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CLC number: TB56

On-line Access: 2010-03-22

Received: 2009-01-15

Revision Accepted: 2009-04-27

Crosschecked: 2009-11-30

Cited: 17

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.4 P.261-269


Optimized simulated annealing algorithm for thinning and weighting large planar arrays

Author(s):  Peng Chen, Bin-jian Shen, Li-sheng Zhou, Yao-wu Chen

Affiliation(s):  Institute of Advanced Digital Technologies and Instrumentation, Zhejiang University, Hangzhou 310027, China, Hangzhou Applied Acoustics Research Institute, Hangzhou 310012, China

Corresponding email(s):   chenpeng123@zju.edu.cn, cyw@mail.bme.zju.edu.cn

Key Words:  Simulated annealing (SA), Sparse planar arrays, 3D underwater sonar imaging, Beam pattern, Optimization

Peng Chen, Bin-jian Shen, Li-sheng Zhou, Yao-wu Chen. Optimized simulated annealing algorithm for thinning and weighting large planar arrays[J]. Journal of Zhejiang University Science C, 2010, 11(4): 261-269.

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%T Optimized simulated annealing algorithm for thinning and weighting large planar arrays
%A Peng Chen
%A Bin-jian Shen
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910037

T1 - Optimized simulated annealing algorithm for thinning and weighting large planar arrays
A1 - Peng Chen
A1 - Bin-jian Shen
A1 - Li-sheng Zhou
A1 - Yao-wu Chen
J0 - Journal of Zhejiang University Science C
VL - 11
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SP - 261
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910037

This paper proposes an optimized simulated annealing (SA) algorithm for thinning and weighting large planar arrays in 3D underwater sonar imaging systems. The optimized algorithm has been developed for use in designing a 2D planar array (a rectangular grid with a circular boundary) with a fixed side-lobe peak and a fixed current taper ratio under a narrow-band excitation. Four extensions of the SA algorithm and the procedure for the optimized SA algorithm are described. Two examples of planar arrays are used to assess the efficiency of the optimized method. The proposed method achieves a similar beam pattern performance with fewer active transducers and faster convergence ability than previous SA algorithms.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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