CN114509737A - CTLR compact polarization SAR data scattering component decomposition method, device, equipment and medium - Google Patents

CTLR compact polarization SAR data scattering component decomposition method, device, equipment and medium Download PDF

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CN114509737A
CN114509737A CN202210086102.4A CN202210086102A CN114509737A CN 114509737 A CN114509737 A CN 114509737A CN 202210086102 A CN202210086102 A CN 202210086102A CN 114509737 A CN114509737 A CN 114509737A
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scattering
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安文韬
冯倩
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NATIONAL SATELLITE OCEAN APPLICATION SERVICE
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    • G—PHYSICS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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    • G—PHYSICS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract

The embodiment of the invention discloses a CTLR (computer-to-laser polarimetric synthetic aperture radar) compact polarimetric SAR (synthetic aperture radar) data scattering component decomposition method, a device, equipment and a medium, wherein the method comprises the following steps: acquiring CTLR compact polarization SAR data; calling an improved m-alpha algorithm, and decomposing scattering components of the acquired SAR data, wherein the volume scattering power ratio in the decomposition result is f (1-m), and the surface scattering and secondary scattering power ratio is 1-f (1-m), wherein f (1-m) < (1-m), m is the polarization degree which is greater than 0 and less than 1, f (1-m) has a first extreme value 1 at the position where 1-m is equal to 1, and has a second extreme value 0 at the position where 1-m is equal to 0; storing a result of the decomposition of the scattering components of the SAR data. The technical scheme provided by the embodiment of the invention can be suitable for a scene of analyzing scattering components of CTLR (China Mobile radio receiver) compact polarization SAR (synthetic aperture radar) data in a synthetic aperture radar system, and can solve the problem of overestimating the scattering power ratio of the ground object in the prior art.

Description

CTLR compact polarization SAR data scattering component decomposition method, device, equipment and medium
Technical Field
The invention relates to the technical field of Synthetic Aperture Radar (SAR) remote sensing, in particular to a CTLR (China Mobile Radar) compact polarization SAR data scattering component decomposition method, device, equipment and medium.
Background
Synthetic Aperture Radar (SAR) is an active microwave imaging sensor carried on an aircraft or a satellite for remote sensing observation of the ground. In the flight observation process, the SAR continuously transmits electromagnetic waves to the ground through the antenna according to a certain frequency, then receives electromagnetic wave signals scattered back to the SAR antenna from the ground, and the ground scattered electromagnetic wave signals received for a period of time in the flight process are subjected to imaging processing, so that the high-resolution microwave remote sensing image of the ground can be obtained.
The SAR can be classified into a single polarization type, a dual polarization type, a full polarization type, and the like according to the polarization mode of the transmitting electromagnetic wave and the polarization mode of the receiving electromagnetic wave. Single polarization means that both transmission and reception use horizontal polarization (H) or vertical polarization (V); the dual polarization is that H or V single polarization is adopted for transmission, and H and V polarization are adopted for simultaneous reception; the full polarization means that H and V polarizations are adopted for alternate transmission, and H and V polarizations are adopted for simultaneous reception. The fully polarized data contains an electromagnetic scattering matrix with complete ground objects and has the largest polarized information content, but because the H polarization and the V polarization are required to be alternately transmitted, the observation width is limited and is only half of that of single polarization and dual polarization. In order to obtain the electromagnetic scattering characteristics of the ground features as much as possible while having a large observation width, compact polarization is proposed. Compact polarization refers to the use of circularly polarized or 45 ° linearly polarized transmission, with simultaneous reception using both H and V polarizations. The compact polarization still belongs to the dual polarization category in theory, but because the transmission and the reception use 3 different polarizations, there is a certain observation advantage for some terrestrial objects.
After the compact polarization is proposed, how to decompose the data to obtain the composition of each scattering component of the ground object is one of the important points of research. For circularly polarized transmit H and V-polarized simultaneous receive (CTLR) compact polarized SAR data, a number of scatter component decomposition algorithms are proposed in succession, typically as follows: the m-delta algorithm, the m-chi algorithm, and the m-alpha algorithm. Among them, the m- α algorithm is the best among the three algorithms and is also the most widely used one. The m-alpha algorithm decomposes the CTLR compact polarization SAR data into two scattering components, the first component corresponds to volume scattering, the second component corresponds to surface scattering and secondary scattering, the power ratio of the two components is 1-m and m respectively, wherein m is the polarization degree.
However, in the research process, the m-alpha algorithm has the problem of overestimation of the volume scattering, namely, the volume scattering power accounts for 1-m to be larger than the actual volume scattering power in each scattering component power of the ground features obtained by decomposing CTLR compact polarization SAR data by the m-alpha algorithm.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method, an apparatus, a device, and a medium for decomposing scattering components of CTLR compact polarization SAR data, so as to solve the problem of overestimating the volume scattering power ratio in the prior art.
