CN113740826A - Method and device for identifying rotating domain of target scattering structure - Google Patents

Method and device for identifying rotating domain of target scattering structure Download PDF

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CN113740826A
CN113740826A CN202111072443.8A CN202111072443A CN113740826A CN 113740826 A CN113740826 A CN 113740826A CN 202111072443 A CN202111072443 A CN 202111072443A CN 113740826 A CN113740826 A CN 113740826A
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CN113740826B (en
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陈思伟
李郝亮
李铭典
王雪松
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National University of Defense Technology
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Abstract

A target polarization scattering matrix rotates around the direction of a polarized radar sight line, and a polarization-related directional diagram of a target is calculated; similarly, a rotating polarization scattering matrix and a corresponding generalized polarization correlation directional diagram of each typical structure, which are compatible with polarization measurement errors, are obtained; respectively extracting rotation invariant features from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure giving consideration to polarization measurement errors, and constructing a target feature vector and a feature coding vector of each typical structure; and carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector. The method is simple and convenient to implement, and has important reference value for the application fields of earth observation, sea surface monitoring, disaster reduction and prevention and the like.

Description

Method and device for identifying rotating domain of target scattering structure
Technical Field
The invention relates to the technical field of radar polarization information processing, in particular to a method and a device for identifying a rotating domain of a target scattering structure.
Background
The polarization radar can obtain polarization information of a target by receiving and transmitting a group of electromagnetic waves with orthogonal polarization states, plays an important role in the fields of target scattering mechanism interpretation, characteristic parameter inversion, target detection and identification and the like, becomes a mainstream sensor in a plurality of important fields such as earth observation, air defense reverse guidance, meteorological detection, sea surface monitoring and the like, and is widely applied.
The target polarization information obtained by polarized radar can be characterized by a polarized scattering matrix. The polarization correlation characteristics between different polarization channels are sensitive to the relative geometrical relationship between the target attitude and the radar sight. For the same target, its polarization scattering properties may differ significantly when its pose with respect to the line of sight of the polarized radar is different. The phenomenon causes inconvenience to radar polarization information processing and application, and is one of technical bottlenecks faced by fine interpretation and quantitative application of a polarization scattering mechanism of a current polarization radar target. The polarization data obtained under the specific imaging geometric condition is rotated around the radar sight line direction, and is expanded to a polarization rotation domain for analysis, so that the polarization information hidden by a target is expected to be mined, the target structure identification is realized, and the method becomes a key for improving the target scattering mechanism interpretation and application performance. Therefore, the development of a method and a device for identifying the rotating domain of the scattering structure of the target is of great value.
Disclosure of Invention
In order to finely interpret the scattering characteristics of a target in a rotating domain around the line of sight of a radar, the invention provides a rotating domain identification method and a rotating domain identification device of a target scattering structure. The polarization rotation domain feature is subjected to visualization processing and parametric depiction in the polarization rotation domain, so that the polarization rotation domain feature can be extracted, the radar targets can be effectively distinguished, the polarization radar system is applicable to polarization radar systems with multiple purposes (such as air monitoring, earth observation, meteorological detection, sea surface monitoring and the like), and the polarization radar system has application value in the fields of air target classification identification, ground object class identification, damage assessment and the like.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method of rotational domain identification of a scattering structure of a target, comprising:
rotating a target polarization scattering matrix obtained by the polarization radar around the direction of the polarization radar sight line, and calculating the target rotation polarization scattering matrix and a corresponding polarization-related directional diagram;
calculating a polarization scattering matrix considering polarization measurement errors of each typical structure based on the ideal polarization scattering matrix of each typical structure, performing rotation processing on the polarization scattering matrix around the sight line direction of the polarization radar, and calculating a rotation polarization scattering matrix considering polarization measurement errors of each typical structure and a corresponding generalized polarization related directional diagram of the rotation polarization scattering matrix;
respectively extracting rotation invariant features from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure giving consideration to polarization measurement errors, and constructing a target feature vector and a feature coding vector of each typical structure;
and carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector.
