CN110133578A - A kind of sub-bottom reflection sound ray incident angle estimation method based on semicolumn volume array - Google Patents
A kind of sub-bottom reflection sound ray incident angle estimation method based on semicolumn volume array Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
- G01S3/80—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using ultrasonic, sonic or infrasonic waves
- G01S3/802—Systems for determining direction or deviation from predetermined direction
- G01S3/803—Systems for determining direction or deviation from predetermined direction using amplitude comparison of signals derived from receiving transducers or transducer systems having differently-oriented directivity characteristics
Abstract
The sub-bottom reflection sound ray incident angle estimation method based on semicolumn volume array that the present invention provides a kind of, semicolumn volume array is divided into several identical planar arrays along axis direction, sound ray azimuth is estimated using on planar array, Beam-former is designed according to estimated azimuth, complete Wave beam forming, it is the reception signal of a single dimension array by the wave beam output equivalent of each planar array, and sound ray pitch angle is estimated using the single dimension array, simplify computation complexity, realize estimation of the volume array to sub-bottom reflection sound ray azimuth and pitch angle efficient quick.Meanwhile the high-resolution to coherent reflection sound ray pitch angle is realized using SAMV algorithm.
Description
Technical field
The present invention relates to field of signal processing, especially a kind of estimation method of sub-bottom reflection sound ray.
Background technique
Sub-bottom reflection is a kind of typical acoustic propagation mode, makes full use of sub-bottom reflection sound ray, can effectively be promoted underwater
Detectivity.The sound ray for reaching receiving end by sub-bottom reflection is numerous, wherein there are four types of sound ray propagation loss, smaller, arrival is connect
The energy of receipts system is higher, therefore is often used for target detection, they are respectively 1 sub-bottom reflection sound ray；1 time seabed is anti-
It penetrates and adds 1 sea surface reflection sound ray；1 sea surface reflection adds 1 sub-bottom reflection sound ray；1 sea surface reflection, 1 sub-bottom reflection pass through again
Cross 1 sea surface reflection sound ray.By carrying out target bearing (Direction of Arrival, DOA) estimation to these four sound rays,
The angle information of effect can be provided with for processing such as subsequent positioning, target detections.
Conventional beamformer (Conventional beamforming, CBF) method is former as traditional DOA algorithm for estimating
Reason is simple, is easily achieved, and more steady to environmental change.But the algorithm receives the limitation of " Rayleigh criterion ", distinguishing
It can not be high.In view of the angle difference of four kinds of sub-bottom reflection sound rays is smaller, it is carried out using CBF algorithm DOA estimation be difficult by
Four kinds of sound rays are separated.Traditional high resolution algorithm such as minimum variance is undistorted to respond (Minimum variance
Distortionless response, MVDR) and multiple signal classification (Multiple signal classification,
MUSIC) algorithm can break through the limitation of " Rayleigh criterion ", but can not handle coherent signal.Due to the coherence of sub-bottom reflection sound ray
It is relatively strong, therefore the DOA that sub-bottom reflection sound ray can not be carried out using traditional high resolution algorithm is estimated.
DOA estimation based on sparse signal processing is the DOA algorithm for estimating that last decade grows up.Estimate with traditional orientation
Calculating method is compared, and sparse signal processing can be used under smaller number of snapshots and lower state of signal-to-noise, and can handle phase
The DOA estimation problem of dry signal, performance are far superior to traditional algorithm.Corresponding Sparse Algorithm be broadly divided into regular parameter class algorithm and it is non-just
Then parameter class algorithm.Wherein regular parameter class algorithm combines sparse item and data error of fitting usually using regular parameter,
Constitute convex optimization problem.Regular parameter seriously affects the performance of algorithm, and the usually more difficult selection of the parameter.It is sparse approximate minimum
Variance (Sparse asymptotic minimum variance, SAMV) algorithm (H.Abeida, Q.Zhang, J.Li, et
al.Iterative sparse asymptotic minimum variance based approaches for array
Processing [J] .Transactions on Signal Processing, 2013,61 (4): 933-944) it is a kind of common
Non- regular parameter class DOA algorithm for estimating, the algorithm is public using the iteration that approximate minimum variance principle extrapolates signal and noise
Formula reconstructs covariance matrix by way of iteration.Entire solution procedure only needs provide the thresholding of iteration stopping, without any
Regular parameter, therefore the algorithm has more practicability than regular parameter class algorithm.
