CN111458689A - Multipath scattering characteristic classification method based on polarization scattering center - Google Patents

Multipath scattering characteristic classification method based on polarization scattering center Download PDF

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CN111458689A
CN111458689A CN202010290931.5A CN202010290931A CN111458689A CN 111458689 A CN111458689 A CN 111458689A CN 202010290931 A CN202010290931 A CN 202010290931A CN 111458689 A CN111458689 A CN 111458689A
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CN111458689B (en
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李永晨
魏飞鸣
顾丹丹
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Shanghai Radio Equipment Research Institute
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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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/411—Identification of targets based on measurements of radar reflectivity
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter

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Abstract

Aiming at the problem of composite multipath scattering of an ultra-low altitude target and a sea surface background, the invention provides a multipath scattering feature classification method based on a polarization scattering center, and the target scattering feature identification under the composite scattering background is realized. The method comprises three steps: the method comprises the steps of firstly, extracting a polarization scattering center of ultra-low-altitude target and sea surface composite scattering data, wherein the polarization scattering center comprises a complex amplitude and a position of the scattering center; polarization decomposition of a two-dimensional scattering matrix of a polarization scattering center and identification of the type of a scatterer; and thirdly, multipath analysis and scattering center classification of the distribution positions of the polarized scattering centers. The method for identifying the ultra-low altitude target and sea surface composite scattering characteristics can identify the scattering center and position of the target under complex multipath interference, filter background multipath clutter interference, effectively solve the target tracking and identifying problems under the current target and environment composite scattering scene, and provide a feasible way for improving the detection and identification precision of the target.

Description

Multipath scattering characteristic classification method based on polarization scattering center
Technical Field
The invention relates to a method for extracting and classifying radar target polarization scattering features, belongs to the technical field of radar target characteristic analysis and identification, and particularly relates to a multipath scattering feature classification method based on a polarization scattering center.
Background
The compound scattering of the ultra-low altitude target and the sea surface is mainly the multi-path scattering between the ultra-low altitude target and the sea surface, and the commonly used multi-path scattering analysis adopts a four-path method, including single scattering, secondary scattering and tertiary scattering. The scattering center is the basic characteristic of the target high-frequency scattering, and the polarized scattering center is an effective way for realizing the classification and identification of the scattering center. The first approach to the study of polarized scattering centers is to extract the polarized scattering centers of the target from the polarized scattering data.
The existing polarized scattering center extraction method mainly comprises the following two types, one is strong scattering peak extraction in a time domain or an image domain, the peak amplitude and the position are directly approximate to a target scattering center, for example, a patent CN103760544A carries out back projection on a pixel unit of which the target range image is larger than a certain threshold value, association and feature extraction of the target scattering center are realized through accumulation of the pixel unit, a patent CN104808187A adopts generalized Hough transformation to extract a target three-dimensional scattering center according to the space position and the change of the scattering center, the other is a frequency domain scattering center extraction method, a priori scattering center model is adopted to carry out scattering center parameter estimation in a model base, for example, a patent CN105389582A realizes parameter estimation of a target point scattering center model through a high-resolution spectrum estimation C L EAN algorithm, the existing technology carries out forward modeling on the target scattering center from a scattering mechanism, a plurality of parameters such as incident wave frequency, angle, scatterer length, orientation and position are taken into consideration, an attribute scattering center model is established, an attribute scattering center model is realized by adopting a sparse model parameterization method, and a particle swarm optimization parameter estimation technology is adopted to realize parameter estimation of a full polarized scattering center.
For the classification and identification of the types of the target polarization scattering centers, a target polarization decomposition method is mainly adopted at present. The target polarization decomposition realizes classification and identification by parametric decomposition of a target polarization scattering matrix and characterization of physical dimensions of different parameter changes. Current methods of coherent decomposition for objects include Pauli decomposition, Krogager decomposition, Cameron decomposition, Paladini decomposition, and the like. For a target scattering matrix meeting symmetry, Pauli decomposition decomposes the scattering matrix into single scattering on a flat surface and secondary scattering at 0-degree and 45-degree orientation dihedral angles, Krogager decomposition decomposes the scattering matrix into three types of scatterers, namely a sphere, a dihedral angle and a helix, Cameron decomposition decomposes the scattering matrix into a plurality of types of scatterers, namely a helix, a dihedral angle, a cylinder, a dipole, a quarter-wave device and the like, and Paladini decomposition realizes the scatterer classification consistent with the Cameron decomposition under the circular polarization basis of the scattering matrix.