In another aspect, the present invention provides an apparatus for identifying a rotating domain of a scattering structure of a target, including:
the first calculation module is used for performing rotation processing on a target polarization scattering matrix obtained by the polarization radar around the polarization radar sight line direction, and calculating the target rotation polarization scattering matrix and a corresponding polarization-related directional diagram;
the second calculation module is used for calculating the polarization scattering matrix giving consideration to the polarization measurement error of each typical structure based on the ideal polarization scattering matrix of each typical structure, performing rotation processing on the polarization scattering matrix around the polarization radar sight line direction, and calculating the rotation polarization scattering matrix giving consideration to the polarization measurement error of each typical structure and the corresponding generalized polarization related directional diagram;
the characteristic vector construction module is used for respectively extracting rotation invariant characteristics from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure considering polarization measurement errors, and constructing a target characteristic vector and a characteristic coding vector of each typical structure;
and the identification module is used for carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector.
The invention has the following beneficial technical effects:
the method can visually and parametrically depict the scattering characteristic of the target polarization correlation value in the field rotating around the radar sight line, and is applied to subsequent target structure identification and the like by constructing the polarization rotation invariant feature code. The method is simple and convenient to implement, and can be directly applied to the target polarization scattering matrix data obtained by the polarization radar systems with different purposes. The method has important reference value for the application fields of earth observation, sea surface monitoring, disaster reduction and prevention and the like.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a polarization dependent pattern of an exemplary scattering structure in accordance with an embodiment of the present invention, where (a1) through (a7) represent the dihedral angle, dipole, cylinder, narrow dihedral angle, quarter-wave device, and helical scatterer, respectively
Figure BDA0003260890210000031
Wherein (b1) to (b7) represent respectively a trihedral angle, a dihedral angle, a dipole, a cylinder, a narrow dihedral angle, a quarter-wave device and a helical diffuser
Figure BDA0003260890210000032
Fig. 3 is a model and Pauli plot of unmanned aerial vehicle electromagnetic simulation data, where (a) represents the model of unmanned aerial vehicle electromagnetic simulation data, (b) represents the Pauli plot corresponding to the unmanned aerial vehicle ISAR image when looking forward, and (c) represents the Pauli plot corresponding to the unmanned aerial vehicle ISAR image when looking obliquely;
fig. 4 is a comparison of recognition results of the electromagnetic simulation data of the unmanned aerial vehicle, where (a1) represents a recognition result of the electromagnetic simulation data of the unmanned aerial vehicle obtained by using the Cameron method on the ISAR image of the unmanned aerial vehicle in oblique view; (a2) representing the identification result of the unmanned aerial vehicle electromagnetic simulation data obtained by the unmanned aerial vehicle ISAR image in oblique vision by using the method; (b1) representing the identification result of the unmanned aerial vehicle electromagnetic simulation data obtained by the unmanned aerial vehicle ISAR image by using a Cameron method in the normal sight; (b2) representing the identification result of the unmanned aerial vehicle electromagnetic simulation data obtained by the method of the invention on the ISAR image of the unmanned aerial vehicle in the normal view.
FIG. 5 comparison of recognition results of L-band ALOS-2 fully polarized SAR data, where (a) represents the original optical image; (b) representing the recognition result obtained by the Cameron method; (c) representing the recognition results obtained with the method of the invention.
The objects, features and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to specific embodiments and the accompanying drawings. It should be noted that, in the drawings or the description, the undescribed contents and parts of english are abbreviated as those well known to those skilled in the art. Some specific parameters given in the present embodiment are only exemplary, and the values may be changed to appropriate values accordingly in different real-time manners.
