DOA Estimation Using Random Linear Arrays Via Compressive Sensing

被引：8
|
作者：
Pazos, S. [1 ,2 ]
Hurtado, M. [1 ,2 ]
Muravchik, C. H. [3 ,4 ]
机构：
[1] UNLP, LEICI Inst Invest Elect Control & Proc Senales LE, La Plata, Buenos Aires, Argentina
[2] Consejo Nacl Invest Cient & Tecn, RA-1033 Buenos Aires, DF, Argentina
[3] UNLP, LEICI IIECPS, La Plata, Buenos Aires, Argentina
[4] CIC PBA, La Plata, Buenos Aires, Argentina
来源：
IEEE LATIN AMERICA TRANSACTIONS | 2014年 / 12卷 / 05期
关键词：
DOA estimation; Random Linear Arrays; Sparse models; Compressive Sensing; SPARSE SIGNAL RECONSTRUCTION; RANDOM SENSOR ARRAYS; PURSUIT; RECOVERY;
D O I：
10.1109/TLA.2014.6872896
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this article we analyze the performance of nonuniform linear arrays for Direction of Arrival (DOA) estimation. We use different classes of sparse recovery algorithms to estimate the direction of arrival of the signal sources and its information. We focus on three array configurations, a structured or virtual array with prefixed potential locations for the elements, a random array and a random array with a restriction on the minimum distance between elements. We provide simulations of the performance of each configuration under these algorithms for different values of aperture, and number of signal sources.
引用
收藏
页码：859 / 863
页数：5
相关论文
共 50 条
  • [1] MUSIC DOA ESTIMATION WITH COMPRESSIVE SENSING AND/OR COMPRESSIVE ARRAYS
    Jouny, Ismail
    [J]. 2011 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION (APSURSI), 2011, : 2016 - 2019
  • [2] Analysis on the DOA estimation of uniform circular arrays based on compressive sensing
    Electronic Engineering College, Naval University of Engineering, Wuhan
    430033, China
    [J]. Tongxin Xuebao, 2
  • [3] Fast Compressive Sensing DOA Estimation Via ADMM Solver
    Wang, Qianli
    Zhao, Zhiqin
    Chen, Zhuming
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (IEEE ICIA 2017), 2017, : 53 - 57
  • [4] DOA Using Uniform/Nonuniform Linear and Uniform Circular Antenna Arrays with Bayesian Compressive Sensing
    Jouny, Ismail
    [J]. 2017 IEEE 8TH ANNUAL UBIQUITOUS COMPUTING, ELECTRONICS AND MOBILE COMMUNICATION CONFERENCE (UEMCON), 2017, : 158 - 161
  • [5] Three-Level Prime Arrays with Compressed Subarray for DOA Estimation Using Compressive Sensing
    Alawsh, Saleh A.
    Muciaibel, Ali H.
    [J]. 2019 2ND IEEE MIDDLE EAST AND NORTH AFRICA COMMUNICATIONS CONFERENCE (IEEEMENACOMM'19), 2019, : 102 - 106
  • [6] Digital Beam Forming and Compressive Sensing Based DOA Estimation in MIMO Arrays
    Belfiori, Francesco
    Anitori, Laura
    van Rossum, Wim
    Otten, Matern
    Hoogeboom, Peter
    [J]. 2011 8TH EUROPEAN RADAR CONFERENCE, 2011, : 285 - 288
  • [7] High-Resolution DOA Estimation Using Compressive Sensing with Deterministic Sensing Matrices and Compact Generalized Coprime Arrays
    El-Khamy, Said E.
    El-Shazly, Ahmed M.
    Eltrass, Ahmed S.
    [J]. 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 2021,
  • [8] Aperiodic geometry design for DOA estimation using compressive sensing
    Asghar, Sayed Zeeshan
    Ng, Boon Poh
    [J]. 2015 INTERNATIONAL CONFERENCE ON SAMPLING THEORY AND APPLICATIONS (SAMPTA), 2015, : 503 - 507
  • [9] Bayesian Compressive Sensing for DOA Estimation using the Difference Coarray
    Wang, Xiangrong
    Amin, Moeness G.
    Ahmad, Fauzia
    Aboutanios, Elias
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 2384 - 2388
  • [10] Compressive Sensing Approach for DOA Estimation Based on Sparse Arrays in the Presence of Mutual Coupling
    Zhang, Jian
    Duan, Zhenzhen
    Zhang, Yang
    Liang, Jing
    [J]. COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL II: SIGNAL PROCESSING, 2020, 516 : 1269 - 1277
12345