CN111856421B - Method and device for polarization rotation domain feature extraction and radar target enhancement - Google Patents
Method and device for polarization rotation domain feature extraction and radar target enhancement Download PDFInfo
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Abstract
The invention discloses a method and a device for polarization rotation domain feature extraction and radar target enhancement, wherein the method comprises the following steps: rotating the obtained polarization scattering matrix in the direction around the polarization radar sight line to obtain a rotating polarization scattering matrix; extracting a scattering vector based on the rotation polarization scattering matrix; extracting a polarization channel combination based on the scattering vector, and performing visualization processing on a polarization correlation value of the polarization channel combination to obtain a polarization correlation directional diagram; extracting the following polarization correlation directional diagram features from the polarization correlation directional diagram for parametric characterization: original polarization-related characteristic value, polarization-related characteristic maximum value, polarization-related characteristic minimum value, polarization correlation degree, polarization-related fluctuation degree, polarization-related contrast degree, polarization-related inverse entropy, maximized rotation angle, minimized rotation angle and polarization-related width. The method solves the problems of unobtrusiveness, difficulty in recognition and the like of the target in the prior art and realizes target enhancement.
Description
Technical Field
The invention relates to the technical field of radar polarization information processing and application, in particular to a method and a device for polarization rotation domain feature extraction and radar target enhancement.
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 polarization information of the target obtained by the polarized radar can be characterized by a polarization scattering matrix. The polarization correlation characteristics among 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 much inconvenience to radar polarization information processing and application, and is one of the technical bottlenecks faced by fine interpretation and quantitative application of the polarization scattering mechanism of the current polarization radar target.
The polarization data obtained under the specific imaging geometric condition is rotated around the radar sight direction, and is expanded to a polarization rotation domain for analysis, so that the polarization information hidden in the target is expected to be mined, the radar target enhancement is realized, and the method becomes a key for improving the target scattering mechanism interpretation and application performance. Therefore, the method and the device for polarization rotation domain feature extraction and radar target enhancement are of great value.
Disclosure of Invention
The invention provides a method and a device for extracting polarization rotation domain features and enhancing a radar target, which are used for overcoming the defects that the radar target has low contrast ratio, the target scattering characteristic is sensitive to the relative geometric relationship between the target attitude and the radar sight line and the like in the prior art, and performing visual processing and parametric depiction on the polarization correlation value between two polarization channels in the polarization rotation domain, so that the polarization rotation domain features can be extracted, the identifiability of the radar target is effectively enhanced, the method and the device are suitable for polarization radar systems with multiple purposes (such as air monitoring, earth observation, meteorological detection, sea surface monitoring and the like), and have application values in the fields of air target classification identification, ground object class identification, damage assessment and the like.
In order to achieve the above object, the present invention provides a method for polarization rotation domain feature extraction and radar target enhancement, comprising:
step 1, performing rotation processing on the obtained polarization scattering matrix in a direction around the polarization radar sight line to obtain a rotation polarization scattering matrix;
step 2, extracting Pauli vectors and Lexicogrphic vectors based on the rotation polarization scattering matrix;
step 3, respectively extracting polarization channel combinations from Pauli vectors and Lexicogrphic vectors, and carrying out visualization processing on polarization correlation values of the polarization channel combinations to obtain polarization correlation directional diagrams;
step 4, extracting the following polarization correlation directional diagram features from the polarization correlation directional diagram for parametric characterization: original polarization-dependent feature values, polarization-dependent feature maximum values, polarization-dependent feature minimum values, polarization dependence degrees, polarization-dependent waviness degrees, polarization-dependent contrast degrees, polarization-dependent inverse entropy degrees, maximized rotation angles, minimized rotation angles, and polarization-dependent widths.
In order to achieve the above object, the present invention further provides an apparatus for polarization rotation domain feature extraction and radar target enhancement, including a memory and a processor, where the memory stores programs for polarization rotation domain feature extraction and radar target enhancement, and the processor executes the steps of the above method when running the programs for polarization rotation domain feature extraction and radar target enhancement.