Disclosure of Invention
The invention provides a polarization scattering center-based multipath scattering feature classification method, which realizes target scattering feature identification under a composite scattering background through the composite multipath scattering feature classification of an ultra-low altitude target and a sea surface background based on a polarization scattering center.
The technical scheme of the invention is to provide a multipath scattering characteristic classification method based on a polarization scattering center, which comprises the following steps:
step one, extracting a polarized scattering center of ultra-low altitude target and sea surface composite scattering: extracting distance direction scattering centers from the target and sea surface composite scattering broadband data by adopting a parametric spectrum estimation method to obtain a polarization scattering matrix comprising scattering center positions and corresponding to each scattering center position;
step two, characteristic decomposition and classification of the polarization scattering center scattering matrix: performing parameter decomposition on the scattering matrix by adopting a coherent target polarization decomposition method, and classifying the types of the scattering centers according to the change of decomposition parameters;
step three, multipath analysis and scattering type identification of the target polarization scattering center position: and solving the relative position relation between the positions of the target scattering centers according to a four-path analysis method of the target and environment composite scattering, thereby realizing the position matching of the composite multi-path scattering centers.
Aiming at the problem of composite multi-path scattering of an ultra-low altitude target and a sea surface background, the invention combines the four-path scattering characteristics of composite scattering of the target and the sea surface and adopts methods of polarized scattering center extraction, classification and position matching to realize the identification of the four-path scattering center of the composite scattering. The invention can identify the scattering center and position of the target under the complex multipath interference, filter background multipath clutter interference, effectively solve the target tracking and identifying problems under the current target and environment composite scattering scene, and provide a feasible way for improving the detection and identification precision of the target.
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FIG. 1 is a schematic diagram of a four-path scattering analysis of a very low altitude target with the sea surface;
FIG. 2 is a schematic diagram of scattering center locations of a target and sea surface multipath scattering;
FIGS. 3a and 3b are schematic diagrams of a composite scattering distance image and scattering center of a spherical ball and a sea surface; HH. The scattering center estimates for HV polarization correspond to fig. 3a, fig. 3b, respectively;
fig. 4 is a flow chart of the multipath scattering feature classification method of the present invention.
Detailed description of the preferred embodiments
The multipath scattering characteristic classification method based on the polarization scattering center is implemented by three parts of extraction, classification and position matching of the polarization scattering center, referring to fig. 4: extracting the composite polarization scattering centers of the ultra-low altitude target and the sea surface by adopting a parametric spectrum estimation method to realize the estimation of the position of each scattering center and a complete polarization scattering matrix; the polarization scattering center classification adopts a Cameron decomposition method to classify the scattering centers into 6 types such as dihedral angles, trihedral angles, cylinders, 1/4 wave devices, helicoids, dipoles and the like; the position matching of the polarization scattering center adopts a four-path analysis method to solve the relative position relation between the positions of the target scattering centers and realize the position matching of the composite multi-path scattering center.
1. Parameterized spectral estimation extraction of polarized scattering centers
The polarized scattering center extraction was performed using the multi-SIgnal Classification (MUSIC) algorithm of parametric spectral estimation. The MUSIC algorithm is a parameter spectrum estimation method of an array signal, and the main idea is as follows: and performing characteristic decomposition on the covariance matrix of the observation data to respectively obtain a signal subspace and a noise subspace, defining the MUSIC spectrum of the signal as the reciprocal of the square of the projection length of the signal observation vector in the noise subspace by utilizing the approximately orthogonal property of the signal subspace and the noise subspace, and estimating the signal parameter by a spectral peak search method.
