Detection of constrained signals

Steven E. Johnson

doi:10.1117/12.437050

20 August 2001 Detection of constrained signals

Steven E. Johnson

Proceedings Volume 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII; (2001) https://doi.org/10.1117/12.437050
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

The problem considered in this paper is the detection of targets in a multispectral image. One of the difficulties encountered in this problem is the fact that the abundances of the observed signals are unknown. The generalized likelihood ratio test (GLRT) is often used in detection problems such as this one. The GLRT replaces the unknown parameters, in this case the signal abundances, with maximum likelihood estimates (MLEs) of those parameters. In general, the GLRT is not an optimal test. It is argued that for the signal model in this paper, constrained least squares (CLS) estimates of the unknown parameters are more appropriate than MLEs. A hypothesis test called the constrained multirank signal detector (CMSD) is derived using CLS estimates of the signal abundances. The performance of this test is calculated and is compared to the performance of the GLRT derived for the same signal model.

Citation Download Citation

Steven E. Johnson "Detection of constrained signals", Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); https://doi.org/10.1117/12.437050

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