The method and the device for extracting the polarization rotation domain features and enhancing the radar target can visually and parametrically depict the characteristics of the polarization correlation value of the target in the rotation domain around the radar sight line by extracting the polarization rotation domain features, and provide application services for subsequent radar target enhancement and the like by extracting the characteristic parameters of a polarization correlation directional diagram. 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.
Drawings
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 flowchart of a method for extracting polarization rotation domain features and enhancing radar targets according to an embodiment of the present invention;
FIG. 2(a) is an RGB pseudo-color image under Pauli-based decomposition of actually measured polarimetric synthetic aperture radar data;
FIG. 2(b) measured polarimetric synthetic aperture radar data ship target true figure;
FIG. 3 is a diagram of a polarization-dependent characteristic of a rotation domain under a horizontal-vertical polarization basis; wherein:
FIG. 3(a) shows a polarization channel SHHAnd SHVA rotation domain polarization correlation characteristic derived from the polarization correlation values of cells;
FIG. 3(b) shows a polarization channel SHHAnd SVVA rotation domain polarization correlation characteristic derived from the polarization correlation values of cells;
FIG. 3(c) shows a polarization channel SHH+SVVAnd SHH-SVVA rotation domain polarization correlation characteristic derived from the polarization correlation values of cells;
FIG. 3(d) shows a polarization channel SHH-SVVAnd SHVA rotation domain polarization correlation characteristic derived from the polarization correlation values of cells;
FIG. 4 is a contrast analysis based radar target enhancement performance contrast chart.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
It should be noted that all directional indicators (such as upper, lower, left, right, front and rear … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indicator is changed accordingly.
In addition, descriptions such as "first", "second", etc. in the present invention are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
In the present invention, unless otherwise explicitly stated or limited, the terms "connected", "fixed", and the like are to be understood broadly, for example, "fixed" may be fixedly connected, may be detachably connected, or may be integrated; the connection can be mechanical connection, electrical connection, physical connection or wireless communication connection; they may be directly connected or indirectly connected through intervening media, or they may be interconnected within two elements or in a relationship where two elements interact with each other unless otherwise specifically limited. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the technical solutions in the embodiments of the present invention may be combined with each other, but it must be based on the realization of those skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination of technical solutions should not be considered to exist, and is not within the protection scope of the present invention.
Example one
As shown in fig. 1, an embodiment of the present invention provides a method for extracting polarization rotation domain features and enhancing radar targets, which mainly includes four steps:
the polarization scattering matrix obtained by the polarized radar is used as an input of the present invention. Targets based on horizontal and vertical polarizationPolarized scattering matrix of
For example. Wherein SHHComplex backscattering coefficients obtained under horizontally polarized transmission and horizontally polarized reception conditions; s. theHVComplex backscattering coefficients obtained under the conditions of horizontal polarization transmission and vertical polarization receiving; s. theVHIs the complex backscattering coefficient obtained under the conditions of vertical polarization transmission and horizontal polarization receiving; sVVAre complex backscattering coefficients obtained under vertically polarized transmit and vertically polarized receive conditions.
Firstly, carrying out rotation processing on a polarization scattering matrix around a radar sight line to obtain a polarization scattering matrix in a polarization rotation domain; before the first step, firstly, a polarization scattering matrix of a target is obtained based on a polarization radar, then, the first step is carried out, the obtained polarization scattering matrix is rotated around the sight line direction of the polarization radar, and a polarization scattering matrix in a polarization rotation domain, namely a rotation polarization scattering matrix, is obtained;
specifically, in the direction around the line of sight of the polarization radar, the polarization scattering matrix S is subjected to rotation processing, and an expression of the rotation polarization scattering matrix S (θ) after rotation processing is calculated for a rotation angle θ in a rotation domain, θ ∈ [ - π, π ], and is:
wherein the rotation matrix
Upper labelTIs a transpose process.
