Research On Antenna Array Based On Whale Optimization Algorithm

With the continuous improvement of various wireless system performance indicators,research on antennas has also become particularly important.According to different requirements,the practical project requires the corresponding antenna to generate patterns with different shapes.By setting the relevant parameters of the array antenna,the target pattern that meets the actual life and application scenarios can be obtained.These array parameters include the excitation current amplitude and phase of each basic unit,the arrangement shape and number of the basic units.When the number of basic elements of the array antenna is large and the desired far-field pattern is more complex,the design of the array antenna becomes a more complicated optimization problem.In the early days,analytical methods or traditional engineering optimization methods were used to solve such problems,but they not only have problems such as long calculation time and insufficient accuracy,but also cannot solve the comprehensive problem of high-dimensional complex demand patterns.With the successive emergence and rapid development of various intelligent optimization algorithms,array antenna researchers have found that intelligent optimization algorithms are very suitable for solving such complex optimization problems,and gradually began to try to use various intelligent optimization algorithms to solve array antenna optimization problems.The well-known genetic algorithm and particle swarm optimization algorithm have also been used to solve the optimization problem of the array antenna,and have achieved good optimization results.As an emerging intelligent optimization algorithm,the research on the whale optimization algorithm is not very extensive.This paper will study the characteristics of the whale optimization algorithm and use it to solve the array antenna optimization problem,such as the amplitude weighted design of the array antenna,the sparse application areas such as array design and beamforming optimization.The whale optimization algorithm is a novel intelligent optimization algorithm proposed by studying the hunting methods of humpback whales in nature.The three steps achieve the following functions respectively: firstly,“surrounding the prey” allows the whale to swim to the nearest position,which can improve the search ability;secondly,“spiral bubble-net attacking method” can improve the convergence speed and conduct in a spiral manner local search,which can promote the search efficiency of whales;thirdly,“searching for prey” is the search of different species groups,which can enrich the diversity of whale populations.The whale optimization algorithm is a very effective optimization algorithm,and the search domain of the algorithm covers the entire training space.It not only has simple operation process and fast operation speed,but also can obtain the global optimal solution.Therefore,it has developed rapidly in recent years.However,the application of it in the field of antenna design is still relatively rare,so it is very valuable to use the whale optimization algorithm to solve the optimization problem in the design of the array antenna.First,this paper introduces the basic knowledge of the antenna and the calculation process of the far-field pattern of the array antenna.The array factor pattern of the linear array antenna and the concentric circular array antenna is introduced in detail,and the traditional Chebyshev synthesis method is also introduced,which lays the theoretical foundation.Secondly,this paper introduces the basic principle,implementation process,operation steps,pseudocode and complexity of the whale optimization algorithm in detail.In order to enrich the diversity of the population,the logistic chaotic map is introduced to initialize the population;the inertia weight is introduced to balance the relationship between the global search and the local search;the binary whale optimization algorithm for the binary optimization problem is studied;three different tests are selected function to verify the effectiveness and convergence speed of the whale optimization algorithm,and compare it with the particle swarm algorithm.Finally,this paper will try to use the whale optimization algorithm to solve the array antenna optimization problem.The excitation amplitude of the uniform linear array is optimized by the whale optimization algorithm to obtain the Chebyshev pattern,and the optimization results are compared with the Chebyshev synthesis method,which verifies the effectiveness of the whale optimization algorithm in the array antenna optimization problem.The binary whale optimization algorithm is used to solve the sparse array optimization problem of low sidelobe linear array and concentric circular array;the flat top beam optimization problem,the cosecant square beam optimization problem and the earth matching beam optimization problem are solved respectively by the whale optimization algorithm.