Optimized Design for Sparse Arrays in 3-D Imaging Sonar Systems Based on Perturbed Bayesian Compressive Sensing
文献类型：期刊论文
| 作者 | Lin, Zhenwei5; Chen, Yaowu4; Liu, Xuesong3; Jiang, Rongxin2; Shen, Binjian1 ; Xin-Xin Guo1
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| 刊名 | IEEE SENSORS JOURNAL
 |
| 出版日期 | 2020-05-15 |
| 卷号 | 20期号:10页码:5554-5565 |
| 关键词 | Bayesian compressed sensing convex optimization element merging phased array 3-D imaging sonar system position perturbation sparse planar array |
| ISSN号 | 1530-437X |
| DOI | 10.1109/JSEN.2020.2971568 |
| 英文摘要 | Sparse planar array designs significantly reduce the hardware complexity and computational overhead in phased array 3-D imaging sonar systems. Recently, Bayesian compressive sensing (BCS) theory has been applied for synthesizing maximally sparse arrays, in which case, the problem is formulated as a pattern matching technique in a probabilistic fashion. Thus, in this study, a perturbed BCS-based method with a minimum inter-element spacing constraint is proposed. In particular, a modified BCS technique is first employed to synthesize the primary sparse array. Then, the position perturbations of the elements are determined via the first-order Taylor expansion to increase their degrees of freedom (DOFs). The position perturbations allow for continuous element arrangement, which compensates for the imperfection of discrete candidate sample locations. After that, an improved element merging technique combined with convex optimization was adopted to establish constraints on element spacing while mitigating beam pattern degradation. In practice, this is a feasible approach, which merges elements close to each other, leading to a sparser array with a minimum inter-element spacing. Our numerical results confirm the validity of the proposed method in matching accuracy, array sparsity, and constraining the minimum spacing between elements. |
| WOS关键词 | ELEMENTS ; NUMBER |
| 资助项目 | Fundamental Research Funds for the Central Universities ; National Science Foundation for YoungScientists of China[41806115] ; National Key Research and Development on Deep Ocean Technology and System[2016YFC0301604] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA22010203] ; Sanya Special Research and Trial Project[2017KS13] |
| WOS研究方向 | Engineering ; Instruments & Instrumentation ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000528845200051 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Fundamental Research Funds for the Central Universities ; National Science Foundation for YoungScientists of China ; National Key Research and Development on Deep Ocean Technology and System ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Sanya Special Research and Trial Project |
| 源URL | [http://ir.idsse.ac.cn/handle/183446/7616]  |
| 专题 | 深海工程技术部_深海信息技术研究室 |
| 通讯作者 | Chen, Yaowu |
| 作者单位 | 1.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Hainan, Peoples R China 2.Zhejiang Univ, Zhejiang Prov Key Lab Network Multimedia Technol, Hangzhou 310027, Zhejiang, Peoples R China 3.Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China 4.Zhejiang Univ, Engn Res Ctr, Embedded Syst Educ Dept, Hangzhou 310027, Peoples R China 5.Zhejiang Univ, Inst Adv Digital Technol & Instrumentat, Hangzhou 310027, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lin, Zhenwei,Chen, Yaowu,Liu, Xuesong,et al. Optimized Design for Sparse Arrays in 3-D Imaging Sonar Systems Based on Perturbed Bayesian Compressive Sensing[J]. IEEE SENSORS JOURNAL,2020,20(10):5554-5565. |
| APA | Lin, Zhenwei,Chen, Yaowu,Liu, Xuesong,Jiang, Rongxin,Shen, Binjian,&Xin-Xin Guo.(2020).Optimized Design for Sparse Arrays in 3-D Imaging Sonar Systems Based on Perturbed Bayesian Compressive Sensing.IEEE SENSORS JOURNAL,20(10),5554-5565. |
| MLA | Lin, Zhenwei,et al."Optimized Design for Sparse Arrays in 3-D Imaging Sonar Systems Based on Perturbed Bayesian Compressive Sensing".IEEE SENSORS JOURNAL 20.10(2020):5554-5565. |
入库方式： OAI收割
来源：深海科学与工程研究所
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