TY - GEN

T1 - Nonlinear sequential methods for impact probability estimation

AU - Linares, Richard

AU - Singla, Puneet

AU - Crassidis, John L.

N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.

PY - 2010

Y1 - 2010

N2 - Orbit determination in application to the estimation of impact probability has the goal of determining the evolution of the state probability density function (pdf) and determining a measure of the probability of collision. Nonlinear gravitational interaction and non-conservative forces can make the pdf far from Gaussian. This work implements three nonlinear sequential estimators: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF) and the Particle Filter (PF) to estimate the impact probability. Both the EKF and the UKF make the Gaussian assumption and this work investigates the effect of this approximation on the impact probability calculation, while the PF can work for non-Gaussian systems.

AB - Orbit determination in application to the estimation of impact probability has the goal of determining the evolution of the state probability density function (pdf) and determining a measure of the probability of collision. Nonlinear gravitational interaction and non-conservative forces can make the pdf far from Gaussian. This work implements three nonlinear sequential estimators: the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF) and the Particle Filter (PF) to estimate the impact probability. Both the EKF and the UKF make the Gaussian assumption and this work investigates the effect of this approximation on the impact probability calculation, while the PF can work for non-Gaussian systems.

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M3 - Conference contribution

AN - SCOPUS:80053395316

SN - 9780877035602

T3 - Advances in the Astronautical Sciences

SP - 787

EP - 806

BT - Spaceflight Mechanics 2010 - Advances in the Astronautical Sciences

T2 - AAS/AIAA Space Flight Mechanics Meeting

Y2 - 14 February 2010 through 17 February 2010

ER -