Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Backscattering enhancement of random discrete scatterers

Not Accessible

Your library or personal account may give you access

Abstract

A recent laboratory-controlled optical experiment demonstrates that a sharp peak of small but finite angular width is exhibited in backscattering from a random distribution of discrete scatterers. In this paper the phenomenon is explained by using a second-order multiple-scattering theory of discrete particles. The theory gives an angular width of the order of the attenuation rate divided by the wave number and is in agreement with experimental observations. The relations of the present results to past theories on backscattering enhancements are also discussed.

© 1984 Optical Society of America

Full Article  |  PDF Article
More Like This
Backscattering enhancement of random discrete scatters of moderate sizes

Akira Ishimaru and Leung Tsang
J. Opt. Soc. Am. A 5(2) 228-236 (1988)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (3)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (27)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.