CN110501669B - Central symmetry acoustic vector circular array fast space spectrum compression super-resolution direction estimation method - Google Patents
Central symmetry acoustic vector circular array fast space spectrum compression super-resolution direction estimation method Download PDFInfo
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- G01—MEASURING; TESTING
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Abstract
The invention provides a method for quickly compressing a spatial spectrum to estimate a super-resolution direction of a centrosymmetric acoustic vector circular array
A steering vector of (a); then, according to the average noise intensity anti-noise principle of the acoustic vector sensor, a covariance matrix is constructed by adopting a sound pressure and vibration velocity combined processing method, so that the vector matrix steering vector matrix dimension is reduced, and the anti-noise capability is improved; then, a new space spectrum function is constructed according to the space spectrums of the real source and the virtual source which is 180 degrees different from the real source to perform half spectrum search, so that the compression of the sound vector circular array space spectrum is realized; finally, the real sound source position is rapidly judged through the discriminant formula constructed by the invention. The method realizes the compression of the spatial spectrum of the vector circular array for the first time, greatly improves the operation efficiency while ensuring high resolution, and realizes the quick and efficient super-resolution azimuth estimation of the acoustic vector circular array.
Description
Technical Field
The invention relates to a method for estimating a central symmetry acoustic vector circular array fast space spectrum compression super-resolution direction, belonging to the field of underwater acoustic vector signal processing.
Background
The vector hydrophone can simultaneously measure the sound pressure and particle vibration velocity information of a sound field, brings the capability of distinguishing left and right ambiguities for the simplest linear array, can realize the ambiguities-free positioning in the full-space direction, improves the detection and estimation capability of the sound pressure array, and has a plurality of advantages. The circular array is widely applied to a sonar system, the uniform circular array can obtain 360-degree omnibearing non-fuzzy azimuth information and approximately the same angle resolution, and the method has great superiority compared with a uniform linear array. However, compared with the fruitful vector linear array, the research on the vector circular array is less.
Yang De sene et al, which decomposes a vector sound field into a series of mutually orthogonal phase modes by using a phase mode transformation principle, and provides a method for estimating the target orientation of an acoustic vector circular array phase mode domain; ye, zhongfu and the like use the symmetry characteristics of a central symmetric circular array to put forward a space average theory and research the azimuth estimation performance of a non-relevant target; zhang Wei, and the like, and provides a mode space vector reconstruction algorithm for solving the problem that a vector reconstruction method based on a uniform linear array cannot be directly used for a uniform circular array; wang Yichuan et al propose a vector circular array time domain analysis MVDR algorithm, and study the principle and implementation flow of the vector circular array time domain analysis MVDR algorithm; shijie et al put forward a sound vector circular array steady broadband MVDR orientation estimation method by performing subband decomposition on sound pressure and vibration velocity data received by a vector circular array to obtain a broadband focusing covariance matrix; according to the structural characteristics of the centrosymmetric acoustic vector circular array, the Househou et al combines the sound pressure and vibration velocity combined processing theory and the forward and backward space average algorithm in the time domain, and provides an acoustic vector circular array orientation estimation method based on the forward and backward space average. The method has a good effect on improving the anti-noise performance, robustness and resolution of the acoustic vector circular array azimuth estimation, but the method cannot be directly applied to sonar equipment because the calculated amount of the method in practical application is huge. At present, a quick direction estimation method suitable for an acoustic vector circular array does not exist.
