IEICE TRANSACTIONS on Communications
Pattern Synthesis of Sparse Linear Arrays Using Spider Monkey Optimization
Summary :
This paper introduces and uses spider monkey optimization (SMO) for synthesis sparse linear arrays, which are composed of a uniformly spaced core subarray and an extended sparse subarray. The amplitudes of all the elements and the locations of elements in the extended sparse subarray are optimized by the SMO algorithm to reduce the side lobe levels of the whole array, under a set of practical constraints. To show the efficiency of SMO, different examples are presented and solved. Simulation results of the sparse arrays designed by SMO are compared with published results to verify the effectiveness of the SMO method.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E100-B No.3 pp.426-432
- Publication Date
- 2017/03/01
- Publicized
- 2016/10/06
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2016EBP3203
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Huaning WU
University of Engineering
Yalong YAN
University of Engineering
Chao LIU
University of Engineering
Jing ZHANG
University of Engineering
Keyword
Latest Issue
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Huaning WU, Yalong YAN, Chao LIU, Jing ZHANG, "Pattern Synthesis of Sparse Linear Arrays Using Spider Monkey Optimization" in IEICE TRANSACTIONS on Communications,
vol. E100-B, no. 3, pp. 426-432, March 2017, doi: 10.1587/transcom.2016EBP3203.
Abstract: This paper introduces and uses spider monkey optimization (SMO) for synthesis sparse linear arrays, which are composed of a uniformly spaced core subarray and an extended sparse subarray. The amplitudes of all the elements and the locations of elements in the extended sparse subarray are optimized by the SMO algorithm to reduce the side lobe levels of the whole array, under a set of practical constraints. To show the efficiency of SMO, different examples are presented and solved. Simulation results of the sparse arrays designed by SMO are compared with published results to verify the effectiveness of the SMO method.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2016EBP3203/_p
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@ARTICLE{e100-b_3_426,
author={Huaning WU, Yalong YAN, Chao LIU, Jing ZHANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Pattern Synthesis of Sparse Linear Arrays Using Spider Monkey Optimization},
year={2017},
volume={E100-B},
number={3},
pages={426-432},
abstract={This paper introduces and uses spider monkey optimization (SMO) for synthesis sparse linear arrays, which are composed of a uniformly spaced core subarray and an extended sparse subarray. The amplitudes of all the elements and the locations of elements in the extended sparse subarray are optimized by the SMO algorithm to reduce the side lobe levels of the whole array, under a set of practical constraints. To show the efficiency of SMO, different examples are presented and solved. Simulation results of the sparse arrays designed by SMO are compared with published results to verify the effectiveness of the SMO method.},
keywords={},
doi={10.1587/transcom.2016EBP3203},
ISSN={1745-1345},
month={March},}
Copy
TY - JOUR
TI - Pattern Synthesis of Sparse Linear Arrays Using Spider Monkey Optimization
T2 - IEICE TRANSACTIONS on Communications
SP - 426
EP - 432
AU - Huaning WU
AU - Yalong YAN
AU - Chao LIU
AU - Jing ZHANG
PY - 2017
DO - 10.1587/transcom.2016EBP3203
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E100-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2017
AB - This paper introduces and uses spider monkey optimization (SMO) for synthesis sparse linear arrays, which are composed of a uniformly spaced core subarray and an extended sparse subarray. The amplitudes of all the elements and the locations of elements in the extended sparse subarray are optimized by the SMO algorithm to reduce the side lobe levels of the whole array, under a set of practical constraints. To show the efficiency of SMO, different examples are presented and solved. Simulation results of the sparse arrays designed by SMO are compared with published results to verify the effectiveness of the SMO method.
ER -
English