The observed signal model of the polarization scatter data is represented as
Figure BDA0002450356250000031
Wherein the subscript "pq" denotes observed signal polarization, pq ═ VV, VH, HV, HH; sm,pqIs a position rmM represents a scattering center location sample; f. ofnFor incident wave frequency sampling, N is the number of frequency samples, u*(. cndot.) is observed noise.
For all-polarization scattering observation pq ═ VV, VH, HV, HH, equation (1) can be transformed into a matrix form
Y＝AS+U (28)
Wherein the content of the first and second substances,
Y＝[yVV,yVH,yHV,yHH](29)
A＝[a(r1),a(r2),…,a(rM)](30)
S＝[sVV,sVH,sHV,sHH](31)
U＝[uVV,uVH,uHV,uHH](32)
y is an N × 4 dimensional measurement matrix, where Ypq＝[ypq(1),ypq(2),…,ypq(N)]TA is an N × M-dimensional observation vector matrix, wherein,
Figure BDA0002450356250000041
the scattering amplitude and the measurement noise of the target under the pq polarization are respectively spq＝[s1,pq,s2,pq,…,sd,pq]T，upq＝[upq(1),upq(2),…,upq(N)]T。
For polarization measurement data Y, its covariance matrix is denoted RY＝E{YYHTo RYThe eigenvalue decomposition is carried out and can be expressed as
Figure BDA0002450356250000042
Wherein λ iskIs RYCharacteristic value of ekIs λkAnd has a characteristic vector of1≥λ2…≥λN. Covariance matrix RYThe characteristic values are positive definite matrixes and are all larger than zero; and is provided with
Figure BDA0002450356250000043
Namely RYIs a Hermitian matrix. Furthermore, RYSatisfies Toeplitz characteristics, so RYIs a Hermitian Toeplitz matrix.
Covariance matrix RYThe estimation of (c) affects the estimation accuracy of MUSIC. For actual observation data, the covariance matrix can be estimated by adopting a space smoothing method
Figure BDA0002450356250000044
Due to the fact that
Figure BDA0002450356250000045
Not Toeplitz matrix, but true covariance matrix RYIs a Toeplitz matrix. By using
Figure BDA0002450356250000046
Is substituted for each diagonal element to improve
Figure BDA0002450356250000047
Toeplitz property of (D).
To correct the covariance matrix estimate, a forward-backward approach is used, and the resulting corrected covariance matrix is expressed as
Figure BDA0002450356250000048
Wherein J represents an N × N-dimensional switching matrix
Figure BDA0002450356250000051
Assuming that the number of scattering centers in the observed signal is d, the corresponding eigenvectors of the d largest eigenvalues form a signal subspace Es＝span{e1,e2,…,edThe rest of the feature vectors are opened into a noise subspace En＝span{ed+1,ed+2,…,eN}. Thus, the MUSIC spectrum of the scattering of the target can be obtained as
Figure BDA0002450356250000052
Performing spectrum peak search on the formula to obtain d maximum spectrum peak positions r1,r2,…,rdI.e. an estimate of the position of the polarized scattering center. According to the position of the spectrum peak, the observation vector corresponding to the position of the extraction formula (4) forms a scattering center observation matrix,
Figure BDA0002450356250000053
estimating the corresponding spectral peak position r by adopting a least square estimation method1,r2,…,rdAmplitude of the emerging polarization scattering center
Figure BDA0002450356250000054
2. Coherent decomposition classification of polarized scattering centers
And performing coherent decomposition on the target polarization scattering center matrix by using Cameron decomposition to realize the scatterer type classification of the target scattering center. The Cameron decomposition of the scattering matrix S is as follows,
Figure BDA0002450356250000055
wherein the content of the first and second substances,
Figure BDA0002450356250000056
norm, theta, representing the vectorrecIndicates the degree to which the scattering matrix satisfies reciprocity, τsymIndicating the extent to which the scattering matrix deviates from the symmetric scatterer,
Figure BDA0002450356250000057
representing a normalized non-reciprocal component of the signal,
Figure BDA0002450356250000058
which represents the normalized maximum symmetric component of the signal,
Figure BDA0002450356250000059
representing the normalized minimum symmetric component.