The basic idea of the invention is as follows: the correlation characteristics between the two polarization channels in the polarization data are sensitive to the relative geometric relationship of the target attitude and the radar line of sight. Under different attitude conditions of the same target, the value of the polarization-related characteristic of the target may be changed significantly. The polarization scattering matrix acquired under the specific imaging geometric condition is rotated around the radar sight line, so that the relative geometric relation between the target attitude and the radar sight line can be changed. By traversing each rotation angle in the rotation domain around the radar line of sight, a sequence of polarization-related values in the rotation domain can be obtained. The polarization correlation value sequence in the rotation domain is visualized and parametrically depicted, so that the change characteristics of the target polarization correlation value in the rotation domain can be completely described, and the scattering mechanism of the target in the polarization rotation domain can be finely interpreted. Therefore, the method can realize the characteristic extraction of the polarization rotation domain and the target structure identification, and is further used in the fields of physical parameter inversion, target identification classification and the like.
Fig. 1 is a flowchart illustrating an embodiment of the present invention, and a method for identifying a rotating domain of a target scattering structure includes the following steps:
firstly, a target polarization scattering matrix obtained by a polarization radar rotates around the direction of a polarized radar sight line, and a polarization related directional diagram of a target is calculated;
secondly, calculating a polarization scattering matrix considering polarization measurement errors of each typical structure based on the ideal polarization scattering matrix of each typical structure, performing rotation processing on the polarization scattering matrix around the polarization radar sight line direction, and calculating a rotation polarization scattering matrix considering polarization measurement errors of each typical structure and a corresponding generalized polarization related directional diagram of the rotation polarization scattering matrix;
thirdly, respectively extracting rotation invariant features from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure giving consideration to polarization measurement errors, and constructing a target feature vector and a feature coding vector of each typical structure;
and fourthly, carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector.
In the first step, a target polarization scattering matrix obtained by the polarization radar rotates around the direction of the polarized radar sight line, and the obtained target rotation polarization scattering matrix is as follows:
Figure BDA0003260890210000051
where θ is the rotation angle, θ ∈ [ - π, π](ii) a Rotation matrix
Figure BDA0003260890210000052
Superscript T is the transpose process, S is the target polarization scattering matrix,
Figure BDA0003260890210000053
h and V represent any two different polarization channels, SHHComplex backscattering coefficients obtained under the conditions of H-polarization transmission and H-polarization receiving; sVHComplex backscattering coefficients obtained under the conditions of V-polarization transmission and H-polarization receiving; sHVComplex backscattering coefficients obtained under the conditions of H polarization transmission and V polarization receiving; sVVIs the complex backscattering coefficient obtained under both V-polarized transmit and V-polarized receive conditions.
The expression of each element of a target polarization scattering matrix S (theta) in a rotation domain, which is obtained by a polarization radar and is subjected to rotation processing around the polarization radar sight direction, is as follows:
SHH(θ)＝SHHcos2θ+SHVcosθsinθ+SVHcosθsinθ+SVVsin2θ
SHV(θ)＝-SHHcosθsinθ+SHVcos2θ-SVHsin2θ+SVVcosθsinθ
SVH(θ)＝-SHHcosθsinθ-SHVsin2θ+SVHcos2θ+SVVcosθsinθ
SVV(θ)＝SHHsin2θ-SHVcosθsinθ-SVHcosθsinθ+SVVcos2θ
discretizing the rotation angle theta in the rotation domain to obtain a discretized rotation angle sequence thetai，
Figure BDA0003260890210000054
The value of N is determined according to actual conditions.
Calculating a sequence of rotation angles thetaiCorresponding polarization correlation characteristic sequence to obtain any two polarization channels s in polarization rotation domain1And s2Polarization dependent directivity pattern of
Figure BDA0003260890210000061
Under the condition of satisfying SHV＝SVHUnder the condition of reciprocity, 3 polarization-dependent directional diagrams can be deduced, namely
Figure BDA0003260890210000062
Figure BDA0003260890210000063
And
Figure BDA0003260890210000064
due to the existence of the following equivalence relation
Figure BDA0003260890210000065
There are thus two independent polarization dependent patterns, namely:
Figure BDA0003260890210000066
Figure BDA0003260890210000067
wherein, is the process of set average, and is the process of taking absolute value, and the superscript is the conjugate process.
Will rotate the angular sequence thetaiAnd expressing the corresponding polarization correlation characteristic sequence in a polar coordinate system to obtain a visual diagram of the polarization correlation characteristic in the polarization rotation domain. The visualization of the polarization-dependent features in the polarization rotation domain characterizes the scattering properties of the polarized radar target in the rotation domain around the radar line of sight.
