Impact of high-risk conjunctions on Active Debris Removal target selection

All rights reserved.Space debris simulations show that if current space launches continue unchanged, spacecraft operations might become difficult in the congested space environment. It has been suggested that Active Debris Removal (ADR) might be necessary in order to prevent such a situation. Selection of objects to be targeted by ADR is considered important because removal of non-relevant objects will unnecessarily increase the cost of ADR. One of the factors to be used in this ADR target selection is the collision probability accumulated by every object. This paper shows the impact of high-probability conjunctions on the collision probability accumulated by individual objects as well as the probability of any collision occurring in orbit. Such conjunctions cannot be predicted far in advance and, consequently, not all the objects that will be involved in such dangerous conjunctions can be removed through ADR. Therefore, a debris remediation method that would address such events at short notice, and thus help prevent likely collisions, is suggested

Impact of high-risk conjunctions on Active Debris Removal target selection

All rights reserved.Space debris simulations show that if current space launches continue unchanged, spacecraft operations might become difficult in the congested space environment. It has been suggested that Active Debris Removal (ADR) might be necessary in order to prevent such a situation. Selection of objects to be targeted by ADR is considered important because removal of non-relevant objects will unnecessarily increase the cost of ADR. One of the factors to be used in this ADR target selection is the collision probability accumulated by every object. This paper shows the impact of high-probability conjunctions on the collision probability accumulated by individual objects as well as the probability of any collision occurring in orbit. Such conjunctions cannot be predicted far in advance and, consequently, not all the objects that will be involved in such dangerous conjunctions can be removed through ADR. Therefore, a debris remediation method that would address such events at short notice, and thus help prevent likely collisions, is suggested

Ballistic coefficient estimation for re-entry prediction of rocket bodies in eccentric orbits based on TLE data

Spent rocket bodies in geostationary transfer orbit (GTO) pose impact risks to the Earth's surface when they re-enter the Earth's at- mosphere. To mitigate these risks, re-entry prediction of GTO rocket bodies is required. In this paper, the re-entry prediction of rocket bod- ies in eccentric orbits based on only Two-Line Element (TLE) data and using only ballistic coefficient (BC) estimation is assessed. The TLEs are preprocessed to filter out outliers and the BC is estimated using only semi-major axis data. The BC estimation and re-entry pre- diction accuracy are analyzed by performing predictions for 101 rocket bodies initially in GTO and comparing with the actual re-entry epoch at different times before re-entry. Predictions using a single and mul- tiple BC estimates and using state estimation by orbit determination are quantitatively compared with each other for the 101 upper stages

Statistical analysis of the inherent variability in the results of evolutionary debris models

Space debris simulations, e.g. those performed by the Inter-Agency Debris Coordination Committee (Liou et al., 2013), showed that the number of objects in orbit is likely to increase. This study analyses the uncertainty in the results of space debris simulations performed using semi-stochastic models that necessitate the use of Monte Carlo simulations, which are often used by the Inter-Agency Debris Coordination Committee, amongst other studies. Statistics of the possible numbers of objects in orbit and collisions over the next 200 years are generated for the “mitigation only” scenario using a sample of 25,000 Monte Carlo runs. Bootstraps on the mean, median, variance, skewness and kurtosis of these distributions are performed. It is shown that the distribution of the objects predicted to be on-orbit becomes log-normal as collisions occur, and that Monte Carlo samples larger than traditionally used are needed to capture the debris simulation uncertainty

Processing two line element sets to facilitate re-entry prediction of spent rocket bodies from geostationary transfer orbit

Predicting the re-entry of space objects enables the risk they pose to the ground population to be managed. The more accurate the re-entry forecast, the more cost-efficient risk mitigation measures can be put in place. However, at present, the only publicly available ephemerides (two line element sets, TLEs) should not be used for accurate re-entry prediction directly. They may contain erroneous state vectors, which need to be filtered out. Also, the object’s physical parameters (ballistic and solar radiation pressure coefficients) need to be estimated to enable accurate propagation. These estimates are only valid between events that change object’s physical properties, e.g. collisions and fragmentations. Thus, these events need to be identified amongst the TLEs. This paper presents the TLE analysis methodology, which enables outlying TLEs and space events to be identified. It is then demonstrated how various TLE filtering stages improve the accuracy of the TLE-based re-entry prediction