CN115718284A - Common polarization channel unbalance calibration method based on circular polarization reflection symmetry - Google Patents
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Abstract
The invention discloses a circular polarization reflection symmetry-based common polarization channel unbalance calibration method, which comprises the following steps of: step 1: selecting a volume scattering dominant region and a surface scattering dominant region based on circular polarization SAR data with undetermined crosstalk and channel unbalance; and 2, step: carrying out block processing on the unmarked circularly polarized data along the azimuth direction and the distance direction; and step 3: solving the cross polarization channel imbalance based on the reciprocity of the surface scattering dominant region; and 4, step 4: selecting a scattering symmetry condition with higher priority under a body scattering leading region of the circularly polarized scattering matrix only with crosstalk; and 5: preliminarily solving the unbalanced result of the common polarization channel and calibrating data by synthesizing the reflection symmetry condition with higher priority; step 6: and solving polarization POA for the circularly polarized data, then correlating with DEMOA, and determining a correct unbalanced phase of the co-polarized channel to obtain a final calibration parameter.
Description
Technical Field
The invention belongs to the field of radar detection, and particularly relates to a circular polarization reflection symmetry-based common polarization channel imbalance calibration method.
Background
A circular polarization Synthetic Aperture Radar (SAR) is an active microwave remote sensing device, can acquire various polarization scattering characteristics of a ground object, provides various choices for different polarization applications, and is widely and effectively applied to the aspects of ground object classification, crop growth detection, sea ice detection, geological disaster analysis and the like.
Due to the influence of the system, the environmental temperature and the like, the difference exists between the electromagnetic waves transmitted and received by the circularly polarized SAR and the ideal state, so that the relative relation between all channels of polarized data has distortion, and the distortion is mainly reflected in the imbalance of the co-polarized channel and the cross-polarized channel, crosstalk and the like. In a practical circular polarization system, there are two main transmission modes, namely, the amplifier of the system is placed before and after the switch for controlling the transmission of signals with different polarizations. The main purpose of the pre-switch mode is to minimize the channel imbalance of the system; the main purpose of the mode after switching is to minimize crosstalk of the system. The present invention mainly analyzes the second mode, which can be considered as a mode with a small crosstalk level, and the channel imbalance is a distortion parameter that mainly needs to be corrected.
Polarization scaling is mainly based on the ground object target with known scattering properties, estimating polarization distortion parameters and correcting the system to an acceptable level. At present, the calibration by using a corner reflector is the most accurate calibration mode of the circularly polarized SAR. Since the arrangement of the corner reflectors is time consuming and laborious and requires different corner reflector sizes at multiple frequencies, a distributed target may be used to determine channel imbalance in order to reduce the use of corner reflectors. Further, in order to suppress the influence of additive noise on solving the imbalance of the channel, the circular polarization SAR scaling generally solves the imbalance of the common polarization channel by using a volume scattering dominant region satisfying reflection symmetry; and solving the cross polarization channel imbalance by using the surface scattering dominant region meeting the reciprocity. However, for areas where scattering is more complex, such as forest areas with lower distribution density, urban areas, and the like, the condition that the average polarization azimuth angle is 0 in the reflection symmetry condition may not be satisfied in the linear polarization basis. Therefore, the reflection symmetry represented by the linear polarization base may not be satisfied by converting the reflection symmetry represented by the circular polarization base into the reflection symmetry represented by the circular polarization base, so that a larger error may exist in solving the common polarization channel imbalance by using the reflection symmetry of the circular polarization base. In order to solve the common polarization channel imbalance finely and eliminate the calibration error caused by improper use of the reflection symmetry condition, it is urgently needed to screen out the preferential reflection symmetry condition in the bulk scattering dominant region and research the corresponding calibration algorithm to solve the common polarization channel imbalance accurately based on the screened condition.
Disclosure of Invention
In view of the above, the present invention provides a method for calibrating imbalance of common polarization channel based on circularly polarized reflection symmetry, which can solve the problem of poor calibration accuracy of imbalance of common polarization channel due to partial reflection symmetry not being satisfied in the bulk scattering dominant region.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a common polarization channel unbalance calibration method based on circular polarization reflection symmetry comprises the following steps:
step 1: selecting a body scattering dominant region and a surface scattering dominant region based on circular polarization SAR data with uncertain crosstalk and channel unbalance;
and 2, step: carrying out block processing on the uncalibrated circularly polarized SAR data along the azimuth direction and the distance direction;
and 3, step 3: solving the cross polarization channel imbalance based on the reciprocity of the surface scattering dominant region;
and 4, step 4: selecting a scattering symmetry condition with higher priority under a body scattering leading region of a circularly polarized base only with crosstalk;
and 5: preliminarily solving the unbalanced result of the common polarization channel and calibrating data by synthesizing the scattering symmetry condition with higher priority;
step 6: and solving a polarization direction angle of the circularly polarized data, then correlating the circularly polarized data with the direction angle obtained by the digital elevation model, and determining a correct unbalanced phase of the co-polarized channel to obtain a final calibration parameter.