Secondly, extracting Pauli vectors and Lexicogrphic vectors based on the rotating polarization scattering matrix; wherein, Pauli vector is defined as
The Lexicogrphic vector is defined as
Thirdly, extracting six polarization channel combinations from Pauli vectors and Lexicogrphic vectors, and carrying out visualization processing on polarization correlation values among the polarization channels to obtain six polarization correlation directional diagrams respectively
And
for the polarized channel X (S)X) And Y (S)Y) And the polarization correlation directional diagram with the polarization correlation value expanded to the rotation domain is defined as follows:
can verify
And is
The remaining four polarization dependent patterns are therefore
This was left for further analysis.
Fourthly, parametrically depicting the polarization correlation directional diagrams, namely extracting the following characteristic parameters from each polarization correlation directional diagram for parametrically depicting: extracting original polarization-dependent eigenvalues
Maximum value of polarization dependent characteristic
Polarization dependent feature minimum
Degree of polarization dependence
Polarization dependent waviness
Polarization dependent contrast ratio
Polarization dependent inverse entropy
Maximizing the angle of rotation
Minimizing the angle of rotation
Width BW related to polarizationαAnd the like. Where subscripts X and Y denote two different polarization channels, respectively.
The polarization dependent pattern characteristic of the polarization dependent pattern in the rotational domain characterizes the scattering behavior of the polarized radar target in the rotational domain around the radar line of sight. In order to utilize the polarization correlation directional diagram, the following characteristic parameters are extracted and parametrically depicted:
1. original polarization dependent eigenvalues
Comprises the following steps:
2. maximum of polarization dependent characteristic
Comprises the following steps:
3. polarization dependent feature minimum
Comprises the following steps:
4. degree of polarization dependence
Comprises the following steps:
5. polarization dependent undulation degree
Comprises the following steps:
6. polarization dependent contrast ratio
Comprises the following steps:
7. polarization dependent inverse entropy
8. Maximizing the rotation angle
Comprises the following steps:
9. minimizing the angle of rotation
Comprises the following steps:
10. polarization dependent width BWαThe method comprises the following steps:
BWαθ '- θ', wherein
And is
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 a standard deviation of the sequence; α is a regulatory factor, and is usually 0.95.
And combining the polarization-related directional diagram with the characterization parameters to obtain the visualization method of the radar target polarization-related characteristics. The parameters are used for depicting and representing the change characteristics of the polarization correlation values in the polarization rotation domain, a series of polarization characteristics can be extracted for radar target enhancement, and support is provided for application of target detection, classification and identification and the like.
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. The polarization correlation directional diagram derived from the polarization correlation value in the rotation domain is visualized and parametrically depicted, so that the change characteristic 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 is finely interpreted. Therefore, the polarization rotation domain feature extraction and radar target enhancement can be realized, and the method is further used in the fields of physical parameter inversion, target detection classification and the like.
Fig. 2 is a schematic diagram of a Synthetic Aperture Radar (SAR) measured data for visually analyzing the method and apparatus of the present invention. FIG. 2(a) is a RGB pseudo-color image under Pauli-based decomposition. Fig. 2(b) is a true value diagram of the measured data, in which black pixel points are sea clutter background, white pixel points are ship targets, and gray is a land area. It should be noted that the invention is not only applicable to polarimetric SAR, but also applicable to other polarized radars of various systems.
Fig. 3 shows a polarization rotation domain feature extraction result based on measured data. Fig. 3(a) - (d) respectively represent four sets of polarization dependent pattern features derived from the four sets of polarization dependent channel combinations. The method can be obtained by visual analysis, and the ship target and the sea clutter background in the polarization-related directional diagram feature have obvious difference in value. In particular, in the original polarization dependent eigenvalues
Maximum value of polarization dependent characteristic
Polarization dependent feature minimum
Degree of polarization dependence
Polarization dependent waviness
Polarization dependent contrastDegree of rotation
And the like, the values of the ships are similar, and the value difference with the sea clutter is large. Compared with the original polarized SAR image, the ship target in the radar image is obviously enhanced from the visual angle.
