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Gradient-based optimization method for interference suppression of linear arrays by the amplitude-only and phase-only control

Published online by Cambridge University Press:  28 September 2021

Renjing Gao ,
Yi Tang Open the ORCID record for Yi Tang [Opens in a new window] ,
Qi Wang  and
Shutian Liu
Renjing Gao
Affiliation:
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China Ningbo Institute of Dalian University of Technology, Ningbo 315016, China
Yi Tang
Affiliation:
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China
Qi Wang*
Affiliation:
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China Ningbo Institute of Dalian University of Technology, Ningbo 315016, China
Shutian Liu*
Affiliation:
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China
*
Author for correspondence: Qi Wang, E-mail: qiwang@dlut.edu.cn; Shutian Liu, E-mail: stliu@dlut.edu.cn
Author for correspondence: Qi Wang, E-mail: qiwang@dlut.edu.cn; Shutian Liu, E-mail: stliu@dlut.edu.cn
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Abstract

This paper presents a gradient-based optimization method for interference suppression of linear arrays by controlling the electrical parameters of each array element, including the amplitude-only and phase-only. Gradient-based optimization algorithm (GOA), as an efficient optimization algorithm, is applied to the optimization problem of the anti-interference arrays that is generally solved by the evolutionary algorithms. The goal of this method is to maximize the main beam gain while minimizing the peak sidelobe level (PSLL) together with the null constraint. To control the nulls precisely and synthesize the radiation pattern accurately, the full-wave method of moments is used to consider the mutual coupling among the array elements rigorously. The searching efficiency is improved greatly because the gradient (sensitivity) information is used in the algorithm for solving the optimization problem. The sensitivities of the design objective and the constraint function with respect to the design variables are analytically derived and the optimization problems are solved by using GOA. The results of the GOA can produce the desired null at the specific positions, minimize the PSLL, and greatly shorten the computation time compared with the often-used non-gradient method such as genetic algorithm and cuckoo search algorithm.

Keywords

Null controllingsidelobe minimizationoptimization methodanti-interference arrays
Type
Antenna Design, Modelling and Measurements
Information
International Journal of Microwave and Wireless Technologies , Volume 14 , Issue 8 , October 2022 , pp. 1002 - 1008
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press in association with the European Microwave Association

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References

Khodier, MM (2005) Linear array geometry synthesis with minimum sidelobe level and null control using particle swarm optimization. IEEE Transactions on Antennas and Propagation 53, 2674–2679.CrossRefGoogle Scholar
Smida, A (2012) Phase-only adaptive nulling with Taguchi's method for antenna array synthesis. American Journal of Applied Sciences 9, 1833–1839.Google Scholar
Babakhani, B (2017) Dual null steering and limited beam peak steering using triple-mode circular microstrip patch antenna. IEEE Transactions on Antennas and Propagation 65, 3838–3848.CrossRefGoogle Scholar
Van Luyen, T (2017) Interference suppression of ULA antennas by phase-only control using bat algorithm. IEEE Antennas and Wireless Propagation Letters 16, 3038–3042.CrossRefGoogle Scholar
Mohammed, JR (2017) Optimal null steering method in uniformly excited equally spaced linear arrays by optimising two edge elements. IEEE Transactions on Antennas and Propagation 53, 835–837.Google Scholar
Aslan, Y (2019) Phase-only control of peak sidelobe level and pattern nulls using iterative phase perturbations. IEEE Antennas and Wireless Propagation Letters 18, 2081–2085.CrossRefGoogle Scholar
Almagboul, MA (2019) Atom search optimization algorithm based hybrid antenna array receive beamforming to control sidelobe level and steering the null. AEU-International Journal of Electronics and Communications 111, 152854.Google Scholar
Darvish, A (2018) Improved fruit-fly optimization algorithm and its applications in antenna arrays synthesis. IEEE Antennas and Wireless Propagation 66, 1756–1766.CrossRefGoogle Scholar
Patidar, H (2019) Synthesis of flat-top beam pattern of linear antenna arrays with restricted side lobe level, VSWR and independent nulls using Flower Pollination algorithm. International Journal of Electronics 106, 1964–1977.CrossRefGoogle Scholar
Zhang, F (2013) Linear aperiodic array synthesis using differential evolution algorithm. IEEE Antennas and Wireless Propagation Letters 12, 797–800.CrossRefGoogle Scholar
Murino, V (1996) Synthesis of equally spaced arrays by simulated annealing. IEEE Transactions on Signal Processing 44, 119–122.CrossRefGoogle Scholar
Tennant, A (1994) Array pattern nulling by element position perturbations using a genetic algorithm. Electronics Letters 30, 174–176.CrossRefGoogle Scholar
Haupt, RL (2009) Low sidelobe arrays via dipole rotation. IEEE Transactions on Antennas and Propagation 57, 1575–1579.CrossRefGoogle Scholar
Yang, B (2019) Multi-objective synthesis of linear arrays by using an improved genetic algorithm. International Journal of Antennas and Propagation 17, 142–152.Google Scholar
Saxena, P (2016) Ant lion optimization algorithm to control side lobe level and null depths in linear antenna arrays. AEU-International Journal of Electronics and Communications 70, 1339–1349.Google Scholar
Karimkashi, S (2010) Invasive weed optimization and its features in electromagnetics. IEEE Transactions on Antennas and Propagation 58, 1269–1278.CrossRefGoogle Scholar
Pappula, L (2014) Linear antenna array synthesis using cat swarm optimization. AEU-International Journal of Electronics and Communications 68, 540–549.Google Scholar
Singh, U (2010) Linear array synthesis using biogeography based optimization. Progress in Electromagnetics Research 11, 25–36.CrossRefGoogle Scholar
Zhang, C (2018) Synthesis of broadside linear aperiodic arrays with sidelobe suppression and null steering using whale optimization algorithm. IEEE Antennas and Wireless Propagation Letters 17, 347–350.CrossRefGoogle Scholar
Khodier, M (2013) Optimisation of antenna arrays using the cuckoo search algorithm. IET Microwaves, Antennas & Propagation 7, 458–464.CrossRefGoogle Scholar
Khodier, M (2019) Comprehensive study of linear antenna array optimisation using the cuckoo search algorithm. IET Microwaves, Antennas & Propagation 13, 1325–1333.CrossRefGoogle Scholar
Zhou, Q (2010) An improved cuckoo search algorithm for optimizing the beam patterns of the random antenna arrays. IEEE 4th International Conference on Computer and Communications (ICCC), 1018–1021.Google Scholar
Chen, Z (2018) Planning optimization of the distributed antenna system in high-speed railway communication network based on improved cuckoo search. International Journal of Antennas and Propagation, 3641286.CrossRefGoogle Scholar
Svanberg, K (1987) The method of moving asymptotes – a new method for structural optimization. International Journal for Numerical Methods in Engineering 24, 458–464.CrossRefGoogle Scholar
Boggs, PT (1995) Sequential quadratic programming. Acta Numerica 4, 1–51.CrossRefGoogle Scholar
Tortorelli, DA (1994) Design sensitivity analysis: overview and review. Inverse Problems in Engineering 1, 71–105.CrossRefGoogle Scholar
Liu, K (2014) An efficient 3D topology optimization code written in Matlab. Structural and Multidisciplinary Optimization 50, 1175–1196.CrossRefGoogle Scholar
Wang, Q (2020) Mapping-based optimization method for pattern synthesis via array element rotation. IEEE Transactions on Antennas and Propagation 68, 2736–2742.CrossRefGoogle Scholar