CN103129752A - Dynamic compensation method for attitude angle errors of optical remote sensing satellite based on ground navigation - Google Patents

Abstract

The invention discloses a dynamic compensation method for attitude angle errors of an optical remote sensing satellite based on ground navigation. The dynamic compensation method includes the following steps: (1) performing effectiveness processing on ephemeris data and attitude data downloaded from the satellite, namely eliminating outliers points in the data and re-determining the values of the points; (2) determining an extracting range of control points on a first level image which is an image corrected by radiation, determining an extracting range of control points on a reference image according to the extracting range on the first level image and data after processing in the step (1), intercepting the extracting ranges on the first level image and the reference image respectively, and generating one sub-image of the first level image which is an image subjected to radiometric correction and one sub-image of the reference image which is an orthoimage; (3) performing automatic pairing of the control points by adopting intercepted the sub-images of the first level image and the reference image, and eliminating mispairing points; (4) selecting at least 3 pairs of homonymy control points with different sequence orders and smallest Euclidean distances apart from a scenario center from the sub-images of the first level image and the reference image, and calculating attitude angle errors; and (5) performing compensation on an attitude angle of the optical remote sensing satellite by adopting determined attitude angle errors.

Description

A kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation

Technical field

The invention belongs to the Optical remote satellite data processing field, be applicable to the optical remote sensing camera.

Background technology

Along with the raising of domestic remote sensing satellite spatial resolution, the geometric positioning accuracy of remote sensing picture becomes an important investigation index.The accuracy of positioning of remote sensing picture is subjected to mainly that on orbital data precision, attitude data precision and star, timing tracking accuracy affects.Adopt current orbit determination technology, can reach meter level as double frequency differential GPS orbit determination accuracy even higher; On the star of satellite, timing tracking accuracy can reach Microsecond grade at present, is 1ms as timing tracking accuracy on star, and satellite velocities is 7.6km/s, and the satellite position deviation that is caused by the asynchronism(-nization) step is 0.44m; But it is larger that satellite is surveyed the appearance difficulty, systematic error in attitude angle, long period error and random error etc. are larger on the impact of geometric positioning accuracy, automatically, in real time, calibration accurately goes out the error of attitude data and compensates, and the image geometry accuracy of positioning is had a more substantial increase.

From present publishing an article and open source information, the research about the calibration of attitude data error and compensation aspect mainly contains following content:

1, " based on the satellite remote-sensing image systematic error compensation of bias matrix " (opened etc., Liaoning Project Technology University's journal, in August, 2007)

Find the solution respectively three independent parameters in excursion matrix, it is compensated as systematic error.

At first utilize camera at the image of facing under condition, carry out geometric correction according to strict imaging model, statistics is along rail direction error Δ N ' P and vertical rail direction error

Calculating Δ ρ and Δ Ψ according to formula (1) and formula (2) is exactly pitch angle and roll angle in excursion matrix.Then utilize camera to go on foot the excursion matrix of obtaining in the image under maximum side-looking condition and substitution, carry out correcting without the image geometry at controlling point according to strict imaging model, statistics is along the error of track alignment

Finding the solution Δ κ according to formula (3), is exactly the yaw angle in excursion matrix.

$\mathrm{\Δ}\tilde{N}P(\frac{(1+\frac{H}{R})\cos \mathrm{\ψ}}{\sqrt{1-{(1+\frac{H}{R})}^2{\sin }^2\mathrm{\ψ}}}-1)\mathrm{R\Δ\ψ}---\left(1\right)$

$\mathrm{\Δ}{N}^{\′}P=\{H+R[1-\cos \left(\arcsin (1+\frac{H}{R})\sin \left(\mathrm{\ψ}\right)\right)-\mathrm{\ψ})\left]\right\}$

${\sec }^2\left(\mathrm{\ρ}\right)\mathrm{\Δ\ρ}=\{H+R[1-\cos (\arcsin (1+\frac{H}{R})\sin \left(\mathrm{\ψ}\right))-\mathrm{\ψ})\left]\right\}\mathrm{\Δ\ρ}---\left(2\right)$