Fig. 4 is a contrast analysis-based radar target enhancement performance contrast map. Contrast Ratio (TCR) is defined as the Ratio of the polarization dependent pattern characteristics of the Target region and the Clutter region in the polarization dependent pattern characteristics. In a polarized SAR image containing a ship target, the ratio of the characteristic sizes of polarization-related directional diagrams of a ship region and a sea clutter region is as follows:
in the above formula, the numerator represents the mean value of the ship region, and the denominator represents the mean value of the sea clutter region. TCR reflects the magnitude of the difference between target and background in the polarization profile. The larger the TCR is, the more obvious the target is over the background, and the more obvious the radar target enhancement effect is.
In this example, the TCR is selected as an index to analyze the performance of different polarization features in radar target enhancement. And selecting the total power SPAN of the polarized SAR data and the characteristics of a polarization-related directional diagram as comparison. The polarization-dependent directional diagram is characterized in that the polarization-dependent values among the polarization channels are expanded to a polarization rotation domain. For the polarization channels X and Y, the polarization dependent pattern whose polarization dependent value extends to the rotation domain is defined as:
can extract the original polarization-dependent eigenvalue | gammaX-Y|orgPolarization dependent characteristic maximum | γX-Y|maxPolarization dependent feature minimum | γX-Y|minPolarization correlation | γX-Y|meanPolarization dependent waviness | γX-Y|stdPolarization dependent contrast | γX-Y|contrastPolarization dependent inverse entropy | γX-Y|AniMaximizing the rotation angle thetaγ-maxMinimize the rotation angle thetaγ-minWidth BW related to polarizationαAnd (3) when the parameters are plotted, the polarization-related characteristic quantity is defined similarly to the polarization-related characteristic quantity, and the difference is that the polarization-related directional diagram is defined differently. In FIG. 4, the dark grey is the TCR of SPAN; the light grey indicates the TCR characteristic of the polarization dependent pattern; the black color indicates the TCR characteristic of the polarization dependent pattern. Besides SPAN, other polarization rotation domain features are divided into four groups according to different polarization channel combinations. In the polarization correlation characteristics, each group of characteristics respectively represents polarization correlation inverse entropy, polarization correlation contrast, polarization correlation maximum value, polarization correlation degree, polarization correlation minimum value, polarization correlation fluctuation and polarization correlation original value from left to right. In the polarization correlation characteristics, each group of characteristics respectively represents polarization correlation inverse entropy, polarization correlation contrast, polarization correlation maximum value, polarization correlation degree, polarization correlation minimum value, polarization correlation fluctuation and polarization correlation original value from left to right.
The total power SPAN of the polarized SAR data is 13. The TCR of the polarization dependent pattern features is smaller and none higher than 3 compared to SPAN, as shown in the enlarged view in the bottom rectangular box of fig. 4. Among them, the highest polarization-dependent directional diagram of TCR is characterized by gamma(HH-VV)-(HV)(θ)|orgAnd its TCR is 3. Compared with the SPAN and the polarization-dependent directional diagram characteristics, the TCR of the polarization-dependent directional diagram characteristics is obviously improved, namely the radar target is obviously enhanced. In particular, the highest 3 polarization dependent patterns of the TCR are characterized by
And
the TCRs were 449, 209, 119, respectively. TCR highest polarization dependent pattern characteristics
The performance of the directional antenna is improved by more than 15dB compared with SPAN and by more than 22dB compared with the highest polarization correlation characteristic of TCR, and the polarization correlation directional diagram characteristic is best used for enhancing the performance of a polarized radar target. Therefore, the contrast experiment verifies that the extracted polarization rotation domain characteristics can be effectively applied to radar target enhancement.
