人工和劳动密集型过程。这项研究的目的是收集和分析来自在各种太阳相位角上拍摄的地球同步卫星的未分辨图像的可见光谱极化数据。随着太阳相位角的变化,使用了不同的收集几何形状来评估太阳能电池阵列,热控制材料,天线和卫星总线的极化贡献。由于空间物体上的材料由于空间环境而老化,因此其极化特征可能会发生足够的变化,从而可以区分在不同时间发射的同一颗卫星。初步数据表明,这种光学特征可以通过在较短时间线上的自动处理来导致对每颗卫星的肯定识别或分类。本实验中使用的仪器是美国空军学院(USAFA)物理系,由20英寸Ritchey-Chretien望远镜和装有偏光分束器的双焦平面光学系统组成。经过严格的校准,在两夜之内,收集了由不同制造商制造并相距数年发射的八颗地球同步卫星的极化数据。当针对时间和太阳相位角绘制斯托克斯参数时,数据表明未分辨图像的极化特征可能有助于对特定卫星进行分类。

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