scholarly journals Study on the method of measuring direction and positioning with the sparse linear array sensor on the Partial discharge(PD)source

2016 ◽  
Author(s):  
Tong Liu ◽  
Xiaolong Xu ◽  
Hao Du
Keyword(s):  
Linear Array ◽  
Partial Discharge ◽  
Array Sensor ◽  
Sparse Linear Array

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

scholarly journals Compressive Imaging of Moving Object Based on Linear Array Sensor

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Changjun Zha ◽  
Yao Li ◽  
Jinyao Gui ◽  
Huimin Duan ◽  
Tailong Xu
Keyword(s):  
Moving Objects ◽  
Linear Array ◽  
Matching Pursuit ◽  
Moving Object ◽  
Imaging Method ◽  
Compressive Imaging ◽  
Array Sensor ◽  
Object Based ◽  
Direct Separation ◽  
Matching Pursuit Algorithm

Using the characteristics of a moving object, this paper presents a compressive imaging method for moving objects based on a linear array sensor. The method uses a higher sampling frequency and a traditional algorithm to recover the image through a column-by-column process. During the compressive sampling stage, the output values of the linear array sensor are multiplied by a coefficient that is a measurement matrix element, and then the measurement value can be acquired by adding all the multiplication values together. During the reconstruction stage, the orthogonal matching pursuit algorithm is used to recover the original image when all the measurement values are obtained. Numerical simulations and experimental results show that the proposed compressive imaging method not only effectively captures the information required from the moving object for image reconstruction but also achieves direct separation of the moving object from a static scene.

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