Example two
Based on the first embodiment, the present invention provides an apparatus for polarization rotation domain feature extraction and radar target enhancement, which includes a memory and a processor, where the memory stores a program for polarization rotation domain feature extraction and radar target enhancement, and the processor executes the steps of any of the above method embodiments when running the program for polarization rotation domain feature extraction and radar target enhancement.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (6)
1. A method for polarization rotation domain feature extraction and radar target enhancement is characterized by comprising the following steps:
step 1, performing rotation processing on an obtained polarization scattering matrix in a direction around a polarization radar sight line to obtain a rotation polarization scattering matrix;
step 2, extracting Pauli vectors and Lexicogrphic vectors based on the rotation polarization scattering matrix; wherein Pauli vector is defined as
The Lexicogrphic vector is defined as
Step 3, respectively extracting polarization channel combinations from Pauli vectors and Lexicogrphic vectors, and performing visualization processing on polarization correlation values of the polarization channel combinations to obtain polarization correlation directional diagrams;
step 4, extracting the following polarization correlation directional diagram characteristics from the polarization correlation directional diagram for parametric characterization: original polarization correlation characteristic value, polarization correlation characteristic maximum value, polarization correlation characteristic minimum value, polarization correlation degree, polarization correlation fluctuation degree, polarization correlation contrast degree, polarization correlation inverse entropy, maximum rotation angle, minimum rotation angle and polarization correlation width;
on the basis of the polarization correlation directional diagram characteristics extracted in the step 4, the polarization correlation directional diagram characteristics are preferably selected for target enhancement based on the index of contrast; the contrast is defined as the ratio of the polarization-related directional diagram characteristic values of a target area and a clutter area in the polarization-related directional diagram characteristic;
in the step 1, the target polarization scattering matrix under the horizontal and vertical polarization base obtained by the polarization radar is:
wherein S isHHComplex backscattering coefficients obtained under horizontally polarized transmission and horizontally polarized reception conditions; s. theHVComplex backscattering coefficients obtained under the conditions of horizontal polarization transmission and vertical polarization receiving; s. theVHComplex backscattering coefficients obtained under vertical polarization transmitting and horizontal polarization receiving conditions; sVVIs the complex backscattering coefficient obtained under the vertical polarization transmitting and vertical polarization receiving conditions;
in the direction of the view of the polarized radar, the polarized scattering matrix S is rotated, and the rotation angle theta in the rotation domain is calculated, wherein the expression of the rotated polarized scattering matrix S (theta) after rotation processing is as follows:
wherein the rotation matrix R2(θ) is:
upper labelTFor transposition, the rotation angle theta is in the range of theta E [ -pi, pi]；
The step 3 comprises the following steps:
for any two polarization channels SXAnd SYTo polarize the channel SXAnd SYThe polarization correlation value is visualized in a rotation domain to obtain a polarization correlation directional diagram, which is defined as:
wherein,<·>for set-averaging, | is absolute value processing, superscript*Conjugation treatment is carried out;
in step 4, the following ten polarization-related directional diagram features are extracted from each polarization-related directional diagram to characterize and characterize the polarization-related directional diagram:
original polarization dependent eigenvalues
Comprises the following steps:
maximum value of polarization dependent characteristic
Comprises the following steps:
polarization dependent feature minimum
Comprises the following steps:
degree of polarization dependence
Comprises the following steps:
polarization dependent undulation degree
Comprises the following steps:
polarization dependent contrast ratio
Comprises the following steps:
polarization dependent inverse entropy
Comprises the following steps:
maximizing the angle of rotation
Comprises the following steps:
minimizing the rotation angle
Comprises the following steps:
polarization dependent width BWαComprises the following steps:
BWαθ '- θ', wherein
And is
Wherein max {. is the maximum value of the sequence; min {. is the minimum value of the sequence; mean {. is averaging the sequence; std {. is standard deviation of sequence; alpha is a regulating factor, and alpha is 0.95.
2. The method of claim 1, wherein the polarization-dependent feature target clutter contrast is defined as a ratio of a target region value to a clutter region value at the polarization direction diagram feature.
3. The method of polarization rotating domain feature extraction and radar target enhancement of claim 1, wherein the polarization dependent feature target clutter contrast TCR expression is:
in the above formula, the molecule ShipmeanMean value, denominator Clutter for representing characteristic values of ship regional polarization related characteristic directional diagrammeanAnd the mean value of the characteristic values of the polarization correlation directional diagram of the sea clutter region is represented.
