Low-Complexity Sparse Array Synthesis Based on Off-Grid Compressive Sensing

In this letter, a novel sparse array synthesis method for nonuniform planar arrays is proposed, which belongs to compressive sensing (CS) based synthesis. Particularly, we propose an off-grid refinement technique to simultaneously optimize the antenna element positions and excitations with a low com...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE antennas and wireless propagation letters Ročník 21; číslo 12; s. 2322 - 2326
Hlavní autori: Yang, Songjie, Liu, Baojuan, Hong, Zhiqin, Zhang, Zhongpei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
ISSN:1536-1225, 1548-5757
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In this letter, a novel sparse array synthesis method for nonuniform planar arrays is proposed, which belongs to compressive sensing (CS) based synthesis. Particularly, we propose an off-grid refinement technique to simultaneously optimize the antenna element positions and excitations with a low complexity, in response to the antenna position optimization problem that is difficult for standard CS. More importantly, we take into account the minimum interelement spacing constraint for ensuring the physically realizable solution. Specifically, the off-grid orthogonal match pursuit algorithm is first proposed with low complexity and then off-grid look ahead orthogonal match pursuit is designed with better synthesis performance but higher complexity. In addition, simulation results have shown that the proposed schemes have more advantages in computational complexity and synthesis performances compared with the related method.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2022.3192308