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 -