A tracking algorithm for infrared images based on reduced sufficient statistics

Author

Anderson, Kraig L. ; Iltis, Ronald A.

Author_Institution

Appl. Signal Technol., Sunnyvale, CA, USA

Volume

33

Issue

2

fYear

1997

fDate

4/1/1997 12:00:00 AM

Firstpage

464

Lastpage

472

Abstract

The problem of tracking a target using a sequence of infrared (IR) images is addressed. A Bayes-closed estimation algorithm developed by Kulhavy 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 method 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; focal planes; image sequences; infrared imaging; optical tracking; performance evaluation; state estimation; target tracking; Bayes-closed estimation algorithm; IR focal plane array; IR tracking; Kulhavy; closed-form expressions; extended Kalman filter; high velocity; infrared images; radiation intensity pattern; reconstruction formula; reduced sufficient statistics; sequence of IR images; tracking algorithm; true posterior density; Adaptive estimation; Closed-form solution; Filters; Image reconstruction; Infrared imaging; Optical computing; Pixel; Shape; Size measurement; State estimation; Statistics; Target tracking;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.575884

Filename

575884