Impact probability computation of near-Earth objects using Monte Carlo line sampling and subset simulation
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Impact probability computation of near-Earth objects using Monte Carlo line sampling and subset simulation Matteo Romano1
· Matteo Losacco1 · Camilla Colombo1 · Pierluigi Di Lizia1
Received: 22 July 2019 / Revised: 21 July 2020 / Accepted: 10 August 2020 / Published online: 27 August 2020 © The Author(s) 2020
Abstract This work introduces two Monte Carlo (MC)-based sampling methods, known as line sampling and subset simulation, to improve the performance of standard MC analyses in the context of asteroid impact risk assessment. Both techniques sample the initial uncertainty region in different ways, with the result of either providing a more accurate estimate of the impact probability or reducing the number of required samples during the simulation with respect to standard MC techniques. The two methods are first described and then applied to some test cases, providing evidence of the increased accuracy or the reduced computational burden with respect to a standard MC simulation. Finally, a sensitivity analysis is carried out to show how parameter setting affects the accuracy of the results and the numerical efficiency of the two methods. Keywords Near-Earth asteroids · Impact probability computation · Monte Carlo simulation · Line sampling · Subset simulation
1 Introduction Earth is subject to frequent impacts by small meteoroids and asteroids (Harris and D’Abramo 2015). Asteroids orbit the Sun along orbits that can allow them to enter the Earth’s neighbourhood (near-Earth asteroids, NEAs), leading to periodic close approaches with our planet with the possibility of impacts on the ground and risks for human activity in space. In parallel, during interplanetary missions, launcher stages and inactive spacecraft are often left into orbits that may come back to the Earth or reach other celestial bodies, with the risk of impacting
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Matteo Romano [email protected] Matteo Losacco [email protected] Camilla Colombo [email protected] Pierluigi Di Lizia [email protected]
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Department of Aerospace Science and Technology, Politecnico di Milano, via La Masa 34, 20156 Milan, Italy
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and contaminating them. For this reason, planetary protection policies set specific requirements to avoid the contamination of celestial bodies due to man-made debris in interplanetary missions, with time periods under study that generally span up to 100 years (Kminek 2012). The estimation and propagation of the orbital state of these objects is therefore of paramount importance. Current approaches for robust detection and prediction of planetary encounters mainly refer to linearised models or full nonlinear orbital sampling. The application of linear methods in the impact plane was introduced by Chodas (1993), whereas the introduction of the Monte Carlo technique to this problem was developed by Yeomans and Chodas (1994) and Chodas and Yeomans (1999), and it is based on the sampling of the linear six-dimensional confidence region of the initial conditions, whose integr
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