CN117390355B - Polarization target decomposition method based on LPC compensation - Google Patents
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Abstract
The invention provides a polarization target decomposition method based on LPC compensation, which comprises the following steps: inputting a first coherence matrix of the target image; compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix; rotating the second interference matrix based on the configuration degree to obtain a third interference matrix; performing eigenvalue decomposition on the third correlation matrix, and characterizing a target distribution ratio based on polarization entropy so as to quantify and distinguish contributions of cross polarization components; the magnitudes of the surface scatter and the even scatter in the contribution of the cross-polarized components are compared and the even scatter parameter, the surface scatter power, and the dihedral angle scatter power are solved. The contribution of cross polarization components is distinguished through the target distribution ratio represented by polarization entropy, and the coupling of same polarization and cross polarization in a polarization scattering matrix during MTD decomposition is relieved by utilizing phase angle compensation and a distribution surface/dihedral angle scattering model, so that the problem of negative power pixels caused by |C|2-SD <0 is solved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a polarization target decomposition method based on LPC compensation.
Background
Polarized synthetic aperture radar (POLSAR) is an advanced earth-looking synthetic aperture radar System (SAR). Compared with the traditional SAR, the polarized SAR greatly improves the acquisition capability of ground target scattering information, and is one of the important directions of the development of the modern SAR. With the progressive penetration of understanding of polarized SAR theory and the continued development of SAR technology, polarized SAR technology has evolved over the last decades. Polarized SAR is becoming increasingly widely and deeply applied in various fields such as land cover classification, ground feature parameter inversion, target identification, topographic mapping, urban change monitoring, ocean monitoring and the like. One basic premise of polarized SAR applications is to analyze the polarization characteristics of the target.
Target polarization decomposition is an important and commonly used target polarization characteristic analysis technique. The incoherent target polarization decomposition based on the model is an important branch of the target polarization decomposition due to simple operation and definite physical meaning. Model-based incoherent target polarization decomposition attracts a great deal of attention of a large number of researchers, and has become a research hotspot and difficulty in the fields of target polarization decomposition and polarized SAR.
In the prior art, the problem of underutilization of negative power pixels and coherence matrix elements is easily caused based on Model-based polarization target decomposition (MTD). The polarized electromagnetic wave is polarized when the target is scattered, so that the coupling exists between the scattering coefficients of the target scattering matrix element and the conventional horizontal-horizontal polarization (HH), vertical-vertical polarization (VV) and horizontal-vertical polarization (HV), the contribution sources of the cross polarization components cannot be distinguished when the coupling is processed, and the negative power pixels appear after the MTD is decomposed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a polarization target decomposition method based on LPC compensation, which aims to solve the technical problems that a scattering model is unreasonable and negative power pixels are easy to appear in the prior art.
In order to achieve the above object, the present invention is achieved by the following technical scheme: the polarization target decomposition method based on LPC compensation comprises the following steps:
inputting full polarization data of a target image, wherein the full polarization data is expressed as a first coherence matrix corresponding to the target image;
calculating to obtain a phase angle corresponding to the first coherence matrix, and compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix;
calculating to obtain a configuration degree corresponding to the second correlation matrix, and rotating the second correlation matrix based on the configuration degree to obtain a third correlation matrix;
performing eigenvalue decomposition on the third correlation matrix to obtain polarization entropy, and characterizing a target distribution ratio based on the polarization entropy to quantify and distinguish contributions of cross polarization components;
decomposing the third dry matrix based on the following expression:
；
in the method, in the process of the invention,a decomposed surface scattering matrix, a dihedral scattering matrix and a bulk scattering matrix respectively,the two-dimensional scattering power and the volume scattering power are respectively the surface scattering power and the dihedral angle scattering power;
decomposing the surface scattering matrix, the dihedral angle scattering matrix and the bulk scattering matrix based on a global orientation angle to compare magnitudes of surface scattering and even scattering in contributions of cross-polarized components;
if the surface scattering is dominant, judging that the even scattering is the metal dihedral angle scattering of the coherent, and solving the surface scattering parameter, the surface scattering power and the dihedral angle scattering power based on the even scattering parameter;
if the dihedral angle scattering is dominant, judging that the surface scattering is the diffuse scattering of the coherence, and solving the even-order scattering parameter, the surface scattering power and the dihedral angle scattering power based on the surface scattering parameter.
