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Research on Synthesis and Optimization Techniques of Sparse Antenna Arrays

Author: ChenKeSong
Tutor: HeZiShu
School: University of Electronic Science and Technology
Course: Signal and Information Processing
Keywords: antenna arrays genetic algorithms (GA) side lobe level thinned arrays sparse arrays optimization
CLC: TN820.15
Type: PhD thesis
Year: 2006
Downloads: 907
Quote: 10
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For many radar and communications applications of scanning array antennas, extreme narrow main beamwidth is desired, whereas high gain is not so extremely required, the sparse antenna arrays, whose element spacing is kept relatively larger thanλ/2 over an antenna aperture, can cover these applications. The sparse antenna arrays have advantages in high-resolution thinned configurations, and fewer elements for comparable beamwidth. The cost of the sparse antenna arrays is much lower to meet the design goal of high-resolution than that of periodic arrays. Due to the array thinning, beamwidth narrowing and element-interaction reduction, the sparse antenna arrays with the strong directivity have a great deal applications in aperiodic arrays. In recent years, the sparse antenna arrays are widly applied in satellite communications, high frequency groundwork phased array radar and interferometer of radio astronomy.The peak side lobe level (PSLL) is a key parameter of an antenna arrays, one of the interesting sparse array synthesis problems is to find an optimum set of element spacings and excitations that would minimize the highest side lobe level (viz.PSLL) in the entire visible region. This is a hard synthesis problem of sparse arrays which has been studied for almost sixty years. These years, the nonuniform antenna arrays have been classified into two categories: sparse arrays with randomly spaced elements and thinned arrays, which are derived by selectively zeroing some elements of an initial equally spaced array. Sparse arrays with incommensurable element spacings have more degree of freedom to lower the peak side lobe level for the simple reason that elements of sparse array do not need to be restricted by the regular linear lattice.In this dissertation, the basic synthesis problem of sparse antenna arrays was studied, that is, how to find the element positions to minimize the PSLL of a sparse antenna array when the array configuration is fixed apriori. The difficult of this problem may be attributed the fact that the side lobe level depends on the element spacings in a highly nonlinear manner, and that, in general, there is no known analytical method to determine the highest side lobe level, or the angular direction where the highest side lobe may occur, even with all element positons given. So the optimization of the element positions of the sparse antenna arrays is a nonlinear optimization. Divisional exhaustive method is applied to optimize the thinning of linear thinned arrays; its performance trials reveal the applicability when it is applied to element spacing synthesis. And various constrains may occurs in the synthesis of sparse arrays, a novel intellectualized method, viz. a modified real genetic algorithms (MGA), is developed to attack the synthesis problem of linear sparse arrays with multiple design constrains. At last, the novel algorithm of MGA was extended to the optimization of the 2-demension sparse antenna arrays.The main contributions of this dissertation include two aspects. One is the study on exhaustive method for the element position design of thinned arrays; the other is the application of genetic algorithms for the optimization of sparse arrays.Several valuable and important results which bring forth new ideas are achieved and listed as the following:1. The mathematical model for the optimization of thinned arrays and sparse arrays was built, and the optimal solutions of sparse antenna arrays were discussed.2. In the process of exhaustive synthesis of minitype thinned arrays, enumerating the configuration of linear thinned arrays is main task of design. Two enumerate algorithms of exhaustive study on configuration of linear thinned arrays are proposed, they are recursion algorithm and binary sequence enumerate algorithm. Some comparison studies on their performance are made in order to reveal the feasibility relations with the thinned ratio and aperture of the array antennas.3. A new method of exhaustive method with divisional pre-processing is proposed, in which the formula of element distribution is modified, and then it is compared with other design methods of thinned arrays.4. The asymmetric configuration is an available degree of freedom to control the characters of thinned arrays. Simulation results show that the optimized asymmetric linear arrays using genetic algorithm which lack the design constraint of bilateral symmetry can not only obtain lower sidelobes, but also weaken the deterioration of scanning beam if the thinned arrays are made up of directional elements. 5. The crossover and mutation strategy of genetic algorithm (GA) with real chromosome are improved, and they can be utilized to improve the side lobe performance of a thinned array by designing the element currents.6. A modified real genetic algorithm (MGA) for the synthesis of sparse linear arrays is developed. It has been utilized to optimize the element positions to reduce the PSLL of the array. And here the multiple optimization constraints include the number of element, the aperture and the minimum element spacing. The MGA utilized the coding resetting of gene variables to avoid infeasible solution during the optimization process. Also, the proposed approach has reduced the size of the searching area of the GA by means of indirect description of individual.7. The MGA is extended for the element position optimization of rectangular sparse plane arrays with multiple optimization constraints. If the space between the elements was simplified from the actual distance (in Euclidean space) to Chebychev distance, the nonlinear constraint of the element spacing can be simplified, and then the MGA can search a smaller solution space and improve the computing efficiency.

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Radio equipment,telecommunications equipment > Antenna > General issues > Signal is sent,the radiation system > Antenna array and antenna combination
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