$\mathrm{\Δ}\tilde{P}Q=\left(R(\arcsin \left((1+\frac{H}{R})\sin \left(\mathrm{\ψ}\right)\right)-\mathrm{\ψ})\right)\cos \mathrm{\κ\Δ\κ}---\left(3\right)$

H is orbit altitude, and R is earth radius

2, " the attitude angle constant calibration of high resolution ratio satellite remote-sensing image " (Yuan Xiuxiao etc., mapping journal, in February, 2008)

1) math modeling of attitude angle calibration

Image coordinate (the x of known control point _c, y _c) and the coordinate (X under the WGS84 system of axes _c, Y _c, Z _c), utilize image row-coordinate y _c, carry out according to the elements of exterior orientation discrete observation value that secondary file provides the principal point coordinate that polynomial interpolation can obtain the respective scanned row

And attitude angle initial value

When controlling point and line element survey precision are enough high, μ in formula (4) _cCan think the exact value of picture point normalisation space auxiliary coordinate, with this foundation as the attitude angle calibration.

${\mathrm{\μ}}_c=\frac{{{\mathrm{\μ}}^{\′}}_c}{\left|\right|{{\mathrm{\μ}}^{\′}}_c\left|\right|}$

In formula, ${{\mathrm{\μ}}^{\′}}_c=\left[\begin{array}{c}{X}_c-X_{P_i}\\ Y_c-Y_{P_i}\\ Z_c-Z_{P_i}\end{array}\right].$

By three components of image space auxiliary coordinate, can list following error equation group to single controlling point.

μ in formula _sBe normalisation image space auxiliary coordinate, $L=\left[\begin{array}{c}{\left({\mathrm{\μ}}_c\right)}_X{-\left({\mathrm{\μ}}_S\right)}_X\\ {\left({\mathrm{\μ}}_c\right)}_Y-{\left({\mathrm{\μ}}_S\right)}_Y\\ {\left({\mathrm{\μ}}_c\right)}_Z-{\left({\mathrm{\μ}}_S\right)}_Z\end{array}\right]$ Be μ _cWith μ _SDifference between each component.

With

For people's formula (5), can obtain its augmentation Δ ω through 3-4 iterative as the attitude angle initial value _i,

Δ κ _iBoth additions just obtain this spot scan row attitude angle or value, i.e. calibration value.

2) utilize a small amount of controlling point to calculate the attitude angle constant

When there was constant in the attitude angle observed value that provides when the Image-aided file, it was estimated can to utilize a small amount of dominating pair of vertices.Because all there is the constant that communicates in the attitude angle of each baseline in image, when can only find single controlling point on a scanning line image time, visual 1) attitude angle augmentation (the Δ ω that calculates in _i,

Δ κ _i) be normal value valuation; When can find n controlling point on the n of image bar scanning line image the time, can be respectively to each controlling point according to 1) in method calculate the attitude angle augmentation of each baseline, get at last the attitude angle augmentation center line average values of each baseline as valuation (the Δ ω of the attitude angle constant of image

Δ κ) after, be added on the attitude angle value of each baseline that formula (6) calculates and just can eliminate the impact of its constant.For avoiding constant to leave data noise, can adopt the resection method to do further adjustment processing, generally need 6 above controlling points this moment.

In formula, a ₀, b ₀, c ₀, d ₀, e ₀, f ₀, centered by the elements of exterior orientation of baseline; a ₀..., f _kBe multinomial coefficient, can obtain according to the elements of exterior orientation discrete observation value match that auxiliary data file provides; T is the i baseline time of exposure capable with respect to centre scan.

3, " the attitude angle constant calibration of ALOS PRISM image " (Liu Chubin etc. survey and draw scientific and technical journal, and 2011, the 28th the 4th phase of volume)

Attitude angle constant calibration model:

Known control point coordinate (X _c, Y _c, Z _c) and principal point coordinate (X _s, Y _s, Z _s) time, the picture point normalisation space auxiliary coordinate that is obtained by controlling point coordinate and principal point coordinate Calculation is

u＝[X _c-X _s，T _c-Y _s，Z _c-Z _c] (7)

Unit vector after its normalisation is

$u_c=\frac{u}{\left|\right|u\left|\right|}$

When controlling point coordinate and principal point measurement of coordinates precision are enough high, the u that formula (8) can be calculated _cThe true value of being used as picture point normalisation space auxiliary coordinate.

