A butterfly algorithm for synthetic aperture radar

Laurent Demanet; Matthew Ferrara; Nicholas Maxwell; Jack Poulson; Lexing Ying

doi:10.1117/12.888948

4 May 2011 A butterfly algorithm for synthetic aperture radar

Laurent Demanet, Matthew Ferrara, Nicholas Maxwell, Jack Poulson, Lexing Ying

Proceedings Volume 8051, Algorithms for Synthetic Aperture Radar Imagery XVIII; 805105 (2011) https://doi.org/10.1117/12.888948
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

It is not currently known if it is possible to accurately form a synthetic aperture radar image from N data points in provable near-linear complexity, where accuracy is defined as the ℓ₂ error between the full O(N²) backprojection image and the approximate image. To bridge this gap, we present a backprojection algorithm with complexity O(log(1/ε)N log N), with ε the tunable pixelwise accuracy. It is based on the butterfly scheme, which works for vastly more general oscillatory integrals than the discrete Fourier transform. Unlike previous methods this algorithm allows the user to directly choose the amount of acceptable image error based on a well-defined metric. Additionally, the algorithm does not invoke the far-field approximation or place restrictions on the antenna flight path, nor does it impose the frequency-independent beampattern approximation required by time-domain backprojection techniques.

Citation Download Citation

Laurent Demanet, Matthew Ferrara, Nicholas Maxwell, Jack Poulson, and Lexing Ying "A butterfly algorithm for synthetic aperture radar", Proc. SPIE 8051, Algorithms for Synthetic Aperture Radar Imagery XVIII, 805105 (4 May 2011); https://doi.org/10.1117/12.888948

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