【摘要】 针对传统的基于广义互相关时延估计的平面五元十字阵被动声音定位算法定位精度低的问题,提出了运用增加采样的时延估计被动声音定位方法,对低采样率采得的信号进行内插,增加采样后再进行五元几何定位。Matlab定位仿真实验结果显示,相同采样率下,改进后的算法平均定位误差仅为传统TDOA算法的1/14,由此表明该方法较大地提高了广义互相关时延估计被动声音定位算法的精度。更多还原

【Abstract】 In order to improve the low precision of traditional Time-Difference-of-Arrival passive acoustic localization algorithm with five-microphone array in generalized cross correlation estimating method,this article proposes a new TDOA algorithm utilizing up-sampling method.This algorithm firstly conduct interpolation on the signal acquired with low sampling frequency to increase its sampling frequency,and then to localize the position of acoustic target geometrically.The simulation results of the localization process in MATLAB prove that the new algorithm improves the precision of traditional TDOA-based passive acoustic localization algorithm by 14 times.更多还原