General Polynomial Factorization-Based Design of Sparse Periodic Linear Arrays

被引:32
|
作者
Mitra, Sanjit K. [1 ]
Mondal, Kalyan [2 ]
Tchobanou, Mikhail K. [3 ]
Dolecek, Gordana Jovanovic [4 ]
机构
[1] Univ So Calif, Dept Elect Engn, Los Angeles, CA 90089 USA
[2] Fairleigh Dickinson Univ, Gildart Haase Sch Comp Sci & Engn, Teaneck, NJ USA
[3] Tech Univ, Moscow Power Engn Inst, Dept Phys Elect, Moscow, Russia
[4] Inst Nacl Astrofis Opt & Electr, Dept Elect, Puebla, Mexico
关键词
PHASED-ARRAY; SIDELOBE;
D O I
10.1109/TUFFC.2010.1643
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
We have developed several methods of designing sparse periodic arrays based upon the polynomial factorization method. In these methods, transmit and receive aperture polynomials are selected such that their product results in a polynomial representing the desired combined transmit/receive (T/R) effective aperture function. A desired combined T/R effective aperture is simply an aperture with an appropriate width exhibiting a spectrum that corresponds to the desired two-way radiation pattern. At least one of the two aperture functions that constitute the combined T/R effective aperture function will be a sparse polynomial. A measure of sparsity of the designed array is defined in terms of the element reduction factor. We show that elements of a linear array can be reduced with varying degrees of beam mainlobe width to sidelobe reduction properties.
引用
收藏
页码:1952 / 1966
页数:15
相关论文
共 50 条
  • [41] A grid-based multilevel incomplete LU factorization preconditioning technique for general sparse matrices
    Zhang, J
    APPLIED MATHEMATICS AND COMPUTATION, 2001, 124 (01) : 95 - 115
  • [42] A method to design an optimum pair of transmit and receive periodic sparse arrays - art. no. 692011
    Kim, Gi-Duck
    Song, Tai-Kyong
    MEDICAL IMAGING 2008: ULTRASONIC IMAGING AND SIGNAL PROCESSING, 2008, 6920 : 92011 - 92011
  • [43] 2-D DOA Estimation Based on Sparse Linear Arrays Exploiting Arbitrary Linear Motion
    Zhang, Zexiang
    Shen, Qing
    Liu, Wei
    Cui, Wei
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 73 (09) : 13248 - 13262
  • [44] The Design of A Novel Sparse Array Using Two Uniform Linear Arrays considering Mutual Coupling
    Xu, Haiyun
    Cui, Weijia
    Mei, Fengtong
    Ba, Bin
    Jian, Chunxiao
    JOURNAL OF SENSORS, 2021, 2021
  • [45] DOA estimation based on smoothed sparse reconstruction with time-modulated linear arrays
    Yin, Yongtai
    Wang, Yuexian
    Dai, Tiantian
    Wang, Ling
    SIGNAL PROCESSING, 2024, 214
  • [46] Single-Shot CNN-Based Ultrasound Imaging with Sparse Linear Arrays
    Perdios, Dimitris
    Vonlanthen, Manuel
    Martinez, Florian
    Arditi, Marcel
    Thiran, Jean-Philippe
    PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IUS), 2020,
  • [47] Sparse General Non-Negative Matrix Factorization Based on Left Semi-Tensor Product
    Chen, Zigang
    Li, Lixiang
    Peng, Haipeng
    Liu, Yuhong
    Zhu, Haihua
    Yang, Yixian
    IEEE ACCESS, 2019, 7 : 81599 - 81611
  • [48] A CS-Based Strategy For the Design of Shaped-Beam Sparse Arrays
    Carlin, M.
    Oliveri, G.
    Massa, Andrea
    2011 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION (APSURSI), 2011, : 1996 - 1999
  • [49] Design of pattern reconfigurable sparse arrays based on multi-task learning
    School of Information and Navigation, Air Force Engineering University, Xi'an
    710077, China
    不详
    100191, China
    Xi Tong Cheng Yu Dian Zi Ji Shu/Syst Eng Electron, 12 (2669-2676): : 2669 - 2676
  • [50] Reliability-based design optimization by adaptive-sparse polynomial dimensional decomposition
    Ren, Xuchun
    Yadav, Vaibhav
    Rahman, Sharif
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2016, 53 (03) : 425 - 452