Computing value u by picture point normalisation space auxiliary coordinate _sThe observational equation of class is

u _c＝u _s＝R _XYR _GASTR _PNR(pitch)R(roll)R(yaw)u ₁ (9)

R _XYBe Ghandler motion matrix, R _PNBe precession of the equinoxes nutating matrix, R _GASTBe rotation on Sunday matrix.

Take attitude error into account, it is processed as constant.3 components by the image space auxiliary coordinate can be listed as following error equation group to single controlling point:

$\left[\begin{array}{c}{V}_X\\ V_Y\\ V_Z\end{array}\right]={\left[\begin{array}{c}\frac{\∂\left(u_s\right)}{\∂\left(\mathrm{yaw}\right)}\\ \frac{\∂\left(u_s\right)}{\∂\left(\mathrm{roll}\right)}\\ \frac{\∂\left(u_s\right)}{\∂\left(\mathrm{pitch}\right)}\end{array}\right]}^T\left[\begin{array}{c}\mathrm{\Δyaw}\\ \mathrm{\Δroll}\\ \mathrm{\Δpitch}\end{array}\right]-L---\left(10\right)$

Δ pitch, Δ yaw and Δ roll are the attitude angle correction; L is u _cWith u _sDifference between each component, V is observed value correction column matrix.Iterative pitch, yaw and roll.

4, " based on the satellite attitude angle systematic error compensation of strict imaging model " (Lei Yufei etc., spacecraft engineering, in February, 2012)

Under body series, error vector E is

E(Δφ _P，Δφ _r，Δφ _y，ξ)＝V _boby-U _body (11)

φ _P, φ _r, φ _yBe pitch angle, roll angle and yaw angle, Δ φ _P, Δ φ _r, Δ φ _yBe φ _P, φ _r, φ _yCompensation.V _Body, U _BodyBe respectively actual observation vector under body coordinate system; ξ is other uncertain factors that cause position error.Utilize a small amount of controlling point (＞=2), by to attitude angle φ _P, φ _r, φ _yDirect adjustment, like the actual observation vector V _BodyWith desirable measurement vector U _BodyBetween angle minimum, thereby realize the compensation of attitude angle systematic error.

Analyze above-mentioned data and find, have following problem:

The first, research contents mainly concentrates on and extracts manually the controlling point, the systematic error of calibration attitude angle.Survey installation situation and the principle of work aspect analysis of appearance device (as star sensor, gyro, infrared horizon instrument etc.) from star, its attitude data of measuring contains systematic error, long period error and random error etc., only systematic error is carried out calibration and compensation, the geometric positioning accuracy of image is improved degree limited, be difficult to satisfy the application requirements of high-resolution remote sensing image geometric positioning accuracy.The factors such as long period error, random error also can not be ignored the impact of geometric positioning accuracy.

The second, in the process of attitude error calibration, the selection range at controlling point is excessive.Due to the defective of optics design and processing, always there is certain geometric distortion in optical camera, and its value increases to field of view edge gradually from primary optical axis, wide visual field camera particularly, and the distortion of close field of view edge position can reach tens tens pixels even.If the controlling point of choosing is away from primary optical axis, its deviations is that the factor by attitude error and lens distortion two aspects causes jointly, and both decoupling zeros are very difficult.The attitude error that this kind situation solves is also inaccurate.

Summary of the invention

Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation is provided, the method can increase substantially the geometric positioning accuracy of remote sensing picture.

