CN103869299A - Polarization synthetic aperture radar calibration method based on natural bare soil - Google Patents

Abstract

The invention discloses a polarization synthetic aperture radar calibration method based on natural bare soil. The method comprises the steps that the crosstalk and cross polarization channel imbalance parameters of a POLSAR radar image are estimated and removed at first; then, the POLSAR radar image is parted in the distance direction and the azimuth direction; finally, an optimization function is built with the low spirochete ingredient of real soil as an optimization object, and imbalance of a same polarization channel is solved through the characteristic that blocks in the same distance direction have the identical unknown numbers. The weak scattering characteristic of the spirochete of the natural bare soil is utilized, calibration is carried out on emission and receiving distortion matrixes existing in a POLSAR radar system, biased observed values are re-calibrated to be a real scattering matrix, and powerful guarantees can be provided for a radar in the application aspects of territorial resources surveys, natural disaster emergency responses and the like.

Description

Polarimetric synthetic aperture radar calibrating method based on natural exposed soil

Technical field

The invention belongs to SAR image processing technology field, particularly a kind of polarimetric synthetic aperture radar (Polarimetric Synthetic Aperture Radar, POLSAR) calibrating method based on natural exposed soil.

Background technology

As a kind of Advanced Synthetic Aperture Radar technology, POLSAR(polarimetric synthetic aperture radar) obtain Terrain Scattering matrix by transmitting, reception level and vertical polarization electromagnetic wave, under round-the-clock, round-the-clock condition, carry out land observation, make up the deficiency of other remote sensings, effectively assist land resources Classification Count, obtain the physical parameter such as vegetation biomass and surface humidity.The information of POLSAR observation tends to the impact that is subject to system transmitting, receives distortion matrix, makes observed reading and actual value generation deviation.Distortion process can be divided into three parts conventionally: crosstalk (Crosstalk), cross polarization channel imbalance (Cross-polarization Channel Imbalance), same polarization channel imbalance (Co-polarization Channel Imbalance).

Existing polarimetric calibration method is utilized reciprocity and the scattering symmetry of natural feature on a map, under the condition that does not need reference target to crosstalking, cross polarization channel imbalance proofreaies and correct; For same polarization channel imbalance, existing calibrating method all need to be laid at least one active or passive corrner reflector and calibrate in scene, and is often difficult to carry out corner reflector laying in some rugged countries, mountain region (as China western part), unmanned desert area.External machine-borne polarization synthetic-aperture radar hardware system is reliable and stable, and while not carrying out the calibration of same polarization channel imbalance, image range error is often less than 0.5dB, phase error is less than 5 degree, can meet the most basic land accuracy of observation requirement; China's electronic hardware systematic error is often higher, and the data of not carrying out polarimetric calibration are difficult to meet remote sensing primary demand, and this has seriously restricted the range of application of China POLSAR system.

Summary of the invention

The deficiency existing for prior art, the present invention proposes a kind of polarimetric synthetic aperture radar calibrating method based on natural exposed soil of estimating same polarization channel imbalance, the method is utilized the low conveyor screw scattering properties of nature exposed soil, by mathematics and electromagnetic scattering model, and a kind of majorized function proposed, by POLSAR observed reading corresponding to natural exposed soil, estimate same polarization channel imbalance.

For solving the problems of the technologies described above, the present invention adopts following technical scheme:

Polarimetric synthetic aperture radar calibrating method based on natural exposed soil, comprises step:

Step 1, taking exposed soil in synthetic-aperture radar image as observed object, estimates and eliminates crosstalking and cross polarization channel imbalance of polarimetric synthetic aperture radar image;

Step 2, the obtaining of covariance matrix observed reading, this step further comprises sub-step:

2.1 by polarimetric synthetic aperture radar image in orientation to be divided into P piece orientation to piece, in distance to being divided into N piece distance to piece, that is, each distance is to the corresponding P piece of piece orientation to piece;

2.2 for each distance to piece, in adjusting the distance respectively to each orientation corresponding to piece to piece, the polarization covariance matrix of exposed soil pixel averages processing, obtain the average polarization covariance matrix of each orientation to piece, the observed reading using the P obtaining an average polarization covariance matrix as distance to piece;

