A class of stable square-root nonlinear information filters

Shiyuan Wang, Jiuchao Feng, Chi Kong Tse

Research output: Journal article publicationJournal articleAcademic researchpeer-review

31 Citations (Scopus)


Information filters can process nonlinear systems with uncertain prior knowledge, and the particular square-root form of adaptive filters can improve numerical stability. Based on a square-root decomposition of information matrix and an extra positive definite matrix, the unscented transform and the cubature rule are applied to the information filtering architecture for nonlinear estimation. A class of stable square-root nonlinear information filters is then proposed in this technical note. In addition, the boundedness of their estimation errors is also proven. Results from simulations of filtering a chaotic map demonstrate that the proposed square-root nonlinear filters can improve numerical stability, and has better filtering performance than other information filters.
Original languageEnglish
Article number6681929
Pages (from-to)1893-1898
Number of pages6
JournalIEEE Transactions on Automatic Control
Issue number7
Publication statusPublished - 1 Jan 2014


  • Nonlinear estimation
  • nonlinear information filter
  • numerical stability
  • square-root decomposition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'A class of stable square-root nonlinear information filters'. Together they form a unique fingerprint.

Cite this