According to an aspect of the foregoing solution, the first coherence matrixThe expression of (2) is as follows:
；
the step of calculating the phase angle corresponding to the first coherence matrix specifically includes:
a phase angle corresponding to the first coherence matrix is obtained based on the following calculation formula:
（2）；
in the method, in the process of the invention,is an arctangent function of four quadrants, im represents taking the imaginary part of the complex number, n= = -j =>Means that the phase angle is limited to +.>，/>Representing a unsigned operation.
According to an aspect of the foregoing technical solution, the step of compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix specifically includes:
compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix according to the following calculation formula:
；
in the method, in the process of the invention,for the second correlation matrix, +.>For the third order unit rotation matrix corresponding to the phase angle,/->J is an imaginary number.
According to an aspect of the foregoing technical solution, the step of calculating the configuration degree corresponding to the second correlation matrix specifically includes:
and obtaining the configuration degree corresponding to the second correlation matrix based on the following calculation formula:
；
in the method, in the process of the invention,for the degree of configuration, ++>The representation takes a real number.
According to an aspect of the foregoing technical solution, the step of rotating the second correlation matrix based on the configuration degree to obtain a third correlation matrix specifically includes:
rotating the second correlation matrix based on the degree of configuration according to the following calculation formula to obtain a third correlation matrix：
；
In the method, in the process of the invention,for the third dry matrix, ++>A third-order unit rotation matrix corresponding to the degree of configuration,；
the third phase dry matrixThe expression of (2) is as follows:
；
in the method, in the process of the invention,for even scattering parameters, +.>For the surface scattering parameter, +.>Is the complex conjugate of the even scattering parameter,for the complex conjugate of the surface scattering parameter, the superscript s indicates surface scattering, and the superscript d indicates dihedral angle scattering, ">，/>Andis the orientation angle +.>A distribution model of uniformly distributed scattering particles;
wherein the elements in the third coherent matrixThe method meets the following conditions: />。
According to an aspect of the foregoing technical solution, the step of performing eigenvalue decomposition on the second correlation matrix to obtain polarization entropy and characterizing a target distribution ratio based on the polarization entropy to quantify and distinguish contributions of cross polarization components specifically includes:
performing eigenvalue decomposition on the second correlation matrix to obtain eigenvaluesAnd obtains polarization entropy H based on the following expression:
；
；
in the method, in the process of the invention,for cross polarization distribution ratio->For the pseudo-probability of the characteristic value, +.>The expression of (2) is:
。
according to one aspect of the above solution, the surface scattering matrixThe expression of (2) is as follows:
，/>；
the dihedral angle scattering matrixThe expression of (2) is as follows:
，/>。
according to an aspect of the foregoing technical solution, the expression of each of the distribution models is as follows:
；
；
；
wherein i is s or d,indicates the orientation angle corresponding to the surface scattering, +.>Indicating the orientation angle corresponding to dihedral angle scattering;
the volume scattering matrixThe expression of (2) is as follows:
。
according to an aspect of the above technical solution, if the surface scattering is dominant, determining that the even scattering is coherent metal dihedral angle scattering, and solving the surface scattering parameter, the surface scattering power and the dihedral angle scattering power based on the even scattering parameter specifically includes:
if it isIf the surface scattering is dominant, judging that the even scattering is coherent metal dihedral angle scattering;
and solving the surface scattering parameter, the surface scattering power and the dihedral angle scattering power according to the even scattering parameter based on the following calculation expression:
；
；
；
；
in the method, in the process of the invention,for matrix elements->Is a complex conjugate of (a) and (b).
According to an aspect of the above technical solution, if dihedral angle scattering is dominant, determining that the face scattering is coherent diffuse scattering, and solving the even-order scattering parameter, the face scattering power and the dihedral angle scattering power based on the global orientation angle specifically includes:
if it isIf the dihedral angle scattering is dominant, judging that the surface scattering is coherent diffuse scattering;
and solving the even scattering parameter, the surface scattering power and the dihedral angle scattering power according to the surface scattering parameter based on the following calculation expression:
；
；
；
。
compared with the prior art, the invention has the beneficial effects that: the contribution of cross polarization components is distinguished through the target distribution ratio represented by polarization entropy, and the coupling of same polarization and cross polarization in a polarization scattering matrix during MTD decomposition is relieved by utilizing phase angle compensation and a distribution surface/dihedral angle scattering model, so that the problem of negative power pixels caused by |C|2-SD <0 is solved.