Further, in the step 2,
partitioning the SAR image along the distance direction, so as to respectively solve the polarization distortion; and the SAR image is simultaneously blocked along the azimuth direction, and the polarization distortion values solved by different azimuth directions are used for mutual correction.
Further, in the step 3,
determining the imbalance of the cross polarization channel based on the reciprocity of the surface scattering dominant region, and removing the influence caused by the imbalance of the cross polarization channel when the imbalance of the common polarization channel is solved subsequently.
Further, in the step 4, the step of,
and solving a reflection symmetry condition in the circularly polarized SAR data of the volume scattering dominant region and determining the priority of the reflection symmetry condition so as to eliminate errors caused by using all the reflection symmetry conditions in actual data.
Further, in the step 5,
and (4) obtaining a reflection symmetry condition with higher priority based on the step (4), preliminarily solving unbalanced amplitude and phase of the common polarization channel, and preliminarily calibrating the data.
Has the beneficial effects that:
the invention uses reciprocity to determine cross-polarization channel imbalance primarily in surface-scattering dominated regions and higher priority reflection symmetry in bulk-scattering dominated regions for scaling co-polarization channel imbalance. Because the partial reflection symmetry condition may not be satisfied in the bulk scattering region, the method has the advantages that the reflection symmetry condition with higher priority is selected and a corresponding algorithm is developed to carry out calibration on the imbalance of the co-polarized channel in the bulk scattering dominant region, so that the calibration error of the imbalance of the co-polarized channel caused by improper use of the reflection symmetry condition is eliminated.
Drawings
FIG. 1 is a reflection symmetry priority comparison of a bulk scattering dominated region; wherein, the graph (a) is the 1 st, 3 rd and 4 th conditional histograms of the reflection symmetry of the circular polarization SAR in the volume scattering, the graph (b) is the percentage graph of the 1 st, 3 rd and 4 th conditions of the reflection symmetry of the circular polarization SAR in the volume scattering being less than 0.05, and the graph (c) is the 2 nd conditional histogram of the reflection symmetry of the circular polarization SAR in the volume scattering;
FIG. 2 is a flow chart of a co-polarization channel imbalance calibration method based on circularly polarized reflection symmetry;
FIG. 3 is a data diagram of the vicinity of an L-band gateway; wherein, the graph (a) is Pauli image of circularly polarized data, the graph (b) is Pauli image after distortion is added, the graph (c) is equivalent view diagram, and the graph (d) is R vb Drawing;
fig. 4 shows the result of solving for the unbalanced amplitude and phase of the co-polarized channel using the proposed algorithm.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying 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, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.
The common polarization channel unbalance calibration method based on circular polarization reflection symmetry comprises the following steps:
firstly, selecting a body scattering dominant region and a surface scattering dominant region based on circular polarization SAR data with undetermined crosstalk and channel unbalance; then, block processing is carried out on the circularly polarized data which are not calibrated along the azimuth direction and the distance direction; solving the imbalance of the cross polarization channel through the reciprocity of the surface scattering leading region, and then calibrating the imbalance of the cross polarization channel on the data; selecting scattering symmetry with higher priority for the body scattering leading region only storing crosstalk under the circular polarization base; preliminarily solving the common polarization channel imbalance result by synthesizing the scattering symmetry condition with higher priority and calibrating the data; and finally, correlating the Polarization Orientation Angle (POA) solved by circular Polarization with the Orientation Angle (DEMOA) obtained by a Digital Elevation Model (DEM), screening correlation results to obtain final calibration parameters, and calibrating the imbalance of the co-Polarization channels.
The applicability analysis of the common polarization channel unbalance calibration method based on circular polarization reflection symmetry comprises the following steps:
for the present algorithm, the bulk scattering dominated and surface scattering dominated regions are mainly utilized, and the two types of scattering dominated regions need to exist in the actual calibration scene. Based on the method, the reflection symmetry characteristic with higher priority is screened out in the bulk scattering dominant region, and a Newton iteration method is used for solving the polarization scaling parameter with higher priority. For the newton iteration method, there may be a case of non-convergence in the iteration process, and the final result needs to be discriminated to remove the influence caused by the singular value.