Step 3, estimates same polarization channel imbalance, and this step further comprises sub-step:

3.1 build majorized function taking soil conveyor screw composition as optimization aim

wherein, p=k ^-1=a+jb, the real part that a and b are p and imaginary part, j is imaginary symbols, k is same polarization channel imbalance to be solved; Im is for asking imaginary part operation; C ₁₂for the element of the 1st row the 2nd row in average covariance matrix C, C ₂₃for the element of the 2nd row the 3rd row in average covariance matrix C;

3.2 according to the observed reading apart to piece, adopts Newton solution by iterative method majorized function to obtain the estimated value of a and b, thereby obtains the same polarization channel imbalance estimated value of each distance to piece;

Step 4, carries out the matching of intensity and phase place to each distance to the same polarization channel imbalance estimated value of piece, obtains closely end and, to same polarization channel imbalance corresponding to remote each pixel, eliminates distortion factor.

Above-mentioned steps 1 further comprises sub-step:

1.1 open respectively the window of big or small n × n in polarimetric synthetic aperture radar image centered by each pixel, adopt grey scale pixel value in window to build polarization coherence matrix corresponding to window, and n value is artificially default;

1.2 taking exposed soil pixel in synthetic-aperture radar image as observed object, the crosstalking and cross polarization channel imbalance of the polarization coherence matrix that adopts Qugen scaling method to eliminate to build.

Above-mentioned sub-step 3.2 further comprises:

A) build system of linear equations BM=L, wherein, $B=\left[\begin{array}{cc}\frac{{\&PartialD;f}_{\mathrm{UZHEX}}^1}{{\&PartialD;a}_x}& \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^1}{{\&PartialD;b}_x}\\ \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;\\ \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^P}{{\&PartialD;a}_x}& \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^P}{{\&PartialD;b}_x}\end{array}\right];M=\left[\begin{array}{c}{\mathrm{\&Delta;a}}_x\\ {\mathrm{\&Delta;b}}_x\end{array}\right],{\mathrm{\&Delta;a}}_x$ With Δ b _yfor corrected value to be solved; $L=\left[\begin{array}{c}{-\mathrm{<figure-callout\; id="1"\; label="f\; UZHEX"\; filenames="1404011455562.png"\; state="\{\{state\}\}">f</figure-callout>}}_{\mathrm{UZHEX}}^{}\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ {-f}_{\mathrm{UZHEX}}^P\end{array}\right];$

represent the majorized function to piece apart from m the orientation to piece, m=1,2 ..., P;

B) iteration initial value p is set _x=a _x+ jb _x, bring iteration initial value and distance into system of linear equations BM=L to the P group observations of piece, solve Δ a _xwith Δ b _y;

C) adopt Δ a _xwith Δ b _yundated parameter a _x=a _x+ Δ a _x, b _y=b _y+ Δ b _y, with the parameter a after upgrading _xand b _yfor parameter current, the corrected value Δ a that adopts this to solve _x, Δ b _yand parameter current a _x, b _ycalculating solves residual error || BM-L|| ₂, and relatively solve residual error || BM-L|| ₂with predetermined threshold value size, if the residual error of solving || BM-L|| ₂be less than predetermined threshold value, parameter current a _x, b _ybe solving result, finishing iteration; Otherwise execution step d);

D) by parameter current a _x, b _yand distance is to the P group observations substitution system of linear equations BM=L of piece, continues to solve corrected value Δ a _xwith Δ b _y, then, execution step c).

In sub-step 3.2, the different iteration initial value p of many groups can be set _x=a _x+ jb _x, adopt described step a)～d) acquisition is organized solving results corresponding to iteration initialization more respectively, will solve residual error || BM-L|| ₂minimum solving result is as final solution.

Compared to the prior art, the present invention has following features:

1, utilize the conveyor screw weak scattering characteristic of nature exposed soil, the transmitting existing in POLSAR radar system, reception distortion matrix are calibrated, observed reading devious is calibrated again as true scattering matrix, can be radar and provide powerful guarantee in application aspect such as survey of territorial resources, disaster emergency responses.

