基于遗传算法的光综合孔径圆周阵优化

从光综合孔径圆周阵列成像的基本原理出发,建立了圆周阵列的优化模型;采用改进的实数编码方法对子孔径阵列位置进行编码,运用遗传算法进行子孔径阵列的优化;以阵列的u-v覆盖点间距最大化及最小冗余度来设计目标函数,实现了8~16个子孔径二维圆周阵的优化排列;分析了二维圆周光综合孔径阵列成像系统的点扩展函数、光学传递函数和衍射成像的基本原理;对优化结果与模拟退火算法的结果进行对比,使用仿真成像程序分析其点扩展函数,并与均匀排布的圆周阵列进行对比。结果表明,采用改进的实数编码的遗传算法可以很好地解决综合孔径阵列优化的问题,相对于模拟退火算法,该方法的计算时间更短,结果更优。

Optical Synthesis Aperture Circle-Array Optimization Based on Genetic Algorithm

An optimized model of circle array was set up from the basic optical synthesis aperture circle-array imaging principle. The sub-apertures array was optimized by adopting genetic algorithm with an improved real coding method coding the location of sub-apertures array. The objective function was designed by maximizing the distances between u-v coverage dots and minimizing redundant array. The point spread function, optical transfer function and diffractive imaging of two-dimensional (2D) circle array synthetic aperture imaging system were analyzed. The optimized result of 8～16 sub-apertures on a two-dimensional circle array was obtained and compared with the result by simulated annealing algorithm. Using the emulator program, the point spread function was analyzed and contrasted to that of a uniform circle array. Results show that the improved real coding genetic algorithm can resolve the synthesis aperture array optimization well, cost less time and get an even better optimization compared with simulated annealing algorithm.