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...

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Bibliographic Details
Published in:IEEE antennas and wireless propagation letters Vol. 21; no. 12; pp. 2322 - 2326
Main Authors: Yang, Songjie, Liu, Baojuan, Hong, Zhiqin, Zhang, Zhongpei
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Antennas
Complexity
Grid refinement (mathematics)
Interelement spacing constraint
Manganese
Matching pursuit algorithms
off-grid compressive sensing (CS)
Optimization
Pattern matching
Planar arrays
Sensors
sparse array synthesis
Synthesis
Transmission line matrix methods
ISSN:1536-1225, 1548-5757
Online Access:Get full text
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Summary: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.
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ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2022.3192308