Sound source positioning method and system based on pattern clustering

Abstract

The invention relates to a sound source positioning method and system based on pattern clustering. The method comprises the steps: extracting effective signals through employing the Mahalanobis distance, carrying out grouping, obtaining a positioning data set of the spatial position and energy of a sound source by employing an SRP-PHAT method according to the wave propagation speed, carrying out clustering on the positioning data set by employing a DBSCAN method, determining the clustering category corresponding to the maximum average energy as a to-be-fused clustering category, calculating the sum of the average energy and the initial energy of the to-be-fused clustering category, determining a loss function value, updating the wave propagation speed when the loss function value is not smaller than a loss threshold value, repeating the above steps, and when the loss function value is smaller than the loss threshold value, fusing all spatial position coordinates in the to-be-fused clustering category by utilizing a PCA weighted fusion method, and determining the fused spatial position coordinate as sound source position. According to the method, a speed model does not need to be established in advance, and the positioning precision of sound source positioning is improved through pattern classification and fusion.

Description

technical field [0001] The invention relates to the field of sound source localization, in particular to a sound source localization method and system based on pattern clustering. Background technique [0002] Sound source localization is widely used in many fields. The current sound source localization methods can be divided into two categories in terms of localization principles. One is a two-step positioning method based on arrival time / arrival time difference estimation, and the other is a one-step positioning method based on beamforming. [0003] The positioning accuracy of the two-step positioning method is limited by the time difference estimation accuracy and the positioning algorithm performance. High-precision arrival time / arrival time difference estimation requires high-quality data. Therefore, the anti-interference ability of the two-step positioning method is poor. [0004] The one-step positioning method can make full use of the time, energy and frequency i...

AI Technical Summary

Problems solved by technology

However, SRP-PHAT will generate a large number of local extrema in the positioning space to form false sound sources and reduce the reliability of sound source localization

[0005] Both one-step positioning and two-step positioning methods are based on model-driven positioning methods, which require the sound propagation velocity to be known or estimated in advance, and accurate velocity models are often difficult to obtain, thus affecting positioning accuracy

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