scholarly journals BAT Algorithm Based Beamformer for Interference Suppression by Controlling the Complex Weight

2018 ◽  
Author(s):  
Luyen Van Tong ◽  
Vu Bang Giang Truong
Keyword(s):  
Particle Swarm Optimization ◽  
Linear Array ◽  
Bat Algorithm ◽  
Side Lobe ◽  
Pattern Synthesis ◽  
Swarm Optimization ◽  
Proposal A ◽  
Null Steering ◽  
Accelerated Particle Swarm Optimization ◽  
Side Lobe Suppression

In this study, an adaptive beamformer for pattern nulling of Uniformly Spaced Linear Array (ULA) antennas, which utilized BAT algorithm (BA) to suppress interferences, has been proposed. This pattern nulling has been obtained by controlling the complex weight (both the phase and the amplitude) of each array element. So as to verify the proposal, a number of scenarios of ULA pattern imposed the pre-set nulls have been carried out and compared with those of accelerated particle swarm optimization (APSO). The proposed beamformer has demonstrated the capability to place with precise single, multiple, and broad nulls at arbitrary interference directions, suppress side lobes, and maintain a predefined beamwidth. Moreover, the beamformer shows faster convergence and higher efficiency regarding null steering and side lobe suppression in pattern synthesis, as compared with an APSO based beamformer.

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 Optimal Pattern Synthesis of Linear Array and Broadband Design of Whip Antenna Using Grasshopper Optimization Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Hengfeng Wang ◽  
Chao Liu ◽  
Huaning Wu ◽  
Bin Li ◽  
Xu Xie
Keyword(s):  
Optimization Algorithm ◽  
Communication Systems ◽  
Linear Array ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Local Optimum ◽  
Pattern Synthesis ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Side Lobe Suppression

Antenna arrays with high directivity, low side-lobe level, and null control in desired direction and whip antenna with wider bandwidth both need to be optimized to meet different needs of communication systems. A new natural heuristic algorithm simulating social behavior of grasshoppers, grasshopper optimization algorithm (GOA), is applied to electromagnetic field as a new effective technology to solve the antenna optimization problem for the first time. Its algorithm is simple and has no gradient mechanism, can effectively avoid falling into local optimum, and is suitable for single-objective and multiobjective optimization problems. GOA is used to optimize the side lobe suppression, null depth, and notch control of arbitrary linear array and then used to optimize the loading and matching network of 10-meter HF broadband whip antenna compared with other algorithms. The results show that GOA has more advantages in side-lobe suppression, null depth, and notch control of linear array than other algorithms and has better broadband optimization performance for HF whip antenna. The pattern synthesis and antenna broadband optimization based on GOA provide a new and effective method for antenna performance optimization.

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