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A Sound Source Localization Method Based on Frequency Divider and Time Difference of Arrival
- Source :
- Applied Sciences, Vol 13, Iss 10, p 6183 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- In recent years, sound source localization, as a passive localization technique with higher safety and convenience compared with other localization techniques such as active emission of electromagnetic waves, has received more and more attention in academia. This paper researches and improves the far-field sound source localization algorithm based on the generalized cross-correlation method (GCC) Time Difference of Arrival (TDOA) estimation algorithm and completes the design and implementation of the microphone array sound source localization system. This paper adds a frequency divider to the traditional generalized correlation time delay estimation algorithm for pre-processing, sampling, and localization of sound source acoustic waves and adopts a low-cost microphone array deployment scheme as far as possible to improve the flexibility and practicality of the localization system; at the same time, the “Minimum Sphere Method” is used at the back end of the algorithm to classify the localization coordinates at different frequencies and, finally, output reasonable sound source coordinates. In the back-end of the algorithm, the “Minimum Sphere Method” is used to classify the localization coordinates at different frequencies and, finally, output the reasonable sound source coordinates. The experimental results show that the sound source localization system designed in this paper has good performance in terms of localization accuracy and cost-effectiveness and overcomes the failure of the generalized mutual correlation algorithm in the original application of high noise environment and multi-source environment localization.
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 13
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Applied Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1ec6acf64f94a9591ddace4a0a9c318
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/app13106183