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author:

Zhao, H. (Zhao, H..) [1] | Li, X. (Li, X..) [2] | Chen, Z. (Chen, Z..) [3] | Hu, J. (Hu, J..) [4]

Indexed by:

Scopus

Abstract:

Radio frequency (RF) source reconstruction is useful for RF radiation analysis and interference diagnosis in Internet of Things. Near field (NF) sampling is a critical step of RF source reconstruction. Accurate RF source reconstruction usually requires a large number of NF samples, which results in tremendous effort of NF sampling. This article presents an adaptive NF sampling method based on the skeletonization scheme. First, sources to be reconstructed are related to NF samples through integral equation (IE). Second, the IE is discretized with the method of moments, and thus the interaction matrix between source and field points is found. Third, strong rank-revealing QR factorization is applied to the interaction matrix, which results in a permutation matrix, a row skeleton matrix, and a transformation matrix. Finally, a small number of skeleton sampling points are selected by analyzing the permutation matrix. The fields at skeleton sampling points can be used to calculate the fields at other sampling points through the transformation matrix. Hence, one only needs to perform NF sampling at a small number of skeleton sampling points, which significantly reduces the expenditure of NF sampling. Simulations using synthetic and measurement data are presented to show the effectiveness and advantages of the proposed sampling method. © 2014 IEEE.

Keyword:

Integral equation (IE); interference diagnosis; method of moments; near field (NF) sampling; radio frequency (RF) radiation; skeletonization scheme; source reconstruction

Community:

  • [ 1 ] [Zhao, H.]School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
  • [ 2 ] [Li, X.]School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
  • [ 3 ] [Chen, Z.]College of Physics and Information Engineering, Fuzhou University, Fujian, 350108, China
  • [ 4 ] [Chen, Z.]Department of Electrical and Computer Engineering, Dalhousie University, Halifax, NS B3H 4R2, Canada
  • [ 5 ] [Hu, J.]School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

Reprint 's Address:

  • [Zhao, H.]School of Electronic Science and Engineering, University of Electronic Science and Technology of ChinaChina

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Source :

IEEE Internet of Things Journal

ISSN: 2327-4662

Year: 2019

Issue: 6

Volume: 6

Page: 10219-10228

9 . 9 3 6

JCR@2019

8 . 2 0 0

JCR@2023

ESI HC Threshold:162

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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