An unscented Rauch-Tung-Striebel smoother for a bearing only tracking problem

Saifudin Razali, Keigo Watanabe, Shoichi Maeyama, Kiyotaka Izumi

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

10 Citations (Scopus)

Abstract

The unscented Kalman filter (UKF) has become a new technique used in a number of nonlinear estimation problems to overcome the limitation of Taylor series linearization. It uses a deterministic sampling approach known as sigma points to propagate nonlinear systems and has been discussed in many literature. However, a nonlinear smoothing problem has received less attention than the filtering problem. Therefore, in this article we examine an unscented smoother based on Rauch-Tung-Striebel form for discrete-time dynamic systems. This smoother has advantages available in unscented transformation over approximation by Taylor expansion as well as its benefit in derivative free. To evaluate the performance of this smoother, we compare this algorithm with an extended Rauch-Tung-Striebel algorithm through the simulations of a bearing-only tracking problem.

Original languageEnglish
Title of host publicationICCAS 2010 - International Conference on Control, Automation and Systems
Pages1281-1286
Number of pages6
Publication statusPublished - Dec 1 2010
EventInternational Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of
Duration: Oct 27 2010Oct 30 2010

Publication series

NameICCAS 2010 - International Conference on Control, Automation and Systems

Other

OtherInternational Conference on Control, Automation and Systems, ICCAS 2010
CountryKorea, Republic of
CityGyeonggi-do
Period10/27/1010/30/10

Keywords

  • Bearing-only tracking problem
  • Rauch-Tung-Striebel smoother
  • Unscented transformation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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