Accurate acoustic source localization at a low sampling rate (less than 10 kHz) is still a challenging problem for small portable systems, especially for a multitasking micro-embedded system. A modification of the generalized cross-correlation (GCC) method with the up-sampling (US) theory is proposed and defined as the US-GCC method, which can improve the accuracy of the time delay of arrival (TDOA) and source location at a low sampling rate. In this work, through the US operation, an input signal with a certain sampling rate can be converted into another signal with a higher frequency. Furthermore, the optimal interpolation factor for the US operation is derived according to localization computation time and the standard deviation (SD) of target location estimations. On the one hand, simulation results show that absolute errors of the source locations based on the US-GCC method with an interpolation factor of 15 are approximately from 1/15- to 1/12-times those based on the GCC method, when the initial same sampling rates of both methods are 8 kHz. On the other hand, a simple and small portable passive acoustic source localization platform composed of a five-element cross microphone array has been designed and set up in this paper. The experiments on the established platform, which accurately locates a three-dimensional (3D) near-field target at a low sampling rate demonstrate that the proposed method is workable.

No abstract

No abstract

No abstract

Compared with the acoustic source localization based on single array, the multi-microphone arrays have the higher robustness and accuracy in complex environment. However, it is still one of the challenges to obtain an optimal result by fusing multiple groups of the position information from multiple sub-arrays. To solve this problem, this paper introduced the Brayden Fletcher Goldfarb Shanno (BFGS) method into the localization method based on multi-microphone arrays. The BFGS method is used to an optimal objective function, which is related to the direction of the acoustic source. In addition, several initial value selection schemes of BFGS method are proposed and compared to select a best initial value. The experiments were carried out on the self-developed platform with four four-element sub-microphone arrays.