Maximum symmetric component
Figure BDA00024503562500000510
Is decomposed into
Figure BDA00024503562500000511
Wherein z is a complex number and represents a characteristic parameter of a scatterer type; psi is the diffuser orientation angle
Figure BDA0002450356250000061
Figure BDA0002450356250000062
In the formula (I), the compound is shown in the specification,
Figure BDA0002450356250000063
representing the Kronecker product of the matrix.
For six standard scatterers of dihedral angle, 1/4 wave device, narrow dihedral angle, dipole, cylinder, and trihedral angle, characteristic parameter score of their polarization scattering matrix Cameron decompositionIs denoted by zc-1, ± j, -1/2,0,1/2, 1; then, for any polarization scattering center scattering matrix, the Cameron decomposition characteristic parameter z, the distance measure between the characteristic parameter and the standard scatterer characteristic parameter is expressed as
Figure BDA0002450356250000064
By distance measure k (z, z)c) The size of (d) classifies the scatterer type of the polarized scattering center.
3. Four-path position matching of polarization scattering centers
A four-path analysis method of target and background composite scattering is adopted to describe a composite multiple scattering path of an ultra-low-altitude target and a sea surface, as shown in figure 1. The four propagation paths of the radar observation scattering signal are respectively as follows:
(1) route 1: radar-target-radar
(2) Route 2: radar-sea-target-radar
(3) Route 3: radar-target-sea-radar
(3) Path 4: radar-sea-target-sea-radar
For the multi-path scattering paths of the ultra-low altitude target and the sea surface, the path 1 and the path 4 are odd-order scattering, the path 2 and the path 3 are even-order scattering, the paths 1 and 4 can be distinguished from the paths 2 and 3 by polarization decomposition scatterer classification, and the paths 2 and 3 are composite scattering of the target and the sea surface. Further, path 4 is the third scattering of the target from the sea surface, the scattering mechanism is of the same type as path 1, and it is difficult to separate the scattering paths 1, 4 directly by polarization-resolved scatterer classification. Next, a scattering center model is used to estimate the position of the scattering center and classify the type of the scattering center to distinguish the tertiary scattering path 4 between the target and the sea surface.
The multiple scattering paths of the target and the background are analyzed using a scattering center model, as shown in fig. 2. In FIG. 2, point A represents the position of the scattering center of the target, and the distance r from the radar to the scattering centerA(ii) a B point represents the position of a reflecting point of multiple scattering of the target and the sea surface, and the distance from the B point to the radar is rB. Under far field observation conditions, radarThe incident wave to the A, B point can be approximated as a uniform plane wave, and the distance from the radar to the B point relative to the A point is expressed as
Figure BDA0002450356250000071
According to the multiple scattering path formed by the target and the sea surface in fig. 1, four scattering paths are respectively represented by points a and B:
(1) route 1: Radar-A-radar
(2) Route 2: Radar-B-A-radar
(3) Route 3: Radar-A-B-radar
(4) Path 4: Radar-B-A-B-radar
And analyzing the position of a scattering center of multipath scattering formed by the target and the sea surface according to the propagation distance of the radar incident wave. For a scattering path 1, single scattering of a target is represented, radar incident waves directly return to the radar after being scattered by the target from a point A, and the length of the incident wave propagation path is
r1＝2rA(46)
Therefore, the scattering center position formed by the single scattering of the target of path 1 is located at point a.
For the scattering paths 2, 3, which represent the secondary scattering of the target from the sea surface, the propagation path lengths of the radar incident waves are exactly the same, which can be expressed as
Figure BDA0002450356250000072
Bringing formula (19) into the above formula
r2,3＝2(rA+hcosθ) (48)
For the position of point C in FIG. 2, the distance from the point C to the point A can be calculated as
rC＝rA+hcosθ (49)
Whereby the radar wave propagation length of the target and sea surface secondary scattering paths 2, 3 is
r2,3＝2rC(50)
The position of the scattering center formed by the available scattering paths 2, 3 is thus located at point C.
