Near-Field Pattern Synthesis for Sparse Focusing Antenna Arrays Based on Bayesian Compressive Sensing and Convex Optimization

2018 ◽  
Vol 66 (10) ◽  
pp. 5249-5257 ◽  
Author(s):  
Zi Xuan Huang ◽  
Yu Jian Cheng
Keyword(s):  
Convex Optimization ◽  
Compressive Sensing ◽  
Antenna Arrays ◽  
Near Field ◽  
Field Pattern ◽  
Pattern Synthesis

Near-field pattern synthesis at optical frequencies

2009 ◽  
Author(s):  
Lucio Vegni ◽  
Filiberto Bilotti
Keyword(s):  
Near Field ◽  
Field Pattern ◽  
Pattern Synthesis

Modifications of active phased antenna arrays near-field diagnosis method based on compressive sensing

2019 ◽  
Vol 11 (7) ◽  
pp. 568-576 ◽  
Author(s):  
Grigory Kuznetsov ◽  
Vladimir Temchenko ◽  
Maxim Miloserdov ◽  
Dmitry Voskresenskiy
Keyword(s):  
Compressive Sensing ◽  
Antenna Arrays ◽  
Near Field ◽  
Practical Implementation ◽  
Phased Antenna Arrays ◽  
Two Factors ◽  
Minimization Procedure ◽  
Diagnosis Method ◽  
Proposed Modification

AbstractThis paper presents two modifications of compressive sensing (CS)-based approach applied to the near-field diagnosis of active phased arrays. CS-based antenna array diagnosis allows a significant reduction of measurement time, which is crucial for the characterization of electrically large active antenna arrays, e.g. used in synthetic aperture radar. However, practical implementation of this method is limited by two factors: first, it is sensitive to thermal instabilities of the array under test, and second, excitation reconstruction accuracy strongly depends on the accuracy of the elements of the measurement matrix. First proposed modification allows taking into account of thermal instability of the array by using an iterative ℓ1-minimization procedure. The second modification increases the accuracy of reconstruction using several simple additional measurements.

scholarly journals Geometrical Synthesis of Sparse Antenna Arrays Using Compressive Sensing for 5G IoT Applications

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 350 ◽  
Author(s):  
Giulia Buttazzoni ◽  
Fulvio Babich ◽  
Francesca Vatta ◽  
Massimiliano Comisso
Keyword(s):  
Compressive Sensing ◽  
Antenna Arrays ◽  
Optimization Problem ◽  
Field Pattern ◽  
Sensors And Actuators ◽  
Iot Applications ◽  
Fifth Generation ◽  
Far Field Pattern ◽  
The Internet Of Things ◽  
Antenna Systems

One of the main targets of the forthcoming fifth-generation (5G) cellular network will be the support of the communications for billions of sensors and actuators, so as to finally realize the Internet of things (IoT) paradigm. This pervasive scenario unavoidably requires the design of cheap antenna systems with beamforming capabilities for compensating the strong attenuations that characterize the millimeter-wave (mmWave) channel. To address this issue, this paper proposes an iterative algorithm for sparse antenna arrays that enables to derive the number of elements, their amplitudes, phases, and positions in the presence of constraints on the far-field pattern. The algorithm, which relies on the compressive sensing approach, is formulated by transforming the original nonconvex optimization problem into a convex one. To prove the suitability of the conceived solution for 5G IoT mmWave applications, numerical examples and comparisons with other existing methods are provided, considering synthesis problems with different pattern and aperture specifications.

scholarly journals Reconfigurable Antenna Arrays with Multiple Requirements: A Versatile 3D Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Massimiliano Comisso ◽  
Giulia Buttazzoni ◽  
Roberto Vescovo
Keyword(s):  
Antenna Arrays ◽  
Mutual Coupling ◽  
Dynamic Range ◽  
Near Field ◽  
Field Pattern ◽  
Deterministic Method ◽  
Iterative Minimization ◽  
Array Structures ◽  
Far Field Pattern ◽  
Ratio Reduction

This paper proposes a deterministic method for the 3D synthesis of antenna arrays that jointly accounts for far-field pattern reconfigurability, polarization setting, dynamic range ratio reduction, and near-field control. The conceived algorithm, which generalizes some existing solutions, relies on a weighted cost function, whose iterative minimization is accomplished by properly derived closed-form expressions. This feature, combined with the possibility of selecting the weighting parameters, provides a fast and versatile approach, whose capabilities are numerically checked by considering different synthesis problems and array structures in the presence of mutual coupling.

scholarly journals Fast 3D Pattern Synthesis with Polarization and Dynamic Range Ratio Control for Conformal Antenna Arrays

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Massimiliano Comisso ◽  
Roberto Vescovo
Keyword(s):  
Antenna Arrays ◽  
Dynamic Range ◽  
Polarization State ◽  
Field Pattern ◽  
Pattern Synthesis ◽  
Conformal Antenna ◽  
Cpu Time ◽  
Conformal Arrays ◽  
Far Field Pattern ◽  
Joint Pattern

This paper proposes an iterative algorithm for the 3D synthesis of the electric far-field pattern of a conformal antenna array in the presence of requirements on both the polarization and the dynamic range ratio (DRR) of the excitations. Thanks to the use of selectable weights, the algorithm allows a versatile control of the DRR and of the polarization in a given angular region and requires a low CPU time to provide the array excitations. Furthermore, a modified version of the algorithm is developed to enable the optimization of the polarization state by phase-only control. Numerical results are presented to verify the usefulness of the proposed approach for the joint pattern and polarization synthesis of conformal arrays with reduced or even unitary DRR.

Sign in / Sign up

Export Citation Format

Share Document