Design of sparse linear arrays by Monte Carlo importance sampling
Date of Original Version
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
Kay, Steven. "Design of sparse linear arrays by Monte Carlo importance sampling." IEEE Journal of Oceanic Engineering 27, 4 (2002): 790-799. doi: 10.1109/JOE.2002.804325.