CN102866385A - Multi-sound-source locating method based on spherical microphone array - Google Patents

Multi-sound-source locating method based on spherical microphone array Download PDF

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CN102866385A
CN102866385A CN2012103310091A CN201210331009A CN102866385A CN 102866385 A CN102866385 A CN 102866385A CN 2012103310091 A CN2012103310091 A CN 2012103310091A CN 201210331009 A CN201210331009 A CN 201210331009A CN 102866385 A CN102866385 A CN 102866385A
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value
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subspace
sound
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CN102866385B (en
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宋涛
黄青华
彭昌友
许广宏
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University of Shanghai for Science and Technology
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Abstract

The invention discloses a multi-sound-source locating method based on a spherical microphone array, and the method comprises the following steps of firstly conducting spherical harmonics decomposition for high-order sound fields collected by a spherical microphone array, and building a noise-contained sound source signal model received by a spherical harmonics domain array; then expressing a covariance matrix of data received by the array; classifying the covariance matrix according to a subspace decomposition method to obtain two mutually-orthogonal signal subspace and noise subspace; utilizing the orthogonality of the signal subspace and the noise subspace to define a guide vector of the signal subspace, and extracting one characteristic vector of the noise subspace to build a space azimuth spectrum; and finally searching a spectrum peak position of an azimuth spectrum function, and determining a space azimuth of a sound source. The method utilizes a three-dimensional space rotary symmetric structure of the spherical microphone array to adequately sample the sound field, so that the operation quantity is remarkably reduced through the high-resolution spectrum estimation and dimensional-reduced noise subspace, the sound source azimuth is accurately estimated, and the method can be widely applied to the fields such as a voice signal processing field.

Description

A kind of many sound localization methods based on spherical microphone array
Technical field
The present invention relates to the many sound localization methods of a kind of three dimensions based on spherical microphone array, can be widely used in the fields such as voice signal processing.Specifically based on dimensional orientation spectrum estimation principle, in conjunction with reduced order subspace, the humorous territory of ball array received signal model is carried out the covariance computing, divide mutually orthogonal subspace, extract the noise subspace proper vector, construct " needle-like " spatial spectrum peak, finally obtain the position of sound source by spectrum peak search.Compare with traditional sound localization method, this method takes full advantage of high resolving power characteristic and the low characteristics of reduced order subspace operand that the dimensional orientation spectrum is estimated, reaches fast, accurately auditory localization effect.
Background technology
The auditory localization technology, namely definite locus that is in simultaneously a plurality of interested signals in a certain zone, space is one of important technology of Array Signal Processing.Utilize microphone array the orientation of sound-source signal is estimated it is the basic skills of auditory localization, it is that one group of microphone sensor is arranged on the diverse location of space by certain way, forms microphone array; Receive the spatial sound source signal with microphone array, the signal of pair array reception is processed again, extracts useful signal characteristic, finally obtains the azimuth information of signal source by certain Algorithm for Solving again.
Spherical microphone array is compared with geometric array such as traditional one dimension straight line microphone array, two dimensional surface microphone arrays, the advantage that has is: the wave beam formation of three-dimensional rotational symmetry structure, high spatial resolution, space any direction and ball Fourier Orthogonal Decomposition framework etc., can sample more fully to sound field, therefore have more advantage aspect three-dimensional many auditory localizations.
The steerable beam that present sound localization method for spherical microphone array mainly is based on the time domain forms, or based on the decomposition of plane wave on the humorous territory of ball.The former forms wave beam to the filtration combined weighted summation of sound-source signal that spherical microphone array collects, and then comes lead beam by search sound source possible position, obtains making that wave beam has a peak power output is the orientation of sound source.The shortcoming of the spherical microphone array sound localization method that forms based on steerable beam is: need to carry out global search, operand is very big, so be difficult to realize; Spherical microphone array sound localization method based on decomposition of plane wave is: at first, sound field is carried out the humorous decomposition transform of ball in the humorous territory of ball, obtain the acoustic pressure of direct projection sound field, then, according to the principle that can occur the peak point of plane of incidence wave amplitude in sound source direct projection direction, the maximum value of search plane of incidence wave amplitude in spherical space, spherical surface position coordinate corresponding to maximum value is the orientation of sound source.Locating effect when the shortcoming of the method is more to sound source is poor, and the precision of auditory localization mainly is subjected to the impact of employed spherical microphone array exponent number size, increase the number of microphone, although can improve the exponent number of array, but increased simultaneously the way of signals collecting, caused the increase of computation complexity.Also having a kind of time delay to estimate also is a kind of effective auditory localization technology, but it is subjected to noise larger, and the array element distance of spherical microphone array is little, causes also to be difficult in the reality obtain accurate time delay, does not have practical value.
Summary of the invention
The objective of the invention is the deficiency for the prior art existence, a kind of many sound localization methods based on spherical microphone array are provided, the method can overcome the deficiency that the classic method calculated amount is large, bearing accuracy is not high, and significantly computation reduction is accurately estimated the sound bearing.