In view of receiving array is usually semicolumn volume array, array element is more, using SAMV algorithm simultaneously to reflected sound
The azimuth of line and pitch angle carry out estimating that calculation amount is larger, and calculating speed is slower.Therefore, suitable mode need to be selected to estimate
The azimuth and pitch angle that sound ray reaches, to improve computational efficiency.
Summary of the invention
For overcome the deficiencies in the prior art, the present invention provides a kind of sub-bottom reflection sound ray based on semicolumn volume array and enters
Penetrate angle estimating method.In order to simplify algorithm computation complexity, semicolumn volume array is divided by the present invention along axis direction
Several identical semicircular ring planar arrays are estimated on any one planar array using azimuth of the SAMV algorithm to sound ray
Meter；Beam-former is designed according to estimated azimuth, Wave beam forming is carried out to each planar array respectively, wave beam output can
It is equivalent to the reception signal of vertical linear array；On equivalent vertical linear array, sound ray pitching angular estimation is carried out using SAMV algorithm,
To complete the efficient estimation to four sub-bottom reflection sound ray azimuths and pitch angle.
The technical solution adopted by the present invention to solve the technical problems be the following steps are included:
Step 1: the estimation of reflection sound ray azimuth
Semicolumn battle array is divided into L planar array along axis direction, L planar array is identical semicircular ring battle array, array element
Number is M, establishes two-dimensional coordinate system using the center of circle as origin for any one planar array, the seat of m array element on the array
Labeled as (xm,ym), wherein m=1 ... uniform plane where planar array is divided into Q discrete mesh points, each grid by M
The vector of the representative azimuth composition of point is denoted as Θ=[θ1,θ2,…,θQ], it is assumed that signal distributions on the grid divided,
Then the signal of array received indicates are as follows:
Y (t)=A (Θ) s (t)+n (t), t=1,2 ..., T (1)
Wherein y (t) is array received signal, and s (t) and n (t) are signal and noise data vector, number of snapshots T, A respectively
(Θ) is array manifold matrix, is expressed as A (Θ)=[a (θ1),a(θ2),…a(θq),…,a(θQ)], list is shown asK is wave number, subscript
" T " is transposition operation, θqIndicate azimuth representated by q-th of mesh point；
Assuming that noise data is independent identically distributed white Gaussian noise, corresponding covariance matrix is E [n (t) nH(t)]=
σ2I, wherein E () is mathematic expectaion operator, and subscript " H " is conjugate transposition operation, σ2For noise power, I is unit matrix, together
When think that signal and noise are uncorrelated, then array output covariance matrix R indicate are as follows:
In formula, P=diag (p1,p2,…,pq,…pQ), pqFor signal power, q=1 ..., Q, diag () indicate diagonal
Matrix, array output covariance matrix R pass through sample covariance matrixEstimation obtains, whereinT is total number of snapshots；
Vector quantities operation is carried out to formula (2) to obtain:
In formula, vec () representing matrix vectorization operator,Indicating Kronecker product, subscript " * " is conjugate operation,
MatrixForVectorFor
According to SAMV algorithm, signal power and noise power, signal power and noise function are calculated by the way of iteration
The iterative formula of rate is as follows:
WhereinWithRespectively q-th of signal power and noise power of (i) secondary iteration, aq=a (θq) indicate
The corresponding azimuthal array manifold vector of q-th of mesh point, Tr () is Matrix Calculating trace operator, and iteration initial value is determined by following formula:
Wherein | | | | indicate 2 norm of vector, when adjacent iteration twice meets following formula:
Wherein η1For selected iteration ends thresholding, when the iterated conditional for meeting formula (6), then iteration ends, are estimated
The corresponding orientation of peak value in the power spectrum of meterAs reflect the azimuth of sound ray；
Step 2: Wave beam forming
The sound ray azimuth according to estimated by step 1It is filtered using CBF algorithm, calculates each planar array in the party
Wave beam output in parallactic angle；
Weighing vector corresponding to CBF algorithm are as follows:
The corresponding wave beam output of first of planar array are as follows:
For first of planar array the equivalent array element of the center point reception signal；
Step 3: reflection sound ray pitch angle estimation
According to step 2, every layer plane battle array is equivalent to the array element of the center point, then it is vertical to be equivalent to L member for the volume array
Linear array, array element spacing is d, and the sound source nearest apart from the water surface is as a reference point, then corresponding to the equivalent vertical line battle array
Array manifold vector isSpace is uniform along the direction perpendicular to equivalent linear array
It is divided into U grid, the vector of the composition of angle representated by each mesh point is denoted asBased on the grid, hang down
Straight battle array received signal model is expressed as:
Wherein WithIt is signal and noise data vector respectively,For battle array
Column manifold matrix, is expressed as
Pitch angle is estimated using SAMV algorithm, at this time the iterative formula of signal power and noise power are as follows:
Wherein,WithRespectively u-th of signal power and noise power of (i) secondary iteration,Indicate the corresponding azimuthal array manifold vector of u-th of mesh point,Indicate the corresponding side of u-th of mesh point
Parallactic angle, For sampling
Covariance matrix；Iteration initial value byIt calculates
It arrives；When adjacent iteration twice meetsThen iteration ends, wherein η2For selected iteration ends thresholding,
The corresponding orientation of peak value in estimated power spectrumAs reflect the pitch angle of sound ray.