Drawings
FIG. 1 is a flowchart of a polarization target decomposition method based on LPC compensation according to an embodiment of the present invention;
the invention will be further described in the following detailed description in conjunction with the above-described figures.
Detailed Description
In order that the invention may be readily understood, a more complete description of the invention will be rendered by reference to the appended drawings. Various embodiments of the invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Referring to fig. 1, an LPC compensation-based polarization target decomposition method according to an embodiment of the invention includes the following steps:
step S100, inputting full polarization data of a target image, wherein the full polarization data is expressed as a first coherence matrix corresponding to the target image. Specifically, the expression of the first coherence matrix is:
（1）。
preferably, in this embodiment, after step S100, the method further includes:
and step S110, performing multi-view and polarization filtering processing on the first coherence matrix.
Step S200, calculating a phase angle corresponding to the first coherence matrix, and compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix.
Specifically, in this embodiment, the step S200 specifically includes:
step S210, obtaining a phase angle corresponding to the first coherence matrix based on the following calculation formula:
（2）；
in the method, in the process of the invention,is an arctangent function of four quadrants, im represents taking the imaginary part of the complex number, n= = -j =>Means that the phase angle is limited to +.>，/>Representing a unsigned operation.
Step S220, obtaining a phase angle corresponding to the first coherence matrix based on the following calculation formula:
（2）；
in the method, in the process of the invention,is an arctangent function of four quadrants, im represents taking the imaginary part of the complex number, n= = -j =>Means that the phase angle is limited to +.>，/>Representing a unsigned operation.
Step S230, compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix according to the following calculation formula:
（4）；
in the method, in the process of the invention,for the second correlation matrix, +.>For the phase angle corresponds toThird order unitary rotation matrix of>J is an imaginary number.
And step S300, calculating the configuration degree corresponding to the second correlation matrix, and rotating the second correlation matrix based on the configuration degree to obtain a third correlation matrix.
Specifically, in the embodiment, the step S300 specifically includes:
step S310, obtaining a configuration degree corresponding to the second correlation matrix based on the following calculation formula:
（5）；
in the method, in the process of the invention,for the degree of configuration, ++>The representation takes a real number.
Step S320, rotating the second correlation matrix based on the degree of configuration according to the following calculation formula to obtain a third correlation matrix：
（6）；
In the method, in the process of the invention,for the third dry matrix, ++>A third-order unit rotation matrix corresponding to the degree of configuration,；
the third phase dry matrixThe expression of (2) is as follows:
（7）；
in the method, in the process of the invention,for even scattering parameters, +.>For the surface scattering parameter, +.>Is the complex conjugate of the even scattering parameter,for the complex conjugate of the surface scattering parameter, the superscript s indicates surface scattering, and the superscript d indicates dihedral angle scattering, ">，/>Andis the orientation angle +.>A distribution model of uniformly distributed scattering particles;
wherein the elements in the third coherent matrixThe method meets the following conditions:
（8）。
specifically, equation (8) above represents the elements of the coherence matrix after LPC compensation of the coherence matrixThe real part of (2) is equal to 0.
And step S400, performing eigenvalue decomposition on the third correlation matrix to obtain polarization entropy, and characterizing a target distribution ratio based on the polarization entropy so as to quantify and distinguish contributions of cross polarization components.
Specifically, in the embodiment, the step S400 specifically includes:
step S410, performing eigenvalue decomposition on the second correlation matrix to obtain eigenvaluesAnd obtains polarization entropy H based on the following expression:
（9）；
in the method, in the process of the invention,for the pseudo-probability of the characteristic value, +.>。
It is assumed that the contribution of the cross-polarized components comes from both bulk scattering and distributed surface scattering or distributed dihedral scattering. Previous target decomposition methods always attribute all cross-polarized components to bulk scatter contributions.
In this embodiment, the cross polarization distribution ratio p before and after the LPC target compensation is defined based on the polarization entropy:
（10）；
in the method, in the process of the invention,is the cross polarization distribution ratio.
Step S500, decomposing the third dry matrix based on the following expression:
（11）；
in the method, in the process of the invention,a decomposed surface scattering matrix, a dihedral scattering matrix and a bulk scattering matrix respectively,the surface scattering power, the dihedral scattering power, and the bulk scattering power, respectively.