In order to achieve the above object, design of the present invention is: at first spherical microphone array is gathered the high-order sound field and carry out the spheric harmonic function decomposition, set up the Noise source signal model of the humorous territory of ball array received; Then express the covariance matrix of array received data; Then, according to digital signal processing covariance matrix is divided, obtained two mutually orthogonal signal subspaces and noise subspace; Recycle the orthogonality of above-mentioned signal subspace and noise subspace, the steering vector of definition signal subspace extracts a proper vector of noise subspace, structure dimensional orientation spectrum; At last, search for the spectrum peak position of orientation spectral function, determine the dimensional orientation of sound source.
According to the foregoing invention design, the technical solution used in the present invention is:
A kind of many sound localization methods based on spherical microphone array mainly comprise following step:
(1), set up spherical coordinate system, the position of each array element on the spherical microphone array is described, the spheric harmonic function that spherical microphone array gathers high-order sound field acoustic pressure is set;
(2), set up the humorous territory of ball array received Noise source signal model;
(3), utilize the second-order statistics of signal, the humorous territory of the ball signal model of setting up is carried out the covariance computing, draw the covariance matrix that spherical microphone array receives signal;
(4), the covariance matrix that obtains in the step (3) is carried out feature decomposition, obtain respectively signal subspace
Figure 2012103310091100002DEST_PATH_IMAGE002
, noise subspace
Figure 2012103310091100002DEST_PATH_IMAGE004
(5), utilize the orthogonality of noise subspace and signal subspace, definition signal subspace
Figure 122997DEST_PATH_IMAGE002
Steering vector
Figure 2012103310091100002DEST_PATH_IMAGE006
, structure normed space azimuth spectrum , from step (4), extract a noise subspace proper vector in the resulting noise subspace, structure dimensional orientation spectrum
Figure 2012103310091100002DEST_PATH_IMAGE010
(6), search azimuth spectrum
Figure 351722DEST_PATH_IMAGE010
Spectrum peak position, extract search value corresponding to peak value, determine the estimated value of sound bearing.
A kind of many sound localization methods based on spherical microphone array of the present invention compared with prior art, have following apparent outstanding substantive distinguishing features and remarkable advantage: the method is utilized spherical microphone array three dimensions rotational symmetry structure, sound field is sampled fully, adopt the spatial noise of High-Resolution Spectral Estimation and dimensionality reduction, when not increasing operand, estimate exactly the sound bearing, can be widely used in the fields such as voice signal processing.
Description of drawings
Fig. 1 is the process flow diagram of a kind of many sound localization methods based on spherical microphone array of the present invention;
Fig. 2 is the spherical coordinate system synoptic diagram that spherical microphone array of the present invention gathers the space sound field;
Fig. 3 is the dimensional orientation spectrogram of spectrum peak search method of the present invention;
Fig. 4 is the process flow diagram of spectrum peak search method of the present invention.
Embodiment
In order to understand better technical scheme of the present invention, below be described in further detail:
The flow process of this method is referring to Fig. 1, a kind of many sound localization methods based on spherical microphone array of the present invention, utilize spherical microphone array to gather the space sound field, carry out many auditory localizations in conjunction with the noise subspace of Estimation of Spatial Spectrum technology and dimensionality reduction, its implementation step is as follows:
(1), set up spherical coordinate system, the position of each array element on the spherical microphone array is described, the spheric harmonic function that spherical microphone array gathers high-order sound field acoustic pressure is set, it is specific as follows:
Set up spherical coordinate system, as shown in Figure 2, among the figure,
Figure 2012103310091100002DEST_PATH_IMAGE012
The point representative is distributed in radius and is
Figure 2012103310091100002DEST_PATH_IMAGE014
Spherical microphone array on separate, isotropic array element, the ading up to of array element
Figure 2012103310091100002DEST_PATH_IMAGE016