Technical solution of the present invention is: a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation, and step is as follows:

(1) almanac data that star is passed up and down and attitude data carry out validity to be processed, and namely rejects the outlier in data and redefines the value of this point;

(2) determine the extraction scope at controlling point from the one-level image, and determine the Control point extraction scope of reference picture according to the data after processing in this extraction scope and step (1), Control point extraction scope on above-mentioned two images is intercepted out respectively, generate one-level image subgraph and reference picture subgraph; Described one-level image is that reference picture is the orthograph picture through the image after radiant correction;

(3) utilize the one-level image subgraph and the reference picture subgraph that intercept out to carry out the controlling point Auto-matching, and go mispairing to process;

(4) at least 3 pairs of row number different controlling points of the same name of selected distance scape center Euclidean distance minimum are carried out the attitude error value and are calculated on one-level image subgraph and the reference picture subgraph;

(5) utilize the attitude error value of determining that the Optical remote satellite attitude angle is compensated.

On the middle one-level image of described step (2), the extraction scope at controlling point determines to satisfy simultaneously following three principles:

A Control point extraction scope should be take along the scape line of centers of rail direction as rotational symmetry, and the rail direction yardstick that hangs down is as far as possible little; The out to out of the rail direction of hanging down is the radial distortion of camera optics parts at the absolute value of a pixel with interior difference apart from primary optical axis pixel row farthest number and scape center point range number;

B in a scape image as far as possible little along rail direction yardstick;

The pixel number that c Control point extraction scope comprises should satisfy the needs of controlling point Auto-matching.

In described step (2), the Control point extraction scope determining step of reference picture is as follows:

(2.1) ranks of four angle points of the Control point extraction scope determined on the one-level image number are extracted respectively, utilize strict imaging model to carry out forward projection, calculate the longitude and latitude of four angle points;

(2.2) use the longitude of latitude, lower-left angle point and the upper right angle point of upper left angle point and bottom right angle point to delimit a scope;

The scope of (2.3) step (2.2) being delimited extends out at least 50 meters along longitude and latitude direction, obtains the extraction scope at reference picture controlling point.

The implementation procedure of described step (5) is as follows:

Utilize the attitude error value of a scape image that calculates in step (4) to determine that in whole rail, each attitude data is measured attitude angle compensation value constantly, each is measured attitude angle compensation value constantly be added on corresponding attitude angle constantly, complete the compensation of Optical remote satellite attitude angle.

The implementation procedure of described step (5) is as follows:

(5.1) choose many scapes image from whole rail image, every scape image calculates the attitude error value according to the step of step (1)～(4);

(5.2) the attitude error value of step (5.1) being calculated is carried out the validity processing, utilizes its front and back attitude error value constantly to carry out interpolation undesirable attitude error value;

(5.3) the attitude error value after step (5.2) processing is carried out interpolation, obtain each attitude data measurement attitude angle compensation value constantly in whole rail image, each is measured attitude angle compensation value constantly be added on corresponding attitude angle constantly, complete the compensation of Optical remote satellite attitude angle.

The present invention compared with prior art beneficial effect is:

(1) the present invention can be automatically, in real time, calibration accurately goes out the error (wherein having comprised systematic error, long period error and random error etc.) of attitude data, the modeling of comprehensive whole rail error condition realizes the optimization of whole rail attitude data; Thereby increase substantially the geometric positioning accuracy of remote sensing picture.

(2) the invention provides the scheme that the controlling point selection range is determined, can realize the decoupling zero of attitude error and distortion two factors, make the controlling point information of extracting in this zone can characterize exactly the accuracy of positioning deviation that the error by attitude angle causes.

Description of drawings

Fig. 1 is diagram of circuit of the present invention;

Fig. 2 is the definite schematic diagram in Control point extraction of the present invention zone;

Fig. 3 is that attitude error value of the present invention is resolved diagram of circuit;

Fig. 4 be A rail data of the present invention when taking different appearance rail prioritization scheme the secondary image in the deviations distribution situation of X and Y-direction;

Fig. 5 be B rail data of the present invention when taking different appearance rail prioritization scheme the secondary image in the deviations distribution situation of X and Y-direction.