The beneficial effects of the present invention are identical since semicolumn volume array is divided into several along axis direction
Planar array estimates sound ray azimuth using on planar array, designs Beam-former according to estimated azimuth, completes
Wave beam forming, is the reception signal of a single dimension array for the wave beam output equivalent of each planar array, and utilizes the single dimension
Array estimates sound ray pitch angle, simplifies computation complexity, realize volume array to sub-bottom reflection sound ray azimuth and
The estimation of pitch angle efficient quick.Meanwhile the high-resolution to coherent reflection sound ray pitch angle is realized using SAMV algorithm.
Detailed description of the invention
Fig. 1 is the overall procedure block diagram of sub-bottom reflection sound ray of the present invention azimuth and pitching angular estimation.
Fig. 2 is semicolumn volume array schematic diagram of the present invention.
Fig. 3 (a) is planar array schematic diagram, and 3 (b) be equivalent vertical linear array schematic diagram.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples.
The present invention is a kind of estimation method based on semicolumn volume array to sub-bottom reflection sound ray azimuth and pitch angle, main
Volume array is successively equivalent to planar array and linear array, azimuthal and pitch angle are estimated respectively, and utilize sparse close
Like minimum variance to the high-resolution of coherent signal, realize each sub-bottom reflection sound ray pitch angle and it is azimuthal be effectively estimated, be
The processing such as succeeding target positioning are provided with the sub-bottom reflection sound ray angle information of effect, relate generally to the fields such as signal processing.
Step 1: the estimation of reflection sound ray azimuth
Semicolumn battle array is divided into L planar array along axis direction, L planar array is identical semicircular ring battle array, array element
Number is M, establishes two-dimensional coordinate system using the center of circle as origin for any one planar array, the seat of m array element on the array
Labeled as (xm,ym), wherein m=1 ... uniform plane where planar array is divided into Q discrete mesh points, each grid by M
The vector of the representative azimuth composition of point is denoted as Θ=[θ1,θ2,…,θQ], it is assumed that signal distributions on the grid divided,
Then the signal of array received indicates are as follows:
Y (t)=A (Θ) s (t)+n (t), t=1,2 ..., T (1)
Wherein y (t) is array received signal, and s (t) and n (t) are signal and noise data vector, number of snapshots T, A respectively
(Θ) is array manifold matrix, is expressed as A (Θ)=[a (θ1),a(θ2),…a(θq),…,a(θQ)], list is shown asK is wave number, subscript
" T " is transposition operation, θqIndicate azimuth representated by q-th of mesh point；
Assuming that noise data is independent identically distributed white Gaussian noise, corresponding covariance matrix is E [n (t) nH(t)]=
σ2I, wherein E () is mathematic expectaion operator, and subscript " H " is conjugate transposition operation, σ2For noise power, I is unit matrix, together
When think that signal and noise are uncorrelated, then array output covariance matrix R indicate are as follows:
In formula, P=diag (p1,p2,…,pq,…pQ), pqFor signal power, q=1 ..., Q, diag () indicate diagonal
Matrix, array output covariance matrix R pass through sample covariance matrixEstimation obtains, wherein
T is total number of snapshots；
Vector quantities operation is carried out to formula (2) to obtain:
In formula, vec () representing matrix vectorization operator,Indicating Kronecker product, subscript " * " is conjugate operation,
MatrixForVectorFor
According to SAMV algorithm, signal power and noise power, signal power and noise function are calculated by the way of iteration
The iterative formula of rate is as follows:
WhereinWithRespectively q-th of signal power and noise power of (i) secondary iteration, aq=a (θq) indicate
The corresponding azimuthal array manifold vector of q-th of mesh point, Tr () is Matrix Calculating trace operator, and iteration initial value is determined by following formula:
Wherein | | | | indicate 2 norm of vector, when adjacent iteration twice meets following formula:
Wherein η1For selected iteration ends thresholding, η is taken in the present invention1It is 10-4As iteration ends thresholding；Work as satisfaction
The iterated conditional of formula (6), then iteration ends, the corresponding orientation of peak value in estimated power spectrumAs reflect the side of sound ray
Parallactic angle；
Step 2: Wave beam forming
The sound ray azimuth according to estimated by step 1It is filtered using CBF algorithm, calculates each planar array at this
Wave beam output on azimuth；
Weighing vector corresponding to CBF algorithm are as follows:
The corresponding wave beam output of first of planar array are as follows:
For first of planar array the equivalent array element of the center point reception signal；
Step 3: reflection sound ray pitch angle estimation
According to step 2, every layer plane battle array is equivalent to the array element of the center point, then it is vertical to be equivalent to L member for the volume array
Linear array, array element spacing is d, and the sound source nearest apart from the water surface is as a reference point, then corresponding to the equivalent vertical line battle array
Array manifold vector isSpace is uniform along the direction perpendicular to equivalent linear array
It is divided into U grid, the vector of the composition of angle representated by each mesh point is denoted asBased on the grid,
Vertical array received signal model is expressed as:
Wherein WithIt is signal and noise data vector respectively,For battle array
Column manifold matrix, is expressed as
Pitch angle is estimated using SAMV algorithm, at this time the iterative formula of signal power and noise power are as follows:
Wherein,WithRespectively u-th of signal power and noise power of (i) secondary iteration,Indicate the corresponding azimuthal array manifold vector of u-th of mesh point,Indicate the corresponding side of u-th of mesh point
Parallactic angle, For sampling
Covariance matrix；Iteration initial value byIt calculates
It arrives；When adjacent iteration twice meetsThen iteration ends, wherein η2For selected iteration ends thresholding,
η of the present invention2Take 10-4As iteration ends thresholding, the corresponding orientation of peak value in estimated power spectrumAs reflect sound ray
Pitch angle.
Fig. 1 of the present invention is using volume array to the flow chart at sub-bottom reflection sound ray azimuth and pitch angle estimation method, tool
Body is implemented as follows:
Assuming that noise is white Gaussian noise, then the covariance matrix of array output signal is represented byFor signal power, σ2Noise power, I are unit battle array, and array is defeated
Covariance matrix R is by sample covariance matrix outEstimation obtains.Vector is carried out to covariance matrix
Change can obtainWhereinVec () representing matrix vectorization operator, Indicate Kronecker product, subscript " * " is conjugation fortune
It calculates,
According to SAMV algorithm it is found that the iterative relation formula of signal and noise are as follows:
WhereinWithRespectively q-th of signal power and noise power of (i) secondary iteration, aq=a
(θq) indicate the corresponding azimuthal array manifold vector of q-th of mesh point,Diag () indicates diagonal matrix.Tr () is
Matrix Calculating trace operator.Iteration initial value can be byMeter
It obtains.When adjacent iteration twice meetsThen iteration ends, wherein η1For selected iteration ends door
Limit selects 10-4As iteration ends thresholding, the corresponding orientation of peak value in estimated power spectrumAs reflect the orientation of sound ray
Angle.
2) the sound ray azimuth according to estimated by step 1)It is filtered using CBF algorithm, weighing vector isCalculate wave beam output of each planar array on the azimuth.The corresponding wave beam output of first of planar array
For The reception signal of the equivalent array element of the center point can be regarded as.
3) every layer plane battle array is equivalent to the array element of the center point, then the volume array is equivalent to L member vertical linear array, between array element
Away from for d.Shown in vertical linear array such as Fig. 3 (b), No. 1 array element is considered as reference point, then array manifold vector is expressed asSpace is evenly dividing along the direction perpendicular to equivalent linear array as U grid,
The vector of the composition of angle representated by each mesh point is denoted asBased on the grid, the received letter of vertical array
Number model is represented byWherein WithIt is signal and noise data vector respectively, number of snapshots T,For array manifold matrix, it is represented by
By SAMV algorithm it is found that the iterative relation formula of signal power and noise power at this time are as follows:
WhereinWithRespectively u-th of signal power and noise power of (i) secondary iteration,Indicate the corresponding azimuthal array manifold vector of u-th of mesh point,Indicate the corresponding side of u-th of mesh point
Parallactic angle, For sampling
Covariance matrix.Iteration initial value can be byIt calculates
It arrives.When adjacent iteration twice meetsThen iteration ends, wherein η2For selected iteration ends thresholding,
Present invention selection 10-4As iteration ends thresholding.Work as iteration ends, the corresponding orientation of peak value in estimated power spectrumAs
Reflect the pitch angle of sound ray.