Based on the background, the invention provides a method for estimating the location of the super-resolution of the central symmetric acoustic vector circular array by fast spatial spectrum compression. The central symmetry of the acoustic vector circular array is utilized to arrange the sensors of the upper and lower semi-circular rings of the acoustic vector circular array according to a specific sequence respectively, and acoustic signals are collected to construct a structure meeting the requirements
The guide vector of (2); then, according to the average noise intensity anti-noise principle of the acoustic vector sensor, a covariance matrix is constructed by adopting a sound pressure and vibration velocity combined processing method, the vector matrix steering vector matrix dimension is reduced, the calculation efficiency is further improved, and the anti-noise capability is improved; then, a new space spectrum function is constructed according to the space spectrums of the real source and the virtual source which is 180 degrees different from the real source to perform half-spectrum search, and azimuth information of the whole space spectrum can be obtained by searching in the half space spectrum, so that compression of the sound vector circular array space spectrum is realized, high resolution is ensured, and meanwhile, the spectrum peak search efficiency is improved; finally, the real sound source direction is rapidly distinguished through the discriminant formula constructed by the invention. The method realizes the fast and efficient super-resolution orientation estimation of the acoustic vector circular array, can meet the application requirement of fast orientation estimation of the acoustic vector circular array, and can be applied to signal processing of underwater buoy sonars, shipborne sonars and other types of sonars.
Disclosure of Invention
The invention aims to provide a method for quickly compressing a spatial spectrum to estimate a super-resolution direction by utilizing the symmetry of a sound vector circular array and adopting a spatial spectrum compression technology.
The purpose of the invention is realized as follows: the method comprises the following steps:
the method comprises the following steps: dividing the acoustic vector circular array into an upper semicircular ring and a lower semicircular ring, and collecting vector circles in an anticlockwise sequenceThe signal data received by the sensor of the semicircular ring on the array is collected according to the clockwise sequence, and then the received signal matrix of the sound pressure channel and the x and y direction vibration velocity channels of the whole acoustic vector circular array at the time t is constructed
And &>
Step two: carrying out azimuth scanning, respectively constructing guide vectors corresponding to the received signals for the sensors of the upper semicircular ring and the lower semicircular ring, and then synthesizing a guide vector matrix of the whole acoustic vector circular array
At this time, for any azimuth angle theta, the steering vector matrix satisfies the following conditions:
wherein, the first and the second end of the pipe are connected with each other,
and &>
Respectively representing the sound pressure channel of the sound vector circular array and the guide vectors of the x-direction channel and the y-direction channel, wherein "-" represents conjugate operation;
step three: the two vibration velocity components are subjected to weighted linear combination, and the azimuth scanning angle theta is used as the guide azimuth of the electronic rotation to obtain the joint vibration velocity of the acoustic vector circular array in the guide direction theta
Comprises the following steps:
step four: performing dimension reduction processing on the vector array covariance matrix data according to the average noise intensity anti-noise principle, and constructing a covariance matrix R when the azimuth scanning angle is theta pv (θ)，
Wherein E [. Cndot. ] represents the expectation, and the superscript "H" represents the conjugate transpose operation;
step five: constructing a spatial spectrum function P (theta) suitable for sound vector circular array rapid spatial spectrum compression super-resolution orientation estimation;
step six: obtaining an azimuth spectrum function value corresponding to the scanning angle theta by using the constructed spatial spectrum function P (theta);
step seven: repeating the second step to the sixth step, and enabling theta to be epsilon [0, pi ]]Or theta k ∈[π,2π]Performing half spectrum scanning within the range of (2), drawing an image of a half space spectrum, and observing the image of the space spectrum to obtain a spectrum peak position theta k ；
Step eight: using theta k Calculating to obtain the whole space spectrum [0,2 pi]Position of another spectral peak in the range theta k * The calculation formula is as follows:
step nine: substituting the angle information of two spectral peaks obtained in the vector circular array semi-spectrum search into a conventional MVDR algorithm spatial spectrum function to obtain two corresponding function values P (theta) k ) And P (theta) k * )：
Step ten: comparing the two obtained function values, and judging by the following formula:
and distinguishing the position of the real sound source from the two spectral peaks, and determining the incoming wave direction of the sound source.