In a first aspect, an embodiment of the present invention provides a scattering component decomposition method for CTLR compact polarization SAR data, where the method includes:
acquiring circularly polarized transmitting horizontal and vertical polarized receiving CTLR compact polarized SAR data;
calling an improved m-alpha algorithm, and decomposing scattering components of the acquired SAR data, wherein the volume scattering power ratio in the decomposition result is f (1-m), and the surface scattering and secondary scattering power ratio is 1-f (1-m), wherein f (1-m) < (1-m), m is the polarization degree which is greater than 0 and less than 1, f (1-m) has a first extreme value 1 at the position where 1-m is equal to 1, and has a second extreme value 0 at the position where 1-m is equal to 0;
storing a result of the decomposition of the scattering components of the SAR data.
Further, f (1-m) ═ 1-mnAnd n is a real number greater than 1.
Further, n ranges from (1, 3).
Further, n is 2.
Further, invoking an improved m-alpha algorithm to decompose scattering components of the acquired SAR data, including:
calculating the power value of each scattering component of the obtained SAR data according to the following formula:
PV＝k1×g0×f(1-m)
PS＝k2×g0(1-f(1-m))cos2(α)
PD＝k3×g0(1-f(1-m))sin2(α)
Figure BDA0003488030360000021
wherein:
Figure BDA0003488030360000022
Figure BDA0003488030360000031
g0、g1、g2and g34 real variables respectively representing the acquired SAR data Stokes vectors; pVRepresents the value of the bulk scattering power, PSRepresents the surface scattering power value, PDRepresents a value of a secondary scattering power,
Figure BDA0003488030360000032
Represents the phase; alpha is a parameter for marking the ratio of the scattering power and the secondary scattering power of the surface; arg (-) denotes the phase, sign of the complex number
Figure BDA0003488030360000033
And the plus or minus symbol corresponds to the CTLR compact polarization SAR data condition of left-hand circular polarization transmission, and the lower symbol corresponds to the CTLR compact polarization SAR data condition of right-hand circular polarization transmission; adjustment coefficient k1、k2、k3Are all greater than 1.
Further, the method further comprises:
acquiring a scattering component decomposition result of real SAR data;
and comparing the stored scattering component decomposition result of the SAR data with the scattering component decomposition result of the real SAR data.
Further, acquiring the CTLR compact polarization SAR data comprises: acquiring full polarization SAR data, and generating CTLR compact polarization SAR data in a simulation mode;
obtaining a scattering component decomposition result of real SAR data, comprising: and calling a complete polarization decomposition algorithm, decomposing the scattering components of the acquired complete polarization SAR data, and taking the decomposition result as the scattering component decomposition result of the real SAR data.
In a second aspect, an embodiment of the present invention provides a CTLR compact polarization SAR data scattering component decomposition apparatus, including:
the acquisition unit is used for acquiring the circularly polarized transmitting horizontal and vertical polarized receiving CTLR compact polarized SAR data;
the decomposition unit is used for calling an improved m-alpha algorithm, and decomposing scattering components of the acquired SAR data, wherein the volume scattering power ratio in the decomposition result is f (1-m), and the surface scattering power ratio and the secondary scattering power ratio in the decomposition result is 1-f (1-m), wherein f (1-m) < (1-m), m is the polarization degree which is greater than 0 and less than 1, and f (1-m) has a first extreme value 1 at the position where 1-m is equal to 1 and a second extreme value 0 at the position where 1-m is equal to 0;
and the storage unit is used for storing the scattering component decomposition result of the SAR data.
Further, the decomposing unit is configured to invoke an improved m- α algorithm to decompose the scattering component of the acquired SAR data, and includes:
calculating the power value of each scattering component of the obtained SAR data according to the following formula:
PV＝k1×g0×f(1-m)
PS＝k2×g0(1-f(1-m))cos2(α)
PD＝k3×g0(1-f(1-m))sin2(α)
Figure BDA0003488030360000041
wherein:
Figure BDA0003488030360000042
Figure BDA0003488030360000043
g0、g1、g2and g34 real variables respectively representing the acquired SAR data Stokes vectors; pVRepresents the value of the bulk scattering power, PSRepresents the surface scattering power value, PDRepresents a value of a secondary scattering power,
Figure BDA0003488030360000044
Represents the phase; alpha is a parameter for marking the ratio of the scattering power and the secondary scattering power of the surface; arg (-) denotes the phase, sign of the complex number
Figure BDA0003488030360000045
And the plus or minus symbols in the upper part correspond to the situation of CTLR compact polarization SAR data of left-hand circular polarization transmission, and the symbols in the lower part correspond to the CTLR compact polarization SAR data of right-hand circular polarization transmission; adjustment coefficient k1、k2、k3Are all greater than 1.
