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High Area-to-Mass Ratio object population assessment from data/track association

机译:来自数据/轨道关联的高面积质量比对象人口评估

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To date, the actual population of High Area-to-Mass Ratio (HAMR) objects in deep Space is still unqualified. These are objects having area-to-mass ratios (AMR's) in the range of around 0.1 -20 m~2/kg and higher. Typical methods for population assessment using optical sensors either count the number of detections per unit time, or employ a disparate sequence of methods to compute HAMR object trajectories, where these methods assume linearized dynamics and fixed-gate correlations. This paper provides results from a set of actual angles (line of sight) data on HAMR objects, where the initial orbit determination and follow-on data/track association is performed probabilistically and autonomously. Moreover, the data are not only used to infer trajectories but also simultaneously exploited for their information content relating to each detected object's albedo-area-to-mass ratio. The results show that the inferred HAMR orbital elements and area-to-mass ratio values (CrA/m), parametrically, can be derived autonomously and without a priori knowledge of the orbit and CrA/m states. This will aid in the correlation of large numbers of uncorrelated tracks.
机译:迄今为止,深空中高面积质量比(HAMR)对象的实际填充量仍不合格。这些物体的面积质量比(AMR)在0.1 -20 m〜2 / kg或更高的范围内。使用光学传感器进行人口评估的典型方法是对每单位时间的检测数量进行计数,或者采用不同的方法序列来计算HAMR对象轨迹,其中这些方法假定线性化动力学和固定门相关性。本文提供了来自HAMR对象上一组实际角度(视线)数据的结果,其中初始轨道确定和后续数据/轨道关联是概率自动地执行的。此外,数据不仅用于推断轨迹,而且还同时利用其数据内容来获取与每个检测到的物体的反照率/面积/质量比有关的信息。结果表明,可以自动导出推断的HAMR轨道元素和面积质量比值(CrA / m),而无需先验了解轨道和CrA / m状态。这将有助于大量不相关轨道的相关。

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