Coordinate origin oBe chosen for the centre of sphere of spherical microphone array, be positioned at sphere
Figure 69143DEST_PATH_IMAGE012
The array element at some place adopts its angle of pitch and position angle
Figure 2012103310091100002DEST_PATH_IMAGE018
Expression.When spherical microphone array gathered sound field, what microphone recorded was the acoustic pressure information of sound field, and wave number is ,
Figure 2012103310091100002DEST_PATH_IMAGE022
,
Figure 2012103310091100002DEST_PATH_IMAGE024
Be wavelength, from
Figure 2012103310091100002DEST_PATH_IMAGE026
Direction incides the far field sound-source signal of the unit amplitude of ball array, the angle of pitch of information source
Figure 2012103310091100002DEST_PATH_IMAGE028
Be the information source incident direction and zThe angle of axle, , the position angle Be from xAxle arrives in the counterclockwise direction the information source incident direction and exists XoyThe angle of projection on the plane,
Figure 2012103310091100002DEST_PATH_IMAGE034
, at sphere The acoustic pressure at some place is the progression form of spheric harmonic function:
Figure 2012103310091100002DEST_PATH_IMAGE038
（1）
Wherein, subscript " * " expression complex conjugate,
Figure 2012103310091100002DEST_PATH_IMAGE040
,
Figure 2012103310091100002DEST_PATH_IMAGE042
The expression exponent number,
Figure 2012103310091100002DEST_PATH_IMAGE044
With
Figure 2012103310091100002DEST_PATH_IMAGE046
Represent respectively incident sound pressure and scattering pressure, when sound-source signal incided open ball surface, sound pressure signal only comprised the acoustic pressure of incident sound field
Figure 87521DEST_PATH_IMAGE044
, when the sphere of sound-source signal incident is the rigidity sphere, be incident sound field acoustic pressure in the acoustic pressure of rigidity sphere
Figure 714942DEST_PATH_IMAGE044
With the scattering acoustic field acoustic pressure Stack,
Figure 2012103310091100002DEST_PATH_IMAGE048
,
Figure 2012103310091100002DEST_PATH_IMAGE050
Be spheric harmonic function, the expression formula of spheric harmonic function is:
Figure 2012103310091100002DEST_PATH_IMAGE052
（2）
Wherein,
Figure 2012103310091100002DEST_PATH_IMAGE054
,
Figure 2012103310091100002DEST_PATH_IMAGE056
Be the associating Legendre function, the expression formula of associating Legendre function is:
Figure 2012103310091100002DEST_PATH_IMAGE058
（3）
Wherein,
Figure 2012103310091100002DEST_PATH_IMAGE060
Represent arbitrary unknown number,
Figure 2012103310091100002DEST_PATH_IMAGE062
Expression is asked
Figure 240656DEST_PATH_IMAGE042
Order derivative,
Figure 2012103310091100002DEST_PATH_IMAGE064
Be Legendre polynomial, be expressed as:
Figure 2012103310091100002DEST_PATH_IMAGE066
（4）
For the ball array of different structure, modal intensity
Figure 2012103310091100002DEST_PATH_IMAGE068
For:
（5）
Wherein,
Figure 2012103310091100002DEST_PATH_IMAGE072
, Be respectively
Figure 2012103310091100002DEST_PATH_IMAGE076
The rank spheric Bessel function and Rank ball Hankel function,
Figure 2012103310091100002DEST_PATH_IMAGE078
With Be respectively The rank spheric Bessel function and
Figure 561455DEST_PATH_IMAGE040
The derivative of rank ball Hankel function;
(2), set up the humorous territory of ball array received Noise source signal model, it is specific as follows:
Suppose the white Gaussian noise environment, in the space
Figure 2012103310091100002DEST_PATH_IMAGE082
Figure 2012103310091100002DEST_PATH_IMAGE084
Individual amplitude is respectively Arrowband, far field sound-source signal respectively from Individual different directions
Figure 2012103310091100002DEST_PATH_IMAGE088
Incide simultaneously spherical microphone array, the
Figure 928162DEST_PATH_IMAGE036
Reception signal on the individual array element
Figure 2012103310091100002DEST_PATH_IMAGE090
For:
Figure 2012103310091100002DEST_PATH_IMAGE092
（6）
Wherein,
Figure 2012103310091100002DEST_PATH_IMAGE094
,
Figure 2012103310091100002DEST_PATH_IMAGE096
,
Figure 2012103310091100002DEST_PATH_IMAGE098
Expression the
Figure 887766DEST_PATH_IMAGE012
Additional noise on the individual array element, average are 0, and variance is
Figure 2012103310091100002DEST_PATH_IMAGE100
, and and signal between separate,
Figure 2012103310091100002DEST_PATH_IMAGE102
Expression
Figure 192976DEST_PATH_IMAGE088
The unit amplitude sound-source signal of direction is
Figure 434602DEST_PATH_IMAGE012
Acoustic pressure on the individual array element, according to formula (1), the top step number that spheric harmonic function is set is
Figure 2012103310091100002DEST_PATH_IMAGE104
,
Figure 21310DEST_PATH_IMAGE104
Satisfy
Figure 2012103310091100002DEST_PATH_IMAGE106
,