The specific embodiment

The principal element that affects high-resolution optical remote sensing satellite positioning precision comprises timing tracking accuracy on attitude data precision, orbital data precision and star.Adopt current orbit determination technology, can reach meter level as double frequency differential GPS orbit determination accuracy even higher; On the star of satellite, timing tracking accuracy can reach Microsecond grade at present, is 1ms as timing tracking accuracy on star, and satellite velocities is 7.6km/s, and the satellite position deviation that is caused by the asynchronism(-nization) step is 0.44m; But it is larger that satellite is surveyed the appearance difficulty, systematic error in attitude angle, long period error and random error etc. are larger on the impact of geometric positioning accuracy, automatically, in real time, calibration accurately goes out the error of attitude data and compensates, and the image geometry accuracy of positioning is had a more substantial increase.

One, method introduction

The present invention is directed to the problem of the technology existence of mentioning in above-mentioned data, and in conjunction with the level that current satellite is developed, proposed a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation, as shown in Figure 1, concrete steps are as follows:

1 almanac data and attitude data validity are processed

Almanac data and attitude data are to extract from the auxiliary data that star passes up and down.Due at a time or survey appearance in a certain period and survey the mode of operation at that time of rail instrument and may occur extremely, and the reason such as number biography error codes, outlier may appear in almanac data and attitude data.Validity is processed and exactly outlier is rejected and recomputated the value of this point.

1.1 almanac data validity is processed

It is to utilize moment almanac data on every side that these data are constantly verified that almanac data validity is processed, and concrete grammar is as follows:

p _iAnd v _iThe position satellite is in the position vector in the i moment and the observed reading of speed vector respectively.Use p _iAnd v _i, prediction i+1 is position vector and the speed vector of satellite constantly, obtains predictor

With

When satellite at i+1 position vector observed reading p constantly _i+1And predictor

The mould of difference value vector less than threshold delta _p, speed vector observed reading v _i+1And predictor

The mould of difference value vector less than threshold delta _vThe time, think p _i+1And v _i+1Effectively.Otherwise think invalid.When invalid value (wild value) occurring, around the method utilization of employing interpolation, the coordinate Calculation of 8 points goes out the coordinate figure of this point.

1.2 attitude data validity is processed

It is to utilize moment attitude data on every side that these data are constantly verified that attitude data validity is processed, and concrete verification method is as follows:

|ξ _i+1-(ξ _i+ξ _i′(t _i+1-t _i))|＜δ (12)

ξ wherein _iAnd ξ _i' be attitude data ξ _i+1The attitude data of previous moment and attitude rate, δ are threshold value, can set according to actual conditions.Above occurring not meeting during the bad point (outlier) of condition, just with around point interpolation obtain the value of current point.

2 Control point extractions are regional to be determined

The method that the Control point extraction zone is determined is mainly based on following 3 principles:

1) decoupling zero of attitude error and lens distortion, the controlling point information of choosing can characterize the accuracy of positioning deviation that the error by attitude angle causes exactly;

2) during the Auto-matching of controlling point, this area division can satisfy the calculating needs of feature point extraction and coupling;

3) scope definite on the Control point extraction scope of determining on the one-level image and reference picture is consistent as far as possible.

According to above-mentioned 3 principles, definite method in Control point extraction zone is specific as follows:

At first, should first determine scope from the one-level image.1) there is distortion in camera lens, increase gradually from the primary optical axis to the lens edge, the controlling point of choosing is the closer to primary optical axis, and the deviations that distortion causes is less, therefore the Control point extraction scope should be take along the scape line of centers of rail direction as rotational symmetry, and the rail direction yardstick that hangs down is as far as possible little.Can be according to the mirror image distortion model of camera optics parts, calculate distortion at a pixel with interior apart from primary optical axis pixel row farthest number, the pixel at this row number and scape center is listed as number subtracts each other and take absolute value, with this out to out as the rail direction of hanging down, realized the decoupling zero of attitude error and lens distortion.2) if the imaging time span of each identical point is large, find the solution the attitude offset angle by its ranks on the one-level image number and the longitude and latitude on reference picture, can cause solving precision not high, therefore should be as far as possible little along rail direction yardstick when delimiting the Control point extraction scope along the rail direction.3) Auto-matching algorithm in controlling point is when extracting and matching feature points, need the point of some to participate in calculating, if that chooses is regional too small, there is no enough counting, can cause feature point extraction or it fails to match, therefore when the Control point extraction scope is determined, can not pursue simply too small along the yardstick of rail and vertical rail direction, should at first guarantee this scope enough feature point extraction of pixel number that comprise and the needs that mate calculating.For convenience of determining Control point extraction scope corresponding on reference picture, the extraction scope on the one-level image is generally rectangle (or square), determines that by the mode that examination is gathered the extraction scope makes it to satisfy simultaneously above-mentioned three principles.