Step S600, decomposing the surface scattering matrix, the dihedral angle scattering matrix and the bulk scattering matrix based on the global orientation angle to compare the magnitudes of the surface scattering and the even scattering in the contribution of the cross polarization component.
Specifically, in the present embodiment, the above-described surface scattering matrixThe expression of (2) is as follows:
，/>（12）；
the dihedral angle scattering matrixThe expression of (2) is as follows:
，/>（13）；
wherein,surface scattering matrix, which can be coherent or incoherent scattering,>the two-angle surface scattering matrix, which may be coherent scattering or incoherent scattering.
Further, the expression of each of the distribution models is as follows:
（14）；
（15）；
（16）；
wherein i is s or d,indicates the orientation angle corresponding to the surface scattering, +.>Indicating the orientation angle corresponding to dihedral angle scattering;
the volume scattering matrixThe expression of (2) is as follows:
（17）。
further can be obtained:
（18）；
expansion (18), obtaining:
（19）；
（20）；
（21）；
（22）；
to find the unknowns, a distribution ratio is introducedDefined as the contribution of the bulk scattering cross-polarization component to the total cross-polarization component, namely:
（23）；
thus, it is possible to obtain:
（24）。
specifically, substitution of the above formula (24) into the formulas (19) and (20) can be used to determine the dominant cases of even-order scattering and surface scattering.
Further, in the present embodiment, the first and second embodiments,usually denoted surface scattering, ">Typically denoted dihedral scattering;
if it isThen surface scattering dominates;
if it isThen it means that dihedral angle scattering dominates;
in step S710, if the surface scattering is dominant, it is determined that the even scattering is the coherent metal dihedral angle scattering, and the surface scattering parameter, the surface scattering power and the dihedral angle scattering power are solved based on the even scattering parameter.
Specifically, the present invention relates to a method for manufacturing a semiconductor device. Surface scattering dominates, even scattering is considered to be coherent metal dihedral scattering, i.e.:
（25）。
then it is obtainable by the above formulae (19) and (22):
（26）；
further, the orientation angle can be solved by the following calculation：
（27）；
Represented by the above formula (27), an alignmentTo make a change to obtain->To obtain the minimum value corresponding to the minimum value +.>Is a value of (2);
thereby obtaining based on the above formulas (14) - (16)、/>And further based on the above formulas (5) to (8):
（28）
（29）；
（30）；
in the method, in the process of the invention,for matrix elements->Is a complex conjugate of (a) and (b).
Step S720, if the dihedral angle scattering is dominant, judging that the face scattering is the coherent diffuse scattering, and solving the even scattering parameter, the face scattering power and the dihedral angle scattering power based on the global orientation angle. Specifically, dihedral scattering dominates, then surface scattering is considered to be coherent diffuse scattering, i.e.:
（31）。
then it is obtainable by the above formulae (20) and (21):
（32）；
further, the orientation angle can be solved by the following calculation：
（33）；
The above formula (33) represents thatTo make a change to obtain->To obtain the minimum value corresponding to the minimum value +.>Is a value of (2);
thereby obtaining based on the above formulas (14) - (16)、/>、/>Further, based on the above formulas (10) and (24):
（34）；
（35）；
（36）。
in summary, the method for decomposing polarization targets based on LPC compensation in the above embodiment of the present invention provides a method for decomposing the configuration factor and phase target compensation (LPC, linear and Phase Compensation) of the correlation matrix element T12 to quantify the contribution (Quantity of Cross polarization contribution) of cross polarization components and reduce the bulk scattering components (lpc+qcmd) to alleviate the above problems. According to the scheme, the contribution of cross polarization components is distinguished through the target distribution ratio of polarization entropy characterization, the coupling of the same polarization and cross polarization in a polarization scattering matrix during MTD decomposition is relieved by utilizing phase angle compensation and a distribution surface/dihedral angle scattering model, and the problem of negative power pixels caused by |C|2-SD <0 is solved.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that various modifications and improvements can be made by those skilled in the art without departing from the spirit of the invention, which falls within the scope of the present invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (6)
1. The polarization target decomposition method based on LPC compensation is characterized by comprising the following steps:
inputting full polarization data of a target image, wherein the full polarization data is expressed as a first coherence matrix corresponding to the target image, and the first coherence matrixThe expression of (2) is as follows:
；
calculating to obtain a phase angle corresponding to the first coherence matrix, and compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix;
calculating to obtain a configuration degree corresponding to the second correlation matrix, and rotating the second correlation matrix based on the configuration degree to obtain a third correlation matrix;
performing eigenvalue decomposition on the third correlation matrix to obtain polarization entropy, and characterizing a target distribution ratio based on the polarization entropy to quantify and distinguish contributions of cross polarization components;