Figure 2012103310091100002DEST_PATH_IMAGE108
, Be expressed as:
Figure 2012103310091100002DEST_PATH_IMAGE110
（7）
Wherein, subscript
Figure 2012103310091100002DEST_PATH_IMAGE112
Represent the computing of Matrix Conjugate transposition,
Figure 2012103310091100002DEST_PATH_IMAGE114
The dimension matrix
Figure 2012103310091100002DEST_PATH_IMAGE116
,
Figure 2012103310091100002DEST_PATH_IMAGE118
Formed by spheric harmonic function:
Figure 2012103310091100002DEST_PATH_IMAGE120
To be element position by variable
Figure 2012103310091100002DEST_PATH_IMAGE122
Spheric harmonic function form,
Figure DEST_PATH_IMAGE124
To be sound source position by variable Spheric harmonic function form,
Figure DEST_PATH_IMAGE126
One The diagonal matrix of dimension, its element is by modal intensity
Figure DEST_PATH_IMAGE130
Form:
Figure DEST_PATH_IMAGE132
（8）
Figure DEST_PATH_IMAGE134
Subscript
Figure DEST_PATH_IMAGE136
The expression exponent number,
Figure DEST_PATH_IMAGE138
,
To own on the sphere
Figure 227404DEST_PATH_IMAGE016
Receive data on the individual array element forms Dimension observation data vector:
Figure DEST_PATH_IMAGE142
（9）
Simultaneously definition
Figure 181585DEST_PATH_IMAGE140
Dimension observation noise vector:
Figure DEST_PATH_IMAGE144
（10）
Obtain the humorous territory of ball array received Noise source signal model:
Figure DEST_PATH_IMAGE146
（11）
Wherein,
Figure DEST_PATH_IMAGE148
, the vector that is formed by the range value of sound source,
Figure DEST_PATH_IMAGE150
Formed by sound pressure level
Figure DEST_PATH_IMAGE152
The dimension matrix, its expression formula is as follows:
Figure DEST_PATH_IMAGE154
（12）
Wherein, matrix Expression the
Figure DEST_PATH_IMAGE158
The acoustic pressure of individual sound-source signal on each array element point of sphere, altogether Individual sound pressure level:
Figure DEST_PATH_IMAGE162
（13）
Subscript wherein
Figure DEST_PATH_IMAGE164
The transposition computing of representing matrix, element
Figure DEST_PATH_IMAGE166
Expression the
Figure 302731DEST_PATH_IMAGE158
Individual sound-source signal array element point On acoustic pressure;
(3), utilize the second-order statistics of signal, the humorous territory of the ball signal model of setting up is carried out the covariance computing, draw the covariance matrix of spherical microphone array receive data, it is specific as follows:
Make up the covariance matrix of array received data
Figure DEST_PATH_IMAGE168
, its expression formula is:
（14）
Wherein,
Figure 900383DEST_PATH_IMAGE100
Be noise power,
Figure DEST_PATH_IMAGE172
A unit matrix,
Figure DEST_PATH_IMAGE174
The covariance matrix of source signal,
Figure DEST_PATH_IMAGE176
Figure 845205DEST_PATH_IMAGE158
Individual sound-source signal
Figure 509273DEST_PATH_IMAGE086
Power;
(4), the covariance matrix that obtains in the step (3) is carried out feature decomposition, obtain respectively signal subspace
Figure DEST_PATH_IMAGE178
, noise subspace
Figure DEST_PATH_IMAGE180
, it is specific as follows:
Covariance matrix to receive data Carrying out feature decomposition obtains
Figure 952073DEST_PATH_IMAGE016
Individual proper vector
Figure DEST_PATH_IMAGE182
With
Figure 185739DEST_PATH_IMAGE016
Individual eigenwert , and
Figure DEST_PATH_IMAGE186
（15）
Wherein,
Figure 834075DEST_PATH_IMAGE158
The power of individual sound-source signal,
Figure DEST_PATH_IMAGE188
Be noise power, front
Figure 70890DEST_PATH_IMAGE082
Individual eigenwert is obviously greater than rear
Figure DEST_PATH_IMAGE190
Individual eigenwert, Decomposition is expressed as:
（16）
Wherein,
Figure DEST_PATH_IMAGE194
By front The diagonal matrix that individual large eigenwert consists of:
Figure DEST_PATH_IMAGE196
（17）
Figure DEST_PATH_IMAGE198
The subspace of being opened by these large eigenwert characteristic of correspondence vectors, i.e. signal subspace:
Figure DEST_PATH_IMAGE200
（18）
Figure DEST_PATH_IMAGE202
Remaining
Figure 578729DEST_PATH_IMAGE190
The diagonal matrix that individual little eigenwert consists of:
Figure DEST_PATH_IMAGE204
（19）
Figure DEST_PATH_IMAGE206
The subspace of being opened by these little eigenwert characteristic of correspondence vectors, i.e. noise subspace:
（20）
(5), utilize the orthogonality of noise subspace and signal subspace, definition signal subspace
Figure 365157DEST_PATH_IMAGE002
Steering vector, from step (4), extract a proper vector of noise subspace in the resulting noise subspace, structure dimensional orientation spectrum, it is specific as follows:
(5-1), the steering vector of definition signal subspace
Figure 393156DEST_PATH_IMAGE006
,
Utilize steering vector and the noise subspace nearly orthogonal of signal subspace, namely
Figure DEST_PATH_IMAGE210
, according to the described spheric harmonic function of formula (2)