Then, according to the Control point extraction scope of determining on the one-level image, determine the Control point extraction scope of reference picture.the ranks of four angle points of the Control point extraction scope determined on the one-level image number are extracted respectively, utilize strict imaging model to carry out forward projection, (strict imaging model is that the multicenter projection approximation with spaceborne line array CCD is single center projection to calculate the longitude and latitude of four angle points, setting up corresponding relation between ground point and imaging point by a series of coordinate transformation on the basis of collinearity condition equation, soon the image space observation vector is completed successively from the focal plane coordinate and is tied to sensor coordinate system, be tied to the satellite body system of axes from sensor coordinates, from the satellite body to the orbital coordinate system, consolidate a series of coordinate transformation of system from orbit coordinate with being tied to, obtain the observation vector under ground is admittedly, again with the position vector addition of satellite, thereby obtain ground point location).Longitude with latitude, lower-left angle point and the upper right angle point of upper left angle point and bottom right delimited a scope.Consider that there is error in appearance rail data, try one's best consistent (or at utmost comprising) with the zone on corresponding one-level image for zone that guarantee to delimit, need extend out at least 50 meters with reference to this scope of delimiting on image along longitude and latitude direction.

Determined the Control point extraction scope, it is intercepted out, the spanning subgraph picture.

In the present invention, take near the method for intercepting subgraph one-level image scape center, shown in Fig. 2 (annotate: this figure is the schematic diagram that the Control point extraction scope is determined, but not true ratio).

3 controlling point Auto-matchings

1) the SIFT algorithm carries out the controlling point Auto-matching

Do the controlling point Auto-matching with intercepting one-level image subgraph and reference picture subgraph out.With respect to the rotation that certain angle is arranged on the one-level image (greater than 10 °), the present invention has selected the SIFT algorithm industry maturation, that matching capacity is stronger when Auto-matching due to the atural object on reference picture.This algorithm can be processed the matching problem that occurs between two width images in translation, rotation, affined transformation situation preferably.After the SIFT proper vector of two width images generates, adopt the Euclidean distance of key point proper vector as the similarity determination tolerance of key point in two width images.

The SIFT characteristic matching has adopted simple effective method, and namely the ratio of the minimum euclidean distance between 128 dimension description vectors of two width image key points and time little Euclidean distance is less than certain threshold xi _mcThe time, think that feature is to mating.ξ _mcLess, mismatch rate lower.Counting due to the control of the same name that participates in the attitude error angle calculating is 6 (as described below), even a mispairing point occurs, on attitude error angle calculation accuracy impact be also very large, so establish ξ in the present invention _mc=0.4.

2) go mispairing to process with the RANSAC algorithm

Although SIFT algorithmic match ability is stronger, still can not avoid occurring mispairing (when occurring the same or similar scenery of large tracts of land in image, being prone to mispairing), so need to go mispairing to process.Adopt the RANSAC algorithm to go mispairing to process in the present invention.The RANSAC algorithm has been widely used in eliminating mispairing at present, and it can improve the characteristic matching effect of SIFT algorithm to a certain extent.

The RANSAC algorithm is by carrying out multi-times random sampling to matching point, each random taking-up is the least possible but abundant a plurality of matching point is determined model parameter, according to fixed model, all matching points are divided again, part matching point is considered as interior point in the certain error scope of this model, a part of data are considered as exterior point outside error limit.Because exterior point is rambling abnormal data, its determined model, the matching point that drops in error limit occupies the minority, and most of matching point all drops on outside error limit.And to by the determined Model approximation of interior point in real model, most of matching points will drop in error limit.After the multi-times random sampling test, the RANSAC algorithm is found out the set that drops on matching points maximum in error limit, then gathers to do optimization with this, finally determines the parameter of model.