2,, based on image block, normalization soil conveyor screw ingredient f is proposed _uZHEX, and by making conveyor screw ingredient f in POLSAR image _uZHEXmeet f _uZHEX=0 solves same polarization channel imbalance k, can effectively avoid the solution trivials such as k=± ∞, and same polarization channel imbalance is estimated in the regional stability that can be dominant at exposed soil.

3, without the artificial scaler of laying in scene, can under round-the-clock, round-the-clock condition, carry out high-precision radar data calibration to the area such as Complex Mountain, unmanned desert, can effectively improve the POLSAR image precision in depopulated zone, expansion POLSAR radar image range of application, the financial cost that reduces the calibration of POLSAR radar image, has broad application prospects and economic worth.

Brief description of the drawings

Fig. 1 is the idiographic flow schematic diagram of the inventive method;

Fig. 2 is the schematic flow sheet that adopts Newton solution by iterative method same polarization channel imbalance.

Embodiment

For estimating the same polarization channel imbalance of POLSAR observation information, first the specific embodiment of the invention adopts classical Kui Geng (Qugen) scaling method that crosstalking of POLSAR radar image estimated with cross polarization channel imbalance parameter and eliminated.Then, build majorized function taking the low conveyor screw composition of true soil as optimization aim, carry out same polarization channel imbalance and solve.Because same polarization channel imbalance is plural number, at least need two different covariance matrixes to solve as observed reading.In embodiment, to POLSAR radar image carry out distance to orientation to piecemeal, utilize same distance to there is the feature of identical unknown number to piece, solve same polarization channel imbalance.

Further illustrate technical solution of the present invention below in conjunction with the drawings and specific embodiments.

Technical solution of the present invention can adopt computer technology to realize automatic operational scheme, and as shown in Figure 1, idiographic flow of the present invention comprises step:

Step 1, estimates and eliminates crosstalking and cross polarization channel imbalance of POLSAR radar image.

Respectively to treat to open centered by recovery point the window of a big or small n × n, undertaken looking processing more by all pixels in window and estimate polarization coherence matrix respectively, treat that recovery point refers to each pixel in POLSAR radar image here.When concrete enforcement, those skilled in the art can be according to concrete image preset window size n value.

This step further comprises following sub-step:

Step 1.1 builds polarization coherence matrix.

Generally speaking, 4 channel datas that POLSAR observation information comprises reflection Terrain Scattering mechanism, i.e. original polarization scattering matrix S2.Original polarization scattering matrix S2 is converted, in n × n size windows, build polarization coherence matrix C _observer:

$S2=\left[\begin{array}{cc}{\mathrm{HH}}_i& {\mathrm{HV}}_i\\ {\mathrm{VH}}_i& {\mathrm{VV}}_i\end{array}\right]\&RightArrow;C_{\mathrm{observer}}=\underset{i=1}{\overset{n\&times;n}{\mathrm{\&Sigma;}}}(l_i\&CenterDot;l_i^{*T})---\left(1\right)$

In formula (1), HH _i, HV _i, VH _i, VV _ibe respectively i grey scale pixel value in the respective window of image that POLSAR radar HH passage observes, image that radar HV passage observes, image that radar VH passage observes, image that radar VV passage observes, i=1,2 ..., n × n.

Complex vector l _ifor:

l _i＝[HH _i,VH _i,HV _i,VV _i] ^T （2）

In formula (2), T representing matrix transposition, * represents conjugate operation.

Step 1.2 is utilized Qugen scaling method, estimates and eliminates and crosstalk and cross polarization channel imbalance as observed object using exposed soil in POLSAR radar image.

Utilize Qugen scaling method to the polarization coherence matrix C building _observerelimination is crosstalked and cross aisle imbalance.