For the triple scattering path 4 between the target and the sea surface, as shown in fig. 2, the length of the propagation path from the incident radar wave to a and a 'is the same through the image point a' of a point relative to the sea surface, which is shown as
Figure BDA0002450356250000073
Therefore, the position of the scattering center formed by the tertiary scattering path 4 is located at the point a'.
The scattering path 4 has a propagation path length of the radar wave relative to point A, which is obtained by substituting equation (19) into the above equation
r4＝2(rA+2hcosθ) (52)
Through multiple scattering analysis of composite scattering of the target and the sea surface, a four-path scattering center model of composite scattering of the target and the sea surface is established by taking a target scattering center position A as a reference
Figure BDA0002450356250000081
Wherein A is1,A2,A3,A4Respectively, the amplitudes of scattering centers formed by the scattering paths 1, 2, 3 and 4, and k represents the wave number of the incident radar wave.
Theoretically, the propagation lengths of radar waves of the target and the sea surface composite scattering paths 2 and 3 are completely the same, and in practice, the random fluctuation of the sea surface changes, so that the scattering center positions formed by the path 2 and the path 3 are not completely overlapped; it is assumed that the scattering center formed by the paths 2, 3 is shifted in position by Δ r in the radar incidence direction. Since the paths 2 and 3 are both secondary scattering, and the order change of the distance from the two paths to the radar is not influenced on the scattering characteristic, it is assumed that the scattering path 2 is closer to the radar, and thus the four-path scattering center model in equation (27) is corrected to obtain
Figure BDA0002450356250000082
The following embodiments take a spherical ball with a height of 3m above the sea surface as an example, and analyze the composite scattering characteristics between the spherical ball and the sea surface. And (3) performing distance direction imaging on the composite scattering data of the spherical ball and the sea surface, as shown in fig. 3a and 3 b. The implementation steps of adopting the polarized scattering center extraction, classification and position matching method to carry out the target scattering feature identification are as follows:
step 1: polarized scattering center extraction is performed by using MUSIC algorithm, and scattering center estimates of HH polarization and HV polarization are obtained and are respectively shown in FIG. 3a and FIG. 3 b;
step 2: the four polarized scattering centers in fig. 3a and 3b are subjected to feature classification by using Cameron decomposition, and the classification result shows that: scattering centers at positions-6 m and near 0m are odd-order scattering mechanisms, and scattering centers at positions-3 m are even-order scattering mechanisms;
and step 3: the position and type of the scattering center in fig. 3a and 3b were analyzed using a four-path scattering center model. Estimating the height of the target scatterer according to the scattering center positions of the path 1, the path 2 and the path 3 of the target and the background scattering
Figure BDA0002450356250000083
By passing
Figure BDA0002450356250000084
The position of the scattering center of the composite scattering path 4 of the target and the background is estimated, and if the scattering center exists in the neighborhood near the position, the composite scattering center of the target and the background is determined. For the four scattering centers in fig. 3a and 3b, it can be determined that the scattering center near the position of-6 m belongs to the third scattering of the sphere and the sea surface, the scattering center near the position of-3 m belongs to the second scattering of the sphere and the sea surface, and the scattering center near the position of 0m belongs to the single scattering of the sphere itself.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.

Claims (6)

1. A multipath scattering characteristic classification method based on a polarization scattering center is characterized by comprising the following steps:
step one, extracting a polarized scattering center of ultra-low altitude target and sea surface composite scattering: extracting distance direction scattering centers from the target and sea surface composite scattering broadband data by adopting a parametric spectrum estimation method to obtain a polarization scattering matrix comprising scattering center positions and corresponding to each scattering center position;
step two, characteristic decomposition and classification of the polarization scattering center scattering matrix: performing parameter decomposition on the scattering matrix by adopting a coherent target polarization decomposition method, and classifying the types of the scattering centers according to the change of decomposition parameters;
step three, multipath analysis and scattering type identification of the target polarization scattering center position: and solving the relative position relation between the positions of the target scattering centers according to a four-path analysis method of the target and environment composite scattering, thereby realizing the position matching of the composite multi-path scattering centers.
