A stochastic approach to detect fragmentation epoch from a single fragment orbit determination

In the last decades, the growing in-orbit population of resident space objects has become one of the main concerns for space agencies and institutions worldwide. In this context, fragmentations further contribute to increase the number of space debris and, operationally, it is fundamental to identify the event epoch as soon as possible, even when just a single fragment orbital state, resulting from an Initial Orbit Determination (IOD) process, is available. This work illustrates the Fragmentation Epoch Detector (FRED) algorithm, which deals with the problem through a stochastic approach, starting from a single fragment IOD result (expressed through mean state and covariance) and parent ephemeris (assumed as deterministic). The process populates the fragment ephemeris with a multivariate normal distribution and, for each couple sample-parent, the epochs of parent transit through the Minimum Orbital Intersection Distance (MOID) are first computed on a time window and then clustered in time. For each cluster, both the three-dimensional MOID and the three-dimensional relative distance distributions are derived, and their similarity is statistically assessed. Given that, at the actual fragmentation epoch, MOID and relative distance were equal, the cluster featuring the best matching between the two distributions is considered as the optimal candidate, and the related fragmentation epoch is returned from the time of parent transit through the MOID, in terms of mean and standard deviation. FRED algorithm performance is assessed through a numerical analysis. The algorithm robustness decreases when parent and fragment orbits share a similar geometry, and results get deteriorated if the perturbations and, moreover, the IOD errors are included in the process, but the correct fragmentation epoch is always present among candidates. Overall, FRED algorithm turns out to be a valid choice in operational scenarios, and a sensitivity analysis tests the algorithm out of the nominal conditions

Conjunction Analysis Software Suite for Space Surveillance and Tracking

The increasing number of objects in Earth orbit has encouraged the development of space surveillance and tracking (SST) applications. A critical aspect of SST is the identification and characterization of close encounters between pairs of space objects. The present work introduces a tool for the analysis of conjunctions, consisting of several modules. The first module, which has been shown to greatly speed up the process, employs a series of geometric and temporal filters to shorten the list of potential colliding pairs. The remaining objects are then propagated to compute important parameters such as time of closest approach (TCA), miss distance (MD), and probability of collision (PoC), the latter using three different methods. When a conjunction assessment returns an MD or a PoC that exceeds predefined alert thresholds, the algorithm enables the planning of an impulsive collision avoidance maneuver (CAM) at specific maneuver epochs. CAM candidates are determined using an analytical Keplerian approach, with the goal of achieving the desired PoC or MD. The user can then verify the performance of a specific candidate through perturbed propagation, and the MD and PoC are recalculated after the maneuver to ensure that they meet the desired thresholds. In conclusion, this paper evaluates the performance of the tool using synthetic and real data, providing valuable insights into its effectiveness