Figure DEST_PATH_IMAGE212
And the described modal intensity matrix of formula (8) , the steering vector of definition signal subspace , its expression formula is:
Figure DEST_PATH_IMAGE216
（21）
Wherein, the space angle of pitch
Figure DEST_PATH_IMAGE218
And position angle
Figure DEST_PATH_IMAGE220
Scan whole dimensional orientation, its variation range is respectively
Figure DEST_PATH_IMAGE222
,
Figure DEST_PATH_IMAGE224
,
Figure DEST_PATH_IMAGE226
One
Figure DEST_PATH_IMAGE228
The dimension matrix, its expression formula is:
Figure DEST_PATH_IMAGE230
（22）
(5-2), structure normed space azimuth spectrum
Figure DEST_PATH_IMAGE232
, at noise subspace
Figure 826729DEST_PATH_IMAGE206
A proper vector of middle extraction noise subspace , structure dimensional orientation spectrum
Figure DEST_PATH_IMAGE236
, it is specific as follows:
If steering vector
Figure 788868DEST_PATH_IMAGE006
With noise subspace
Figure DEST_PATH_IMAGE238
The long-pending inverse that multiplies each other is the normed space azimuth spectrum, and its expression formula is:
Figure DEST_PATH_IMAGE240
（23）
Wherein,
Figure 666564DEST_PATH_IMAGE006
For
Figure 843598DEST_PATH_IMAGE140
The dimension matrix, For
Figure DEST_PATH_IMAGE242
The dimension matrix is from noise subspace
Figure 591291DEST_PATH_IMAGE206
A proper vector of middle extraction noise subspace
Figure DEST_PATH_IMAGE244
,
Figure DEST_PATH_IMAGE246
, structure dimensional orientation spectrum, its expression formula is:
Figure DEST_PATH_IMAGE248
（24）
(6), search azimuth spectrum
Figure 225590DEST_PATH_IMAGE010
Spectrum peak position, extract search value corresponding to peak value, determine the estimated value of sound bearing, as shown in Figure 4, it is specific as follows:
Above-mentioned dimensional orientation spectral function is a search volume angle of pitch and position angle
Figure DEST_PATH_IMAGE250
Function, Fig. 3 is an array element
Figure DEST_PATH_IMAGE252
The spherical microphone array that distributes of equal angles, the dimensional orientation spectrogram that formula when having 4 sound-source signals in the space (24) is corresponding,
Figure 22644DEST_PATH_IMAGE060
Axle is the search angle
Figure 631480DEST_PATH_IMAGE220
Value, scope is
Figure 867290DEST_PATH_IMAGE224
,
Figure DEST_PATH_IMAGE254
Axle is the search angle
Figure 877971DEST_PATH_IMAGE218
Value, scope is
Figure 658976DEST_PATH_IMAGE222
,
Figure DEST_PATH_IMAGE256
Axle represents the spectrum value.In the very little scope in spectrum place, peak, carry out little step-searching at these among a small circle, obtain the spectrum peak position of dimensional orientation spectrum, extract the dimensional orientation of sound source, in each step-searching, formula (23) need to be carried out
Figure DEST_PATH_IMAGE258
Inferior complex multiplication, formula (24) is at need
Figure DEST_PATH_IMAGE260
Inferior complex multiplication operation is reduced to formula (23) operand
Figure DEST_PATH_IMAGE262
, in the auditory localization algorithm of spherical microphone array, array number
Figure DEST_PATH_IMAGE264
, greatly having reduced volumes of searches, the process of the spectrum peak search of dimensional orientation spectrum is as follows:
(6-1), exist
Figure 817425DEST_PATH_IMAGE060
On the axle
Figure DEST_PATH_IMAGE266
In the scope, equidistantly select
Figure DEST_PATH_IMAGE268
Individual value: ,
Figure 840614DEST_PATH_IMAGE254
On the axle
Figure DEST_PATH_IMAGE272
In the scope, equidistantly select
Figure 581168DEST_PATH_IMAGE268
Individual value
Figure DEST_PATH_IMAGE274
,
Figure DEST_PATH_IMAGE276
, Be the sound source number, substitution formula (24) is calculated corresponding spectrum value
Figure DEST_PATH_IMAGE278
, and then definite threshold value , its expression formula is:
Figure DEST_PATH_IMAGE282
（25）
Wherein,
Figure DEST_PATH_IMAGE284
(6-2), count number greater than the spectrum value of thresholding
Figure DEST_PATH_IMAGE286
,
Select
Figure 739671DEST_PATH_IMAGE060
Step-size in search on the axle is
Figure DEST_PATH_IMAGE288
,
Figure 989387DEST_PATH_IMAGE254
Step-size in search on the axle is
Figure DEST_PATH_IMAGE290
, carry out
Figure DEST_PATH_IMAGE292
Inferior stepping spectrum peak search is successively point
Figure DEST_PATH_IMAGE294
Substitution formula (24) is calculated corresponding spectrum value, respectively with spectrum value and the threshold value of each correspondence
Figure 787710DEST_PATH_IMAGE280
Compare one by one, count greater than threshold value
Figure 159785DEST_PATH_IMAGE280
The number of spectrum value
Figure 230510DEST_PATH_IMAGE286
(6-3) number of the described spectrum value greater than thresholding of determining step (6-2) Whether less than the number of signal source