Further, the acquiring unit is further configured to acquire a scattering component decomposition result of the real SAR data;
the device further comprises: and the comparison unit is used for comparing the proximity degree of the scattering component decomposition result of the SAR data stored in the storage unit and the scattering component decomposition result of the real SAR data acquired by the acquisition unit.
Further, the acquiring unit is used for acquiring CTLR compact polarization SAR data, and includes: acquiring full polarization SAR data, and generating CTLR compact polarization SAR data in a simulation mode;
the acquisition unit is used for acquiring a scattering component decomposition result of real SAR data, and comprises: and calling a complete polarization decomposition algorithm, decomposing the scattering components of the acquired complete polarization SAR data, and taking the decomposition result as the scattering component decomposition result of the real SAR data.
In a third aspect, an embodiment of the present invention provides an electronic device, where the electronic device includes: the device comprises a shell, a processor, a memory, a circuit board and a power circuit, wherein the circuit board is arranged in a space enclosed by the shell, and the processor and the memory are arranged on the circuit board; a power supply circuit for supplying power to each circuit or device of the electronic apparatus; the memory is used for storing executable program codes; the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, for executing the aforementioned CTLR packed polarization SAR data scattering component decomposition method.
In a fourth aspect, embodiments of the present invention provide a computer-readable storage medium storing one or more programs, which are executable by one or more central processing units to implement the aforementioned CTLR packed polarization SAR data scattering component decomposition method.
The technical scheme provided by the embodiment of the invention adopts a novel method for reducing the volume scattering power ratio, and the method does not use a single fixed coefficient, but uses a function related to the polarization degree m value to dynamically adjust the reduction ratio, thereby having good scattering component decomposition performance.
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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 drawings without creative efforts.
FIG. 1 is a flow chart of a scattering component decomposition method for CTLR compact polarization SAR data according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing typical region selection of Bolnuer experimental data of a Chinese GF-3 satellite;
FIG. 3 is a schematic drawing showing a typical region selection of experimental data of the Indian RISAT satellite san Francisco;
fig. 4 is a schematic structural diagram of a scattering component decomposition apparatus for CTLR compact polarization SAR data according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention are described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiments of the present invention provide a CTLR compact polarization SAR data scattering component decomposition method, which may be performed by a corresponding CTLR compact polarization SAR data scattering component decomposition apparatus, which may be integrated in an electronic device deployed with data interaction and data processing functions. Referring to fig. 1, the method specifically comprises the following steps 101-103.
Step 101, acquiring CTLR compact polarization SAR data.
And step 102, calling an improved m-alpha algorithm, and decomposing scattering components of the acquired CTLR compact polarization SAR data.
A number of experiments have shown that decomposing the CTLR compact polarimetric SAR data using the existing m-alpha algorithm yields a bulk scattering power fraction that is too high for 1-m, and therefore is preferably less than 1-m if a new, more reasonable bulk scattering power fraction is sought. In the embodiment of the invention, the new volume scattering power ratio is a function related to 1-m, namely f (1-m). f (1-m) < (1-m), wherein m is a polarizability of more than 0 and less than 1. The function f (1-m) was found by analysis to have two extreme values:
the first extreme corresponds to the case where the feature contains only volume scattering, i.e., 1-m-1, in which case it is reasonable to assume that f (1-m) is 1:
the second extreme corresponds to the case where the feature contains only completely coherent scattering, where the token vector of the CTLR compact polarimetric SAR data Stokes is completely polarized, i.e., 1-m is 0, and it is reasonable to assume that f (1-m) is 0 in this case.
Meanwhile, a large number of experiments also show that for the multi-view total polarization scattering of actual ground objects, in addition to the depolarization partial power of the Stokes vector of CTLR compact polarization SAR data generated by the body scattering component, the sum of the rest 2 above surface scattering or secondary scattering components also generates the depolarization power of a part of Stokes vector. The magnitude of the second part depolarization power is related to the magnitudes of the surface scattering power and the secondary scattering power, and because the ratio of the surface scattering power to the secondary scattering power in the total power of the Stokes vector is m, it is reasonable to assume that the ratio of the second part depolarization power in the total depolarization power is m; a direct corollary of this assumption is that the proportion of the depolarization fraction power corresponding to volume scattering to the total depolarization power is 1-m. The ratio of the two depolarized partial powers corresponds exactly to the new volumetric scatter component power fraction f (1-m). The new volume scattering component power ratio f (1-m) is practically equivalent to dividing the Stokes vector depolarization part power ratio 1-m into two parts, f (1-m) and 1-m-f (1-m). The first part corresponds to the volume scattering component, and the second part corresponds to the depolarization power caused by the sum of more than 2 surface scattering or secondary scattering components, so that the power of the depolarization power is divided according to the surface scattering and secondary scattering power ratios determined by alpha parameters.
