A high order filter for estimation of nonlinear dynamic systems

Taewook Lee, Puneet Singla, Manoranjan Majji

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


In this paper, a high order filter is presented for estimation of nonlinear dynamic systems. The proposed filter computes higher order moment update equations in a Jacobian free manner and a computationally attractive manner. Compared to the conventional filters such as the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), the proposed filter captures desired order of statistical moments by making use of the higher order state transition matrices developed in our previous works, providing more accurate estimates through sparse measurements. The connection between the conventional high order method, the higher order state transition matrices and the proposed filter is discussed. Orbit estimation problem is considered to demonstrate the numerical efficiency and accuracy of the proposed filter.

Original languageEnglish (US)
Title of host publicationAAS/AIAA Astrodynamics Specialist Conference, 2018
EditorsPuneet Singla, Ryan M. Weisman, Belinda G. Marchand, Brandon A. Jones
PublisherUnivelt Inc.
Number of pages21
ISBN (Print)9780877036579
StatePublished - 2018
EventAAS/AIAA Astrodynamics Specialist Conference, 2018 - Snowbird, United States
Duration: Aug 19 2018Aug 23 2018

Publication series

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


ConferenceAAS/AIAA Astrodynamics Specialist Conference, 2018
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science


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