Figure DEST_PATH_IMAGE298
If, the number greater than the spectrum value of thresholding described in the step (6-2)
Figure 681255DEST_PATH_IMAGE296
Less than the signal source number
Figure DEST_PATH_IMAGE300
, then turn step (6-2), proceed
Figure DEST_PATH_IMAGE302
Inferior spectrum peak search is until greater than the spectrum value number of thresholding
Figure 334084DEST_PATH_IMAGE296
More than or equal to the signal source number
Figure 814744DEST_PATH_IMAGE082
If the number greater than the spectrum value of thresholding described in the step (6-2)
Figure 169502DEST_PATH_IMAGE296
More than or equal to the signal source number
Figure 26600DEST_PATH_IMAGE082
, then turn step (6-4);
(6-4), with
Figure DEST_PATH_IMAGE304
Individually consist of codomain greater than search value corresponding to the spectrum peak of thresholding, in codomain, carry out the stepping spectrum peak search, obtain
Figure 32471DEST_PATH_IMAGE304
Search value corresponding to spectrum peak in the individual codomain, it is specific as follows:
If the
Figure DEST_PATH_IMAGE306
In the inferior stepping spectrum peak search greater than threshold value
Figure 684032DEST_PATH_IMAGE280
Spectrum peak number
Figure DEST_PATH_IMAGE308
, write down greater than search value corresponding to the spectrum value of threshold value
Figure DEST_PATH_IMAGE310
, choose search value
Figure DEST_PATH_IMAGE312
Point is rectangular center, consists of a rectangular codomain: Span on the axle is
Figure DEST_PATH_IMAGE314
,
Figure 311508DEST_PATH_IMAGE254
Span on the axle is
Figure DEST_PATH_IMAGE316
, wherein , what consist of
Figure DEST_PATH_IMAGE320
In the individual codomain, choose
Figure 171886DEST_PATH_IMAGE060
Step-size in search on the axle is
Figure DEST_PATH_IMAGE322
,
Figure 259928DEST_PATH_IMAGE254
Step-size in search on the axle is
Figure DEST_PATH_IMAGE324
, carry out successively the stepping spectrum peak search, obtain search value corresponding to spectrum peak in each codomain
Figure DEST_PATH_IMAGE326
,
Figure 589278DEST_PATH_IMAGE318
(6-5), determine the estimated value of sound bearing, it is specific as follows:
If (6-4) greater than the spectrum peak number of thresholding Equal information source number
Figure 601227DEST_PATH_IMAGE082
, the search value that then spectrum peak search obtains in the step (6-4) The estimated value of sound bearing, wherein,
If (6-4) greater than the spectrum peak number of thresholding
Figure 263470DEST_PATH_IMAGE328
Greater than information source number
Figure 80116DEST_PATH_IMAGE082
, the search value that then spectrum peak search in the step (6-4) is obtained
Figure 817128DEST_PATH_IMAGE326
Substitution formula (23) is calculated, and obtains
Figure 340513DEST_PATH_IMAGE328
Individual spectrum peak
Figure DEST_PATH_IMAGE332
, Individual
Figure DEST_PATH_IMAGE334
Arranged sequentially by from small to large of spectrum peak is before the deletion
Figure DEST_PATH_IMAGE336
Individual spectrum peak, remaining
Figure 57988DEST_PATH_IMAGE082
Individual spectrum peak,
Figure 598691DEST_PATH_IMAGE082
The search value that individual spectrum peak is corresponding The estimated value of sound bearing, wherein
Figure DEST_PATH_IMAGE340

Claims (3)

1. many sound localization methods based on spherical microphone array is characterized in that the method may further comprise the steps:
(1), set up spherical coordinate system, the position of each array element on the spherical microphone array is described, the spheric harmonic function that spherical microphone array gathers high-order sound field acoustic pressure is set;
(2), set up the humorous territory of ball array received Noise source signal model;
(3), utilize the second-order statistics of signal, the humorous territory of the ball signal model of setting up is carried out the covariance computing, draw the covariance matrix that spherical microphone array receives signal;
(4), the covariance matrix that obtains in the step (3) is carried out feature decomposition, obtain respectively signal subspace
Figure 839394DEST_PATH_IMAGE001
, noise subspace
Figure 611041DEST_PATH_IMAGE002
(5), utilize the orthogonality of noise subspace and signal subspace, definition signal subspace
Figure 561679DEST_PATH_IMAGE001
Steering vector
Figure 444185DEST_PATH_IMAGE003
, structure normed space azimuth spectrum
Figure 796669DEST_PATH_IMAGE004
, and from step (4), extract a noise subspace proper vector in the resulting noise subspace, structure dimensional orientation spectrum
Figure 676900DEST_PATH_IMAGE005
(6), search azimuth spectrum Spectrum peak position, extract search value corresponding to peak value, determine the estimated value of sound bearing.