2. The method for classifying the multipath scattering characteristics based on the polarized scattering center as claimed in claim 1, wherein in the first step, a multi-signal classification algorithm of parametric spectrum estimation is used to extract the polarized scattering center, the covariance matrix of the observed data is subjected to characteristic decomposition to obtain a signal subspace and a noise subspace respectively, the signal subspace and the noise subspace are defined by using the approximately orthogonal property of the signal subspace and the noise subspace, the MUSIC spectrum of the signal is defined as the inverse of the square of the projection length of the signal observation vector in the noise subspace, and the signal parameters are estimated by spectrum peak search.
3. The method for classifying multipath scattering features based on polarized scattering center as recited in claim 2, wherein in step one, the observed signal model of the polarized scattering data is represented as
Figure FDA0002450356240000011
Wherein the subscript "pq" denotes observed signal polarization, pq ═ VV, VH, HV, HH; sm,pqIs a position rmM represents a scattering center location sample; f. ofnFor incident wave frequency sampling, N is the number of frequency samples, u*(. to) is observed noise;
for all polarization scattering observation pq ═ VV, VH, HV, HH, the above formula was transformed into a matrix form
Y＝AS+U (2)
Wherein the content of the first and second substances,
Y＝[yVV,yVH,yHV,yHH](3)
A＝[a(r1),a(r2),…,a(rM)](4)
S＝[sVV,sVH,sHV,sHH](5)
U＝[uVV,uVH,uHV,uHH](6)
y is an N × 4 dimensional measurement matrix, where Ypq＝[ypq(1),ypq(2),…,ypq(N)]TA is an N × M-dimensional observation vector matrix, wherein,
Figure FDA0002450356240000021
the scattering amplitude of the target under pq polarization and the measurement noise are respectively
spq＝[s1,pq,s2,pq,…,sd,pq]T，upq＝[upq(1),upq(2),…,upq(N)]T；
For polarization measurement data Y, its covariance matrix is denoted RY＝E{YYHTo RYPerforming eigenvalue decomposition, expressed as
Figure FDA0002450356240000022
Wherein λ iskIs RYIs characterized byValue of ekIs λkAnd has a characteristic vector of1≥λ2…≥λN；
Estimating covariance matrix by adopting space smoothing method
Figure FDA0002450356240000023
By using
Figure FDA0002450356240000024
Is substituted for each diagonal element to improve
Figure FDA0002450356240000025
Toeplitz property of (a);
the corrected covariance matrix is expressed as forward-backward
Figure FDA0002450356240000026
Wherein J represents an N × N-dimensional switching matrix
Figure FDA0002450356240000027
The number of scattering centers in the observation signal is d, and the corresponding eigenvectors of the d largest eigenvalues form a signal subspace Es＝span{e1,e2,…,edThe rest of the feature vectors are opened into a noise subspace En＝span{ed+1,ed+2,…,eN}; thus, obtaining a MUSIC spectrum of the scattering of the target as
Figure FDA0002450356240000031
Performing spectrum peak search on the formula to obtain d maximum spectrum peak positions r1,r2,…,rdI.e. polarization scatteringA position estimate of the center; according to the position of the spectrum peak, the observation vector corresponding to the position of the extraction formula (4) forms a scattering center observation matrix,
Figure FDA0002450356240000032
estimating the corresponding spectral peak position r by adopting a least square estimation method1,r2,…,rdAmplitude of the emerging polarization scattering center
Figure FDA0002450356240000033
4. The method for classifying the multipath scattering characteristics based on the polarization scattering center as recited in claim 3, wherein in the second step, a Cameron decomposition is adopted to carry out coherent decomposition on the target polarization scattering center matrix, so as to realize the scatterer type classification of the target scattering center;
the Cameron decomposition of the scattering matrix S is as follows,
Figure FDA0002450356240000034
wherein the content of the first and second substances,
Figure FDA0002450356240000035
norm, theta, representing the vectorrecIndicates the degree to which the scattering matrix satisfies reciprocity, τsymIndicating the extent to which the scattering matrix deviates from the symmetric scatterer,
Figure FDA0002450356240000036
representing a normalized non-reciprocal component of the signal,
Figure FDA0002450356240000037
which represents the normalized maximum symmetric component of the signal,
