A Method of Dual Sound Source Localization Based on Uniformly Focused Transform Least Squares Method

Abstract

The invention discloses a double sound source localization method based on a consistent focusing transform least square method. According to the method, a predesigned six-element circular microphone array is applied to acquire sound source signals, and the covariance matrix of the acquired signals is acquired; a focusing transform matrix is defined by utilizing the center frequency point of frequency range, and the focusing transform matrix is solved by the least square method; and a signal spatial spectrum corresponding to each center frequency point is acquired by utilizing the center frequency points of different bandwidths, a consistent focusing matrix and a multiple signal classification method, and then the average estimation value of the signal spatial spectrum is obtained by utilizing the average value of the frequency points and a time snapshot estimation method (MUSIC) so that a sound source azimuth angle estimation value is acquired. The method is high in sound source localization estimation accuracy so that an azimuth ambiguity problem can be effectively overcome.

Description

technical field [0001] The invention relates to the field of sound source localization, in particular to a dual sound source localization method based on the consistent focus transformation least square method. Background technique [0002] In array signal processing, using Direction of Arrival (DOA) to estimate sound source position is a new research direction. In sonar detection (see literature: Wang Yan, Zou Nan, Liang Guolong. Near-field active correction method for array position[J]. Acta Physica Sinica, 2015, 64(2): 024304 1-10), speech recognition and tracking (see literature: Qi Yubo, Zhou Shihong, Zhang Renhe, Ren Yun. A β-based Passive sound source distance estimation method based on -warping transformation operator [J]. Acta Physica Sinica, 2015, 64(7): 074301 1-6), the movement of robots in unknown environments (see literature: Ju Tailiang. Based on microphone array acoustic Source localization algorithm research [D]. Doctoral dissertation (Chengdu: University o...

AI Technical Summary

Problems solved by technology

The literature (Jingdong Chen, Jacob Benesty, Yiteng Huang. Time delay estimation in room acoustic environments: an overview [J]. EURASIP Journal on Applied Signal Processing, 2006, 26503: 1-19) gives a review of TDOA orientation estimation technology; In a single sound source, due to the interference of noise, reverberation, etc., the signals collected between the microphone pairs will be affected, and the accuracy of the positioning estimation results will be reduced. The literature (Francesco Nesta, Maurizio Omologo. J]. IEEE Transactions on Audio, Speech, and Language Processing, 2012, 20(1): 246-260.) Provides an improved TDOA estimation method

Further research found that localizing multiple sound sources simultaneously is a more difficult problem

In fact, even a brief sound will cause a slight overlap in the collected speech signals, which may lead to inaccurate localization of multiple source signals (see literature: JacekP. Dmochowski, Jacob Benesty, Sofiene Affes. Broadband MUSIC: Opportunities and challenges for multiple source localization[C].IEEE Workshop on Applications of Signal Processing to Audio and Acoustics,2007:18-21)

For the multi-sound source localization problem, one is the traditional multiple signal classification (Multiple Signal Classification, MUSIC) method, which belongs to the classical subspace method. This method is aimed at narrowband signals and performs eigendecomposition according to the subspace covariance matrix of the collected signals. , and then estimate the source signal orientation (see literature: Dumidu S.Talagala, Wen Zhang.Broadband DOA EstimationUsing Sensor Arrays on Complex-Shaped Rigid Bodies[J].IEEE Transactions onAudio,Speech,and Language Processing,2013,21(8): 1573-1585.), since the frequency bandwidth of speech signals is generally [300Hz, 3000Hz], the classical subspace method is only for narrowband signals, which will lead to inaccurate sound source localization results; the other is source localization based on independent component analysis method, this method first uses the blind source separation (Blind Source Separation, BSS) method to obtain the separated single signal, and then uses the method of locating the single source signal to estimate the location (see literature: Anthony Lombard, Yuanhang Zheng, Herbert Buchner, Walter Kellermann .TDOA Estimation for Multiple Sound Sources in Noisy and Reverberant Environments Using Broadband Independent Component Analysis[J].IEEE Transactions on Audio,Speech,and Language Processing,2011,19(6):1490-1503.), but this source location method , because the voice signal is separated before positioning, the integrity of the source signal will be destroyed, the positioning result will be unstable, and the positioning accuracy will not be high

In addition, as the number of microphones increases, the positioning accuracy of the direction of arrival (DOA) estimation will also increase, but in actual situations, the linear microphone array model is usually used, which will cause positioning ambiguity problems (the sound source cannot be accurately distinguished at the front or back of the array)

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