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International Journal of Antennas and Propagation
Volume 2016 (2016), Article ID 3592973, 6 pages
http://dx.doi.org/10.1155/2016/3592973
Research Article

Beam Performance Optimization of Multibeam Imaging Sonar Based on the Hybrid Algorithm of Binary Particle Swarm Optimization and Convex Optimization

College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Received 27 January 2016; Revised 8 April 2016; Accepted 27 April 2016

Academic Editor: Sotirios K. Goudos

Copyright © 2016 Weijie Xia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

It should be noted that the peak sidelobe level (PSLL) significantly influences the performance of the multibeam imaging sonar. Although a great amount of work has been done to suppress the PSLL of the array, one can verify that these methods do not provide optimal results when applied to the case of multiple patterns. In order to suppress the PSLL for multibeam imaging sonar array, a hybrid algorithm of binary particle swarm optimization (BPSO) and convex optimization is proposed in this paper. In this algorithm, the PSLL of multiple patterns is taken as the optimization objective. BPSO is considered as a global optimization algorithm to determine best common elements’ positions and convex optimization is considered as a local optimization algorithm to optimize elements’ weights, which guarantees the complete match of the two factors. At last, simulations are carried out to illustrate the effectiveness of the proposed algorithm in this paper. Results show that, for a sparse semicircular array with multiple patterns, the hybrid algorithm can obtain a lower PSLL compared with existing methods and it consumes less calculation time in comparison with other hybrid algorithms.