Based on the above analysis, as shown in fig. 2, according to an embodiment of the present invention, a method for calibrating co-polarization channel imbalance based on circular polarization reflection symmetry is provided, the method includes the following steps:
step 1: selecting a volume scattering dominant region and a surface scattering dominant region based on circular polarization SAR data with undetermined crosstalk and channel unbalance;
step 2: carrying out block processing on the uncalibrated circularly polarized SAR data along the azimuth direction and the distance direction;
and step 3: solving the cross polarization channel imbalance based on the reciprocity of the surface scattering dominant region;
and 4, step 4: selecting a scattering symmetry condition with higher priority under a body scattering leading region of a circularly polarized base only with crosstalk;
and 5: preliminarily solving the common polarization channel imbalance result by synthesizing the scattering symmetry condition with higher priority and calibrating the data;
and 6: and solving polarization POA for the circular polarization data, then correlating with DEMO, and determining the correct unbalanced phase of the co-polarization channel to obtain the final calibration parameter.
Further, the step 1 comprises:
based on the minimum crosstalk emission model, the full circular polarization scaling model can be expressed as:
wherein, O 4LR For the measured circularly polarized data back scattering matrix,O xy (x,y=l,r) Expressed as a measurement for each polarization channel; s. the 4LR Is an ideal back-scattering matrix and is,S xy (x,y=l,r) Expressed as undistorted values for each polarization channel; x is a matrix of cross-talk distortion,u、v、w、zis the actual crosstalk value; q is a cross-polarization channel imbalance matrix;αis the cross polarization channel imbalance value; k 4 Is a co-polarized channel imbalance matrix;kis the co-polarized channel imbalance value. By equation (1), a covariance matrix of polarization distortion
Can be expressed as:
wherein, the first and the second end of the pipe are connected with each other,
for multi-view processing, the purpose is to eliminate the influence of speckle noise as much as possible; superscript is the conjugate transpose operation.
Before distributed target scaling, in order to eliminate the influence of additive noise on channel imbalance scaling as much as possible, regions with strong scattered energy in different channels are used for polarization scaling. Through the conversion of the linear polarization base and the circular polarization base, the energy of the body scattering dominant region is stronger on the co-polarization channel of the circular polarization SAR; on a cross-polarized channel with circular polarization, the surface scattering dominates the region with stronger energy. Therefore, the present invention next selects regions where bulk scattering energy dominates and regions where surface scattering energy dominates.
Firstly, in an actual scene, a complex artificial building area and the like generally contain different scattering mechanisms, and reflection symmetry is mostly not satisfied. Therefore, in the first step of selecting the area, the influence of the selected area caused by complex scattering such as a building area is removed. Here, equivalent views (ENL) are used to distinguish artificial areas from natural areas. For the artificial region, the surface feature texture is more complex, and the ENL is lower; however, for natural scenes, the feature texture is more consistent, and the ENL is generally higher. The invention next uses the ratio of co-polarized energy to cross-polarized channel energy:
to distinguish between surface and bulk scattering dominated regions. WhereinM xy (x,y=1,2,3,4) represents
To (1)xGo to the firstyColumn elements. As can be seen from equation (3), when the volume scattering energy is high,R vb the numerical value is larger; while for a surface where the scattered energy is high,R vb the numerical value is small. Thus, by computing natural features from the removed artificial regionR vb And setting a threshold value for the surface scattering dominant region and the bulk scattering dominant region to be appropriate.
The step 2 comprises the following steps:
in actual SAR payload flight, polarization distortion varies with the angle of incidence. However, since the azimuth time is short and the polarization distortion changes little, the polarization distortion is considered to be constant in the azimuth direction and to change in the distance direction. Therefore, in order to make the actual calculation more accurate, the block calculation is performed along the distance direction and the azimuth direction of the SAR data. In the subsequent processing, the variable name and symbol of each data block will not be specifically described, not specifically stated.