Claims (1)
1. a kind of sub-bottom reflection sound ray incident angle estimation method based on semicolumn volume array, it is characterised in that including following steps
It is rapid:
Step 1: the estimation of reflection sound ray azimuth
Semicolumn battle array is divided into L planar array along axis direction, L planar array is identical semicircular ring battle array, element number of array
For M, two-dimensional coordinate system is established using the center of circle as origin for any one planar array, the coordinate note of m array element on the array
For (xm,ym), wherein m=1 ... uniform plane where planar array is divided into Q discrete mesh points, each mesh point institute by M
The vector of the azimuth composition of representative is denoted as Θ=[θ1,θ2,…,θQ], it is assumed that signal distributions are on the grid divided, then battle array
Column received signal indicates are as follows:
Y (t)=A (Θ) s (t)+n (t), t=1,2 ..., T (1)
Wherein y (t) is array received signal, and s (t) and n (t) are signal and noise data vector, number of snapshots T, A (Θ) respectively
For array manifold matrix, it is expressed as A (Θ)=[a (θ1),a(θ2),…a(θq),…,a(θQ)], list is shown asK is wave number, subscript
" T " is transposition operation, θqIndicate azimuth representated by q-th of mesh point；
Assuming that noise data is independent identically distributed white Gaussian noise, corresponding covariance matrix is E [n (t) nH(t)]=σ2I,
Wherein E () is mathematic expectaion operator, and subscript " H " is conjugate transposition operation, σ2For noise power, I is unit matrix, is recognized simultaneously
Uncorrelated for signal and noise, then array output covariance matrix R is indicated are as follows:
In formula, P=diag (p1,p2,…,pq,…pQ), pqFor signal power, q=1 ..., Q, diag () are indicated to angular moment
Battle array, array output covariance matrix R pass through sample covariance matrixEstimation obtains, whereinT
For total number of snapshots；
Vector quantities operation is carried out to formula (2) to obtain:
In formula, vec () representing matrix vectorization operator,Indicate Kronecker product, subscript " * " is conjugate operation, matrixForVectorFor
According to SAMV algorithm, signal power and noise power are calculated by the way of iteration, signal power and noise power
Iterative formula is as follows:
WhereinWithRespectively q-th of signal power and noise power of (i) secondary iteration, aq=a (θq) indicate q-th
The corresponding azimuthal array manifold vector of mesh point, Tr () is Matrix Calculating trace operator, and iteration initial value is determined by following formula:
Wherein | | | | indicate 2 norm of vector, when adjacent iteration twice meets following formula:
Wherein η1For selected iteration ends thresholding, when the iterated conditional for meeting formula (6), then iteration ends, estimated function
The corresponding orientation of peak value in rate spectrumAs reflect the azimuth of sound ray；
Step 2: Wave beam forming
The sound ray azimuth according to estimated by step 1It is filtered using CBF algorithm, calculates each planar array in the orientation
Wave beam output on angle；
Weighing vector corresponding to CBF algorithm are as follows:
The corresponding wave beam output of first of planar array are as follows:
For first of planar array the equivalent array element of the center point reception signal；
Step 3: reflection sound ray pitch angle estimation
According to step 2, every layer plane battle array is equivalent to the array element of the center point, then the volume array is equivalent to the vertical alignment of L member
Battle array, array element spacing is d, and the sound source nearest apart from the water surface is as a reference point, then array corresponding to the equivalent vertical line battle array
Manifold vector isSpace is evenly dividing along the direction perpendicular to equivalent linear array
For U grid, the vector of the composition of angle representated by each mesh point is denoted asBased on the grid, vertical array
Received signal model is expressed as:
Wherein WithIt is signal and noise data vector respectively,For array manifold
Matrix is expressed as
Pitch angle is estimated using SAMV algorithm, at this time the iterative formula of signal power and noise power are as follows:
Wherein,WithRespectively u-th of signal power and noise power of (i) secondary iteration,Indicate the corresponding azimuthal array manifold vector of u-th of mesh point,Indicate the corresponding side of u-th of mesh point
Parallactic angle,To adopt
Sample covariance matrix；Iteration initial value byIt calculates
It arrives；When adjacent iteration twice meetsThen iteration ends, wherein η2For selected iteration ends thresholding,
The corresponding orientation of peak value in estimated power spectrumAs reflect the pitch angle of sound ray.
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