NDLI: Analyzing electromagnetic scattering using characteristic basis function method with compressed sensing

Content Provider	IEEE Xplore Digital Library
Author	Quan-Quan Wang Tao Jin Hong-Bo Zhu Ru-Shan Chen
Copyright Year	2013
Description	Author affiliation: Dept. of Commun. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China (Ru-Shan Chen) \|\| Dept. of Commun. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China (Quan-Quan Wang; Tao Jin; Hong-Bo Zhu)
Abstract	In this paper, the efficient analysis of electromagnetic scattering from objects is performed utilizing the characteristic basis function method (CBFM) with the compressed sensing (CS) technique. CBFM generates sets of high-level basis functions, i.e. the characteristic basis function (CBF), defined over macro domains of the object under discussion, to significantly reduce the matrix size and storage and make the reduced linear system easily manageable and solvable. In the conventional fulfillment, to generate the CBF, a series of matrix equations need to be solved repeatedly with various excitations of multiple incident angles and different polarizations. With the help of CS, much fewer excitations are necessary to solve the matrix equations, and one can obtain the measurements of the induced currents accordingly. Finally, the orthogonal matching pursuit (OMP) method is used to reconstruct the real induced currents and from which the CBF is generated. Numerical examples are included to demonstrate the performance of the proposed method.
Sponsorship	IEEE Eng.Med. Biol. Soc.
Starting Page	1633
Ending Page	1637
File Size	277697
Page Count	5
File Format	PDF
e-ISBN	9781479927647
DOI	10.1109/CISP.2013.6743938
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	compressed sensing Electromagnetic scattering Integral equations Matching pursuit algorithms Educational institutions Antennas Compressed sensing Equations characteristic basis function method electromagnetic scattering
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Compressed sensing based on FE-BI for solving electromagnetic scattering problems

Use of Compressed Sensing in analysis of electric field integral equation by the Method of Moments

Sparse basis expansions for compressive sensing of electromagnetic scattering patterns computed using iterative physical optics

An efficient algorithm for electromagnetic scattering analysis using curve RWG basis function and adaptively modified characteristic basis function method

A new method combining compressive sensing and method of moments for bistatic scattering problems

Sparse reconstruction for compressed sensing using Stagewise Polytope Faces Pursuit

Analysis of electromagnetic radiation and scattering using characteristic basis function method with higher order method

Nonlinear basis pursuit

Parallelized multilevel Characteristic Basis Function method applied to scattering model for forest remote sensing

Analyzing electromagnetic scattering using characteristic basis function method with compressed sensing

Similar Documents

Compressed sensing based on FE-BI for solving electromagnetic scattering problems

Use of Compressed Sensing in analysis of electric field integral equation by the Method of Moments

Sparse basis expansions for compressive sensing of electromagnetic scattering patterns computed using iterative physical optics

An efficient algorithm for electromagnetic scattering analysis using curve RWG basis function and adaptively modified characteristic basis function method

A new method combining compressive sensing and method of moments for bistatic scattering problems

Sparse reconstruction for compressed sensing using Stagewise Polytope Faces Pursuit

Analysis of electromagnetic radiation and scattering using characteristic basis function method with higher order method

Nonlinear basis pursuit

Parallelized multilevel Characteristic Basis Function method applied to scattering model for forest remote sensing

Analyzing electromagnetic scattering using characteristic basis function method with compressed sensing