In specific implementation, an improved m-alpha algorithm is called to decompose scattering components of the acquired CTLR compact polarization SAR data, and the method comprises the following steps:
calculating the power value of each scattering component of the obtained CTLR compact polarization SAR data according to the following formula:
PV＝k1×g0×f(1-m)
PS＝k2×g0(1-f(1-m))cos2(α)
PD＝k3×g0(1-f(1-m))sin2(α)
Figure BDA0003488030360000071
wherein:
Figure BDA0003488030360000072
Figure BDA0003488030360000073
g0、g1、g2and g34 real variables respectively representing the acquired said SAR data Stokes vectors, the 4 real variables being the basic representation of the compact polarization data, the physical meaning of which is well known to the person skilled in the art; pVRepresents the value of the bulk scattering power, PSRepresents the surface scattering power value, PDRepresents a value of a secondary scattering power,
Figure BDA0003488030360000074
Represents a phase; alpha is a parameter for marking the ratio of the scattering power and the secondary scattering power of the surface; arg (-) denotes the phase, sign of the complex number
Figure BDA0003488030360000075
And the plus or minus symbols correspond to the situation of CTLR compact polarization SAR data transmitted by left-hand circular polarization, and the symbols below correspond to the situation of CTLR compact polarization SAR data transmitted by right-hand circular polarization; adjusting the coefficient k1、k2、k3Are all larger than 1, so that the corresponding scattering component power values are close to the real values in absolute magnitude. Therein, with respect to symbols
Figure BDA0003488030360000076
And "±", may be specifically understood as: symbol
Figure BDA0003488030360000077
The negative sign of the middle upper part corresponds to the CTLR compact polarization SAR data condition of left-hand circular polarization transmission, and the positive sign of the lower part corresponds to the CTLR compact polarization SAR data condition of right-hand circular polarization transmission; the positive sign in the plus or minus sign corresponds to the case of the CTLR compact polarization SAR data for left-hand circular polarization transmission, and the negative sign in the lower sign corresponds to the case of the CTLR compact polarization SAR data for right-hand circular polarization transmission.
Further, based on the above 2 extreme values, two end points of the [1-m, f (1-m) ] curve can be determined as [0,0] and [1,1 ]. Therefore, the embodiment of the present invention may set the specific form of f (1-m) as follows:
f(1-m)＝(1-m)n
where n is a real number. Since f (1-m) needs to be less than 1-m, n needs to be greater than 1. It has been found through a lot of experiments that if n is greater than 3, the volume scattering power ratio in the decomposition result is too low, and thus it can be confirmed that the reasonable value range of n is (1, 3). Typically, in the present embodiment, n is 2, i.e. the new volume scattering power ratio is (1-m)2Verified (1-m)2Is still [0, 1]]And which is always less than 1-m. When n is 2, the adjustment coefficient k in the above formula1、k2、k3Are all equal to 2.
The improved m-alpha algorithm has an important attribute: and no polarization information is lost in the decomposition process, and the output of the decomposition process can completely reconstruct the input. For example, when f (1-m) ═ 1-m2And adjust the coefficient k1、k2、k3When the average value is 2, the output of the decomposition result can be completely calculated and recovered according to the following formula to obtain 4 real variables g of the Stokes vector of the CTLR compact polarization SAR data0、g1、g2And g3Polarization m and parameter α:
g0＝(PV+PS+PD)/2
Figure BDA0003488030360000081
Figure BDA0003488030360000082
g1＝mg0 sin2αcosφ
Figure BDA0003488030360000083
g3＝±mg0 cos2α
the existing m- α decomposition algorithm is as follows:
PV＝(1-m)g0
PS＝mg0cos2(α)
PD＝mg0 sin2(α)
Figure BDA0003488030360000084
the improved m-alpha decomposition algorithm in the embodiment of the invention has 3 improvement points. Firstly, the most significant improvement is that the volume scattering power in the decomposition result is changed to a function f (1-m) smaller than 1-m decomposed from the original m-alpha; then the corresponding surface scattering and secondary scattering power sum ratio is changed from 1- (1-m) ═ m to 1-f (1-m); finally, the improved m-alpha algorithm multiplies all the scattered component powers by an adjusting coefficient, so that the decomposition result is comparable to the full polarization data decomposition result in absolute magnitude.
And 103, storing the scattering component decomposition result of the CTLR compact polarization SAR data.
On the basis of the above scheme, the scattering component decomposition method for the CTLR compact polarization SAR data provided by the embodiment of the present invention further includes the following steps:
acquiring a scattering component decomposition result of real SAR data;
and comparing the stored scattering component decomposition result of the CTLR compact polarization SAR data with the scattering component decomposition result of the real SAR data.
