大型综合巡天望远镜观测到的地球同步轨道碎片轨迹的贝叶斯联系
Bayesian Linking of Geosynchronous Orbital Debris Tracks as seen by the Large Synoptic Survey Telescope
摘要：
我们描述了一个贝叶斯抽样模型的链接和约束轨道模型的角度观测光学望远镜图像中的“条纹”。我们的算法是特别适合的情况下，观察时间是所观察到的物体的轨道周期的一小部分，或当有显着的混乱的对象在观测场。我们使用马尔可夫链蒙特卡罗从联合后验分布的多个轨道模型的参数（观测轨道的数量）和参数描述的轨道与轨道模型。使用这种算法，我们预测的限制，地球同步（GEO）的碎片轨道可与计划的大型综合巡天望远镜（LSST）。由于15秒的曝光时间很短，从LSST初步确定地球同步轨道物体的轨道确定将在轨道要素上产生很大的退化误差。考虑到目前计划的观测节奏，再加上预计地球同步轨道碎片密集的区域，将很难可靠地将长距离SST观测中的轨道轨道联系起来。
英文摘要：
We describe a Bayesian sampling model for linking and constraining orbit models from angular observations of "streaks" in optical telescope images. Our algorithm is particularly suited to situations where the observation times are small fractions of the orbital periods of the observed objects or when there is significant confusion of objects in the observation field. We use Markov Chain Monte Carlo to sample from the joint posterior distribution of the parameters of multiple orbit models (up to the number of observed tracks) and parameters describing which tracks are linked with which orbit models. Using this algorithm, we forecast the constraints on geosynchronous (GEO) debris orbits achievable with the planned Large Synoptic Survey Telescope (LSST). Because of the short 15 second exposure times, preliminary orbit determinations of GEO objects from LSST will have large and degenerate errors on the orbital elements. Combined with the expected crowded fields of GEO debris it will be challenging to reliably link orbital tracks in LSST observations given the currently planned observing cadence.
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