基于高拉伸度遗传算法的相关干涉仪测向算法

Direction finding algorithm of correlated interferometer based on genetic algorithm with high degree of stretching

针对相关干涉仪测向中相位差模糊导致的强非线性问题,提出一种基于高拉伸度的改进遗传算法,该算法以遗传算法中择优选取机制为基础,通过定义拉伸度,根据相关干涉仪测向中相关函数及其对自变量的偏导数在目标方向附近均趋近于0的特性,设计新的适应度函数,增大全局最大值附近适应度函数的拉伸度,扩大与其他方向的适应度的差距,从而实现对选取机制的优化。仿真实验表明,该算法复杂度低,当测向精度基本相同时,测向时间约为网格法的1/600,且具有良好的适用性,可以广泛应用于其他求解最大值的问题中。

To cope with the problem of strong-nonlinearity resulting from fuzzy phase difference,an improved genetic algorithm(GA)based on high degree of stretching is proposed.Based on merit-based selection mechanism in GA,the algorithm designs new fitness functions by defining the degree of stretching and utilizing the characteristic that correlation function and its partial derivative are both close to zero.The algorithm could optimize the selection mechanism by means of increasing the degree of stretching of fitness functions around the global maximum and widening the gap among this function and fitness functions from other directions.Simulation experiments indicate that,compared with grid method,the improved GA performs better in algorithm complexity and spends only one six-hundredth of the time which grid method uses.And the algorithm could be widely applied to solve other problems about searching the global maximum of the function of nonlinear correlation.