By comparing the result of the decomposition of the scattering component of the obtained CTLR compact polarization SAR data by using the improved m-alpha algorithm with the real decomposition result, the accuracy of the improved m-alpha algorithm can be obtained, the closer the two decomposition results are, the better the compact polarization decomposition performance is, otherwise, the larger the difference between the two decomposition results is, the worse the compact polarization decomposition performance is, and when the difference exceeds the preset threshold, the specific form of f (1-m) can be adjusted or the adjustment can be modified according to the compared closeness degreeCoefficient k1、k2And k3。
Illustratively, the acquiring CTLR compact polarization SAR data in step 101 includes: acquiring full polarization SAR data, and generating CTLR compact polarization SAR data in a simulation mode;
accordingly, obtaining a scattering component decomposition result of the real SAR data comprises: and calling a complete polarization decomposition algorithm, decomposing the scattering components of the acquired complete polarization SAR data, and taking the decomposition result as the scattering component decomposition result of the real SAR data.
In the following, the modified m- α algorithm is exemplified by the following calculation formula:
PV＝2g0(1-m)2
PS＝2g0(1-(1-m)2)cos2(α)
PD＝2g0(1-(1-m)2)sin2(α)
Figure BDA0003488030360000091
Figure BDA0003488030360000092
Figure BDA0003488030360000093
the specific implementation method and implementation effect of the improved m-alpha algorithm of the embodiment of the invention are described in detail by combining two specific examples, and experiments prove that the improved m-alpha algorithm has advantages in SAR data scattering component decomposition performance compared with other existing compact polarization decomposition algorithms.
Example 1
The experimental data used in this example are C-band full polarization data obtained by observing the russian barnaer city area and its peripheral region with a chinese high-resolution third satellite (GF-3) of 5 months and 5 days in 2018. The reason why the full polarization data are used is that various compact polarization data can be generated through simulation based on the full polarization data so as to carry out a compact polarization decomposition experiment, and meanwhile, the true value of the power ratio of each scattering component of the ground object can be obtained based on the full polarization data and a full polarization decomposition algorithm, so that a basis is provided for judging the quality of each compact polarization decomposition result. The closer the power ratio of each scattering component in the compact polarization decomposition result is to that of each scattering component in the full polarization decomposition result, the better the compact polarization decomposition performance is, and otherwise, the performance is worse.
The specific experimental procedure is as follows.
(1) Simulation generation of CTLR packed polarization data from GF-3 fully polarized data
After the full polarization scattering matrix data is changed into polarization coherent matrix data through space multi-view and polarization filtering, the method for generating the multi-view CTLR compact polarization data by the polarization coherent matrix is shown as the following formula:
Figure BDA0003488030360000101
wherein t isijTo polarize the elements of the coherence matrix T, the following is specific
Figure BDA0003488030360000102
A large number of example experiments show that the experimental results of the left-hand circular polarization transmission and the right-hand circular polarization transmission are very similar, so that only the experimental results of the right-hand circular polarization transmission are shown later.
(2) Multi-algorithm compact polarization decomposition
The multi-view CTLR compact polarization data obtained by simulation is respectively processed by using three algorithms of original m-alpha algorithm decomposition, Wang algorithm decomposition and improved m-alpha decomposition of the embodiment of the invention to obtain respective decomposition results. Wang et al teach a decomposition algorithm (called the Wang algorithm) to reduce the volume-scattered power fraction to 0.65 (1-m).
(3) Full polarization decomposition
The fully polarized data is decomposed and processed by using a classical Freeman-Durden algorithm, and the decomposition result can be considered as a true power value of each scattering component of the ground object.
(4) Comparing and analyzing the four decomposition experimental results
In order to analyze and compare results more quantitatively, three typical ground features, namely a bare land, a forest and an urban area, are selected from an experimental area, and are specifically shown as A, B, C white rectangular boxes in fig. 2; then, the average of the ratios of the respective scattering powers of all the pixels in the rectangular frame is calculated, and the result is shown in table 1. The area A results in the table 1 have the highest surface scattering power ratio, wherein the surface scattering power ratio decomposed by the original m-alpha algorithm is obviously lower than that of the other algorithm results, and the surface scattering power ratio decomposed by the improved m-alpha algorithm is the highest, and the decomposition result of the improved m-alpha algorithm is relatively optimal considering that a bare ground is mainly a surface scattering mechanism. The volume scattering power of the B region in the table 1 is the highest, which is consistent with the physical reality that the forest region is mainly based on the volume scattering mechanism; wherein the volume scattering power of the improved m-alpha algorithm decomposition is slightly less than the result very close to the Freeman-Durden algorithm decomposition, and the improved m-alpha algorithm decomposition has the optimal result in consideration of the problem that the Freeman-Durden algorithm decomposition has overestimated volume scattering; the volume scattering power ratio decomposed by the original m-alpha algorithm is even higher than that decomposed by the Freeman-Durden algorithm, so that the original m-alpha algorithm is proved to have a more serious overestimation volume scattering problem; the volume scattering power ratio decomposed by the Wang algorithm is obviously lower than that of other decomposition algorithms, and the poor result is unacceptable, which proves that the forest region volume scattering estimation is low by using the fixed coefficient of 0.65. The secondary scattering percentage of the C region in the table 1 is the highest, which is consistent with the physical reality that more secondary scattering should exist in urban areas; both the improved m-alpha decomposition and the Wang decomposition have results that are relatively close to those of the Freeman-Durden decomposition, while the results of the original m-alpha decomposition are significantly lower than those of the other decomposition algorithms.