Figure FDA0002450356240000038
represents a normalized minimum symmetric component;
maximum symmetric component
Figure FDA0002450356240000039
Is decomposed into
Figure FDA00024503562400000310
Wherein z is a complex number and represents a characteristic parameter of a scatterer type; psi is the diffuser orientation angle
Figure FDA00024503562400000311
Figure FDA00024503562400000312
In the formula (I), the compound is shown in the specification,
Figure FDA0002450356240000041
representing the Kronecker product of the matrix;
for six standard scatterers of dihedral angle, 1/4 wave device, narrow dihedral angle, dipole, cylinder and trihedral angle, characteristic parameters of their polarization scattering matrix Cameron decomposition are respectively expressed as zc-1, ± j, -1/2,0,1/2, 1; then, for any polarization scattering center scattering matrix, the Cameron decomposition characteristic parameter z, the distance measure between the characteristic parameter and the standard scatterer characteristic parameter is expressed as
Figure FDA0002450356240000042
By distance measure k (z, z)c) The size of (d) classifies the scatterer type of the polarized scattering center.
5. The method for classifying the characteristics of the multipath scattering based on the polarized scattering center as claimed in claim 1, wherein in the third step, point A is set to represent the targetPosition of scattering center, distance of radar to the scattering center being rA(ii) a B point represents the position of a reflecting point of multiple scattering of the target and the sea surface, and the distance from the B point to the radar is rB(ii) a Under far-field observation conditions, the position of an incident radar wave to A, B point is approximate to a uniform plane wave, and the distance from the radar to the B point is expressed by the distance from the A point to the B point
Figure FDA0002450356240000043
Using points a and B, four scattering paths are represented:
first scattering path: Radar-A-radar
A second scattering path: Radar-B-A-radar
Third scattering path: Radar-A-B-radar
Fourth scattering path: Radar-B-A-B-radar
Through multiple scattering analysis of composite scattering of the target and the sea surface, a four-path scattering center model of composite scattering of the target and the sea surface is established and corrected into
Figure FDA0002450356240000044
Wherein A is1,A2,A3,A4Respectively representing the amplitudes of scattering centers formed by the first, second, third and fourth scattering paths, and k represents the wave number of the incident wave of the radar; in the radar incidence direction, the position deviation of a scattering center formed by the second scattering path and the third scattering path is delta r; h distance to sea surface at point a.
6. The method for classifying the characteristics of the multipath scattering based on the polarization scattering center as claimed in claim 5, wherein in the third step, the first scattering path represents the single scattering of the target, the radar incident wave directly returns to the radar after scattering from the target to the point A, and the propagation path length of the incident wave is
r1＝2rA(21)
The position of a scattering center formed by single scattering of the target of the first scattering path is positioned at the point A;
the second and third scattering paths represent the secondary scattering of the target and the sea surface, and the propagation paths of the radar incident waves have the same length and are represented as
r2,3＝2(rA+hcosθ) (22)
Setting the position from the point A to the sea surface as a point C, and calculating to obtain the distance from the lightning to the point C
rC＝rA+hcosθ (23)
Whereby the radar wave propagation lengths of the second and third scattering paths are
r2,3＝2rC(24)
The scattering center formed by the second and third scattering paths is positioned at the point C;
the fourth scattering path represents a cubic scattering path of the target and the sea surface, and the path lengths of the incident radar waves from A to A ' and A ' are the same through the image point A ' of A relative to the sea surface and are represented as
Figure FDA0002450356240000051
Thus, the position of the scattering center formed by the fourth scattering path is located at point a';
the fourth dispersion path has a propagation path length of the radar wave relative to point A
r4＝2(rA+2hcosθ) (26)。
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