2. a kind of many sound localization methods based on spherical microphone array according to claim 1 is characterized in that the orthogonality of utilizing noise subspace and signal subspace described in the above-mentioned steps (5), definition signal subspace
Figure 237249DEST_PATH_IMAGE001
Steering vector
Figure 444240DEST_PATH_IMAGE003
, structure normed space azimuth spectrum
Figure 557689DEST_PATH_IMAGE004
, and from step (4), extract a noise subspace proper vector in the resulting noise subspace, structure dimensional orientation spectrum
Figure 420603DEST_PATH_IMAGE005
, it is specific as follows:
(5-1), the steering vector of definition signal subspace
Figure 644911DEST_PATH_IMAGE003
,
Utilize steering vector and the noise subspace nearly orthogonal of signal subspace, that is,
Figure 971987DEST_PATH_IMAGE006
, the steering vector of definition signal subspace
Figure 990759DEST_PATH_IMAGE003
Expression formula is:
Figure 403285DEST_PATH_IMAGE007
Wherein, the space angle of pitch
Figure 368967DEST_PATH_IMAGE008
And position angle
Figure 550550DEST_PATH_IMAGE009
Scan whole dimensional orientation, its variation range is respectively
Figure 5802DEST_PATH_IMAGE010
,
Figure 640046DEST_PATH_IMAGE011
,
Figure 143839DEST_PATH_IMAGE012
One Dimension matrix, its element are that the spheric harmonic function of element position forms by variable, and expression formula is:
Figure 71661DEST_PATH_IMAGE014
(5-2), structure normed space azimuth spectrum
Figure 193201DEST_PATH_IMAGE015
, and at noise subspace
Figure 999221DEST_PATH_IMAGE016
A proper vector of middle extraction noise subspace
Figure 155395DEST_PATH_IMAGE017
, structure dimensional orientation spectrum :
If steering vector
Figure 561286DEST_PATH_IMAGE003
With noise subspace The long-pending inverse that multiplies each other is the normed space azimuth spectrum, and its expression formula is:
Figure 417564DEST_PATH_IMAGE020
Wherein, For
Figure 481652DEST_PATH_IMAGE021
The dimension matrix,
Figure 193256DEST_PATH_IMAGE019
For
Figure 996127DEST_PATH_IMAGE022
The dimension matrix is from noise subspace
Figure 134984DEST_PATH_IMAGE016
A proper vector of middle extraction noise subspace
Figure 718412DEST_PATH_IMAGE017
Figure 233707DEST_PATH_IMAGE023
, have
Figure 953401DEST_PATH_IMAGE024
, structure dimensional orientation spectrum, its expression formula is:
Figure 200843DEST_PATH_IMAGE025
。
3. a kind of many sound localization methods based on spherical microphone array according to claim 2 is characterized in that the search azimuth spectrum described in the above-mentioned steps (6)
Figure 271567DEST_PATH_IMAGE005
Spectrum peak position, extract search value corresponding to peak value, determine the estimated value of sound bearing, it is specifically lower:
The dimensional orientation spectral function is a search volume angle of pitch and position angle
Figure 324974DEST_PATH_IMAGE026
Function, the dimensional orientation spectral function can represent with the dimensional orientation spectrogram of three-dimensional, Axle is the search angle
Figure 81632DEST_PATH_IMAGE009
Value, scope is
Figure 639652DEST_PATH_IMAGE028
, Axle is the search angle Value, scope is ,
Figure 560018DEST_PATH_IMAGE031
Axle represents the spectrum value, in the very little scope in spectrum place, peak, carries out little step-searching at these among a small circle, obtains the spectrum peak position of dimensional orientation spectrum, determines the dimensional orientation of sound source, and the process of the spectrum peak search of dimensional orientation spectrum is as follows:
(6-1), exist
Figure 955227DEST_PATH_IMAGE027
On the axle
Figure 769599DEST_PATH_IMAGE032
In the scope, equidistantly select
Figure 592062DEST_PATH_IMAGE033
Individual value:
Figure 796778DEST_PATH_IMAGE034
,
Figure 995678DEST_PATH_IMAGE029
On the axle
Figure 664557DEST_PATH_IMAGE035
In the scope, equidistantly select
Figure 657921DEST_PATH_IMAGE033
Individual value
Figure 349933DEST_PATH_IMAGE036
,
Figure 86945DEST_PATH_IMAGE037
,
Figure 610331DEST_PATH_IMAGE038
For the sound source number, bring into Calculate corresponding spectrum value
Figure 718019DEST_PATH_IMAGE040
, and then definite threshold value
Figure 993142DEST_PATH_IMAGE041
, its expression formula is:
Figure 636613DEST_PATH_IMAGE042
Wherein,
Figure 971779DEST_PATH_IMAGE043
(6-2), count number greater than the spectrum value of thresholding