In summary, the following conclusions can be obtained by the scattering power ratio quantitative analysis: 1) the ratio of the surface scattering power and the ratio of the secondary scattering power decomposed by the original m-alpha algorithm are obviously weaker than the full polarization decomposition result, and the ratio of the bulk scattering power is too high. 2) The Wang algorithm decomposition has the problem that the forest region volume scattering power ratio estimation is low. 3) The performance of the improved m-alpha algorithm decomposition is obviously better than that of the original m-alpha algorithm decomposition and Wang algorithm decomposition, and the result is very close to that of Freeman-Durden algorithm decomposition.
TABLE 1
Mean value of ratio of scattering component powers of three typical ground object regions in GF-3 satellite Balnagel experimental data
Figure BDA0003488030360000111
Figure BDA0003488030360000121
Wherein Span is PS+PD+PV。
Example two
The experimental data used in this example are the CTLR compact polarization data of the actual right-hand circularly polarized transmission obtained from 2016, 8, 9 th day indian ristat satellite on observations of the city of san francisco, usa at an angle of incidence of 38.2 °. After the data is subjected to spatial multi-view, the obtained multi-view Stokes vector image comprises 1384 multiplied by 1089 pixel points.
Respectively applying the original m-alpha algorithm decomposition, the Wang algorithm decomposition and the improved m-alpha algorithm decomposition of the embodiment of the invention to the multi-vision compact polarization data,
selecting three typical ground objects of oceans, forests and urban areas from the experimental area, wherein the three typical ground objects are specifically shown as D, E, F white rectangular boxes in FIG. 3; then, the average of the ratios of the respective scattering powers of all the pixels in the rectangular frame is calculated, and the result is shown in table 2. Because the fully polarized data of the current view RISAT data is unknown, the fully polarized decomposition algorithm can not be used, namely the true value of each scattering power ratio of each typical object region can not be known, so that the following analysis is only carried out. As shown in table 2, the ocean in region D is mainly surface scattering, the improved m- α algorithm decomposes the result with the highest surface scattering power ratio, and the performance is relatively optimal; the forest of the region E is mainly subjected to volume scattering, the volume scattering power of Wang algorithm decomposition is the lowest, and the original m-alpha decomposition result is higher; the urban region F is mainly based on secondary scattering, the secondary scattering power ratio of the improved m-alpha decomposition is obviously superior to that of the original m-alpha decomposition, but is slightly lower than that of the Wang algorithm decomposition, but the volume scattering power ratio of the Wang algorithm decomposition is obviously higher than that of the improved m-alpha algorithm decomposition, and the performance of the improved m-alpha decomposition and the improved m-alpha decomposition are similar in comprehensive view.
In conclusion, through the scattering component power ratio quantitative analysis, the conclusion is consistent with the simulation experiment using the full polarization data, namely the performance of improving the m-alpha algorithm decomposition is relatively optimal.
TABLE 2
Mean value of ratio of scattered component powers of three typical ground object areas in RISAT satellite san Francisco data
Figure BDA0003488030360000131
Wherein Span is PS+PD+PV。
Correspondingly, the embodiment of the invention also provides a CTLR compact polarization SAR data scattering component decomposition device which can be realized by software and/or hardware. Referring to fig. 4, the apparatus includes:
an obtaining unit 401, configured to obtain circular polarization transmitting horizontal and vertical polarization receiving CTLR compact polarization SAR data;
a decomposition unit 402, configured to invoke an improved m- α algorithm, and perform decomposition on a scattering component of the acquired SAR data, where a volume scattering power ratio in a decomposition result is f (1-m), and a surface scattering and secondary scattering power ratio in the decomposition result is 1-f (1-m), where f (1-m) < (1-m), m is a polarization degree greater than 0 and less than 1, and f (1-m) has a first extreme value 1 at a position where 1-m is equal to 1 and a second extreme value 0 at a position where 1-m is equal to 0;
a storage unit 403, configured to store a result of decomposition of the scattering component of the SAR data.
Further, f (1-m) ═ 1-mnAnd n is a real number greater than 1.
Further, n ranges from (1, 3).
Further, n is 2.
