电子科技 ›› 2023, Vol. 36 ›› Issue (7): 24-31.doi: 10.16180/j.cnki.issn1007-7820.2023.07.004

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基于遗传算法的平面麦克风阵列构型优化方法

张大桂1,周志峰1,张怡2   

  1. 1.上海工程技术大学 机械与汽车工程学院,上海 201620
    2.上海市松江区新桥职业技术学校,上海 201612
  • 收稿日期:2022-01-12 出版日期:2023-07-15 发布日期:2023-06-21
  • 作者简介:张大桂(1996-),男,硕士研究生。研究方向:阵列信号处理算法。|周志峰(1976-),男,博士,副教授。研究方向:计算机测控、数字信号处理。
  • 基金资助:
    上海市科学技术委员会科研基金(17511106700)

Optimization Method of Planar Microphone Array Configuration Based on Genetic Algorithm

ZHANG Dagui1,ZHOU Zhifeng1,ZHANG Yi2   

  1. 1. School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science, Shanghai 201620,China
    2. Shanghai Songjiang Xinqiao Vocational and Technical School,Shanghai 201612,China
  • Received:2022-01-12 Online:2023-07-15 Published:2023-06-21
  • Supported by:
    Scientific Research Fund of Science and Technology Commission of Shanghai Municipality(17511106700)

摘要:

在有限平面范围内使用较少的麦克风数量设计阵列构型,使得阵列具有更好的性能是声源定位系统中需解决的首要问题。文中提出了一种基于遗传算法的阵列优化方法,该方法以阵列波束方向图的主瓣宽度和旁瓣级为基础,兼顾麦克风的数量设计了遗传算法的适应度目标函数,通过改进遗传算法,使其在麦克风阵列优化的应用中得到实现。仿真结果表明,与传统的十字形和矩形平面均匀阵列相比,优化后的阵列构型在保证阵列性能的同时,可以减少麦克风的使用数量。相比于粒子群优化算法,改进遗传算法优化后的阵列具有更优异的性能。

关键词: 麦克风阵列, 遗传算法, 波束方向图, 主瓣, 旁瓣, 主瓣宽度, 旁瓣级, 粒子群算法

Abstract:

In the sound source localization system, the first problem to be solved is to use a smaller number of microphones and design an array configuration with better performance in a limited plane range. This sutdy proposes an array optimization method based on genetic algorithm to solve the problem. The design of the fitness objective function of the genetic algorithm comprehensively considers the array beam pattern, the width of the main lobe, the level of the side lobe and the number of microphones. By improving the genetic algorithm, the genetic algorithm can be realized in the application of microphone array optimization. The simulation results show that: compared with the traditional cross-shaped and rectangular planar regular arrays, the optimized array configuration can reduce the number of microphones used while ensuring the performance of the array. Compared with the particle swarm optimization algorithm, the array optimized by the improved genetic algorithm has better performance.

Key words: microphone array, genetic algorithm, beam pattern, main lobe, side lobe, main lobe width, sidelobe level, particle swarm algorithm

中图分类号: 

  • TP912