基于粒子群优化的TDOA声源定位方法

doi:10.16180/j.cnki.issn1007-7820.2023.09.004

摘要/Abstract

摘要：

针对平面麦克风阵列的声源三维坐标估计问题,文中在TDOA(Time Difference of Arrival)声源定位算法中引入粒子群优化算法进行位置估计。利用PHAT(Phase Transform)加权函数的广义互相关法计算得到时延差的真实值,结合麦克风的坐标位置,通过几何关系计算出假设声源到达麦克风之间的时延差的估计值。设计时延真实值和估计值差值的平方和为粒子适应度函数,利用粒子群优化算法搜索空间中符合适应度函数的声源点,实现声源位置估计。仿真结果表明,在计算速度与球形插值法相近的情况下,文中所提算法比球形插值法具有更好的鲁棒性和抗噪性。

关键词: 麦克风阵列, 粒子群优化算法, TDOA, 声源定位, 时延估计, 位置估计, 广义互相关, 球形插值法

Abstract:

In order to solve the problem of 3D coordinate estimation of sound source based on planar microphone array, this study introduces particle swarm optimization algorithm in TDOA(Time Difference of Arrival) sound source localization algorithm. The true value of the delay difference is calculated using the generalized cross-correlation method of the PHAT(Phase Transform) weighting function. Combined with the coordinate position of the microphone, the estimated value of the delay difference between the hypothetical sound source arriving at the microphone is calculated through the geometric relationship. The sum of the squares of the error between the actual value and the estimated value of the design delay is the particle fitness function. The particle swarm optimization algorithm is used to search for the sound source points in the space that conform to the fitness function, so as to realize the sound source position estimation. The simulation results show that the proposed algorithm has better robustness and noise resistance than the spherical interpolation method when the calculation speed is similar to that of the spherical interpolation method.

Key words: microphone array, particle swarm optimization algorithm, TDOA, sound source localization, delay estimation, location estimation, generalized cross correlation, spherical interpolation method

中图分类号:

TP912

张大桂,周志峰,张怡,王立端. 基于粒子群优化的TDOA声源定位方法[J]. 电子科技, 2023, 36(9): 21-28.

ZHANG Dagui,ZHOU Zhifeng,ZHANG Yi,WANG Liduan. TDOA Sound Source Localization Method Based on Particle Swarm Optimization Algorithm[J]. Electronic Science and Technology, 2023, 36(9): 21-28.