Further, the decomposition unit 402 is configured to invoke an improved m- α algorithm to decompose the scattering component of the acquired SAR data, including:
calculating the power value of each scattering component of the obtained SAR data according to the following formula:
PV＝k1×g0×f(1-m)
PS＝k2×g0(1-f(1-m))cos2(α)
PD＝k3×g0(1-f(1-m))sin2(α)
Figure BDA0003488030360000141
wherein:
Figure BDA0003488030360000142
Figure BDA0003488030360000143
g0、g1、g2and g34 real variables respectively representing the acquired SAR data Stokes vectors; pVRepresents the value of the bulk scattering power, PSRepresents the surface scattering power value, PDRepresents a value of a secondary scattering power,
Figure BDA0003488030360000144
Represents the phase; alpha is a parameter for marking the ratio of the scattering power and the secondary scattering power of the surface; arg (-) denotes the phase, sign of the complex number
Figure BDA0003488030360000145
And the plus or minus symbol corresponds to the CTLR compact polarization SAR data condition of left-hand circular polarization transmission, and the lower symbol corresponds to the CTLR compact polarization SAR data condition of right-hand circular polarization transmission; adjustment coefficient k1、k2、k3Are all greater than 1.
Further, the obtaining unit 401 is further configured to obtain a scattering component decomposition result of the real SAR data;
the scattering component decomposition device for the CTLR compact polarization SAR data provided by the embodiment of the invention further comprises:
a comparing unit 404, configured to compare the proximity of the scattering component decomposition result of the SAR data stored in the storage unit with the scattering component decomposition result of the real SAR data acquired by the acquiring unit.
Further, the obtaining unit 401 is configured to obtain CTLR compact polarization SAR data, and includes:
acquiring full polarization SAR data, and generating CTLR compact polarization SAR data in a simulation mode;
the obtaining unit 401 is configured to obtain a scattering component decomposition result of the real SAR data, and includes:
and calling a complete polarization decomposition algorithm, decomposing the scattering components of the acquired complete polarization SAR data, and taking the decomposition result as the scattering component decomposition result of the real SAR data.
The CTLR compact polarization SAR data scattering component decomposition device provided in this embodiment and the aforementioned embodiment of the CTLR compact polarization SAR data scattering component decomposition method belong to the same inventive concept, and the technical details that are not described in this embodiment may refer to the related description in the aforementioned embodiment of the method, and are not described herein again.
In addition, the embodiment of the invention also provides the electronic equipment. Fig. 5 is a schematic structural diagram of an embodiment of an electronic device of the present invention, which can implement the process of the embodiment shown in fig. 1 of the present invention, and as shown in fig. 5, the electronic device may include: the device comprises a shell 51, a processor 52, a memory 53, a circuit board 54 and a power circuit 55, wherein the circuit board 54 is arranged inside a space enclosed by the shell 51, and the processor 52 and the memory 53 are arranged on the circuit board 54; a power supply circuit 55 for supplying power to each circuit or device of the electronic apparatus; the memory 53 is used to store executable program code; the processor 52 executes a program corresponding to the executable program code by reading the executable program code stored in the memory 53, for executing the method for scattering component decomposition of CTLR compact polarization SAR data as described in any of the embodiments.
The specific execution process of the above steps by the processor 52 and the steps further executed by the processor 52 by running the executable program code may refer to the description of the embodiment shown in fig. 1 of the present invention, and are not described herein again.
The electronic device may exist in a variety of forms, including but not limited to:
(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications; such terminals include: smart phones (e.g., iphones), multimedia phones, functional phones, and low-end phones, etc.;
(2) ultra mobile personal computer device: the equipment belongs to the category of personal computers, has the functions of calculation and processing, and generally has the characteristic of mobile internet access; such terminals include: PDA, MID, and UMPC devices, etc., such as iPad;
(3) a portable entertainment device: such devices can display and play multimedia content; this kind of equipment includes: audio, video players (e.g., ipods), handheld game consoles, electronic books, and smart toys and portable car navigation devices;
(4) a server: the device for providing the computing service, the server comprises a processor, a hard disk, a memory, a system bus and the like, the server is similar to a general computer architecture, but the server needs to provide highly reliable service, so the requirements on processing capacity, stability, reliability, safety, expandability, manageability and the like are high;
(5) other electronic devices with data interaction and processing functions.
Furthermore, an embodiment of the present invention also provides a computer-readable storage medium storing one or more programs, which are executable by one or more central processing units to implement the method for scattering component decomposition of CTLR packed polarization SAR data according to the foregoing embodiment.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The term "and/or" in the embodiments of the present invention describes an association relationship of associated objects, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments.
