Passive sound source two-dimensional DOA (direction of arrival) estimation method under complex environment

Abstract

The invention discloses a passive sound source two-dimensional DOA (direction of arrival) estimation method under a complex environment, comprising the steps that (1) voice signals in a room are collected by a uniform circular array; (2) the voice signals received by the uniform microphone array are preprocessed in a spectral subtraction method; (3) an M_AEDA algorithm is adopted to estimate the relative time delay of each microphone; (4) a direction coefficient vector is determined according to a direction coefficient formula; (5) the direction coefficient vector and the voice signals preprocessed in the step (2) are correspondingly multiplied to serve as an input signal for minimum variance undistorted response; (6) an minimum variance undistorted response algorithm is adopted to process the input signal; and (7) the output average power is subjected to spectrum peak search, and the estimation value of the sound source two-dimensional DOA is obtained accordingly. The passive sound source two-dimensional DOA (direction of arrival) estimation method under the complex environment has the advantages that the sound source can be accurately located under a reverberation and low signal-to-noise ratio environment; during sound source location, the location accuracy and accuracy rate are high; and the required equipment is simple, the passive sound source two-dimensional DOA estimation method can be applicable to real life in the aspects of video conference, robots and the like.

Description

technical field [0001] The invention relates to a two-dimensional DOA estimation method of a passive sound source in a complex environment. Background technique [0002] As an important part of array processing technology research, DOA (Direction-of-arrival) plays an increasingly important role in the fields of voice processing such as video conferencing, robot navigation, and voice control. Estimate the location of the signal source. For example, in a multimedia conferencing system, it is necessary to adjust the position of the camera according to the estimated spatial information of the sound source to realize the automatic recording function; in the voice call system, noise from other directions can also be removed according to the direction of the sound source, making the call clearer. [0003] Microphone array sound source localization techniques can be roughly divided into three categories: beamforming methods, subspace methods (also known as direction estimation or s...

AI Technical Summary

Problems solved by technology

Beamforming sound source localization algorithms require prior knowledge of noise and sound sources, and the amount of calculation is large; the algorithms of MUSIC and ESPRIT belong to the subspace-based methods, which have low complexity and are suitable for small reverberation (T60≤ 100ms) and there is noise, the sound source location can be completed with high positioning accuracy, but it is not suitable for the situation above moderate reverberation; most of the delay estimation methods are suitable for ideal environments

[0004] In the existing technology, more accurate time delay estimation can be obtained for reverberation and colored noise, reverberation and spatial noise, but if you want to obtain the spatial information of the sound source, you need to use algorithms such as the least squares rule and the microphone array structure. Do more complicated calculations; accurate sound source spatial information can also be obtained through the group delay MUSIC method, but it only considers the noise but not the reverberation, and the existence of the reverberation seriously affects the positioning performance of the system. Therefore, it is an urgent problem to locate the sound source in the environment of reverberation and low signal-to-noise ratio.

Images