A reduced sufficient statistics tracking algorithm for infared images

Author

Anderson, Kraig L. ; Iltis, Ronald A.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

Volume

1

fYear

1994

fDate

31 Oct-2 Nov 1994

Firstpage

711

Abstract

The problem of tracking a target using a sequence of infrared (IR) images is addressed. A Bayes-closed estimation algorithm developed by Kulhavy (see International Journal of Adaptive Control and Signal Processing, vol.4, p.271-285, 1990) is shown to be well-suited to the IR tracking problem. Due to the form of the model for the radiation intensity pattern on the IR focal plane array, closed-form expressions are found for the reduced sufficient statistics (RSS) which are used to approximate the true posterior density in the Kulhavy algorithm. An estimate of the target state is then derived via a reconstruction formula from the RSS. For comparison, both a previously developed IR tracking algorithm based on an extended Kalman filter (EKF) and the new RSS-based algorithm are used to track a target through a sequence of IR images. It is shown, that the RSS algorithm can maintain track in high velocity scenarios where the EKF diverges

Keywords

Bayes methods; Kalman filters; filtering theory; focal planes; image sequences; optical tracking; statistical analysis; target tracking; tracking filters; Bayes-closed estimation algorithm; IR focal plane array; IR image sequence; IR tracking; IR tracking algorithm; Kulhavy algorithm; closed-form expressions; extended Kalman filter; high velocity scenarios; infared images; posterior density; radiation intensity pattern; reconstruction formula; reduced sufficient statistics tracking algorithm; target state estimation; Adaptive control; Adaptive signal processing; Array signal processing; Closed-form solution; Image reconstruction; Infrared imaging; Signal processing algorithms; State estimation; Statistics; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-6405-3

Type

conf

DOI

10.1109/ACSSC.1994.471544

Filename

471544