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@ARTICLE{Bangun:1024633,
      author       = {Bangun, Arya and Culotta-Lopez, Cosme},
      title        = {{O}ptimizing {S}ensing {M}atrices for {S}pherical
                      {N}ear-{F}ield {A}ntenna {M}easurements},
      journal      = {IEEE transactions on antennas and propagation},
      volume       = {71},
      number       = {2},
      issn         = {0018-926X},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2024-02306},
      pages        = {1716 - 1724},
      year         = {2023},
      abstract     = {In this article, we address the problem of reducingthe
                      number of required samples for spherical near-field(SNF)
                      antenna measurements by using compressed sensing (CS).A
                      condition to ensure the numerical performance of
                      sparserecovery algorithms is the design of a sensing matrix
                      with lowmutual coherence. Without fixing any part of the
                      samplingpattern, we directly find sampling points that
                      minimize themutual coherence of the respective sensing
                      matrix. Numericalexperiments show that the proposed sampling
                      scheme yields ahigher recovery success in terms of phase
                      transition diagramwhen compared to other known sampling
                      patterns, such asthe spiral and Hammersley sampling schemes.
                      Furthermore, wealso demonstrate that the application of CS
                      with an optimizedsensing matrix requires fewer samples than
                      classical approachesto reconstruct the spherical mode
                      coefficients (SMCs) and farfieldpattern.Index
                      Terms—Compressed sensing (CS), near-field to
                      far-fieldtransformation (NFFFT), optimization, spherical
                      near-field (SNF)antenna measurements.},
      cin          = {IAS-8},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IAS-8-20210421},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5112},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000965610700001},
      doi          = {10.1109/TAP.2022.3227010},
      url          = {https://juser.fz-juelich.de/record/1024633},
}