In order to utilize a polarization correlation directional diagram conveniently, an original polarization correlation characteristic value, a polarization correlation characteristic maximum value, a polarization correlation characteristic minimum value, a polarization correlation degree, a polarization correlation fluctuation degree, a polarization correlation contrast degree, a polarization correlation inverse entropy, a maximum rotation angle, a minimum rotation angle and a polarization correlation width are extracted to be parameterized and depicted, and the method specifically comprises the following steps:
(1) the original polarization-dependent eigenvalues are:
Figure BDA0003260890210000068
(2) the maximum value of the polarization dependent characteristic is:
Figure BDA0003260890210000069
(3) the polarization dependent characteristic minimum is:
Figure BDA00032608902100000610
(4) the polarization dependence is:
Figure BDA00032608902100000611
(5) the polarization dependent waviness is:
Figure BDA0003260890210000071
(6) the polarization dependent contrast ratio is:
Figure BDA0003260890210000072
(7) the polarization dependent inverse entropy is:
Figure BDA0003260890210000073
(8) the maximum rotation angle is:
Figure BDA0003260890210000074
(9) the minimum rotation angle is:
Figure BDA0003260890210000075
(10) the polarization dependent width is:
Figure BDA0003260890210000076
wherein max {. is the maximum value of the sequence; min {. is the minimum value of the sequence; mean {. is the mean of the sequence; std {. cndot } is the standard deviation of the sequence.
In the second step, the kind and number of typical scattering structures can be set by those skilled in the art according to the requirements. Referring to fig. 2, in a preferred embodiment of the present invention, 7 typical scattering structures are selected, including a tri-plane angle, a dihedral angle, a dipole, a cylinder, a narrow dihedral angle, a quarter-wave device, and a helical scatterer. The ideal polarization scattering matrix and the corresponding polarization dependent pattern for each exemplary structure are shown in the table below.
Figure BDA0003260890210000077
Figure BDA0003260890210000081
Theoretically, the three-plane structure has the characteristic of rotation invariance around the radar sight line, and the co-polarization related directional diagram is circular. In contrast, dihedral has a pronounced directional effect, varying periodically. The difference is caused by the two different scattering mechanisms. Different typical structures have different polarization rotation domain characteristics, which provides a theoretical basis for distinguishing them.
Since the polarization radar is a multi-channel system, it is usually affected by non-ideal factors such as cross coupling and channel imbalance during actual measurement, thereby affecting target structure interpretation. In addition, the system still has measurement errors after polarization calibration. Considering polarization isolation and polarization channel imbalance factors, the polarization scattering matrix considering polarization measurement errors of the kth typical structure is:
Figure BDA0003260890210000082
where δ is the polarization isolation, a is the polarization channel amplitude and phase imbalance, and N is the system noise, the noise is considered negligible for simplicity of discussion.
Figure BDA0003260890210000083
For the ideal polarization scattering matrix of the kth exemplary structure, H and V represent any two different polarization channels,
Figure BDA0003260890210000084
complex backscattering coefficients obtained under H-polarization transmitting and H-polarization receiving conditions for the kth typical structure;
Figure BDA0003260890210000085
complex backscattering coefficients obtained under the conditions of V-polarized transmission and H-polarized reception for the kth typical structure;
Figure BDA0003260890210000086
complex backscattering coefficients obtained under H-polarization transmitting and V-polarization receiving conditions for the kth typical structure;
Figure BDA0003260890210000087
complex backscattering coefficients obtained under V-polarized transmit and V-polarized receive conditions for the kth exemplary structure.
