Irregular Subarray Design Strategy Based on Weighted L1 Norm Iterative Convex Optimization

被引:10
|
作者
Chen Jiyuan [1 ]
Xu, Zhen-Hai [1 ]
Xiao Shunping [1 ]
机构
[1] Natl Univ Def Technol, Coll Eletron Sci & Technol, Changsha 410073, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Convex functions; Optimization; Mathematical models; Apertures; Dictionaries; Brain modeling; Convergence; Irregular subarray; subarray tiling; weighted L1 norm; PHASED-ARRAYS;
D O I
10.1109/LAWP.2021.3132001
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Subarray technology is an effective tradeoff between the sensor array radiation performance and manufacturing cost control. This letter proposes an irregular subarray tiling strategy based on the weighted L1 norm iterative convex optimization (WL1X) method. We first establish a subarray partition model and solve the L0 norm constraint problem by weighted L1 norm iterative convex optimization and then the optimal solution is selected based on the radiation performance. Further, We adopt a good initial point for the local optimization to improve scheme acquisition and selection efficiency. The proposed method can quickly obtain a subarray partition structure with better performance. The effectiveness and potential of the proposed methods are verified by various numerical examples.
引用
收藏
页码:376 / 380
页数:5
相关论文
共 50 条
  • [1] Sparse Array Synthesis Based on Iterative Weighted L1 Norm
    Tu, Guangpeng
    Chen, Ence
    [J]. 2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PROBLEM-SOLVING (ICCP), 2013, : 238 - 240
  • [2] Iterative Weighted l1 Optimization for Compressed Sensing and Coding
    Khajehnejad, M. Amin
    Dimakis, Alexandros G.
    Hassibi, Babak
    [J]. 2010 CONFERENCE RECORD OF THE FORTY FOURTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS (ASILOMAR), 2010, : 768 - 774
  • [3] Bi-ISAR imaging based on weighted l1 norm optimization algorithm
    Xue, Dongfang
    Zhu, Xiaoxiu
    Hu, Wenhua
    Guo, Baofeng
    Zeng, Huiyan
    [J]. Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2021, 43 (04): : 944 - 953
  • [4] Hyperspectral unmixing based on iterative weighted L1 regularization
    Wu, Ze-Bin
    Wei, Zhi-Hui
    Sun, Le
    Liu, Jian-Jun
    [J]. Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology, 2011, 35 (04): : 431 - 435
  • [5] Contrast preserving decolorization based on the weighted normalized L1 norm
    Jing Yu
    Fang Li
    Xiaoguang Lv
    [J]. Multimedia Tools and Applications, 2021, 80 : 31753 - 31782
  • [6] Contrast preserving decolorization based on the weighted normalized L1 norm
    Yu, Jing
    Li, Fang
    Lv, Xiaoguang
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (21-23) : 31753 - 31782
  • [7] Weighted Isotonic Regression under the L1 Norm
    Angelov, Stanislav
    Harb, Boulos
    Kannan, Sampath
    Wang, Li-San
    [J]. PROCEEDINGS OF THE SEVENTHEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, 2006, : 783 - +
  • [8] Joint Optimization of Domino Subarray Tiling and Generalized Directivity Based on Iterative Convex Relaxation
    Pu, Shangqing
    Dong, Wei
    Xu, Zhenhai
    Zeng, Hui
    Yang, Gongqing
    [J]. IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, 2024, 23 (02): : 483 - 487
  • [9] Adaptive Convolutional Sparse Coding with Weighted l1 Norm
    Qiu, Jiale
    Yang, Min
    [J]. PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 7746 - 7750
  • [10] l1 norm of coherence is not equal to its convex roof quantifier
    Xu, Jianwei
    [J]. JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2022, 55 (14)