decomposing the third dry matrix based on the following expression:
；
in the method, in the process of the invention,a decomposed surface scattering matrix, a dihedral scattering matrix and a bulk scattering matrix respectively,the two-dimensional scattering power and the volume scattering power are respectively the surface scattering power and the dihedral angle scattering power;
decomposing the surface scattering matrix, the dihedral angle scattering matrix and the bulk scattering matrix based on a global orientation angle to compare magnitudes of surface scattering and even scattering in contributions of cross-polarized components;
if the surface scattering is dominant, judging that the even scattering is the metal dihedral angle scattering of the coherent, and solving the surface scattering parameter, the surface scattering power and the dihedral angle scattering power based on the even scattering parameter;
if the dihedral angle scattering is dominant, judging that the surface scattering is the diffuse scattering of the coherence, and solving the even scattering parameter, the surface scattering power and the dihedral angle scattering power based on the surface scattering parameter;
the step of calculating the phase angle corresponding to the first coherence matrix specifically includes:
a phase angle corresponding to the first coherence matrix is obtained based on the following calculation formula:
；
in the method, in the process of the invention,is an arctangent function of four quadrants, im represents taking the imaginary part of the complex number, n= = -j =>Means that the phase angle is limited to +.>，/>Representing a sign taking operation;
the step of compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix specifically includes:
compensating the first coherence matrix based on the phase angle to obtain a second coherence matrix according to the following calculation formula:
；
in the method, in the process of the invention,for the second correlation matrix, +.>For the third-order unitary rotation matrix corresponding to the phase angle,j is an imaginary number;
the step of calculating the configuration degree corresponding to the second correlation matrix specifically includes:
and obtaining the configuration degree corresponding to the second correlation matrix based on the following calculation formula:
；
the step of rotating the second interference matrix based on the configuration degree to obtain a third interference matrix specifically includes:
rotating the second correlation matrix based on the degree of configuration according to the following calculation formula to obtain a third correlation matrix：
；
In the method, in the process of the invention,for the third dry matrix, ++>A third-order unit rotation matrix corresponding to the degree of configuration,；
the third phase dry matrixThe expression of (2) is as follows:
；
in the method, in the process of the invention,for even scattering parameters, +.>For the surface scattering parameter, +.>For the conjugate complex number of the even scattering parameter, < >>For the complex conjugate of the surface scattering parameter, the superscript s indicates surface scattering, and the superscript d indicates dihedral angle scattering, ">，/>And->Is the orientation angle +.>A distribution model of uniformly distributed scattering particles;
wherein the elements in the third coherent matrixThe method meets the following conditions: />。
2. The method for polarization target decomposition based on LPC compensation according to claim 1, wherein the step of performing eigenvalue decomposition on the third correlation matrix to obtain polarization entropy and characterizing a target distribution ratio based on the polarization entropy to quantify and distinguish contributions of cross polarization components specifically comprises:
performing eigenvalue decomposition on the third coherent matrix to obtain eigenvaluesAnd obtains polarization entropy H based on the following expression:
；
；
in the method, in the process of the invention,for cross polarization distribution ratio->For the pseudo-probability of the characteristic value, +.>The expression of (2) is:
。
3. the LPC compensation-based polarization target decomposition method of claim 2, wherein the surface scattering matrixThe expression of (2) is as follows:
；
the dihedral angle scattering matrixThe expression of (2) is as follows:
。
4. the polarization target decomposition method based on LPC compensation according to claim 3, wherein the expression of each of the distribution models is as follows:
；
；
；
wherein i is s or d,indicates the orientation angle corresponding to the surface scattering, +.>Indicating the orientation angle corresponding to dihedral angle scattering;
the volume scattering matrixThe expression of (2) is as follows:
。
5. the method for decomposing a polarized target based on LPC compensation according to claim 4, wherein if the surface scattering is dominant, determining that the even scattering is coherent metal dihedral angle scattering, and solving the surface scattering parameter, the surface scattering power and the dihedral angle scattering power based on the even scattering parameter specifically comprises:
if it isIf the surface scattering is dominant, judging that the even scattering is coherent metal dihedral angle scattering;
and solving the surface scattering parameter, the surface scattering power and the dihedral angle scattering power according to the even scattering parameter based on the following calculation expression:
；
；
；
；
in the method, in the process of the invention,for matrix elements->Is a complex conjugate of (a) and (b).