Suppose observing matrix C _observerfor:

$C_{\mathrm{observer}}=\left[\begin{array}{cccc}{C}_{o11}& C_{o12}& C_{o13}& C_{o14}\\ C_{o21}& C_{o22}& C_{o23}& C_{o24}\\ C_{o31}& C_{o32}& C_{o33}& C_{o34}\\ C_{o41}& C_{o42}& C_{o43}& C_{o44}\end{array}\right]---\left(3\right)$

Solve plural number crosstalk factor u, v, w, z and plural cross aisle unbalance factor α:

u＝(C _o44C _o21-C _o41C _o24)/(C _o11C _o44-|C _o14| ²)

v＝(C _o11C _o24-C _o21C _o14)/(C _o11C _o44-|C _o14| ²)

z＝(C _o44C _o31-C _o41C _o34)/(C _o11C _o44-|C _o14| ²) （4）

w＝(C _o11C _o34-C _o31C _o14)/(C _o11C _o44-|C _o14| ²)

$\mathrm{\&alpha;}=\frac{\left|\mathrm{\&beta;\&gamma;}\right|-1+\sqrt{{\left(\right|\mathrm{\&beta;\&gamma;}|-1)}^2+4{\left|\mathrm{\&gamma;}\right|}^2}}{2\left|\mathrm{\&gamma;}\right|}\&CenterDot;\exp (j\&CenterDot;\mathrm{Arg}\left(\mathrm{\&beta;}\right))$

In formula (4), $\mathrm{\&beta;}=\frac{C_{o22}-u{C}_{o12}-v{C}_{o42}}{C_{o32}-z{C}_{o12}-w{C}_{o42}},\mathrm{\&gamma;}=\frac{C_{o33}-z{C}_{o21}-v{C}_{o42}}{C_{o33}-z^{*}{C}_{o31}-w^{*}{C}_{o34}},$ Arg is that plural number is asked phase operation, and j represents imaginary symbols.

According to plural number the crosstalk factor and plural cross aisle unbalance factor definition matrix distortion matrix X, Q and permutation matrix A:

$X=\left[\begin{array}{cccc}1& w& v& \mathrm{vw}\\ u& 1& \mathrm{uv}& v\\ z& \mathrm{wz}& 1& w\\ \mathrm{<figure-callout\; id="1"\; label="uz\; z\; u"\; filenames="1404011455562.png"\; state="\{\{state\}\}">uz</figure-callout>}& z& u& 1\end{array}\right],Q=\left[\begin{array}{cccc}\mathrm{\&alpha;}& 0& 0& 0\\ 0& \mathrm{\&alpha;}& 0& 0\\ 0& 0& 1& 0\\ 0& 0& 0& 1\end{array}\right],A=\begin{array}{c}\left[\begin{array}{ccc}1& 0& 0\\ 0& 1/\sqrt{2}& 0\\ 0& 1/\sqrt{2}& 0\\ 0& 0& 1\end{array}\right]\end{array}---\left(5\right)$

Because the data of eliminating cross polarization channel imbalance meet VH ≡ HV, definable polarization covariance matrix C ₃:

C ₃＝A ^*(XQ) ^-1C _observer(Q ^*X ^*) ^-1A （6）

In formula (6), subscript * represents conjugate transpose.

About covariance matrix C ₃calculating can be referring to document: A unified algorithm for phase and cross-talk calibration of polarimetric data-theory and observations-1994.

Step 2, the processing of POLSAR radar image piecemeal.

Because same polarization channel imbalance k to be solved is plural number, at least need two different covariance matrixes to solve as observed reading.This embodiment to POLSAR radar image in orientation to being divided into 64, adjusting the distance to being divided into 100, POLSAR radar image is divided into 64*100 piece.Due to same polarization channel imbalance in orientation to comparatively stable, distance to change comparatively violent, therefore can think that each distance is upwards affected by identical unknown number k in 64 orientation to little image blocks.

When concrete enforcement, for each distance to 64 orientation corresponding to piece to piece, by orientation to covariance matrix C corresponding to all exposed soil pixels in piece ₃average processing, after being added to corresponding element in covariance matrix corresponding to all exposed soil pixels in piece by each orientation divided by each orientation to exposed soil pixel quantity in piece, observed reading using 64 average covariance matrix C after average treatment as from distance to piece, each distance is to all corresponding 64 observed readings of piece.