The rotating polarization scattering matrix with polarization measurement error taken into account for the kth typical structure is:
Figure BDA0003260890210000088
where θ is the rotation angle, θ ∈ [ - π, π](ii) a Rotation matrix
Figure BDA0003260890210000089
Superscript T is transposition processing;
rotating polarization scattering matrix MkThe expression of each element of (θ) in the rotational domain is:
Figure BDA00032608902100000810
Figure BDA0003260890210000091
Figure BDA0003260890210000092
Figure BDA0003260890210000093
discretizing the rotation angle theta in the rotation domain to obtain a discretized rotation angle sequence thetaiCalculating a sequence of rotation angles thetaiCorresponding polarization correlation characteristic sequence to obtain rotation polarization scattering matrix M in polarization rotation domaink(θ) a corresponding generalized polarization dependent pattern characterized by:
Figure BDA0003260890210000094
Figure BDA0003260890210000095
polarization measurement errors can affect the polarization dependent patterns of typical structures. For a certain polarized radar system, the polarization isolation and polarization channel imbalance parameters are known. Polarization-rotation domain polarization-related features can be extracted from the generalized polarization-related directional diagram, and include original polarization-related feature values, polarization-related feature maximum values, polarization-related feature minimum values, polarization-correlation degrees, polarization-related fluctuation degrees, polarization-related contrast degrees, polarization-related inverse entropy, maximized rotation angles, minimized rotation angles and polarization-related widths.
In the third step, rotation invariant features are extracted from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and the generalized polarization correlation directional diagram of each typical structure giving consideration to polarization measurement errors and are used for constructing a target feature vector and a feature coding vector of each typical structure. Among polarization rotation domain polarization dependent features, there are 7 rotation invariant features including a polarization dependent feature maximum, a polarization dependent feature minimum, a polarization correlation, a polarization dependent waviness, a polarization dependent contrast, a polarization dependent inverse entropy, and a polarization dependent width. The person skilled in the art can select a plurality of rotation-invariant features from them for constructing the target feature vector and the feature encoding vector for each typical structure based on the prior knowledge.
In an embodiment of the present invention, the above 7 rotation invariant features are utilized, and feature optimization is performed according to the "class spacing maximization" criterion. Features are selected that maximize the class spacing for each of the two classes, and the selected features are accumulated. Polarization isolation within the range of-40 dB to-5 dB (0.1 dB at interval), amplitude imbalance within the range of 0dB to 5dB (0.1 dB at interval) and phase imbalance within the range of 0 to 30 degrees (0.1 degree at interval) are added to the ideal polarization scattering matrix of each typical structure respectively, and a sample data set is constructed. These seven exemplary structures may form 21 pairs of structures. Feature selection results the table below shows, with numbers in parentheses indicating the number of times a feature was selected.
Figure BDA0003260890210000101
Finally, the polarization correlation degree is preferably selected
Figure BDA0003260890210000102
Polarization dependent undulation degree
Figure BDA0003260890210000103
Polarization dependent width
Figure BDA0003260890210000104
Polarization dependent minimum
Figure BDA0003260890210000105
Polarization dependent inverse entropy
Figure BDA0003260890210000106
These 5 polarization rotation invariant features are used to construct the construction target feature vector and the feature encoding vector for each canonical structure. That is, in the third step of the embodiment of the present invention, the polarization correlation degrees are respectively extracted from the polarization correlation directional diagram corresponding to the target polarization scattering matrix and the generalized polarization correlation directional diagram considering the polarization measurement error of each typical structure
Figure BDA0003260890210000107
Polarization dependent undulation degree
Figure BDA0003260890210000108
Polarization dependent width
Figure BDA0003260890210000109
Polarization dependent minimum
Figure BDA00032608902100001010
Polarization dependent inverse entropy
Figure BDA00032608902100001011
The 5 polarization rotation invariant features construct a target feature vector w and a feature coding vector v of each typical structurek：
Figure BDA00032608902100001012
In which the degree of polarization correlation is calculated
Figure BDA00032608902100001013
Polarization dependent undulation degree
Figure BDA00032608902100001014
Polarization dependent width
Figure BDA00032608902100001015
Polarization dependent minimum
Figure BDA00032608902100001016
Polarization dependent inverse entropy
Figure BDA00032608902100001017
The formulas (A) and (B) are shown in the above (1) to (10), and are not described in detail herein.
