稀疏孔径结构优化的蒙特卡罗反演方法

Method of Monte Carlo inversion for optimization of sparse-aperture system

  • 摘要: 对光学稀疏孔径结构与系统调制传递函数的基本关系进行了讨论。提出一种利用蒙特卡罗反演方法进行稀疏孔径结构优化设计的新方法。新方法对模型空间进行离散化后使待考察孔径结构模型的数量大大缩减,并用随机搜索和系统搜索交替的方式对模型空间进行搜索,提高了孔径结构优化的速度。为了验证新方法的有效性进行了相应的计算机仿真实验。在仿真实验中对子孔径数为3,4,5,6和7的二维稀疏孔径结构进行了优化计算。优化结果与相关文献的分析结果基本一致,从而证明了该方法的正确性。同时,对新方法的优化效率进行了测试。测试结果表明:该方法具有较高的优化效率。

     

    Abstract: The relation between sub-apertures configurations of optical sparse-aperture imaging systems and MTF is discussed. A new method, based on Monte Carlo inversion, for the aperture configuration optimization of sparse-aperture systems is proposed. The number of the aperture models under test is greatly reduced through discrete model space and optimization speed is improved through searching the model space by alternate random search and systematic search. The effectiveness of the new method was evaluated and analysed by computer simulation experiment. The optimality results of the three, four, five, six and seven sparse-aperture structures are accordance with the results of the other references. The optimization efficiency of the method was tested simultaneously. The test result shows that the method has higher optimization efficiency.

     

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