4. The method of claim 3, wherein the three higher TCR polarization-dependent pattern features are each
And
wherein,
denotes the polarization path SHH-SVVAnd SHVThe original polarization-dependent eigenvalues in between,
denotes the polarization path SHHAnd SHVThe original polarization-dependent eigenvalues in between,
denotes the polarization path SHH-SVVAnd SHVThe minimum value of the polarization-dependent characteristic between, the rotation angle theta epsilon [ -pi, pi]。
5. The method of polarization rotating domain feature extraction and radar target enhancement of claim 4, wherein the TCR highest polarization dependent pattern is characterized by
6. An apparatus for polarization rotation domain feature extraction and radar target enhancement, comprising a memory storing a program of polarization rotation domain feature extraction and radar target enhancement and a processor executing the steps of the method of any one of claims 1 to 5 when the program of polarization rotation domain feature extraction and radar target enhancement is run.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105528767A (en) * | 2015-12-05 | 2016-04-27 | 中国人民解放军国防科学技术大学 | Enhancement method of target polarization coherent characteristic in polarization SAR image |
| CN105676203A (en) * | 2016-01-23 | 2016-06-15 | 中国人民解放军国防科学技术大学 | Visualized method for object polarized coherent feature of full-polarization radar |
| CN106443673A (en) * | 2016-09-18 | 2017-02-22 | 中国人民解放军国防科学技术大学 | Building falling loss rate estimation method based on rotating domain polarization coherence characteristic |
| CN106897741A (en) * | 2017-02-20 | 2017-06-27 | 中国人民解放军国防科学技术大学 | With reference to the polarization SAR terrain classification method of rotational domain polarization coherence property |
| CN110244295A (en) * | 2019-07-17 | 2019-09-17 | 广州大学 | Underground linear goal based on polarization Ground Penetrating Radar moves towards measurement method and system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2957541A1 (en) * | 2014-08-08 | 2016-02-11 | Urthecast Corp. | Apparatus and methods for quad-polarized synthetic aperture radar |
-
2020
- 2020-01-17 CN CN202010052848.4A patent/CN111856421B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105528767A (en) * | 2015-12-05 | 2016-04-27 | 中国人民解放军国防科学技术大学 | Enhancement method of target polarization coherent characteristic in polarization SAR image |
| CN105676203A (en) * | 2016-01-23 | 2016-06-15 | 中国人民解放军国防科学技术大学 | Visualized method for object polarized coherent feature of full-polarization radar |
| CN106443673A (en) * | 2016-09-18 | 2017-02-22 | 中国人民解放军国防科学技术大学 | Building falling loss rate estimation method based on rotating domain polarization coherence characteristic |
| CN106897741A (en) * | 2017-02-20 | 2017-06-27 | 中国人民解放军国防科学技术大学 | With reference to the polarization SAR terrain classification method of rotational domain polarization coherence property |
| CN110244295A (en) * | 2019-07-17 | 2019-09-17 | 广州大学 | Underground linear goal based on polarization Ground Penetrating Radar moves towards measurement method and system |
Non-Patent Citations (5)
| Title |
|---|
| Polarimetric Coherence Pattern: A Visualization and Characterization Tool for PolSAR Data Investigation;Si-Wei Chen et al.;《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》;20180131;第56卷(第1期);第286-297页 * |
| Si-Wei Chen et al..Polarimetric Coherence Pattern: A Visualization and Characterization Tool for PolSAR Data Investigation.《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》.2018,第56卷(第1期), * |
| 利用全极化SAR数据去方位向模糊的舰船目标检测方法;魏钜杰等;《测绘学报》;20130815(第04期);全文 * |
| 基于目标分解的极化SAR图像对比增强与分类方法研究;何其钰;《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》;20111215;正文第27-28页 * |
| 极化SAR目标散射旋转域解译理论与应用;陈思伟等;《雷达学报》;20171231(第05期);全文 * |
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