The aim of this contribution is to present an approach that allows to improve the quality of the reconstruction of the far-field from a small number of measured samples by means of sparse recovery using a relatively coarse grid for source positions (with sample spacing of the order of λ/8) compared to the grid usually required. In particular, the iterative method proposed employs a smooth-weighted constrained minimization, that guarantees a better probability of correct estimate of the sparse sources and an improved quality in the reconstruction, with a similar computational effort respect to the standard ℓ1 re-weighted minimization approach.

Accurate reconstruction of the radiation of sparse sources from a small set of near-field measurements by means of a smooth-weighted norm for cluster-sparsity problems

Pinchera D.
;
Migliore M. D.
2021

Abstract

The aim of this contribution is to present an approach that allows to improve the quality of the reconstruction of the far-field from a small number of measured samples by means of sparse recovery using a relatively coarse grid for source positions (with sample spacing of the order of λ/8) compared to the grid usually required. In particular, the iterative method proposed employs a smooth-weighted constrained minimization, that guarantees a better probability of correct estimate of the sparse sources and an improved quality in the reconstruction, with a similar computational effort respect to the standard ℓ1 re-weighted minimization approach.
File in questo prodotto:
File Dimensione Formato  
Jn107-21 electronics sparse cluster array recostruction.pdf

accesso aperto

Licenza: Creative commons
Dimensione 1.71 MB
Formato Adobe PDF
1.71 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11580/90885
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
social impact