Antenna array optimization for the new GIMS demonstrator

Author(s):  
Cheng Zhang ◽  
Hao Liu ◽  
Ji Wu
2011 ◽  
Vol 59 (8) ◽  
pp. 3112-3116 ◽  
Author(s):  
Shaya Karimkashi ◽  
Ahmed A. Kishk ◽  
Darko Kajfez

2011 ◽  
Vol 59 (8) ◽  
pp. 2862-2871 ◽  
Author(s):  
Pierre Minvielle ◽  
Emilia Tantar ◽  
Alexandru-Adrian Tantar ◽  
Philippe Berisset

2019 ◽  
Vol 8 (2S3) ◽  
pp. 1184-1187

Antenna array optimization is a major research problem in the field of electromagnetic and antenna engineering. The optimization typically involves in handling several radiation parameters like Sidelobe level (SL) and beamwidth (BW). In this paper, the linear antenna array (LAA) configuration is considered with symmetrical distribution of excitation and special distribution. The objective of the design problem considered involves in generating optimized patterns in terms of SLL and BW and check the robustness of the social group optimization algorithm (SGOA). The analysis of the design problem is carried out in terms of radiation pattern plots. The simulation is carried out in Matlab.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhikun Chen ◽  
Tao Li ◽  
Dongliang Peng ◽  
Kang Du

Polarized smart antenna array has attracted considerable interest due to its capacity of matched reception or interference suppression for active sensing systems. Existing literature does not take full advantage of the combination of polarization isolation and smart antennas and only focuses on uniform linear array (ULA). In this paper, an innovative synthesis two-dimensional beampattern method with a null that has cross-polarization for polarized planar arrays is proposed in the first stage. This method aims to further enhance the capability of interference suppression whose optimization problem can be solved by second-order conic programming. In the second stage, a new sparse array-optimized method for the polarized antenna array is proposed to reduce the high cost caused by the planar array that is composed of polarized dipole antennas. Numerical examples are provided to demonstrate the advantages of the proposed approach over state-of-the-art methods.


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