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中文摘要：
针对有阵元间距上、下限约束与口径约束的稀布直线阵列综合问题,提出了一种基于向量映射的改进遗传算法.该方法将遗传变量与阵元间距按照特定的关系进行映射,从而使阵元间距的强约束优化问题转换为仅含遗传变量上、下限约束的优化问题,从根本上避免了遗传操作中的不可行解.通过抑制天线峰值旁瓣电平（PSLL）的稀布阵仿真,验证了该方法的有效性和稳健性,且能获得比现有方法更高的优化效率.
英文摘要：
Considering a linear sparse array with the constraints of the array aperture,the minimum and the maximum element spacing,an improved genetic algorithm（IGA）for the element position synthesis is proposed to reduce the peak sidelobe level（PSLL）of the array.In order to avoid the infeasible solution during the optimization,a special vector mapping between the element spaces and their gene coding is utilized by the IGA.Then the strong constrained optimization problem is transformed to an optimization problem with only upper and lower limit,and the infeasible solution is naturally avoided.The computational cost of the IGA can be far less than that of a recently reported modified real genetic algorithm.And the efficiency and the robustness of the IGA have been illustrated clearly from the simulations.
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