Reseach On Sparse Array Pattern Synthesis Optimization Algorithms

For many applications that extreme narrow main beamwidth is desired, whereas high gain is not so extremely required, the sparse antenna arrays whose element spacing is discrete over an antenna aperture is an effective and economic methods. The sparse array have the advantage of lower cost, lower mutual coupling, lower failure rate and the same high-resolution with periodic arrays, due to these advantages, in recent years the sparse arrays are widely applied in radar, sonar, electronic countermeasure, satelite communications. Beampattern synthesis is the inverse problem of beampattern analysis.The purpose of antenna array beampattern synthesis is to determine the array element layouts and the array element excitations which produces a radiation pattern that is closest to the desired pattern. In this paper, some traditional algorithms of beampattern synthesis is summarized and developped to solve the sparse array beampattern synthesis problem, and we also talk about the large-scale linear sparse array and planar array beampattern synthesis methods, at last we integrate the spare linear and planar array methods into a phased array beampattern synthesis software. The main work and innovations of this dissertation are summarized as follows:Firstly, this article starts from the array beampattern theory of the regular linear lattice planar array, concentric circular antenna array, conformal antenna array. Then,the genetic algorithm is studied in the beampattern synthesis of the small-scale thinned and sparse antenna array. We introduce the mathmatic model of the optimization of the element layouts and weight coefficients of the thinned and sparse array, what’s more,the mathmatic model can be applied to the optimization of planar antenna array.Afterwards, Aiming to obtain low sidelobe levels of an array, the adaptive particle swarm optimization(APSO) that features better search efficiency than classical particle swarm optimization(PSO) is firstly applied in the optimization of the element positions and weights of the linear sparse arrays. Accelerating convergence speed and avoiding the local optima have become the two most important and appealing goals in PSO research. To achieve both goals, adaptive PSO is formulated in this paper by developing a systematic parameter adaptation scheme and an elitist learning strategy(ELS).Compared with some Evolutionary algorithms such as genetic algorithm, the APSO has the advantages of less parameters and easier to be implemented. Simulation results of alinear sparse array show that the algorithm can handle global optimization problem properly and the algorithm can be applied to the synthesis of sparse planar antenna array.Thirdly, this article also discussed the array beampattern synthesis of the large-scale linear sparse array, the large-scale planar array, the large-scale concentric circular antenna array. Because of the CVX algorithm and global optimization cannot handle the synthesis of large-scale antenna array problems, we use the nonuniform fast Fourier transform algorithm to interpolate the nonuniform antenna array into uniform antenna array, then we use the iterative fast Fourier transform algorithm to caculate the array element weight coefficients. First we use the nonuniform fast Fourier transform algorithmto introduce the beampattern synthesis of the large-scale nonuniform planar array, include the large-scale linear sparse array, the large-scale planar array, the large-scale concentric circular antenna array, related simulation results show that the nonuniform fast Fourier transform algorithm can be applied to the beampattern synthesis in satelite communication and radio astronomy.Finally, The computer simulation and verification on phased antenna array beampattern synthesis software platform is developed on MATLAB software.The overall design conception is elaborated, and the feature model and the basic parameter setting modules on the platform are also presented in the beginning. The software adoptted the genetic algorithm, particle swarm optimization algorithm, the CVX algorithm, the iterative fast Fourier transform algorithm, the nonuniform fast Fourier transform algorithm to solve the synthesis problem of the uniform antenna array and the sparse and thinned antenna array. Related simulation results show that the software can solve the engineering problems.