Target identification for stripmap- and spotlight-mode SARs using physics-based signatures

Chen-Pang Yeang; Jeffrey H. Shapiro

doi:10.1117/12.357690

13 August 1999 Target identification for stripmap- and spotlight-mode SARs using physics-based signatures

Chen-Pang Yeang, Jeffrey H. Shapiro

Proceedings Volume 3721, Algorithms for Synthetic Aperture Radar Imagery VI; (1999) https://doi.org/10.1117/12.357690
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

A physics-based target detection theory is developed for spotlight-mode operation of a synthetic aperture radar (SAR). The target return and clutter return models are constructed from electromagnetic scattering theory. A polar-format Fourier-transform processor for spotlight-mode SAR images with adjustable processing durations, and a Neyman-Pearson optimum whitening-filter processor for single-component targets are considered. Detection performance for these spotlight-mode SAR processors are compared with those for corresponding stripmap- mode SAR processors. Target detection theory for multi- component targets is also developed. For two conditions -- unknown component phases, and unknown component phases with uncertain component positions -- we develop likelihood-based detectors and numerically evaluate the associated receiver operating characteristics.

Citation Download Citation

Chen-Pang Yeang and Jeffrey H. Shapiro "Target identification for stripmap- and spotlight-mode SARs using physics-based signatures", Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); https://doi.org/10.1117/12.357690

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