6. The method for decomposing a polarized target based on LPC compensation according to claim 4, wherein if dihedral angle scattering is dominant, determining that the facial scattering is coherent diffuse scattering, and solving for even-order scattering parameters, facial scattering power, and dihedral angle scattering power based on the global orientation angle specifically comprises:
if it isIf the dihedral angle scattering is dominant, judging that the surface scattering is coherent diffuse scattering;
and solving the even scattering parameter, the surface scattering power and the dihedral angle scattering power according to the surface scattering parameter based on the following calculation expression:
；
；
；
。
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104408467A (en) * | 2014-11-26 | 2015-03-11 | 西安电子科技大学 | Polarimetric SAR (synthetic aperture radar) image classification method based on pyramid sampling and SVM (support vector machine) |
| CN110412573A (en) * | 2019-08-08 | 2019-11-05 | 内蒙古工业大学 | Polarimetric SAR image decomposition method and storage medium |
| CN111665504A (en) * | 2020-05-29 | 2020-09-15 | 武汉大学 | Fully-polarized SAR target decomposition method for angle optimization processing |
| CN112630741A (en) * | 2020-12-11 | 2021-04-09 | 江西师范大学 | Full-polarization synthetic aperture radar image target compensation PEOC method |
| CN115221455A (en) * | 2022-08-15 | 2022-10-21 | 江西师范大学 | Polarization decomposition method and device based on model and storage medium |
| WO2023104167A1 (en) * | 2021-12-10 | 2023-06-15 | 深圳先进技术研究院 | Fully polarimetric synthetic aperture radar image classification method and system, and terminal |
| CN116879860A (en) * | 2023-07-10 | 2023-10-13 | 西安理工大学 | Polarized SAR data multi-element scattering energy decomposition method based on eigenvalue decomposition |
| CN117111063A (en) * | 2023-08-22 | 2023-11-24 | 上海无线电设备研究所 | Polarized SAR image feature extraction method |
-
2023
- 2023-12-12 CN CN202311695774.6A patent/CN117390355B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104408467A (en) * | 2014-11-26 | 2015-03-11 | 西安电子科技大学 | Polarimetric SAR (synthetic aperture radar) image classification method based on pyramid sampling and SVM (support vector machine) |
| CN110412573A (en) * | 2019-08-08 | 2019-11-05 | 内蒙古工业大学 | Polarimetric SAR image decomposition method and storage medium |
| CN111665504A (en) * | 2020-05-29 | 2020-09-15 | 武汉大学 | Fully-polarized SAR target decomposition method for angle optimization processing |
| CN112630741A (en) * | 2020-12-11 | 2021-04-09 | 江西师范大学 | Full-polarization synthetic aperture radar image target compensation PEOC method |
| WO2023104167A1 (en) * | 2021-12-10 | 2023-06-15 | 深圳先进技术研究院 | Fully polarimetric synthetic aperture radar image classification method and system, and terminal |
| CN115221455A (en) * | 2022-08-15 | 2022-10-21 | 江西师范大学 | Polarization decomposition method and device based on model and storage medium |
| CN116879860A (en) * | 2023-07-10 | 2023-10-13 | 西安理工大学 | Polarized SAR data multi-element scattering energy decomposition method based on eigenvalue decomposition |
| CN117111063A (en) * | 2023-08-22 | 2023-11-24 | 上海无线电设备研究所 | Polarized SAR image feature extraction method |
Non-Patent Citations (3)
| Title |
|---|
| 基于极化功率比与极化熵的目标分类方法;张向峰;马德宝;邬钧霆;牛朝阳;;信息工程大学学报;20060330(第01期);第43页 * |
| 宽带全极化雷达目标HRRP极化特征提取与优选;郭雷;肖怀铁;赵宏钟;付强;;自然科学进展;20090715(第07期);全文 * |
| 高分辨率全极化合成孔径雷达数据海冰二次分类方法研究;刘眉洁;戴永寿;张杰;任广波;孟俊敏;张晰;;海洋学报(中文版);20130715(第04期);全文 * |
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