Fast Monostatic Scattering Analysis Based on Bayesian Compressive Sensing

被引:0
|
作者
Zhang, Huan-Huan [1 ]
Zhao, Xun-Wang [1 ]
Lin, Zhong-Chao [1 ]
Sha, Wei E. I. [2 ]
机构
[1] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
[2] Univ Hong Kong, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China
来源
APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL | 2016年 / 31卷 / 11期
关键词
Bayesian compressive sensing; method of moments; monostatic; scattering; FAST-MULTIPOLE ALGORITHM; ELECTROMAGNETIC SCATTERING; INTEGRAL-EQUATIONS; MOMENTS; SOLVER;
D O I
暂无
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
The Bayesian compressive sensing algorithm is utilized together with the method of moments to fast analyze the monostatic electromagnetic scattering problem. Different from the traditional compressive sensing based fast monostatic scattering analysis method which cannot determine the required measurement times, the proposed method adopts the Bayesian framework to recover the underlying signal. Error bars of the signal can be obtained in the recovery procedure, which provides a means to adaptively determine the number of compressive-sensing measurements. Numerical results are given to demonstrate the accuracy and effectiveness of proposed method.
引用
收藏
页码:1279 / 1285
页数:7
相关论文
共 50 条
  • [21] Parallel Wavelet-based Bayesian Compressive Sensing based on Gibbs Sampling
    Zhou, Jian
    Chakrabarti, Chaitali
    PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING SYSTEMS (SIPS), 2018, : 140 - 145
  • [22] Adaptive Step Size Selection based Bayesian Compressive Spectrum Sensing
    Sun, Xuekang
    Zhou, Rikang
    Zhang, Nuoya
    Gao, Li
    2017 INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATION SYSTEMS (ISWCS), 2017, : 96 - 100
  • [23] A Novel Reconstruction Algorithm for Bioluminescent Tomography Based on Bayesian Compressive Sensing
    Wang, Yaqi
    Feng, Jinchao
    Jia, Kebin
    Sun, Zhonghua
    Wei, Huijun
    MEDICAL IMAGING 2016-BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING, 2016, 9788
  • [24] Adaptive Compressed Sampling Method for Fast Comuatation of Monostatic Scattering
    Liu, Zhiwei
    Zhang, Yueyuan
    Zhang, Xiaoyan
    PIERS 2012 MOSCOW: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2012, : 729 - 732
  • [25] RBM Based Cooperative Bayesian Compressive Spectrum Sensing with Adaptive Threshold
    Sun, Xuekang
    Gao, Li
    Luo, Xudong
    Su, Kun
    2016 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), 2016,
  • [26] Tree-Structured Bayesian Compressive Sensing based Image Watermarking
    Li, Xiumei
    Bai, Huang
    Sun, Junmei
    ELEVENTH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING SYSTEMS, 2019, 11384
  • [27] Bayesian compressive sensing using wavelet based Markov random fields
    Torkamani, Razieh
    Sadeghzadeh, Ramazan Ali
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2017, 58 : 65 - 72
  • [28] Dual-Layer Compressive Sensing Scheme Incorporating Adaptive Cross Approximation Algorithm for Solving Monostatic Electromagnetic Scattering Problems
    Gao, Yalan
    Akbar, Muhammad Firdaus
    Jawad, Ghassan Nihad
    Cui, Lin
    IEEE ACCESS, 2024, 12 : 97572 - 97580
  • [29] Randomised orthogonal matching pursuit algorithm with its application in fast analysis of wide-angle electromagnetic scattering problems based on compressive sensing
    Qi, Qi
    Fan, Yunuo
    Cao, Xinyuan
    Liu, Yi
    Kong, Meng
    Huang, Zhixiang
    Wu, Xianliang
    IET MICROWAVES ANTENNAS & PROPAGATION, 2024, 18 (09) : 646 - 653
  • [30] Autofocus Bayesian Compressive Sensing for Multipath Exploitation in Urban Sensing
    Wu, Qisong
    Zhang, Yimin D.
    Amin, Moeness G.
    Ahmad, Fauzia
    2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2015, : 80 - 84