Modeling of heavily tailed aliasing distribution for undersampled IRST systems

Robert A. Makl; Hector A. Quevedo

doi:10.1117/12.241174

31 May 1996 Modeling of heavily tailed aliasing distribution for undersampled IRST systems

Robert A. Makl, Hector A. Quevedo

Proceedings Volume 2759, Signal and Data Processing of Small Targets 1996; (1996) https://doi.org/10.1117/12.241174
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

Common module and staring focal plane arrays used in IR search and track applications exhibit inherent under sampling in either one or both spatial dimensions producing signal and clutter aliasing is modeled as a stochastic noise process with a uniformly distributed sample phasing. This paper transcends previous attempts at modeling aliasing by deriving the joint density function of the matched filtered SNR normalized by the density function of the local nose estimate. The resulting probability of detection distribution has been compared with experimental results through simulation. Finally, the use of this probability density function is discussed to further enhance the performance of a multiple hypothesis tracker.

Citation Download Citation

Robert A. Makl and Hector A. Quevedo "Modeling of heavily tailed aliasing distribution for undersampled IRST systems", Proc. SPIE 2759, Signal and Data Processing of Small Targets 1996, (31 May 1996); https://doi.org/10.1117/12.241174

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