图/表 12

图1

图2

图3

图4

表1

图5

图6

图7

表2

表3

表4

表5

参考文献 18

[1]	林焕楠. 分布式麦克风阵列声源跟踪方法的研究[J]. 电子科技, 2017, 30(6):82-84.
	Lin Huannan. Distributed microphone array sound source tracking method[J]. Electronic Science and Technology, 2017, 30(6):82-84.
[2]	杨旭, 行鸿彦, 张军, 等. 基于七元传声器阵列的声源定位算法及性能分析[J]. 传感技术学报, 2019, 32(7):1034-1039.
	Yang Xu, Xing Hongyan, Zhang Jun, et al. Performance analysis of sound source localization algorithm based on seven-element microphone array[J]. Chinese Journal of Sensors and Actuators, 2019, 32(7):1034-1039.
[3]	张智, 邓建交, 刘英杰, 等. 交叉层波束形成方法的发动机噪声源识别[J]. 声学技术, 2021, 40(5):680-687.
	Zhang Zhi, Deng Jianjiao, Liu Yingjie, et al. Identification of engine noise source by beamforming based cross-layer method[J]. Technology Acoustics, 2021, 40(5):680-687.
[4]	刘海涛, 陈永华, 林艳明, 等. 基于TDOA多声源定位的虚假声源消除方法[J]. 振动、测试与诊断, 2021, 41(2):319-326.
	Liu Haitao, Chen Yonghua, Lin Yanming, et al. Multi-source localization method of eliminating phantom sound sources based on TDOA[J]. Journal of Vibration, Measurement and Diagnosis, 2021, 41(2):319-326.
[5]	Armansyah R F, Ikram F D, Nolika S S, et al. Efficient sound-source localization system using low cost TDOA computation[C]. Bandung: Proceedings of the International Symposium on Electronics and Smart Devices, 2016:315-319.
[6]	Knapp C, Carter G. The generalized correlation method for estimation of time delay[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1976, 24(4):320-327. doi: 10.1109/TASSP.1976.1162830
[7]	程方晓, 刘璐, 姚清华, 等. 基于改进时延估计的声源定位算法[J]. 吉林大学学报(理学版), 2018, 56(3):681-687.
	Cheng Fangxiao, Liu Lu, Yao Qinghua, et al. Acoustic source localization algorithm based on improved time delay estimation[J]. Journal of Jilin University(Science Edition), 2018, 56(3):681-687.
[8]	王楷, 宗志亚, 孙小惟, 等. 改进的自适应特征值分解声源定位算法研究[J]. 仪器仪表学报, 2013, 34(6):42-47.
	Wang Kai, Zong Zhiya, Sun Xiaowei, et al. Study on improved adaptive eigenvalue decomposition algorithm for acoustic source localization[J]. Chinese Journal of Scientific Instrument, 2013, 34(6):42-47.
[9]	屈顺彪, 俞华, 芦竹茂, 等. 面向声源定位的改进广义互相关时延估计方法[J]. 导航定位与授时, 2021, 8(6):118-124.
	Qu Shunbiao, Yu Hua, Lu Zhumao, et al. Improved generalized cross-correlation time delay estimation method forsound source localization[J]. Navigation Positioning and Timing, 2021, 8(6):118-124.
[10]	李保伟, 张兴敢. 基于广义互相关改进的麦克风阵列声源定位方法[J]. 南京大学学报(自然科学), 2020, 56(6):917-922.
	Li Baowei, Zhang Xinggan. Improved microphone array sound source localization method based on generalized cross correlation[J]. Journal of Nanjing University (Natural Science), 2020, 56(6):917-922.
[11]	姜志鹏, 陈正宇, 刘影, 等. TOA定位算法非线性优化问题研究[J]. 传感技术学报, 2015, 28(11):1716-1719.
	Jiang Zhipeng, Chen Zhengyu, Liu Ying, et al. Study on nonlinear optimization for TOA location algorithm[J]. Chinese Journal of Sensors and Actuators, 2015, 28(11):1716-1719.
[12]	黄静, 胡馨月. 基于麦克风阵列的室内三维声源定位优化算法[J]. 计算机系统应用, 2021, 30(9):212-218.
	Huang Jing, Hu Xinyue. Indoor 3D sound source localization optimization algorithm based on microphone array[J]. Computer System Application, 2021, 30(9):212-218.
[13]	张焕强, 黄时春, 蒋伟康. 基于传声器阵列的汽车鸣笛声定位算法及实现[J]. 噪声与振动控制, 2018, 38(3):10-14. doi: 10.3969/j.issn.1006-1355.2018.03.002
	Zhang Huanqiang, Huang Shichun, Jiang Weikang. Car horn localization algorithm and its implementation based on microphone arrays[J]. Noise and Vibration Control, 2018, 38(3):10-14. doi: 10.3969/j.issn.1006-1355.2018.03.002
[14]	朱金福, 马睿馨, 彭安娜, 等. 基于粒子群优化算法的机场群航班优化配置研究[J]. 重庆交通大学学报(自然科学版), 2021, 40(9):1-8.
	Zhu Jinfu, Ma Ruixin, Peng Anna, et al. Flight schedule optimization in multi-airport system based on particle swarm optimization algorithm[J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(9):1-8.
[15]	胡骏, 乐英高, 蔡绍堂, 等. 基于改进变异粒子群算法的TDOA/AOA定位研究[J]. 组合机床与自动化加工技术, 2019(4):14-19.
	Hu Jun, Le Yinggao, Cai Shaotang, et al. Research on TDOA/AOA location algorithm based on improve mutational particle swarm optimization[J]. Modular Machine Tool and Automatic Manufacturing Technique, 2019(4):14-19.
[16]	王万良, 金雅文, 陈嘉诚, 等. 多角色多策略多目标粒子群优化算法[J]. 浙江大学学报(工学版), 2022, 56(3):531-541.
	Wang Wanliang, Jin Yawen, Chen Jiacheng, et al. Multi-objective particle swarm optimization algorithm with multi-role and multi-strategy[J]. Journal of Zhejiang University(Engineering Edition), 2022, 56(3):531-541.
[17]	冯茜, 李擎, 全威, 等. 多目标粒子群优化算法研究综述[J]. 工程科学学报, 2021, 43(6):745-753.
	Feng Qian, Li Qing, Quan Wei, et al. Overview of multi-objective particle swarm optimization algorithm[J]. Chinese Journal of Engineering, 2021, 43(6): 745-753.
[18]	翟彦蓉, 黄欢, 张申, 等. 改进粒子群优化算法在TDOA定位中的应用[J]. 传感器与微系统, 2013, 254(4):145-148.
	Zhai Yanrong, Huang Huan, Zhang Shen, et al. Application of improved particle swarm optimization algorithm in TDOA positioning[J]. Transducer and Microsystem Technologies, 2013, 254(4):145-148.

	粒子群空间搜索				球形插值
	x轴误差	y轴误差	z轴误差	相对误差	x轴误差	y轴误差	z轴误差	相对误差
均值	9.363 6	7.367 7	8.131 7	8.059 4	15.855 1	12.176 3	13.529 6	13.514 3
方差	55.791 2	33.339 5	38.781 2	38.997 0	136.356 0	70.136 3	72.877 5	82.301 5

	粒子群空间搜索				球形插值
	x轴误差	y轴误差	z轴误差	相对误差	x轴误差	y轴误差	z轴误差	相对误差
均值	23.602 5	18.780 4	20.410 5	20.111 0	49.664 9	39.902 9	42.039 7	42.129 1
方差	589.398 1	383.209 9	343.166 4	315.485 7	819.315 8	589.350 3	309.363 7	299.870 8

	粒子群空间搜索				球形插值
	x轴误差	y轴误差	z轴误差	相对误差	x轴误差	y轴误差	z轴误差	相对误差
均值	30.780 5	25.190 2	25.817 7	26.197 7	77.170 2	61.881 6	67.200 4	66.931 7
方差	763.205 0	482.129 3	501.322 1	523.465 4	647.410 6	603.945 9	305.998 7	296.390 7

	粒子群空间搜索				球形插值
	x轴误差	y轴误差	z轴误差	相对误差	x轴误差	y轴误差	z轴误差	相对误差
均值	43.029 5	32.169 9	35.915 6	35.888 9	101.215 4	84.410 5	81.808 3	80.892 1
方差	1232.500 0	800.124 9	1 168.500 0	1 041.900 0	5161.700 0	8 901.500 0	242.606 1	243.940 2