The invention also includes such structural features:
1. the fifth step is specifically as follows:
(1) Reducing the covariance matrix R after dimension reduction pv (theta) introducing an MVDR beam former to obtain a spatial spectrum function of a real sound source as follows:
wherein, the superscript "-1" represents the inversion operation;
(2) Satisfied by post-reconstruction signal steering vector matrix
This relationship is found in [0,2 π]The spatial spectrum function of a virtual source within the range which has a 180-degree difference with the incident angle of the real sound source is as follows:
(3) Fitting the space spectrums of the real source and the virtual source to construct a space spectrum function suitable for half-spectrum search:
compared with the prior art, the invention has the beneficial effects that: the invention realizes the rapid super-resolution signal processing of the sound vector circular array received signals, solves the problems that the current vector circular array signal processing method has large calculation amount and can not improve the calculation efficiency, and can be applied to the signal processing of underwater buoy sonars, ship-borne sonars and other types of sonars. 1) The method realizes the compression of the circular array space spectrum for the first time, obtains the azimuth information of the whole spectrum space in the vector circular array half-spectrum search result, greatly reduces the spectral peak search calculation amount, improves the azimuth estimation efficiency of the vector circular array, and has great advantages in engineering application; 2) The method fully utilizes the advantages of vector array elements and an MVDR algorithm in resolution, and has higher resolution in azimuth estimation; 3) Compared with a sound pressure array, the vector array has remarkable advantages, the resolution can be obviously improved, side lobes can be obviously inhibited, and the covariance matrix can be improved in calculation efficiency and better in anti-noise performance by adopting a sound pressure and vibration velocity combined processing mode to construct the covariance matrix; 4) The method is suitable for signal processing of underwater buoy sonar, ship-borne sonar and other types of sonar, and aims to solve the problem of low calculation efficiency in the direction estimation of the underwater acoustic system with the array type.
Drawings
Fig. 1 is an acoustic vector circular array measurement model.
FIG. 2 is a flow chart of a method for estimating a super-resolution orientation by fast spatial spectrum compression of a centrosymmetric acoustic vector circular array.
FIG. 3 is an azimuth spectrum obtained by applying the conventional MVDR method and the semi-spectral search method of the present invention to a sound pressure array with a single sound source.
FIG. 4 is the azimuth spectrum obtained by the method of the present invention for the sound pressure array and the vector array half spectrum search when the sound source is single.
FIG. 5 is an azimuth spectrum obtained by applying the conventional MVDR method and the half-spectrum search of the method of the present invention to a sound pressure array with two sound sources.
FIG. 6 is a diagram of the azimuth spectrum obtained by the method of the present invention for the semi-spectrum search of the acoustic pressure matrix and the vector matrix when the sound sources are dual.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The array model of the method of the invention is shown in fig. 1, the signal processing flow chart is shown in fig. 2, and the specific implementation scheme is as follows:
the method comprises the steps of firstly, dividing a central symmetric vector circular array into an upper semicircular ring and a lower semicircular ring by utilizing the symmetry of the acoustic vector circular array, collecting signal data received by sensors of the upper semicircular ring and the lower semicircular ring of the vector circular array in an anticlockwise sequence, collecting signal data received by sensors of the lower semicircular ring of the vector circular array in a clockwise sequence, and constructing a received signal matrix of a sound pressure channel and x-direction and y-direction vibration velocity channels of the whole acoustic vector circular array at the moment t
And &>
The concrete implementation is as follows:
1) The vector circular array measurement model is shown in fig. 1, the radius is r, an acoustic vector circular array formed by M-element (M is an even number) two-dimensional acoustic vector sensors is positioned in an xoy plane, and M sensors on the acoustic vector circular array are marked as No. 1, no. 2 to No. M in turn according to the anticlockwise sequence. The center of the circle coincides with the origin of the coordinate system, and the directions of the two vibration speed channels of the acoustic vector sensor are respectively along the positive directions of the x axis and the y axis.
