Share Email Print
cover

Proceedings Paper

Multiple sensor estimation using a high-degree cubature information filter
Author(s): Bin Jia; Ming Xin; Khanh Pham; Erik Blasch; Genshe Chen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In this paper, a high-degree cubature information filter (CIF) is proposed for multiple sensor estimation. Astatistical linear error propagation method incorporates the high-degree cubature integration rule into the extended information filtering (EIF) framework such that more accurate estimation can be achieved than the extended information filter as well as the unscented information filter (UIF). In addition, the high-degree CIF maintains close performance to the Gauss-Hermite Quadrature information filter (GHQIF) but uses significantly fewer quadrature points. As a result, the curse of dimensionality problem existing in the tensor product based GHQIF can be greatly alleviated. Besides the improved estimation accuracy and computational efficiency, the high-degree CIF also exhibits the desirable robustness under unknown noise statistics. The proposed CIF is compared with other information filters (e.g., EIF, UIF, GHQIF) via a target tracking problem and demonstrates the best performance.

Paper Details

Date Published: 21 May 2013
PDF: 13 pages
Proc. SPIE 8739, Sensors and Systems for Space Applications VI, 87390T (21 May 2013); doi: 10.1117/12.2015546
Show Author Affiliations
Bin Jia, Intelligent Fusion Technology, Inc. (United States)
Ming Xin, Mississippi State Univ. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Genshe Chen, Intelligent Fusion Technology, Inc. (United States)


Published in SPIE Proceedings Vol. 8739:
Sensors and Systems for Space Applications VI
Khanh D. Pham; Joseph L. Cox; Richard T. Howard; Genshe Chen, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray