CN112130112B - Information source number estimation method based on acoustic vector array joint information processing - Google Patents

Information source number estimation method based on acoustic vector array joint information processing Download PDF

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CN112130112B
CN112130112B CN202010991187.1A CN202010991187A CN112130112B CN 112130112 B CN112130112 B CN 112130112B CN 202010991187 A CN202010991187 A CN 202010991187A CN 112130112 B CN112130112 B CN 112130112B
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惠娟
郭嘉宾
向悠扬
赵安邦
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Abstract

The invention belongs to the technical field of array signal processing, and particularly relates to an information source number estimation method based on acoustic vector array joint information processing. The method is based on acoustic vector array sound pressure and vibration velocity combined information processing, and is suitable for the problem that the information source number estimation algorithm is inaccurate under the condition of low signal to noise ratio in the underwater acoustic environment. The invention adopts acoustic vector array sound pressure and vibration velocity combined information processing to estimate the number of information sources, and aims at solving the problem that signals of certain directions are possibly filtered or weakened due to the space filtering action when the observation direction is fixed. The invention utilizes the advantage of acoustic vector array azimuth scanning, avoids the weakening of signals in a certain direction due to spatial filtering, and improves the performance of the traditional information source number estimation algorithm.

Description

Information source number estimation method based on acoustic vector array joint information processing
Technical Field
The invention belongs to the technical field of array signal processing, and particularly relates to an information source number estimation method based on acoustic vector array joint information processing.
Background
Underwater acoustic array signal processing is an important technology for underwater detection, identification, communication and the like, and one of important tasks is to estimate the target orientation. The subspace type high-resolution spectrum estimation algorithm represented by the multiple signal classification algorithm is proposed successively, and the subspace type high-resolution spectrum estimation algorithm has good prospects in the field of underwater acoustic engineering for estimating the direction of arrival. The source number estimation is a prerequisite for the high-resolution subspace-like spectrum estimation algorithm to perform the azimuth estimation, so that the research of the source number estimation is one of the important research directions in the array signal processing.
Based on radar and sonar scalar arrays, the method is mainly divided into two categories of algorithms based on characteristic value information and characteristic vector information, the performance of the information source number estimation algorithm is poor under low signal-to-noise ratio, and in underwater acoustic environments, the problem to be solved is how to accurately estimate the information source number under low signal-to-noise ratio.
In the article, the acoustic vector array source number detection and orientation estimation (Chinese edition) based on the combined processing of sound pressure and vibration velocity is disclosed in 'Baixingyu, Jiangyu, Zhao Chunhui', 2008(01):56-61. The method adopts the method of acoustic vector array PVc combined information processing, cannot well inhibit noise, has performance decline under the condition of low signal-to-noise ratio, has narrow application range, and cannot adopt acoustic vector array sound pressure and vibration velocity combined processing to estimate the information source number with various criteria.
The Yao straight image is a vector array rotation invariant subspace orientation estimation method [ J ] based on sound pressure and vibration velocity combined processing, university of Beijing science and technology, 2012,32(05):513 +521 ], wherein a sound vector array is utilized to carry out cover-type circle criterion information source number estimation by adopting sound pressure and vibration velocity combined processing.
In summary, accurate estimation of underwater information source number under low signal-to-noise ratio is lacked in the current stage, so that the method is popularized to an acoustic vector array sound pressure and vibration velocity combined information processing feature projection method for carrying out an information source number estimation algorithm.
Disclosure of Invention
The invention aims to provide an information source number estimation method based on acoustic vector array joint information processing, which can accurately estimate the underwater information source number under the underwater acoustic low signal-to-noise ratio.
The purpose of the invention is realized by the following technical scheme: the method comprises the following steps:
step 1: receiving far-field plane wave data of a plurality of information sources by utilizing a two-dimensional acoustic vector hydrophone uniform linear array to obtain an output component p of a sound pressure channel of an array element m m (t), output component v of vibration velocity x channel xm (t), output component v of the vibration velocity y channel ym (t)：
Figure BDA0002691018740000021
Wherein M is the number of acoustic vector arrays of the vector hydrophones; k is the number of space signals of incident sound to the vector array; theta.theta. k For the k-th space signal s k (t) a two-dimensional spatial angle of arrival; n is pm (t),
Figure BDA0002691018740000022
Respectively corresponding to the noise of the m-th array element sound pressure channel, the vibration velocity x channel and the vibration velocity y channel; a (theta) k ) The vector is a guide vector of a uniform linear array;
Figure BDA0002691018740000023
step 2: arranging and combining the received data of each array element to obtain the output P (t) of the sound pressure channel of the acoustic vector hydrophone array and the output V of the vibration velocity x channel x (t) and output V of the Y channel y (t)；
Figure BDA0002691018740000024
And step 3: the vibration velocity x channel data V x (t) and velocity y channel data V y (t) combining them to obtain data V of combined channel c (t)；
Figure BDA0002691018740000025
Wherein the content of the first and second substances,
Figure BDA0002691018740000026
is the leading azimuth;
and 4, step 4: guiding azimuth angles to scan according to uniform intervals within an acoustic vector array observation angle range;
and 5: constructing a covariance matrix R (in a certain range) of sound pressure and vibration velocity joint processing under each azimuth guiding azimuth angle p+v ) v ；
Figure BDA0002691018740000027
Step 6: the covariance matrix constructed for each azimuth angle is arranged from large to small according to the row and norm thereof;
and 7: the covariance matrixes corresponding to the rows and the first 25 percent of the norm are added to obtain a new covariance matrix R pv ；
And step 8: r is to be pv Projecting the image into an eigenvector matrix U to obtain a projection P ═ U H R pv (ii) a Wherein the projection P ═ U H R pv Is P in the ith column (i ═ 1, 2.., M) i ＝[p 1i ,p 2i ,...,p mi ,...,p Mi ] T ；
And step 9: calculate and make
Figure BDA0002691018740000031
The m value with the maximum value is used as the estimated value of the number of the information sources
Figure BDA0002691018740000032
Wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0002691018740000033
being the average of all the element modes of the m-th row of the projection P,
Figure BDA0002691018740000034
the invention has the beneficial effects that:
the invention provides the acoustic vector array joint information processing-based information source number estimation method which can accurately estimate the underwater information source number under the underwater acoustic low signal-to-noise ratio and popularize the information source number estimation algorithm to the acoustic vector array sound pressure and vibration velocity joint information processing. The method is based on acoustic vector array sound pressure and vibration velocity combined information processing, and is suitable for the problem that the information source number estimation algorithm is inaccurate under the condition of low signal to noise ratio in the underwater acoustic environment. The method adopts acoustic vector array sound pressure and vibration velocity combined information processing to estimate the number of the information sources, and can enable the selected covariance matrix to consider the information sources incident at each direction aiming at the problem that the signals of certain directions are filtered or weakened due to the space filtering action when the observation direction is fixed, thereby reducing the influence caused by the space filtering action when the observation direction is fixed.
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FIG. 1 is a flow chart of the present invention.
Fig. 2 is a schematic diagram of the received signals of a uniform linear array of acoustic vector hydrophones.
FIG. 3 is a diagram of the accuracy of source estimation under the eigenspace Projection (ESP) source estimation and the SNR relationship between the method of the present invention and the prior art method.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention provides the acoustic vector array joint information processing-based information source number estimation method which can accurately estimate the underwater information source number under the underwater acoustic low signal-to-noise ratio and popularize the information source number estimation algorithm to the acoustic vector array sound pressure and vibration velocity joint information processing.
Step 1: firstly, a two-dimensional acoustic vector hydrophone uniform linear array is utilized to receive far-field plane wave data of a plurality of information sources, M acoustic vector arrays of the acoustic vector hydrophones are utilized, K space signals are incident on the acoustic vector arrays, and the kth space signal s k (t) Has a two-dimensional arrival angle of theta k To obtain the output component p of the acoustic pressure channel of the array element m m (t), output component v of vibration velocity x channel xm (t), output component v of channel of vibration velocity y ym (t)：
Figure BDA0002691018740000041
n pm (t),
Figure BDA0002691018740000042
Respectively corresponding to the m-th array element sound pressure channel, the vibration velocity x channel and the vibration velocity y channel. a (theta) i ) Steering vector for uniform linear array:
Figure BDA0002691018740000043
step 2: arranging and combining the received data of each array element to obtain an acoustic vector hydrophone array sound pressure channel P (t) and a vibration velocity x channel V x (t) channel V of vibration velocity y y Output of (t):
Figure BDA0002691018740000044
and step 3: the vibration velocity x channel data V x (t) and velocity y channel data V y (t) combining with each other to obtain data of a combined channel:
Figure BDA0002691018740000045
wherein
Figure BDA0002691018740000046
Is the leading azimuth;
and 4, step 4: guiding azimuth angles to scan according to uniform intervals within an acoustic vector array observation angle range;
and 5: constructing a covariance matrix of sound pressure and vibration velocity combined processing under each azimuth guiding azimuth angle:
Figure BDA0002691018740000047
step 6: the covariance matrix constructed for each azimuth angle is arranged from large to small according to the row and norm of the covariance matrix;
and 7: the covariance matrixes corresponding to the rows and the first 25 percent of the norm are added to obtain a new covariance matrix R pv 。
And 8: r is to be pv Projecting the image into an eigenvector matrix U to obtain a projection P ═ U H R pv The ith column (i ═ 1, 2.., M) indicates: p is i ＝[p 1i ,p 2i ,...,p mi ,...,p Mi ] T The source number estimation is performed by processing the projection matrix P. The mean of all the element modes in the m-th row of P is recorded as
Figure BDA0002691018740000048
Has a value of
Figure BDA0002691018740000049
p m L can be used as criterion for estimating the number of information sources, p m I is divided into two groups, the larger group corresponds to the incident sound signals, and the value of m in the larger group is the number of the information sources;
and step 9: the feature Space Projection (ESP) algorithm performs discrimination by using the following relational expression
Figure BDA0002691018740000051
Estimation of the number of sources
Figure BDA0002691018740000052
Taking the value of m which maximizes the value of the formula;
compared with the existing information source number estimation method, the method has the following beneficial effects:
firstly, the method is based on acoustic vector array sound pressure and vibration velocity combined information processing, and is suitable for the problem that the information source number estimation algorithm is not accurate under the condition of low signal to noise ratio in the underwater acoustic environment.
Secondly, the invention adopts acoustic vector array sound pressure and vibration velocity combined information processing to estimate the number of the information sources, and aims at solving the problem that signals of certain directions are possibly filtered or weakened due to the space filtering action when the observation direction is fixed.
Example 1:
the method provided by the invention and the existing method are adopted for simulation calculation, the simulation conditions are calculated by using MATLAB on a computer, and the specific parameters of the simulation environment are as follows:
array properties: a two-dimensional acoustic vector hydrophone array;
the number of array elements: 8;
array element spacing: half of the incident wavelength of the signal;
number of signal sources: 3, the number of the cells is 3;
signal source properties: mutually independent signals;
the incident angle of the signal source is as follows: (15 DEG, 30 DEG, 60 DEG)
Fast beat number: 1000, parts by weight;
signal-to-noise ratio: -20-10 dB;
experimental contents and results:
experiment 1: the method adopts the characteristic space projection to carry out the information source number estimation, and the performance is obviously improved
(1) Two mutually independent equal-power narrow-band signal sources are arranged and respectively marked as a signal source 1 and a signal source 2, the center frequency of the two independent equal-power narrow-band signal sources is 150Hz, and the incident angles are respectively 15 degrees, 30 degrees and 60 degrees; the array is an 8-element acoustic vector uniform linear array, the distance between array elements is half wavelength, the sampling frequency of the array is 10kHz, and the receiving bandwidth is 20 Hz-1500 Hz; the observation direction of the acoustic vector hydrophone array is set to scan between 60 degrees and 60 degrees. The background noise is band-limited white Gaussian noise, the range of the signal-to-noise ratio is-20 dB to 10dB, the variation step length is 1dB, the snapshot number is 1000, and 500 times of Monte Carlo simulation is carried out on each signal-to-noise ratio.
Fig. 3 shows the relationship between the accuracy of the source number estimation using eigenspace Projection (ESP) and the signal-to-noise ratio in the method of the present invention and the method of the prior art.
The prior direction adopts a method proposed in the article of Yao Zheng Xiang, Jiangcao, Guohui and Chenjiang, a vector array rotation invariant subspace direction estimation method based on sound pressure and vibration velocity combined processing [ J ], university of Beijing university of science and technology, 2012,32(05): 513-.
Referring to fig. 3, the method provided by the present invention and the method in the prior art adopt the relationship between the accuracy of the characteristic Space Projection (ESP) information source estimation and the signal-to-noise ratio, and it can be seen from the figure that under the same signal-to-noise ratio, the success probability of the information source detection of the method of the present invention is far higher than that of the other two methods, and when the signal-to-noise ratio is-13 dB, the success probability of the detection of the method of the present invention completely approaches 1, and the method of the present invention has excellent performance at low signal-to-noise ratio. The method provided by the invention is obviously superior to the existing method and the method adopting sound pressure information processing, and the success probability of information source number estimation is obviously improved.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (1)

1. A method for estimating the information source number based on acoustic vector array joint information processing is characterized by comprising the following steps:
step 1: receiving far-field plane wave data of a plurality of information sources by utilizing a two-dimensional acoustic vector hydrophone uniform linear array to obtain an output component p of a sound pressure channel of an array element m m (t), output component v of vibration velocity x channel xm (t), output component v of the vibration velocity y channel ym (t)：
Figure FDA0003762944370000011
Wherein M is the number of acoustic vector arrays of the vector hydrophones; k is the incident sound to vectorThe number of spatial signals on the array; theta k For the k-th space signal s k (t) a two-dimensional spatial angle of arrival;
Figure FDA0003762944370000017
respectively corresponding to the noise of the m-th array element sound pressure channel, the vibration velocity x channel and the vibration velocity y channel; a (theta) k ) The vector is a guide vector of a uniform linear array;
Figure FDA0003762944370000012
step 2: arranging and combining the received data of each array element to obtain the output P (t) of the sound pressure channel of the acoustic vector hydrophone array and the output V of the vibration velocity x channel x (t) and output V of the Y channel y (t)；
Figure FDA0003762944370000013
And step 3: the vibration velocity x channel data V x (t) and speed of vibration y channel data V y (t) combining them to obtain data V of combined channel c (t)；
Figure FDA0003762944370000014
Wherein the content of the first and second substances,
Figure FDA0003762944370000015
is the leading azimuth;
and 4, step 4: guiding azimuth angles to scan according to uniform intervals within an acoustic vector array observation angle range;
and 5: constructing a covariance matrix R of sound pressure and vibration velocity combined processing under each azimuth guiding azimuth angle (p+v)v ；
Figure FDA0003762944370000016
Step 6: the covariance matrix constructed for each azimuth angle is arranged from large to small according to the row and norm thereof;
and 7: the covariance matrixes corresponding to 25% of the rows and the norm are added to obtain a new covariance matrix R pv ；
And 8: r is to be pv Projecting the image into an eigenvector matrix U to obtain a projection P ═ U H R pv (ii) a Wherein the projection P ═ U H R pv Is listed as P i ＝[p 1i ,p 2i ,...,p mi ,...,p Mi ] T ，i＝1,2,...,M；
And step 9: calculate and make
Figure FDA0003762944370000021
The m value with the maximum value is used as the estimated value of the number of the information sources
Figure FDA0003762944370000022
Wherein the content of the first and second substances,
Figure FDA0003762944370000023
being the average of all the element modes of the m-th row of the projection P,
Figure FDA0003762944370000024
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