Assuming N narrowband signals s 1 (t),…,s n (t),…,s N (t) from a direction parallel to the xoy plane at an incident angle θ, respectively 1 (t),…,θ n (t),…,θ N (t) the sound pressure and the vibration speed signals of the x-direction channel and the y-direction channel which are respectively P received by the mth array element of the two-dimensional sound vector circular array at the time t are obtained by incidence to the sound vector circular array m (t) and V xm (t)、V ym (t)。
2) And collecting signal data received by the sensors of the semi-circular rings on the vector circular array in a counterclockwise sequence of 1,2, … and M/2:
in the formula, P up (t) and V xup (t)、V yup And (t) respectively representing sound pressure received by a sensor of a semicircular ring on the two-dimensional sound vector circular array and channel vibration velocity components in the x direction and the y direction.
3) Then, signal data received by sensors of a lower semicircular ring of the vector circular array are collected according to the clockwise sequence of M, … and M/2+1:
in the formula, P down (t) and V xdown (t)、V ydown And (t) respectively representing sound pressure received by the sensor of the lower semicircular ring of the two-dimensional sound vector circular array and channel vibration velocity components in the x direction and the y direction.
4) Constructing a receiving signal matrix of each channel of the whole acoustic vector circular array at the time t as follows:
wherein the content of the first and second substances,
and &>
And respectively representing the sound pressure signal of the reconstructed whole acoustic vector circular array and the receiving signal matrixes of the x-direction and y-direction vibration velocity channels, wherein the superscript T represents transposition operation.
Secondly, azimuth scanning is carried out, theta is any azimuth in the scanning range, guide vectors corresponding to received signals are respectively constructed for the sensors of the upper half ring and the lower half ring, and then a guide vector matrix of the whole acoustic vector circular array is synthesized
The concrete implementation is as follows:
1) For the upper semicircular ring configuration the steering vector is:
the steering vectors are for the lower semicircular ring configuration:
in the formula, A up (theta) and A xup (θ)、A yup (theta) respectively represents the guide vectors corresponding to the sound pressure channel and the x and y direction channels of the semicircular ring sensor on the acoustic vector circular array, A down (theta) and A xdown (θ)、A ydown (theta) respectively represents the guide vectors corresponding to the sound pressure channel and the x-direction and y-direction channel receiving signals of the lower semicircular ring sensor of the acoustic vector circular array, and a m (θ)、a ym (θ)、a ym (theta) represents a guide vector corresponding to a sound pressure channel and x and y direction channels of the mth array element, wherein:
in the formula (I), the compound is shown in the specification,
the angle between the m-th acoustic vector sensor and the positive direction of the x axis is defined, k =2 pi f/c is the wave number, c is the sound velocity, and f is the signal frequency.
2) Then constructing a guide vector matrix of the whole acoustic vector circular array as follows:
according to the following steps:
the important property is derived, and for any azimuth angle theta, the constructed steering vector satisfies the following conditions:
wherein "-" denotes a conjugate operation.
Thirdly, performing weighted linear combination on the two vibration velocity components, and taking an azimuth scanning angle theta as a guide azimuth of electronic rotation to obtain a combined vibration velocity of the acoustic vector circular array in a guide direction theta
Comprises the following steps:
fourthly, reducing the dimension of the vector array covariance matrix data according to the average noise intensity anti-noise principle, and constructing a covariance matrix R when the azimuth scanning angle is theta pv Comprises the following steps:
where E [. Cndot. ] represents the expectation, and the superscript "H" represents the conjugate transpose operation.
In theory, it is possible to use,
wherein: psi c ＝diag(cos(θ 1 -θ),cos(θ 2 -θ),…,cos(θ n - θ)), diag (-) denotes a diagonal matrix made of (-) N c (t)＝N x (t)cos(θ r )+N y (t)sin(θ r ) Is a noise signal combining the vibration velocity signals, N (t), N x (t)、N y And (t) respectively represents noise signals received by a sound pressure channel, an x-direction vibration velocity channel and a y-direction vibration velocity channel. The array is in an isotropic noise field, and the noise signals received by the sound pressure and vibration velocity units are not related theoretically for a uniform vector circular array, namely
The covariance matrix R constructed by the method pv The noise-resistant performance is better in an isotropic noise field.