The step 3 comprises the following steps:
considering that commutative nature exists for diagonal matrix multiplication, the full circular polarization scaling model (1) can be transformed into:
therefore, the cross polarization channel imbalance value can be eliminated through the model (4)αMay bring too bigkThe scaling effect becomes poor. Based on the reciprocity of surface scattering, the cross-polarization channel imbalance value can be solved using the following equationα：
∠(α)=∠(M 32 ) (6)
Wherein, | · | represents an absolute value operator; the angle (·) represents the phase operator. By pairsαAfter calibration, the calibration model is rewritten as:
the step 4 comprises the following steps:
in this step, an inapplicable scattering symmetry is screened out based on actual data and a scattering symmetry with a higher priority is selected. Under the linear polarization base and the circular polarization base, the repeated equation caused by the reciprocity is removed, and the reflection symmetry is generally expressed as:
wherein Lin g (g=1, 2) represents a reflection symmetry condition on a linearly polarized basis; cir h (h=1,2,3,4) reflection symmetry condition in circular polarization base; s hh ，S hv ，S vv Representing the true scattering matrix component, h representing the horizontal direction, v representing the vertical direction; superscript denotes the conjugation operation on the imaginary number;
and with
Expressing the imaginary part and the real part of the imaginary number;Spanrepresenting the total energy of the full circular polarization. Considering Cir 2 Is generally used to solvekWhich can be converted to solve forkDirect form of the phase:
next, for 9 sets of linear polarization data, the urban area is removed first, and then the bulk scattering dominant area is selected. The reflection symmetry of the volume scattering dominated region at the circularly polarized basis is shown in fig. 1 by converting the circularly polarized base data from the linearly polarized base data.
As can be seen from diagram (a) of FIG. 1, cir 1/3/4 The numerical value is small. Plot (b) of FIG. 1 shows Cir in the volume scatter-dominated region of the different data 1/3/4 A percentage of less than 0.1, each of which is higher than 98%, can be considered to satisfy Cir in the bulk scattering dominated region 1/3/4 The reflection symmetry requirement represented, and Cir 1 、Cir 3 And Cir 4 The percentage of points less than 0.1 is Cir 1 >Cir 4 >Cir 3 . Cir represented by formula (9) in FIG. 1 (c) 2 As a result, it can be seen that the phase distribution is not concentrated. Therefore, in practical solution, cir 1 And Cir 4 Solving reflection symmetry characteristics as priorityk。
The step 5 comprises the following steps:
cir represented by equation (8) neglecting the influence of crosstalk 1 And Cir 4 Can be represented by combining formula (1) with formula (7):
wherein the content of the first and second substances,pis thatkThe inverse number of (c) is,
to represent
To (1) axGo to the firstyThe elements of the column. With respect to the formula (10),|p|can be solved accurately as:
equation (11) can be solved by newton's iteration. Due to the fact thatp=0 is a constant solution of formula (11), so first divide formula (11)|p|Eliminating the influence of 0 solution, cir 4 May be further denoted as UCir 4 Namely:
order top=a+b*jWhereina、bAre all real and
. Abouta、bTaking the derivative, one can derive:
considering that there are two real unknowns for equation (13), at least two sets of data are needed for solving. Because the polarization distortion parameters of a plurality of blocks along the same direction are unique, the numerical values of the blocks along different directions in the same distance direction are used for solving the uniquepThe value is obtained. Assuming upwards at a certain distanceD(D≧ 2) azimuthal patches with selected volume scattering regions, thendSecond orderIn the generation process,aandbamount of change is ΔaAnbIt can be expressed as:
p d =p d－1 +∆a+j∆b (15)
final utilization of Cir 4 Solve outpThe value is obtained. It should be noted that it is preferable that,p*e j0 、p*e jπ andp*e j π(－) are all solutions of equation (13). Finally, the invention binds to Cir 1/4 Solved amplitude and Cir 4 The solved phase is found to be three preliminarykThe solution of (1).
The step 6 comprises the following steps:
then will remove the product obtained in the previous stepkThe ambiguity value of the intermediate phase. First, by making three preliminarykAnd (5) putting the solution into a calibration model to obtain three circularly polarized backscattering matrixes which are calibrated primarily. Next, the Polarization Orientation Angle (POA) is solved separately and correlated with the Orientation Angle (DEMOA) obtained by the Digital Elevation Model (DEM). When the POA obtained by the fuzzy phase solution is correlated, the correlation result is smaller than that obtained by the correct phase, so that the correct phase value can be obtained by the size relation. Finally, by obtainingkThe amplitude and the phase of the data are calibrated according to the data processed in the data step 3, and a final actual result is obtained.