Defining average covariance matrix is C:

$C=\left[\begin{array}{ccc}{C}_{11}& C_{12}& C_{13}\\ C_{12}^{*}& C_{22}& C_{23}\\ C_{13}^{*}& C_{23}^{*}& C_{33}\end{array}\right]=\left[\begin{array}{ccc}{C}_{11}& C_{12\mathrm{re}}+j\&CenterDot;C_{12\mathrm{im}}& C_{13\mathrm{re}}+j\&CenterDot;C_{13im}\\ C_{12\mathrm{re}}-j\&CenterDot;C_{12\mathrm{im}}& C_{22}& C_{23\mathrm{re}}+j\&CenterDot;C_{23\mathrm{im}}\\ C_{13\mathrm{re}}-j\&CenterDot;C_{13\mathrm{im}}& C_{23\mathrm{re}}-j\&CenterDot;C_{23\mathrm{im}}& C_{33}\end{array}\right]---\left(7\right)$

In formula (7), j represents imaginary symbols; Re and im represent respectively real part and imaginary part, that is, and and C _12rerepresent C ₁₂real part, C _12imrepresent C ₁₂imaginary part.

Step 3, builds majorized function taking the low conveyor screw composition of true soil as optimization aim, adopt the majorized function building to solve each distance to same polarization channel imbalance corresponding to piece.

Observed reading taking each distance to 64 average covariance matrix C corresponding to piece as from distance to piece, builds majorized function f _uZHEX:

$f_{\mathrm{UZHEX}}=\frac{1}{\sqrt{2}}\mathrm{Im}\left(\right|p|p{C}_{12}+\frac{1}{\left|p\right|}p{C}_{23})=0---\left(8\right)$

In formula (8), p=k ^-1=a+ib, the real part that a and b are p and imaginary part, i is imaginary symbols, k is same polarization channel imbalance to be solved; Im is for asking imaginary part operation; C ₁₂with C ₂₃for the element in average covariance matrix C.

Majorized function f _uZHEXbe conveyor screw composition, specifically can be referring to document: Four-component scattering model for polarimetric SAR image decomposition-2005.This step solves and makes conveyor screw composition is that fUZHEX is 0 p, thereby obtains same polarization channel imbalance estimated value.

For the reliable solving result of quick obtaining, the required partial derivative of the Newton process of iteration of having derived while specifically enforcement:

$\begin{array}{c}\frac{{\&PartialD;f}_{\mathrm{UZHEX}}}{\&PartialD;A}=\frac{1}{\sqrt{2}}[\frac{a(a{C}_{12\mathrm{im}}+b{C}_{12\mathrm{re}})+C_{23\mathrm{im}}}{\sqrt{a^2+b^2}}+]\sqrt{a^2+b^2}{C}_{12\mathrm{im}}-\frac{a(a{C}_{23\mathrm{im}}+b{C}_{23\mathrm{re}})}{\sqrt{{(a^2+b^2)}^3}}\\ \frac{{\&PartialD;f}_{\mathrm{UZHEX}}}{\&PartialD;b}=\frac{1}{\sqrt{2}}[\frac{b(a{C}_{12\mathrm{im}}+b{C}_{12\mathrm{re}})+C_{23\mathrm{re}}}{\sqrt{a^2+b^2}}+]\sqrt{a^2+b^2{C}_{12\mathrm{re}}}-\frac{b(a{C}_{23\mathrm{im}}+b{C}_{23\mathrm{re}})}{\sqrt{{(a^2+b^2)}^3}}\end{array}---\left(9\right)$

To piece, adopt respectively the each distance of Newton solution by iterative method to see Fig. 2 to the same polarization channel imbalance process of piece for each distance, specific as follows:

A, iteration initial value p is set _x=a _x+ jb _x, bring iteration initial value and distance into majorized function f to 64 observed readings of piece _uZHEX, build system of linear equations (10) and solve corrected value Δ a _xwith Δ b _y:

$\mathrm{BM}=L\&RightArrow;\left[\begin{array}{cc}\frac{{\&PartialD;\mathrm{<figure-callout\; id="1"\; label="f\; UZHEX"\; filenames="1404011455562.png"\; state="\{\{state\}\}">f</figure-callout>}}_{\mathrm{UZHEX}}^{}}{{\&PartialD;a}_x}& \frac{{\&PartialD;\mathrm{<figure-callout\; id="1"\; label="f\; UZHEX"\; filenames="1404011455562.png"\; state="\{\{state\}\}">f</figure-callout>}}_{\mathrm{UZHEX}}^{}}{{\&PartialD;b}_x}\\ \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;\\ \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^{64}}{{\&PartialD;a}_x}& \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^{64}}{{\&PartialD;b}_x}\end{array}\right]\left[\begin{array}{c}{\mathrm{\&Delta;a}}_x\\ {\mathrm{\&Delta;b}}_x\end{array}\right]=\left[\begin{array}{c}{-\mathrm{<figure-callout\; id="1"\; label="f\; UZHEX"\; filenames="1404011455562.png"\; state="\{\{state\}\}">f</figure-callout>}}_{\mathrm{UZHEX}}^{}\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ {-f}_{\mathrm{UZHEX}}^{64}\end{array}\right]---\left(10\right)$

In formula (10), subscript represents that distance is to 64 orientation corresponding to piece to piece,

represent that distance is to m orientation corresponding to piece to fast majorized function, m=1,2 ..., 64.

B, employing corrected value Δ a _xwith Δ b _yupgrade parameter a to be solved _x=a _x+ Δ a _x, b _y=b _y+ Δ b _y, with the parameter a after upgrading _x, b _yfor parameter current, the corrected value Δ a that adopts this to solve _x, Δ b _yand parameter current a _x, b _ycalculating solves residual error || BM-L|| ₂if solve residual error || BM-L|| ₂be less than threshold value 10 ^-6, parameter current a _x, b _ybe solving result, finishing iteration, exports solving result and solves residual error; If the residual error of solving || BM-L|| ₂be not less than threshold value 10 ^-6, execution step c;

C, by parameter current a _x, b _ywith 64 the observed reading substitution majorized function fs of distance to piece _uZHEX, build system of linear equations (10) and solve corrected value Δ a _xwith Δ b _y, then, execution step b.

See Fig. 2, for eliminating the impact of iteration initial value, in embodiment, general-3dB to 3dB ,-pi to pi are divided into 30 parts separately respectively as a and b initial value input Newton process of iteration, and minimum is solved to solving result corresponding to residual error as final solution.Pi is standard round frequency.

Adopt said method to solve respectively the estimated value of 100 distances to same polarization channel imbalance corresponding to piece.

Step 4, adjusts the distance and carries out the linear fit of intensity and phase place to same polarization channel imbalance estimated value corresponding to piece, obtains closely end and, to same polarization channel imbalance corresponding to remote each pixel, completes the final elimination of distortion factor.

Specific embodiment described herein is only to the explanation for example of the present invention's spirit.Those skilled in the art can make various amendments or supplement or adopt similar mode to substitute described specific embodiment, but can't depart from spirit of the present invention or surmount the defined scope of appended claims.

Claims (4)

1. the polarimetric synthetic aperture radar calibrating method based on natural exposed soil, is characterized in that, comprises step:

Step 1, taking exposed soil in synthetic-aperture radar image as observed object, estimates and eliminates crosstalking and cross polarization channel imbalance of polarimetric synthetic aperture radar image;

Step 2, the obtaining of covariance matrix observed reading, this step further comprises sub-step:

2.1 by polarimetric synthetic aperture radar image in orientation to be divided into P piece orientation to piece, in distance to being divided into N piece distance to piece, that is, each distance is to the corresponding P piece of piece orientation to piece;

2.2 for each distance to piece, in adjusting the distance respectively to each orientation corresponding to piece to piece, the polarization covariance matrix of exposed soil pixel averages processing, obtain the average polarization covariance matrix of each orientation to piece, the observed reading using the P obtaining an average polarization covariance matrix as distance to piece;