The feature vector corresponding to each canonical structure is defined as a feature code vector. The feature code vectors under different measurement errors can be obtained. For example, in one embodiment, the obtained signature code vector with polarization isolation of-40 dB is:
Figure BDA00032608902100001018
wherein v iskFor the feature-encoded vectors of class k typical structures, k ═ 1,2,3,4,5,6,7 represent the trihedral angle, dihedral angle, dipole, cylinder, narrow dihedral angle, quarter-wave device, and helical scatterer, respectively.
The 7 types of typical structures can be distinguished by feature coding vectors. And fourthly, performing similarity measurement on the target feature vector and the feature coding vectors of the typical structures, selecting a theoretical value with the closest distance, wherein the corresponding structure type is the structure type of the target:
Figure BDA0003260890210000111
where w is the measured target feature vector and d indicates the typical structure corresponding to the feature code vector that minimizes the distance.
Fig. 3 is a model and Pauli diagram of the electromagnetic simulation data of the unmanned aerial vehicle. Wherein (a) is that the unmanned aerial vehicle is an all-metal model. The simulation center frequency is 10GHz, the bandwidth is 4GHz, and the pitch angle is 0 degree. Fig. 3 (b) and (c) are Pauli diagrams corresponding to the ISAR images of the drone at azimuth angles of 0 ° and 45 °, respectively, i.e., at front view and oblique view.
Fig. 4 is a comparison diagram of the recognition result of the electromagnetic simulation data of the unmanned aerial vehicle, in which (a1) represents the recognition result of the electromagnetic simulation data of the unmanned aerial vehicle obtained by the Cameron method from the ISAR image of the unmanned aerial vehicle in oblique view; (a2) representing the identification result of the unmanned aerial vehicle electromagnetic simulation data obtained by the unmanned aerial vehicle ISAR image in oblique vision by using the method; (b1) representing the identification result of the unmanned aerial vehicle electromagnetic simulation data obtained by the unmanned aerial vehicle ISAR image by using a Cameron method in the normal sight; (b2) representing the identification result of the unmanned aerial vehicle electromagnetic simulation data obtained by the method of the invention on the ISAR image of the unmanned aerial vehicle in the normal view. Scattering centers in radar images appear as pixels with local peak intensities, thus each energy intensity point in the image is taken as an independent scattering center. In elevation, the 4 scattering centers at the wing and fuselage interface correspond to narrow dihedral structures, while the Cameron method identifies one of the scattering centers as a quarter-wave device. This is not in line with the overall symmetry of the drone. In oblique view, the red marked area is the unmanned aerial vehicle antenna part and should be a dipole structure. The scattering type judgment result of the invention basically accords with the actual structure, which verifies that the invention has higher precision on the identification of the target structure.
FIG. 5 is a comparison graph of the recognition results of L-band ALOS-2 fully polarized SAR data. The data set was obtained in san francisco on day 21, 8.8.2018, with a nominal resolution of 5.1m × 4.3m (range direction × azimuth direction). An area containing a ship target is selected, the data size is 50 x 120 pixels, an optical image is shown as (a) in fig. 5, and the identification results obtained by the Cameron decomposition method and the method are shown as (b) in fig. 5 and (c) in fig. 5 respectively. The stern and sides of the vessel consist primarily of even order scattering mechanisms, corresponding to dihedral and narrow dihedral structures. The deck has a cylindrical structure, and some local structures are quarter-wave devices. The red oval marked areas should be of a flat plate configuration and a cylindrical configuration, respectively. Compared with Cameron decomposition, the method can more accurately identify the structure type of the target. The comparison experiment further verifies that the rotating domain method can be effectively applied to radar target identification.