And fifthly, constructing a spatial spectrum function P (theta) suitable for the sound vector circular array rapid spatial spectrum compression super-resolution orientation estimation, and concretely realizing the following steps:
1) Reducing the covariance matrix R after dimension reduction pv (theta) introducing an MVDR beam former to obtain a spatial spectrum function of a real sound source as follows:
wherein the superscript "-1" indicates the inversion operation.
2) Satisfied by post-reconstruction signal steering vector matrix
This relationship is found in [0,2 π]The spatial spectrum function of a virtual source within a range 180 degrees different from the incident angle of a real sound source is as follows:
3) Fitting the space spectrums of the real source and the virtual source to construct a space spectrum function suitable for half spectrum search:
according to the circular array guide vector, A (theta) = A (theta + pi) * This property is known as follows: p (θ) = = P (θ + pi), and therefore, by performing a search using this spatial spectrum, the azimuth information of the entire spatial spectrum can be compressed in half the spatial spectrum.
And sixthly, using the constructed spatial spectrum function P (theta) to obtain an azimuth spectrum function value corresponding to the scanning angle theta.
The seventh step, repeating the second to sixth steps, where theta is equal to 0, pi]Or theta k ∈[π,2π]The half spectrum scanning is carried out in the range of (2), an image of a half space spectrum is drawn, and the spectrum peak position theta is obtained by observing the image of the space spectrum k 。
Eighth step of using θ k Calculating to obtain the whole space spectrum theta k ∈[0,2π]Position of another spectral peak in the range theta k * The calculation formula is as follows:
the ninth step, the angle information of two spectral peaks obtained in the vector circular array semi-spectrum search is substituted into the space spectrum function of the conventional MVDR algorithm to obtain two corresponding function values P (theta) k ) And P (theta) k * )：
Step ten, comparing the two obtained function values, and distinguishing through the following formula:
according to the property, the real source and the virtual source obtained by vector circular array semi-spectrum search can be distinguished by carrying out discrimination according to the formula, so that the real incoming wave direction of the sound source is determined.
The above description has been made in detail on the embodiments of the present disclosure. Through the steps, the method realizes the compression of the spatial spectrum of the vector circular array, obtains the azimuth information of the whole spatial spectrum space through the search of the half spatial spectrum of the vector circular array, improves the calculation efficiency while ensuring high resolution, has stronger isotropic noise resistance, and realizes the quick and efficient super-resolution azimuth estimation of the acoustic vector circular array. The invention is further described below by means of simulation experiments.
Example one: single sound source processing effect analysis
Example one parameter setting is as follows: the method comprises the steps that 8-element uniform circular arrays are formed, the radius R =0.5m of the circular arrays, narrow-band sound signals with the sound source frequency of 1kHz are incident to the circular arrays from a far field, the incident angle is 220 degrees, the fast beat number is 500, the search step length is 0.5 degrees, the signal-to-noise ratio is 10dB, and noise is white Gaussian noise. Fig. 3 shows an azimuth spectrum obtained by performing a half spectrum search within 0,180 ° according to a different method under a single sound source, wherein a curve with a "+" represents a conventional MVDR method using a sound pressure array element, and a curve with a "+" represents the method of the present invention using a sound pressure array element, i.e., a fast MVDR method. Fig. 4 shows an azimuth spectrum obtained by performing a half-spectrum search within [0,180 ° ] according to different methods under a single sound source, wherein a curve with a "+" represents the method of the present invention when using a sound pressure array element, and a curve with a "+" represents the fast MVDR method based on an acoustic vector array finally provided by the present invention.
