Nonlinear sequential methods for impact probability estimation

Richard Linares, Puneet Singla, John L. Crassidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationSpaceflight Mechanics 2010 - Advances in the Astronautical Sciences
Subtitle of host publicationProceedings of the AAS/AIAA Space Flight Mechanics Meeting
Pages787-806
Number of pages20
StatePublished - Dec 1 2010
EventAAS/AIAA Space Flight Mechanics Meeting - San Diego, CA, United States
Duration: Feb 14 2010Feb 17 2010

Publication series

NameAdvances in the Astronautical Sciences
Volume136
ISSN (Print)0065-3438

Other

OtherAAS/AIAA Space Flight Mechanics Meeting
CountryUnited States
CitySan Diego, CA
Period2/14/102/17/10

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

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    Linares, R., Singla, P., & Crassidis, J. L. (2010). Nonlinear sequential methods for impact probability estimation. In Spaceflight Mechanics 2010 - Advances in the Astronautical Sciences: Proceedings of the AAS/AIAA Space Flight Mechanics Meeting (pp. 787-806). (Advances in the Astronautical Sciences; Vol. 136).