Figure 700701DEST_PATH_IMAGE044
Select
Figure 717199DEST_PATH_IMAGE027
Step-size in search on the axle is
Figure 215176DEST_PATH_IMAGE045
,
Figure 986823DEST_PATH_IMAGE029
Step-size in search on the axle is
Figure 937461DEST_PATH_IMAGE046
, carry out
Figure 757650DEST_PATH_IMAGE047
Inferior stepping spectrum peak search is successively point Substitution
Figure 52682DEST_PATH_IMAGE039
, calculate corresponding spectrum value, respectively with spectrum value and the threshold value of each correspondence
Figure 490617DEST_PATH_IMAGE041
Compare one by one, count greater than threshold value
Figure 911234DEST_PATH_IMAGE041
The number of spectrum value
Figure 321486DEST_PATH_IMAGE044
(6-3) number of the described spectrum value greater than thresholding of determining step (6-2)
Figure 434936DEST_PATH_IMAGE049
Whether less than the number of signal source
Figure 360167DEST_PATH_IMAGE050
If, the number greater than the spectrum value of thresholding described in the step (6-2)
Figure 584475DEST_PATH_IMAGE049
Less than the signal source number
Figure 82190DEST_PATH_IMAGE051
, then turn step (6-2), proceed
Figure 366541DEST_PATH_IMAGE052
Inferior spectrum peak search is until greater than the spectrum value number of thresholding
Figure 779067DEST_PATH_IMAGE049
More than or equal to the signal source number
Figure 807066DEST_PATH_IMAGE038
If the number greater than the spectrum value of thresholding described in the step (6-2)
Figure 926332DEST_PATH_IMAGE049
More than or equal to the signal source number
Figure 116005DEST_PATH_IMAGE038
, then turn step (6-4);
(6-4), with Individually consist of codomain greater than search value corresponding to the spectrum peak of thresholding, in codomain, carry out the stepping spectrum peak search, obtain
Figure 519621DEST_PATH_IMAGE053
Search value corresponding to spectrum peak in the individual codomain, it is specific as follows:
If the
Figure 821290DEST_PATH_IMAGE054
In the inferior stepping spectrum peak search greater than threshold value
Figure 181864DEST_PATH_IMAGE041
Spectrum peak number
Figure 568983DEST_PATH_IMAGE055
, write down greater than search value corresponding to the spectrum value of threshold value
Figure 938784DEST_PATH_IMAGE056
, choose search value
Figure 767063DEST_PATH_IMAGE056
Point is rectangular center, consists of a rectangular codomain:
Figure 564118DEST_PATH_IMAGE027
Span on the axle is
Figure 172954DEST_PATH_IMAGE057
, Span on the axle is
Figure 793346DEST_PATH_IMAGE058
, wherein
Figure 761302DEST_PATH_IMAGE059
, what consist of
Figure 857434DEST_PATH_IMAGE060
In the individual codomain, choose
Figure 569038DEST_PATH_IMAGE027
Step-size in search on the axle is
Figure 434225DEST_PATH_IMAGE061
,
Figure 510766DEST_PATH_IMAGE029
Step-size in search on the axle is
Figure 94194DEST_PATH_IMAGE062
, carry out successively the stepping spectrum peak search, obtain search value corresponding to spectrum peak in each codomain
Figure 343910DEST_PATH_IMAGE063
,
Figure 329183DEST_PATH_IMAGE059
(6-5), determine the estimated value of sound bearing, it is specific as follows:
If (6-4) greater than the spectrum peak number of thresholding
Figure 576625DEST_PATH_IMAGE064
Equal information source number
Figure 647349DEST_PATH_IMAGE038
, the search value that then spectrum peak search obtains in the step (6-4)
Figure 700756DEST_PATH_IMAGE063
The estimated value of sound bearing, wherein,
If (6-4) greater than the spectrum peak number of thresholding
Figure 958879DEST_PATH_IMAGE064
Greater than information source number
Figure 251320DEST_PATH_IMAGE038
, the search value that then spectrum peak search in the step (6-4) is obtained
Figure 108418DEST_PATH_IMAGE063
Substitution formula (23) is calculated, and obtains
Figure 802704DEST_PATH_IMAGE064
Individual spectrum peak
Figure 890483DEST_PATH_IMAGE065
,
Figure 873483DEST_PATH_IMAGE064
Individual
Figure 268692DEST_PATH_IMAGE065
Arranged sequentially by from small to large of spectrum peak is before the deletion
Figure 817485DEST_PATH_IMAGE066
Individual spectrum peak, remaining
Figure 905527DEST_PATH_IMAGE038
Individual spectrum peak,
Figure 110243DEST_PATH_IMAGE038
The search value that individual spectrum peak is corresponding
Figure 309144DEST_PATH_IMAGE067
The estimated value of sound bearing, wherein
Figure 712443DEST_PATH_IMAGE068
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