Example two: dual source processing effect analysis
Example two parameter settings were as follows: the array comprises 8-element uniform circular arrays, wherein the radius R =0.5m of the circular arrays, narrow-band sound signals with the frequency of 1kHz are incident to the circular arrays from a far field, the incidence directions are 220 degrees and 260 degrees, the snapshot number is 500, the search step length is 0.5 degree, the signal-to-noise ratio is 10dB, and the noise is white Gaussian noise. Fig. 5 shows an azimuth spectrum obtained by performing a half-spectrum search within 0,180 ° according to different methods under dual sound sources, wherein a curve with a "+" represents a conventional MVDR method using a sound pressure array element, and a curve with a "+" represents the method of the present invention using a sound pressure array element, i.e., a fast MVDR method. Fig. 6 shows an azimuth spectrum obtained by performing a half-spectrum search within [0,180 ° ] according to different methods under dual sound sources, wherein a curve with a "+" represents the method of the present invention when using a sound pressure array element, and a curve with a "+" represents the fast MVDR method based on an acoustic vector array finally provided by the present invention.
Example three: orientation estimation efficiency analysis
Example three parameter settings were as follows: 8-element uniform sound vector circular array, wherein the radius R =0.5m of the circular array, two narrow-band incoherent sound signals with the frequency of 1kHz are incident to the circular array from a far field, the fast beat number is 500, the signal-to-noise ratio is 10dB, the noise is white Gaussian noise, and 200 Monte Carlo experiments are carried out to ensure the reliability of a simulation result. The tic function and the toc function in the MATLAB are used, the running time of the algorithm in the computer is recorded, the time used by the two methods for DOA estimation with different searching steps in the acoustic vector circular array is compared, and the results are shown in the following table:
time (unit/s) used for DOA estimation by vector circular array two methods
The first and second examples show that the application of the rapid MVDR algorithm provided by the invention in the acoustic vector circular array and the sound pressure circular array can realize the complete and accurate azimuth information in the semi-spectrum search, the resolution ratio is almost the same as that of the conventional MVDR method, and the resolution ratio is higher; fig. 3 and 5 in the example show that when the incident angle is not in the searched spectrum range, the conventional MVDR algorithm obviously cannot estimate the signal azimuth in the half-spectrum search, but the fast MVDR algorithm provided by the present invention can obtain azimuth information in the half-spectrum search, and the real incident direction of the sound source can be obtained by performing discrimination in steps 7 to 9 on the spectrum peak angle; fig. 4 and fig. 6 show that the anti-noise performance of the vector circular array using the sound pressure and vibration velocity combined processing method is significantly superior to that of the sound pressure array, and can significantly suppress side lobe fluctuation and improve spatial resolution; the third example shows that the method can obviously improve the efficiency of the acoustic vector circular array azimuth estimation method and realize the rapid azimuth estimation of the acoustic vector circular array.
By combining three examples, the method disclosed by the invention can ensure high resolution, improve the calculation efficiency of the acoustic vector circular array and obviously improve the performance of the acoustic vector circular array azimuth estimation. The invention successfully provides a high-resolution and high-calculation-efficiency rapid azimuth estimation method for a centrosymmetric acoustic vector circular array, and solves the problems that the resolution is continuously improved but the calculation amount is larger and the calculation efficiency cannot be improved in the conventional vector circular array signal processing method.
