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题名: Synthesis of Sparse Linear Array with Multiple Patterns Based on Joint Sparse Recovery
作者: Zhao, Xiaowen; null(杨青山); Yunhua Zhang(张云华); Yunhua Zhang(张云华)
作者部门: 微波遥感部
通讯作者: Zhao, XW (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, CAS Key Lab Microwave Remote Sensing, Beijing, Peoples R China.
会议名称: International Symposium of IEEE-Antennas-and-Propagation-Society / USNC/URSI National Radio Science Meeting
会议日期: JUL 09-14, 2017
会议地点: San Diego, CA
会议录: 2017 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION & USNC/URSI NATIONAL RADIO SCIENCE MEETING
出版日期: 2017
收录类别: EI ; CPCI
页码: 425-426
ISSN号: 1522-3965
ISBN号: 978-1-5386-3284-0
关键词: sparse array synthesis ; multi patterns ; joint sparse recovery ; convex optimization ; compressed sensing
英文摘要: An innovative methodology based on joint sparse recovery is proposed for sparse linear array synthesis using a minimum number of elements to generate multiple patterns with different shapes. The synthesis is formulated as a convex problem with the minimization of mixed l(2)/l(1)-norm in terms of the joint sparse recovery in Compressed Sensing. Then convex optimization is properly adopted to solve the above problem efficiently. The proposed method can perform a complete optimization on the number of elements, the common element positions as well as the individual element excitations for all desired patterns simultaneously. Preliminary results are presented to show the effectiveness and flexibility of the proposed method in achieving a sparse linear array including focused, cosec-squared and flat-topped beams.
语种: 英语
内容类型: 会议论文
URI标识: http://ir.nssc.ac.cn/handle/122/6226
Appears in Collections:微波遥感部_会议论文

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