Example 1
The aerospace information innovation research institute of Chinese academy of sciences aerospace microwave remote sensing system part carries out a large amount of airborne SAR flight near the Chengdu Yuhe road junction in 2021 and 9 months, linear polarization data of an L wave band are obtained, and finally a good ground object application result is obtained. Considering that the simulation data is utilized, namely, the algorithm error can be clearly calculated according to the calculated value and the theoretical value by adding crosstalk and channel imbalance to the image, and the analysis is facilitated, the simulation data is utilized to carry out the analysis on the imageThe present disclosure is directed to a detailed analysis and validation. The simulation parameters are set as follows: adding the phase with the amplitude ranging from-3dB to 3dB and the phase ranging from-180 degrees to 180 degrees along the distance directionαAndkand uniformly adding crosstalk with amplitude ranging from-50 dB to-15 dB and random phase along the distance.
Fig. 3 shows data near the L-band gateway, with the number of pixels in azimuth and range directions being 2000 × 2000 and the pixel resolution being 0.7 × 0.7m. Fig. 3, graphs (a) - (b), are respectively circular polarized Pauli images of the selected region and the simulated added crosstalk and channel imbalance Pauli images. By comparing the simulated image with the Pauli image of the real scattering, it can be seen that the scattering of the simulated image is not the same as the actual scattering, and calibration is required. Fig. 3 (c) shows the result of determining ENL from the simulation graph. It can be seen that the ENL of the artificial target and the forest with lower distribution density is smaller, while the ENL of the forest with higher distribution density and the surface scattering dominant region is larger, so that the complex scattering region can be removed. Graph (d) of FIG. 3 is for simulation dataR vb Graph, results show volume scattering dominated regionsR vb Higher, and surface scattering dominated regionR vb And is lower. By ENL andR vb the bulk scattering-dominant region as well as the surface scattering-dominant region can be screened out.
FIG. 4 is a schematic view ofkAnd (5) calibrating the result. Wherein the circles represent the results of the estimation using an algorithm and the least squares fitting. By comparing the real values represented by the black lines with those represented by the solid lines, the amplitude error was 0.1287dB and the phase error was 4.4537 °. It can be seen that both the amplitude and phase have better fitting effects, and the other two lines in the phase can be removed by DEMOA and POA.
It will be understood by those skilled in the art that the foregoing is only an exemplary embodiment of the present invention, and is not intended to limit the invention to the particular forms disclosed, since various modifications, substitutions and improvements within the spirit and scope of the invention are possible and within the scope of the appended claims.
Claims (5)
1. A common polarization channel unbalance calibration method based on circular polarization reflection symmetry is characterized by comprising the following steps:
step 1: selecting a volume scattering dominant region and a surface scattering dominant region based on circularly polarized SAR data with uncertain crosstalk and channel imbalance;
step 2: carrying out block processing on the uncalibrated circularly polarized SAR data along the azimuth direction and the distance direction;
and 3, step 3: solving the cross polarization channel imbalance based on the reciprocity of the surface scattering dominant region;
and 4, step 4: selecting a reflection symmetry condition with higher priority under a body scattering dominant region of a circularly polarized base only with crosstalk;
and 5: preliminarily solving the common polarization channel imbalance result by synthesizing the reflection symmetry condition with higher priority and calibrating the data;
step 6: and solving the polarization direction angle of the circularly polarized SAR data, then correlating the polarization direction angle with the direction angle obtained by the digital elevation model, and determining the correct co-polarization channel unbalanced phase to obtain the final calibration parameter.
2. The method for calibrating co-polarized channel imbalance based on circularly polarized reflection symmetry according to claim 1, wherein in step 2,
partitioning the SAR image along the distance direction, so as to respectively solve the polarization distortion; and the SAR image is simultaneously blocked along the azimuth direction, and the polarization distortion values solved by different azimuth directions are used for mutual correction.
3. The circularly polarized reflection symmetry based co-polarized channel imbalance calibration method of claim 2, wherein in step 3,
determining the imbalance of the cross polarization channel based on the reciprocity of the surface scattering dominant region, and removing the influence caused by the imbalance of the cross polarization channel when the imbalance of the common polarization channel is solved subsequently.
4. The circularly polarized reflection symmetry based co-polarized channel imbalance calibration method of claim 3, wherein in step 4,
and solving a reflection symmetry condition in the circularly polarized SAR data of the volume scattering dominant region and determining the priority of the reflection symmetry condition so as to eliminate errors caused by using all the reflection symmetry conditions in actual data.
5. The circularly polarized reflection symmetry based co-polarized channel imbalance calibration method according to claim 4, wherein in the step 5,
and (4) obtaining a reflection symmetry condition with higher priority based on the step (4), preliminarily solving unbalanced amplitude and phase of the common polarization channel, and preliminarily calibrating the data.
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