most citedLikelihood Scouting Via Map Inversion For A Posterior-Sampled Particle Filter

9 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IT20249 cited

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…

stat.AP20241 cited

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…

cs.CV20241 cited

Markers Identification for Relative Pose Estimation of an Uncooperative Target

Batu Candan, Simone Servadio

This paper introduces a novel method using chaser spacecraft image processing and Convolutional Neural Networks (CNNs) to detect structural markers on the European Space Agency's (…

cs.IT2024

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…

cs.IT2024

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…

astro-ph.EP2024

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…