Design of sparse linear arrays by Monte Carlo importance sampling

Document Type

Article

Date of Original Version

10-1-2002

Abstract

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.

Publication Title, e.g., Journal

IEEE Journal of Oceanic Engineering

Volume

27

Issue

4

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