An embodiment of the present invention provides a device for identifying a rotation domain of a target scattering structure, including:
the first calculation module is used for performing rotation processing on a target polarization scattering matrix obtained by the polarization radar around the polarization radar sight line direction, and calculating the target rotation polarization scattering matrix and a corresponding polarization-related directional diagram;
the second calculation module is used for calculating the polarization scattering matrix giving consideration to the polarization measurement error of each typical structure based on the ideal polarization scattering matrix of each typical structure, performing rotation processing on the polarization scattering matrix around the polarization radar sight line direction, and calculating the rotation polarization scattering matrix giving consideration to the polarization measurement error of each typical structure and the corresponding generalized polarization related directional diagram;
the characteristic vector construction module is used for respectively extracting rotation invariant characteristics from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure considering polarization measurement errors, and constructing a target characteristic vector and a characteristic coding vector of each typical structure;
and the identification module is used for carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector.
The implementation method of each above component module is the same as the implementation method of the corresponding step in the above-mentioned rotating domain identification method of the target scattering structure, and is not described herein again.
The foregoing description of the preferred embodiments of the present invention has been included to describe the features of the invention in detail, and is not intended to limit the inventive concepts to the particular forms of the embodiments described, as other modifications and variations within the spirit of the inventive concepts will be protected by this patent. The subject matter of the present disclosure is defined by the claims, not by the detailed description of the embodiments.

Claims (10)

1. A method for identifying a rotating domain of a scattering structure of a target, comprising:
rotating a target polarization scattering matrix obtained by the polarization radar around the direction of the polarization radar sight line, and calculating the target rotation polarization scattering matrix and a corresponding polarization-related directional diagram;
calculating a polarization scattering matrix considering polarization measurement errors of each typical structure based on the ideal polarization scattering matrix of each typical structure, performing rotation processing on the polarization scattering matrix around the sight line direction of the polarization radar, and calculating a rotation polarization scattering matrix considering polarization measurement errors of each typical structure and a corresponding generalized polarization related directional diagram of the rotation polarization scattering matrix;
respectively extracting rotation invariant features from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure giving consideration to polarization measurement errors, and constructing a target feature vector and a feature coding vector of each typical structure;
and carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector.
2. The method for identifying a rotating domain of a target scattering structure as claimed in claim 1, wherein the target rotating polarization scattering matrix is:
Figure FDA0003260890200000011
where θ is the rotation angle, θ ∈ [ - π, π](ii) a Rotation matrix
Figure FDA0003260890200000012
Superscript T is the transpose process, S is the target polarization scattering matrix,
Figure FDA0003260890200000013
h and V represent any two ofPolarized channel of, SHHComplex backscattering coefficients obtained under the conditions of H-polarization transmission and H-polarization receiving; sVHComplex backscattering coefficients obtained under the conditions of V-polarization transmission and H-polarization receiving; sHVComplex backscattering coefficients obtained under the conditions of H polarization transmission and V polarization receiving; sVVComplex backscattering coefficients obtained under the conditions of V-polarized transmission and V-polarized receiving;
the expression of each element of the target rotating polarization scattering matrix S (theta) in the rotating domain is:
SHH(θ)＝SHHcos2θ+SHVcosθsinθ+SVHcosθsinθ+SVVsin2θ
SHV(θ)＝-SHHcosθsinθ+SHVcos2θ-SVHsin2θ+SVVcosθsinθ
SVH(θ)＝-SHHcosθsinθ-SHVsin2θ+SVHcos2θ+SVVcosθsinθ
SVV(θ)＝SHHsin2θ-SHVcosθsinθ-SVHcosθsinθ+SVVcos2θ。
3. the method of claim 2, wherein calculating a polarization dependent pattern comprises:
discretizing the rotation angle theta in the rotation domain to obtain a discretized rotation angle sequence thetai，
Figure FDA0003260890200000021
Calculating a sequence of rotation angles thetaiAnd obtaining a polarization correlation directional diagram of the polarization correlation characteristic in the polarization rotation domain by the corresponding polarization correlation characteristic sequence.
4. The method of claim 3, wherein the polarization dependent pattern is selected from the group consisting of:
Figure FDA0003260890200000022
Figure FDA0003260890200000023
wherein the content of the first and second substances,<·>for set-averaging, |, for absolute value processing, superscript*Is a conjugation process.
5. The method of rotational domain identification of a scattering structure of an object according to claim 2, wherein the typical structures comprise a tri-plane, a dihedral, a dipole, a cylinder, a narrow dihedral, a quarter-wave device and a helical scatterer.
