基于遗传算法的HBT干涉声定位阵列优化

Optimization of HBT interferometric acoustic localization array based on genetic algorithm

针对声学定位性能易受麦克风阵列结构影响的问题,提出一种适用于汉伯瑞·布朗和特威斯(HBT)干涉定位的遗传算法阵列结构优化方案。该方法以相邻两阵元距离差值为个体构造中间种群,按基因由升序排序转换到距离间隔种群。接着以方向图函数为适应度函数,构造基于最大旁瓣电平的目标函数,将麦克风间距作为优化对象,把目标函数转化为无约束优化问题。通过遗传算法求解该问题,得到定位性能最高的阵列结构。仿真结果表明七元阵优化效果最为显著,近点定位旁瓣峰值由0.4374降低至0,远点定位干扰旁瓣数降低至0,该方法可以有效提高定位精度。

A genetic algorithm array structure optimization scheme for Hanbury-Brown-Twiss(HBT)interference localization is proposed for the problem that the acoustic localization performance is easily affected by the microphone array structure.The method constructs intermediate populations with the distance difference between two adjacent array elements as individuals,and converts them to distance-spaced populations by gene sorted by ascending order.Then,the objective function based on the maximum parametric level is constructed with the directional map function as the fitness function,and the microphone spacing is taken as the optimization object to transform the objective function into an unconstrained optimization problem.The problem is solved by genetic algorithm to obtain the array structure with the highest localization performance.The simulation results show that the optimization effect of the seven-element array is the most significant,and the peak value of the near-point positioning partials is reduced from 0.4374to 0,and the number of distant-point positioning interference partials is reduced to 0.This method can effectively improve the positioning accuracy.