多声源定位的关联模糊消除方法研究  

Method of association ambiguity elimination for multi-source localization

作　　者：刘海涛 陈永华[1,3] 周家盛 程贤福 肖乾 LIU Hai-tao;CHEN Yong-hua;ZHOU Jia-sheng;CHENG Xian-fu;XIAO Qian(School of Mechanotronics and Vehicle Engineering,East China Jiaotong University,Nanchang 330013,China;Tsinghua University Suzhou Automotive Research Institute,Suzhou 215131,China;School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,China)

机构地区：[1]华东交通大学机电与车辆工程学院,江西南昌330013 [2]清华大学苏州汽车研究院,江苏苏州215131 [3]华南理工大学土木与交通学院,广东广州510640

出　　处：《振动工程学报》2023年第1期138-146,共9页Journal of Vibration Engineering

基　　金：国家自然科学基金资助项目(51765017,12104153);江西省自然科学基金资助项目(20202BABL204043);江西省主要学科学术和技术带头人培养计划资助项目(20204BCJL23034);华东交通大学科研基础经费资助项目(26541022)。

摘　　要：基于到达时差(Time Difference of Arrival,TDOA)的多声源定位中,由于麦克风阵列对测量的TDOA值无法与目标声源进行关联,声源定位过程会产生关联模糊,从而影响多声源定位结果的精度。针对这一问题,提出基于阵列重构的多声源关联模糊消除方法。通过广义互相关(Generialized Cross⁃Correlation,GCC)算法估计麦克风阵列的TDOA值,再利用排序算法获得定位麦克风阵列所有可能的TDOAs序列,并基于Chan算法估计所有可能的声源。通过轮换定位麦克风阵列的参考麦克风,构造多组校验子阵列,利用真实声源与阵列麦克风的相对位置关系来滤除虚假声源。对于不同校验子阵列筛选出的所有声源位置,以出现频数最大化原则再次进行冗余校验,从而提升最终筛选真实声源的准确性。仿真及实验结果表明,该方法能够以最少数量常规麦克风有效消除多声源定位中的虚假声源。在同等麦克风数量的情况下,该方法的定位精度及定位鲁棒性高于对比方法。For the multi-source localization based on TDOA,because the measured TDOA values from the microphone array can⁃not associate with the target sources,the process of source localization will produce association ambiguity,thus affecting the accu⁃racy of multi-source localization results.The GCC algorithm is used to estimate TDOA values of microphone array.Then all possi⁃ble TDOAs sequences of microphone array are obtained by permutation algorithm,and all possible sound sources can be estimated based on Chan algorithm.A group of check sub-arrays is constructed by switching the reference microphone in the array,and the phantom sound sources are filtered out by the relative position relationship between the true sound sources and the array micro⁃phones.For all sound source locations screened by different check sub-arrays,redundancy check is carried out again according to the principle of maximum occurrence frequency,so as to improve the accuracy of the final real sound sources.The simulation and experiment results show that the proposed method can effectively eliminate the phantom sound sources in multi-sources localization by using the least number of conventional microphones.The localization accuracy and localization robustness of the proposed meth⁃od are higher than that of the comparison method with the same number of array microphones.

关 键 词：多声源定位 到达时差(TDOA) 关联模糊 互相关算法 CHAN算法 

分 类 号：TB52[理学—物理]