Improved Target Prediction Using An IR Imager

D. D. Sworder

doi:10.1117/12.939863

20 September 1987 Improved Target Prediction Using An IR Imager

D. D. Sworder

Proceedings Volume 0750, Infrared Systems and Components; (1987) https://doi.org/10.1117/12.939863
Event: OE LASE'87 and EO Imaging Symposium, 1987, Los Angeles, CA, United States

Abstract

Conventional algorithms for predicting the position of a maneuvering target are based upon the point-mass properties of the target; e.g., the position and velocity of the "center-of-gravity". In addition to providing estimates of these tradi-tional target states, an IR imaging sensor can be used to make inferences regarding the "fine structure" of the target. For example, the orientation of the target with respect to the image plane has a major impact on the perceived tracking dynamics. It follows, therefore, that an algorithm which utilizes orientation information will tend to make smaller mean-square prediction errors than does one which is based upon point-mass states alone. This paper presents a image-based algorithm for predicting the position of an evasive target moving in space or the upper atmosphere where the aerodynamic drag is small. This paper employs a simple stochastic model of acceleration and orientation dynamics to derive a useful prediction algorithm. This prediction has an easily computed form even in the presence of interfeature dependence. The paper concludes with a simple example illustrating the procedures proposed in the paper. The relationship of this approach with a "constant-velocity' extrapolation is made explicit in the example.

Citation Download Citation

D. D. Sworder "Improved Target Prediction Using An IR Imager", Proc. SPIE 0750, Infrared Systems and Components, (20 September 1987); https://doi.org/10.1117/12.939863

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available