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Creation of a synthetic population of space debris to reduce discrepancies between simulation and observations

机译:创建综合性空间碎片,以减少模拟和观察之间的差异

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The number of space debris has increased in the orbital environment, and consequently, the risk of collision between satellites and space debris or space debris and space debris has become a hot topic in Celestial Mechanics. Unfortunately, just a small fraction of the biggest and brightest objects are visible by means of radar and optical telescopes. In the last years, many efforts have been made to simulate the creation of space debris populations through different models, which use different sources and diverse orbital propagators, to study how they evolve in the near future. Modeling a fragmentation event is rather complex; furthermore, large uncertainties appear in the number of created fragments, the ejection directions and velocities. In this paper, we propose an innovative way to create a synthetic population of space debris from simulated data, which are constrained by observational data, plus an iterative proportional fitting method to adjust the simulated population by statistical means. The final purpose consists in improving a synthetic population of space debris created with a space debris model helped by an additional data set which allows to converge toward a new synthetic population whose global statistical properties are more satisfying.
机译:在轨道环境中,空间碎片的数量增加,因此,卫星和空间碎片或空间碎片和空间碎片之间的碰撞风险已成为天体力学的热门话题。不幸的是,通过雷达和光学望远镜可见,只有最大和最亮的物体的一小部分。在过去的几年里,已经通过不同的模型来模拟创建空间碎片群体,这些模型使用不同的来源和不同的轨道传播者来研究它们如何在不久的将来发展。建模碎片事件相当复杂;此外,在创建的片段,喷射方向和速度的数量中出现大的不确定性。在本文中,我们提出了一种创新的方法来创建从模拟数据创造一种综合的空间碎片,这是由观察数据约束的,以及通过统计手段调整模拟群体的迭代比例拟合方法。最终目的在于改进了使用附加数据集帮助的空间碎片模型产生的综合群,该空间碎片模型允许达到全局统计特性更令人满意的新的合成群。

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