Design of sparse linear arrays by Monte Carlo importance sampling

Authors

Steven Kay, University of Rhode Island

Document Type

Conference Proceeding

Date of Original Version

12-1-2000

Abstract

The formation of acoustic images in real-time requires an enormous computational burden. To alleviate this demand the use of sparse arrays for beamforming is mandated. The design of these arrays for adequate main-lobe 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 the optimization method is presented and some examples given to illustrate its effectiveness.

Publication Title, e.g., Journal

Oceans Conference Record (IEEE)

Volume

3

Citation/Publisher Attribution

Kay, Steven. "Design of sparse linear arrays by Monte Carlo importance sampling." Oceans Conference Record (IEEE) 3, (2000): 1501-1507. doi: 10.1109/JOE.2002.804325.