6. The method for identifying a rotating domain of a scattering structure as claimed in claim 5, wherein the polarization scattering matrix of the kth canonical structure considering polarization measurement errors is:
Figure FDA0003260890200000024
wherein, δ is polarization isolation, a is polarization channel amplitude and phase imbalance, and N is system noise;
Figure FDA0003260890200000031
for the ideal polarization scattering matrix of the kth exemplary structure, H and V represent any two different polarization channels,
Figure FDA0003260890200000032
complex backscattering coefficients obtained under H-polarization transmitting and H-polarization receiving conditions for the kth typical structure;
Figure FDA0003260890200000033
complex backscattering coefficients obtained under the conditions of V-polarized transmission and H-polarized reception for the kth typical structure;
Figure FDA0003260890200000034
complex backscattering coefficients obtained under H-polarization transmitting and V-polarization receiving conditions for the kth typical structure;
Figure FDA0003260890200000035
complex backscattering coefficients obtained under V-polarized transmit and V-polarized receive conditions for the kth exemplary structure.
7. The method for identifying the rotated domain of a scattering structure of an object according to claim 6, wherein the rotated polarization scattering matrix considering polarization measurement errors of the kth canonical structure is:
Figure FDA0003260890200000036
where θ is the rotation angle, θ ∈ [ - π, π](ii) a Rotation matrix
Figure FDA0003260890200000037
Superscript T is transposition processing;
rotating polarization scattering matrix MkThe expression of each element of (θ) in the rotational domain is:
Figure FDA0003260890200000038
Figure FDA0003260890200000039
Figure FDA00032608902000000310
Figure FDA00032608902000000311
discretizing the rotation angle theta in the rotation domain to obtain a discretized rotation angle sequence thetaiCalculating a sequence of rotation angles thetaiCorresponding polarization correlation characteristic sequence to obtain rotation polarization scattering matrix M in polarization rotation domaink(θ) a corresponding generalized polarization dependent pattern characterized by:
Figure FDA00032608902000000312
Figure FDA00032608902000000313
8. the method for identifying the rotating domain of the target scattering structure as claimed in claim 6, wherein 5 polarization rotation invariant features including polarization correlation degree, polarization correlation fluctuation, polarization correlation width, polarization correlation minimum value and polarization correlation inverse entropy are respectively extracted from the polarization correlation directional diagram corresponding to the target polarization scattering matrix and the generalized polarization correlation directional diagram considering the polarization measurement error of each typical structure to construct a target feature vector w and a feature coding vector v of each typical structurek，vkThe vector is encoded for the features of the kth canonical structure.
9. The method of claim 8, wherein the type of the representative structure corresponding to the target feature vector is determined according to the following formula:
Figure FDA0003260890200000041
where d represents a typical structure type corresponding to the characteristic coding vector that minimizes the distance.
10. An apparatus for rotational domain identification of a scattering structure of an object, comprising:
the first calculation module is used for performing rotation processing on a target polarization scattering matrix obtained by the polarization radar around the polarization radar sight line direction, and calculating the target rotation polarization scattering matrix and a corresponding polarization-related directional diagram;
the second calculation module is used for calculating the polarization scattering matrix giving consideration to the polarization measurement error of each typical structure based on the ideal polarization scattering matrix of each typical structure, performing rotation processing on the polarization scattering matrix around the polarization radar sight line direction, and calculating the rotation polarization scattering matrix giving consideration to the polarization measurement error of each typical structure and the corresponding generalized polarization related directional diagram;
the characteristic vector construction module is used for respectively extracting rotation invariant characteristics from a polarization correlation directional diagram corresponding to the target polarization scattering matrix and a generalized polarization correlation directional diagram of each typical structure considering polarization measurement errors, and constructing a target characteristic vector and a characteristic coding vector of each typical structure;
and the identification module is used for carrying out similarity measurement on the target characteristic vector and the characteristic coding vectors of the typical structures to obtain the typical structure type corresponding to the target characteristic vector.
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