Step 3, estimates same polarization channel imbalance, and this step further comprises sub-step:

3.1 build majorized function taking soil conveyor screw composition as optimization aim

wherein, p=k ^-1=a+jb, the real part that a and b are p and imaginary part, j is imaginary symbols, k is same polarization channel imbalance to be solved; Im is for asking imaginary part operation; C12 is the element of the 1st row the 2nd row in average covariance matrix C, C ₂₃for the element of the 2nd row the 3rd row in average covariance matrix C;

3.2 according to the observed reading apart to piece, adopts Newton solution by iterative method majorized function to obtain the estimated value of a and b, thereby obtains the same polarization channel imbalance estimated value of each distance to piece;

Step 4, carries out the matching of intensity and phase place to each distance to the same polarization channel imbalance estimated value of piece, obtains closely end and, to same polarization channel imbalance corresponding to remote each pixel, eliminates distortion factor.

2. the polarimetric synthetic aperture radar calibrating method based on natural exposed soil as claimed in claim 1, is characterized in that:

Step 1 further comprises sub-step:

1.1 open respectively the window of big or small n × n in polarimetric synthetic aperture radar image centered by each pixel, adopt grey scale pixel value in window to build polarization coherence matrix corresponding to window, and n value is artificially default;

1.2 taking exposed soil pixel in synthetic-aperture radar image as observed object, the crosstalking and cross polarization channel imbalance of the polarization coherence matrix that adopts Qugen scaling method to eliminate to build.

3. the polarimetric synthetic aperture radar calibrating method based on natural exposed soil as claimed in claim 1, is characterized in that:

Sub-step 3.2 further comprises:

A) build system of linear equations BM=L, wherein, $B=\left[\begin{array}{cc}\frac{{\&PartialD;f}_{\mathrm{UZHEX}}^1}{{\&PartialD;a}_x}& \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^1}{{\&PartialD;b}_x}\\ \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;\\ \&CenterDot;& \&CenterDot;\\ \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^P}{{\&PartialD;a}_x}& \frac{{\&PartialD;f}_{\mathrm{UZHEX}}^P}{{\&PartialD;b}_x}\end{array}\right];M=\left[\begin{array}{c}{\mathrm{\&Delta;a}}_x\\ {\mathrm{\&Delta;b}}_x\end{array}\right],{\mathrm{\&Delta;a}}_x$ With Δ b _yfor corrected value to be solved; $L=\left[\begin{array}{c}{-f}_{\mathrm{UZHEX}}^1\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ {-f}_{\mathrm{UZHEX}}^P\end{array}\right];$

represent the majorized function to piece apart from m the orientation to piece, m=1,2 ..., P;

B) iteration initial value p is set _x=a _x+ jb _x, bring iteration initial value and distance into system of linear equations BM=L to the P group observations of piece, solve Δ a _xwith Δ b _y;

C) adopt Δ a _xwith Δ b _yundated parameter a _x=a _x+ Δ a _x, b _y=b _y+ Δ b _y, with the parameter a after upgrading _xand b _yfor parameter current, the corrected value Δ a that adopts this to solve _x, Δ b _yand parameter current a _x, b _ycalculating solves residual error || BM-L|| ₂, and relatively solve residual error || BM-L|| ₂with predetermined threshold value size, if the residual error of solving || BM-L|| ₂be less than predetermined threshold value, parameter current a _x, b _ybe solving result, finishing iteration; Otherwise execution step d);

D) by parameter current a _x, b _yand distance is to the P group observations substitution system of linear equations BM=L of piece, continues to solve corrected value Δ a _xwith Δ b _y, then, execution step c).

4. the polarimetric synthetic aperture radar calibrating method based on natural exposed soil as claimed in claim 3, is characterized in that:

The different iteration initial value p of many groups is set _x=a _x+ jb _x, adopt described step a)～d) acquisition is organized solving results corresponding to iteration initialization more respectively, will solve residual error || BM-L|| ₂minimum solving result is as final solution.

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