Pattern synthesis of sparse linear array by off‐grid Bayesian compressive sampling

2015 ◽  
Vol 51 (25) ◽  
pp. 2141-2143 ◽  
Author(s):  
Jincheng Lin ◽  
Xiaochuan Ma ◽  
Shefeng Yan ◽  
Li Jiang
Keyword(s):  
Linear Array ◽  
Compressive Sampling ◽  
Pattern Synthesis ◽  
Sparse Linear Array

Complex-Weight Sparse Linear Array Synthesis by Bayesian Compressive Sampling

2012 ◽  
Vol 60 (5) ◽  
pp. 2309-2326 ◽  
Author(s):  
Giacomo Oliveri ◽  
Matteo Carlin ◽  
Andrea Massa
Keyword(s):  
Linear Array ◽  
Compressive Sampling ◽  
Sparse Linear Array

scholarly journals A Hybrid Method Based on the Iterative Fourier Transform and the Differential Evolution for Pattern Synthesis of Sparse Linear Arrays

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Xin-Kuan Wang ◽  
Gui-Bao Wang
Keyword(s):  
Fourier Transform ◽  
Differential Evolution ◽  
Hybrid Method ◽  
Linear Array ◽  
Hardware Cost ◽  
Pattern Synthesis ◽  
Linear Arrays ◽  
Half Wavelength ◽  
Low Sidelobe ◽  
Sparse Linear Array

A hybrid method that combines the iterative Fourier transform (IFT) and the algorithm of differential evolution (DE) is proposed to address the synthesis of low sidelobe sparse linear array (SLA) including many elements. Firstly, a thinned linear array (TLA) with the lattices spaced at half wavelength is obtained by the IFT. Then, for the elements of the TLA whose left or right spacing are greater than half wavelength, their placements are selected as the candidates which will be further optimized by the DE, as long as the interelement spacing is not less than half wavelength. Consequently, the convergence pressure of DE is greatly alleviated for the reason that the selected elements only accounts for a small part of the total. Therefore, the SLA with improved sidelobe performance can be obtained at relative low hardware cost. Several numerical instances confirmed the effectiveness of the proposed method.

scholarly journals Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Lei Liang ◽  
Jie Sun ◽  
Hailin Li ◽  
Jialing Liu ◽  
Yachao Jiang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Linear Array ◽  
Particle Swarm ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Pattern Synthesis ◽  
Swarm Optimization ◽  
Time Modulation ◽  
Sparse Linear Array

An efficient pattern synthesis approach is proposed for the synthesis of a time-modulated sparse linear array (TMSLA) in this paper. Due to the introduction of time modulation, the low/ultralow side lobe level can be obtained with a low amplitude dynamic range ratio. Besides, it helps reduce the difficulty of antenna feeding system effectively. Based on particle swarm optimization (PSO) and convex (CVX) optimization, this paper proposes a hybrid optimization method to suppress the grating lobes of the sparse arrays, peak side lobe level (PSLL), and peak sideband level (PSBL). Firstly, the paper utilizes the CVX optimization as a local optimization algorithm to optimize the elements’ switch-on duration time, which reduces the side lobe of the array. Secondly, with the PSBL as the objective function, the paper adopts the PSO as a global optimization algorithm to optimize the elements’ positions and switch-on time instant, which helps reduce the loss of sideband power caused by time modulation. With respect to the time modulation model, variable aperture sizes (VAS) and more flexible pulse-shifting (PS) schemes are used in this paper. Owing to the introduction of time modulation and CVX optimization, the proposed method is much more feasible and efficient than conventional approaches. Furthermore, it has better array pattern synthesis performance. Numerical examples of the TMSLA and comparisons with the reference are presented to demonstrate the effectiveness of the proposed method.

scholarly journals Three-Dimensional Imaging of Terahertz Circular SAR with Sparse Linear Array

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2477 ◽  
Author(s):  
Jubo Hao ◽  
Jin Li ◽  
Yiming Pi
Keyword(s):  
3D Imaging ◽  
Linear Array ◽  
Ground Plane ◽  
Three Dimensional ◽  
Terahertz Waves ◽  
Recovery Method ◽  
Imaging Algorithm ◽  
Imaging Geometry ◽  
Imaging Results ◽  
Sparse Linear Array

Due to the non-contact detection ability of radar and the harmlessness of terahertz waves to the human body, three-dimensional (3D) imaging using terahertz synthetic aperture radar (SAR) is an efficient method of security detection in public areas. To achieve high-resolution and all aspect imaging, circular trajectory movement of radar and linear sensor array along the height direction were used in this study. However, the short wavelength of terahertz waves makes it practically impossible for the hardware to satisfy the half-wavelength spacing condition to avoid grating lobes. To solve this problem, a sparse linear array model based on the equivalent phase center principle was established. With the designed imaging geometry and corresponding echo signal model, a 3D imaging algorithm was derived. Firstly, the phase-preserving algorithm was adopted to obtain the 2D image of the ground plane for each sensor. Secondly, the sparse recovery method was applied to accomplish the scattering coefficient reconstruction along the height direction. After reconstruction of all the range-azimuth cells was accomplished, the final 3D image was obtained. Numerical simulations and experiments using terahertz radar were performed. The imaging results verify the effectiveness of the 3D imaging algorithm for the proposed model and validate the feasibility of terahertz radar applied in security detection.

Localisation of mixed near‐field and far‐field sources using the largest aperture sparse linear array

2018 ◽  
Vol 12 (2) ◽  
pp. 155-162 ◽  
Author(s):  
Ali Akbar Ebrahimi ◽  
Hamid Reza Abutalebi ◽  
Mahmood Karimi
Keyword(s):  
Linear Array ◽  
Near Field ◽  
Far Field ◽  
Sparse Linear Array

Hybrid Sparse Linear Array Synthesis Applied to Phased Antenna Arrays

2014 ◽  
Vol 13 ◽  
pp. 185-188 ◽  
Author(s):  
Leonardo F. Yepes ◽  
David H. Covarrubias ◽  
Miguel A. Alonso ◽  
Ramon Ferrus
Keyword(s):  
Antenna Arrays ◽  
Linear Array ◽  
Phased Antenna Arrays ◽  
Sparse Linear Array
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