In conclusion, the invention provides a method for estimating the location of the super-resolution of the central symmetric acoustic vector circular array by fast spatial spectrum compression. Firstly, the sensors of the upper and lower semi-circular rings of the acoustic vector circular array are respectively arranged according to a specific sequence, acoustic signals are collected, and the acoustic vector circular array is constructed to meet the requirements
A steering vector of (a); then, according to the average noise intensity anti-noise principle of the acoustic vector sensor, a covariance matrix is constructed by adopting a sound pressure and vibration velocity combined processing method, so that the vector matrix steering vector matrix dimension is reduced, and the anti-noise capability is improved; then, a new space spectrum function is constructed according to the space spectrums of the real source and the virtual source which is 180 degrees different from the real source to perform half-spectrum search, so that the compression of the sound vector circular array space spectrum is realized; finally, the real sound source position is rapidly judged through the discriminant formula constructed by the invention. The method realizes the compression of the spatial spectrum of the vector circular array for the first time, greatly improves the operation efficiency while ensuring high resolution, and realizes the quick and efficient super-resolution azimuth estimation of the acoustic vector circular array. />
Claims (2)
1. A central symmetry acoustic vector circular array fast space spectrum compression super-resolution direction estimation method is characterized in that: the method comprises the following steps:
the method comprises the following steps: dividing the acoustic vector circular array into an upper semicircular ring and a lower semicircular ring, collecting signal data received by sensors of the semicircular rings on the acoustic vector circular array in an anticlockwise sequence, collecting signal data received by sensors of the semicircular rings on the acoustic vector circular array in a clockwise sequence, and constructing a received signal matrix of a sound pressure channel and x-direction and y-direction vibration velocity channels of the whole acoustic vector circular array at the time t
And
step two: carrying out azimuth scanning, respectively constructing guide vectors corresponding to the received signals for the sensors of the upper semicircular ring and the lower semicircular ring, and then synthesizing a guide vector matrix of the whole acoustic vector circular array
At this time, for any azimuth angle theta, the steering vector matrix satisfies the following conditions:
wherein, the first and the second end of the pipe are connected with each other,
and
respectively representing the guide vectors of a sound pressure channel and x and y direction vibration velocity channels of the sound vector circular array, wherein "+" represents conjugate operation;
step three: the two vibration velocity components are subjected to weighted linear combination, and the azimuth scanning angle theta is used as the guide azimuth of the electronic rotation to obtain the joint vibration velocity of the acoustic vector circular array in the guide direction theta
Comprises the following steps:
step four: performing dimension reduction processing on the vector array covariance matrix data according to the average noise intensity anti-noise principle, and constructing a covariance matrix R when the azimuth scanning angle is theta pv (θ)，
Wherein E [. Cndot. ] represents the expectation, and the superscript "H" represents the conjugate transpose operation;
step five: based on MVDR beamformer, using covariance matrix R pv (theta) and steering vector matrix
Constructing a space spectrum function P (theta) for realizing rapid and super-resolution orientation estimation;
step six: obtaining an azimuth spectrum function value corresponding to the scanning angle theta by using the constructed spatial spectrum function P (theta);
step seven: repeating the second step to the sixth step, and determining the theta in the range of 0, pi]Or theta epsilon [ pi, 2 pi ]]The half spectrum scanning is carried out in the range of (2), an image of a half space spectrum is drawn, and the spectrum peak position theta is obtained by observing the image of the space spectrum k ；
Step eight: using theta k Calculating to obtain the whole space spectrum [0,2 pi ]]Position of another spectral peak in the range theta k * The calculation formula is as follows:
step nine: substituting the position information of two spectral peaks obtained in the vector circular array semi-spectrum search into a conventional MVDR algorithm space spectrum function to obtain two corresponding function values P (theta) k ) And P (theta) k * )：
Step ten: comparing the two obtained function values, and judging by the following formula:
and distinguishing the position of the real sound source from the two spectral peaks, and determining the incoming wave direction of the sound source.
2. The method for fast spatial spectrum compression super-resolution azimuth estimation of the centrosymmetric acoustic vector circular array according to claim 1, characterized in that: the fifth step is specifically as follows:
(1) Reducing the covariance matrix R after dimension reduction pv (theta) introducing an MVDR beam former to obtain a spatial spectrum function of a real sound source as follows:
wherein, the superscript "-1" represents the inversion operation;
(2) Satisfied by post-reconstruction signal steering vector matrix
This relationship is found in [0,2 π]The spatial spectrum function of a virtual source within the range which has a 180-degree difference with the incident angle of the real sound source is as follows:
(3) Fitting the space spectrums of the real source and the virtual source to construct a space spectrum function suitable for half-spectrum search:
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