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Multi-channel Group Sparse Linear Prediction Delay Estimation Method

A time delay estimation and linear prediction technology, which is applied to radio wave measurement systems, measurement devices, instruments, etc., can solve the problems of reducing estimation performance, not comprehensively utilizing multi-channel space and time prediction whitening capabilities, etc.

Inactive Publication Date: 2017-12-05
SOUTHWEAT UNIV OF SCI & TECH
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Problems solved by technology

However, this method pre-whitens the data of the two channels separately in the case of dual-channel, that is, only pre-whitens the data in time, and does not comprehensively utilize the whitening ability of multi-channel space and time prediction, thereby reducing the estimation performance of the method

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[0044] In order to better illustrate the technical content of the present invention, the signal model and method derivation used in the present invention will be described first.

[0045] Suppose a broadband sound source radiates a plane wave signal, and an array of M microphones is used to receive the sound signal. If the first microphone is chosen as the reference point, the signal sample x picked up by the mth microphone at time n m (n) can be expressed as:

[0046] x m (n) = α m s[n-t-f m (τ)]+w m (n) (1)

[0047] Among them, m=1,2,...,M, α m is the attenuation factor caused by the transmission effect of the acoustic signal, s(n) is the unknown zero-mean causal broadband sound source signal, t is the transmission time from the sound source to the first microphone, w m (n) is the additive noise on the mth microphone, assuming that the noise is not related to the sound source signal and the noise of other microphones, τ is the time delay between the sound source signa...

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Abstract

The invention discloses a multi-channel group sparsity linear prediction and time delay estimation method. A multi-channel cross correlation coefficient is calculated by adopting various possible time delay values, and time delay corresponding to a maximum value of the square of the multi-channel cross correlation coefficient is taken as a time delay estimation value. A calculation method of the multi-channel cross correlation coefficient comprises the steps that a signal frame with the length of L is intercepted from a sound signal picked by each microphone, and after time shifting is performed on the signal frames, the signal frames are stacked up into a signal vector and a signal matrix; a time delay estimation model is built according to an F / l<1, 2> norm optimization criteria; a group sparsity prediction coefficient matrix is solved; a prediction error correlation matrix is calculated, and the multi-channel cross correlation coefficient is calculated according to the prediction error correlation matrix. According to the method, the F / l<1, 2> norm optimization criteria is built through the group sparsity characteristic of the prediction coefficient matrix vector, the multi-channel cross correlation coefficient method and a multi-channel space-time prediction method are integrated, and the time delay estimation performance is improved by jointly applying the whitening capacity of space and time linear prediction.

Description

technical field [0001] The invention belongs to the technical field of sound source localization, and more specifically relates to a multi-channel group sparse linear prediction time delay estimation method. Background technique [0002] Delay estimation is to use the acoustic signal picked up by the microphone array to estimate the arrival time difference between the sound source and each array element, and plays an extremely important role in the sound source localization and tracking of radar, sonar and hands-free voice communication systems. Common time delay estimation methods include generalized cross-correlation method, blind channel identification method, information theory method, time delay estimation based on certain characteristics of speech signals, etc. However, in indoor acoustic environments, time delay estimation based on microphone arrays is a challenging task due to the adverse effects of noise and reverberation. [0003] In order to improve the robustnes...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S5/22G01S5/26
CPCG01S5/22G01S5/26
Inventor 何宏森陈景东杨涛
Owner SOUTHWEAT UNIV OF SCI & TECH
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