In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
For convenience of description, the above devices are described separately in terms of functional division into various units/modules. Of course, the functionality of the various units/modules may be implemented in the same software and/or hardware in the implementation of the invention.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. A method of CTLR compact polarimetric SAR data scatter component decomposition, the method comprising:
acquiring circularly polarized transmitting horizontal and vertical polarized receiving CTLR compact polarized SAR data;
calling an improved m-alpha algorithm, and decomposing scattering components of the acquired SAR data, wherein the volume scattering power ratio in the decomposition result is f (1-m), and the surface scattering and secondary scattering power ratio is 1-f (1-m), wherein f (1-m) < (1-m), m is the polarization degree which is greater than 0 and less than 1, f (1-m) has a first extreme value 1 at the position where 1-m is equal to 1, and has a second extreme value 0 at the position where 1-m is equal to 0;
storing a result of the decomposition of the scattering components of the SAR data.
2. The method of claim 1, wherein f (1-m) ═ 1-mnAnd n is a real number greater than 1.
3. The method of claim 2, wherein n ranges from (1, 3).
4. The method of claim 3, wherein n is 2.
5. The method of claim 1, wherein invoking the modified m- α algorithm to decompose the scattering component of the obtained SAR data comprises:
calculating the power value of each scattering component of the obtained SAR data according to the following formula:
PV＝k1×g0×f(1-m)
PS＝k2×g0(1-f(1-m))cos2(α)
PD＝k3×g0(1-f(1-m))sin2(α)
Figure FDA0003488030350000011
wherein:
Figure FDA0003488030350000012
Figure FDA0003488030350000013
g0、g1、g2and g34 real variables respectively representing Stokes vectors (Stokes) vectors of the acquired SAR data; pVRepresents the value of the bulk scattering power, PSRepresents the surface scattering power value, PDRepresents a value of a secondary scattering power,
Figure FDA0003488030350000014
Represents the phase; alpha is a parameter for marking the ratio of the scattering power and the secondary scattering power of the surface; arg (-) denotes the phase, sign of the complex number
Figure FDA0003488030350000015
And the plus or minus symbol corresponds to the CTLR compact polarization SAR data condition of left-hand circular polarization transmission, and the lower symbol corresponds to the CTLR compact polarization SAR data condition of right-hand circular polarization transmission; adjustment coefficient k1、k2、k3Are all greater than 1.
6. Method according to claim 5, characterized in that the adjustment coefficient k is1、k2、k3Are all equal to 2.
7. The method of claim 1, further comprising:
acquiring a scattering component decomposition result of real SAR data;
and comparing the stored scattering component decomposition result of the SAR data with the scattering component decomposition result of the real SAR data.
8. The method of claim 7, wherein obtaining the CTLR compact polarization SAR data comprises: acquiring full polarization SAR data, and generating CTLR compact polarization SAR data in a simulation mode;
obtaining a scattering component decomposition result of real SAR data, comprising: and calling a complete polarization decomposition algorithm, decomposing the scattering components of the acquired complete polarization SAR data, and taking the decomposition result as the scattering component decomposition result of the real SAR data.
9. A CTLR compact polarimetric SAR data scatter component decomposition apparatus, comprising:
the acquisition unit is used for acquiring circularly polarized transmitting horizontal and vertical polarized receiving CTLR compact polarized SAR data;
the decomposition unit is used for calling an improved m-alpha algorithm, and decomposing scattering components of the acquired SAR data, wherein the volume scattering power ratio in the decomposition result is f (1-m), and the surface scattering power ratio and the secondary scattering power ratio in the decomposition result is 1-f (1-m), wherein f (1-m) < (1-m), m is the polarization degree which is greater than 0 and less than 1, and f (1-m) has a first extreme value 1 at the position where 1-m is equal to 1 and a second extreme value 0 at the position where 1-m is equal to 0;
and the storage unit is used for storing the scattering component decomposition result of the SAR data.
10. An electronic device, characterized in that the electronic device comprises: the device comprises a shell, a processor, a memory, a circuit board and a power circuit, wherein the circuit board is arranged in a space enclosed by the shell, and the processor and the memory are arranged on the circuit board; a power supply circuit for supplying power to each circuit or device of the electronic apparatus; the memory is used for storing executable program codes; the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, for performing the method of any of the preceding claims 1-8.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116797845A (en) * 2023-07-05 2023-09-22 中国科学院空天信息创新研究院 Unsupervised reduced polarization classification method based on scattering mechanism
CN117034559A (en) * 2023-07-07 2023-11-10 中国自然资源航空物探遥感中心 CTLR simplified polarization interference synthetic aperture radar decomposition method

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116797845A (en) * 2023-07-05 2023-09-22 中国科学院空天信息创新研究院 Unsupervised reduced polarization classification method based on scattering mechanism
CN116797845B (en) * 2023-07-05 2024-01-26 中国科学院空天信息创新研究院 Unsupervised reduced polarization classification method based on scattering mechanism
CN117034559A (en) * 2023-07-07 2023-11-10 中国自然资源航空物探遥感中心 CTLR simplified polarization interference synthetic aperture radar decomposition method

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