9 citations · 12 across the 10 of their papers we have counts for
6 papers · 1 filter
Likelihood Scouting Via Map Inversion For A Posterior-Sampled Particle Filter
Simone Servadio
An exploit of the Sequential Importance Sampling (SIS) algorithm using Differential Algebra (DA) techniques is derived to develop an efficient particle filter. The filter creates a…
Parameters Evolution in Source-Sink Space Population Evolutionary Models
Erin Ashley, Carla Simon Sanz, Simone Servadio +1
MOCAT-SSEM is a Source-Sink model that predicts the Low Earth Orbit (LEO) space population divided into families using a predefined set of interaction parameters. Thanks to data fr…
Propagation of Uncertainty with the Koopman Operator
Simone Servadio, Giovanni Lavezzi, Christian Hofmann +2
This paper proposes a new method to propagate uncertainties undergoing nonlinear dynamics using the Koopman Operator (KO). Probability density functions are propagated directly usi…
Uncertainty Propagation and Filtering via the Koopman Operator in Astrodynamics
Simone Servadio, William Parker, Richard Linares
The Koopman Operator (KO) provides an analytical solution of dynamical systems in terms of orthogonal polynomials. This work exploits this representation to include the propagation…
Threat Level Estimation From Possible Break-Up Events In LEO
Simone Servadio, Daniel Jang, Richard Linares
The NASA Standard Break-Up Model models collisions and explosions in space, which identifies the future distribution of debris. Given a possible break-up event, this work analyses…
A New Monte-Carlo Model for the Space Environment
Daniel Jang, Davide Gusmini, Peng Mun Siew +4
This paper introduces a novel Monte Carlo (MC) method to simulate the evolution of the low-earth orbit environment, enhancing the MIT Orbital Capacity Analysis Tool (MOCAT). In rec…