Dilute Disposal List Of Antenna Array Element Distribution Optimization Design Research

In some specific engineering applications, a single antenna is often difficult to achieve high gain and strong directionality, or make the radiation pattern scanning. The problem-solving method is to use array antennas which consist of many antennas according to certain rules of arrangement. Because of sparse distribution of antenna elements in the array aperture, the sparse array antennas realize beamwidth narrowing, high-resolution and element-interaction reduction with fewer elements, and greatly reduce the production cost. The sparse array antennas have been more widely applied in radar and communications electronic fields.The peak side lobe level is a key parameter of the sparse array antennas. The array optimization design techniques discussed in this dissertation, is how to find the elements positions to minimize the peak side lobe level, when the elements number, the element spacing and the array configuration are predetermined.In this dissertation, an iterative FFT algorithm and a dimension reduction optimization method based on modified genetic algorithms are used to design the sparse array antennas, the main work and contributions include the following several aspects:1. The basic theory of the array antennas is introduced, then the various forms of linear array and planar array are detailedly analysed, and the corresponding pattern function and optimization design model are given.2. According to the Fourier transform relationship exists between the array factor and the element excitations in thinned array, an iterative fast Fourier transform algorithm based on the classic density-tapered array optimization design is presented and the detailed theory of the method is discussed.3. The iterative FFT algorithm is used to design the linear thinned array and the plane thinned array. Comparison with the existing research results, the simulated results confirming the great efficiency and the robustness of the new method are shown in this dissertation.4. A new dimension reduction optimization method based on modified genetic algorithms for sparse plane array featuring an optimal peak side-lobe level is presented. The method transforms two-dimensional sparse concentric rings array into one-dimensional linear sparse array, and greatly reduces the computation time and the complexity of the model. Meanwhile, due to the combined optimization of all elements, the freedom of array optimization design is improved.