By Topic

Design of sparse linear arrays by Monte Carlo importance sampling

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kay, S. ; Dept. of Electr. & Comput. Eng., Rhode Island Univ., Kingston, RI, USA ; Saha, S.

The formation of acoustic images in real-time requires an enormous computational burden. To reduce this demand the use of sparse arrays for beamforming is mandated. The design of these arrays for adequate mainlobe width and low sidelobe level is a difficult nonlinear optimization problem. A new approach to the joint optimization of sensor placement and shading weights is discussed. Based on the concept of importance sampling an optimization method is presented and some examples given to illustrate its effectiveness.

Published in:

Oceanic Engineering, IEEE Journal of  (Volume:27 ,  Issue: 4 )