3) choosing a fixed point resolves participating in the attitude error value

After going mispairing, selected distance scape center Euclidean distance minimum some to (establishing its value and be n _GCP, in this example, n _GCP=6) row number different controlling point of the same name participates in the calculating of attitude error value; If the controlling point logarithm that success is mated is less than n _GCP, the attitude error value that is considered as this scape is calculated unsuccessfully, carries out next attitude data measurement attitude error value constantly and resolves.

Extract the ranks of controlling point on the one-level subgraph number (m, n), at the longitude and latitude (lon, lat) of reference subgraph.

4 attitude error values are resolved

The attitude error value is resolved and is adopted the forward model method, and calculation process as shown in Figure 3.

Flow process mainly is divided into 2 the tunnel, one the tunnel is the ranks information (m at the controlling point that will be extracted by 1 grade of image, n), through a series of coordinate transformation, obtain the nominal observation vector u of imaging vector in controlling point in the satellite body system of axes under the system of axes of camera focal plane _SATAnother road is with by the controlling point latitude and longitude information (lon of the same name that extracts in reference picture, lat) and the altitude figures information (h) of extracting from the altitude figures file, calculate through a series of system of axes conversions and vector, obtain the actual observation vector of controlling point of the same name under the satellite body system of axes

Concrete steps are as follows:

1) calculate image space observation vector u according to row n, pixel dimension, pixel number and the focal distance f at controlling point on the one-level image _FP

u _FP＝[x/f，y/f，1] ^T。

X=0 wherein $y=y_{\mathrm{pixel}}\·(n-\frac{N_{\mathrm{pixel}}+1}{2}),$

y _PixelBe pixel dimension, N _PixelBe the pixel number.

2) with image space observation vector u _FPBe converted to the vectorial u under sensor coordinate system _SEN

u _SEN＝T _SEN/FP×u _FP。

Wherein, T _SEN/FPBe tied to the transition matrix of sensor coordinate system for the focal plane coordinate.

3) with the vectorial u under sensor coordinate system _SENBe transformed into the vectorial u under the satellite body system of axes _SAT

u _SAT＝T _SAT/SEN×u _SI。

Wherein, T _SAT/SENBe tied to the transition matrix of satellite body system of axes for sensor coordinates, i.e. the installation matrix of sensor.

4) be coordinate (X, Y, Z) admittedly with reference to the latitude and longitude information (lon, lat) at controlling point of the same name on image and the elevation information (h) in the altitude figures file with being converted to _ECR

X＝(N+h)·cos(Lat/180·π)·cos(Lon/180·π)

Y＝(N+h)·cos(Lat/180·π)·sin(Lon/180·π)

Z＝(N+h)·e ²·sin(Lat/180·π)

Wherein, a, b are respectively the long and short axle radius of the earth.e ²＝1-b ²/a ²，

$N=\frac{a}{{(1-e^2\·{\sin }^2(\mathrm{Lat}/180\·\mathrm{\π}))}^{1/2}}.$

5) ground according to controlling point of the same name is coordinate (X, Y, Z) admittedly _ECRWith this imaging almanac data (P constantly _X, P _Y, P _Z), generate the measurement vector under the solid system in ground

${\hat{u}}_{\mathrm{ECR}}={[X-P_X,Y-P_Y,Z-P_Z]}^T$

6) measurement vector under with ground being admittedly converts the measurement vector under track system to

$\hat{u}\mathrm{ORB}=T_{\mathrm{ORB}/\mathrm{ECR}}\×\hat{u}\mathrm{ECR}$

Wherein, T _ORB/ECRAdmittedly be tied to the transition matrix of track system for ground,

$T_{\mathrm{ORB}/\mathrm{ECR}}={\left[\begin{array}{ccc}{\hat{b}}_1& {\hat{b}}_2& {\hat{b}}_3\end{array}\right]}^{-1}$

${\hat{b}}_3=-P/\left|\right|P\left|\right|$

${\hat{b}}_2=({\hat{b}}_3\×V)/\left|\right|{\hat{b}}_3\×V\left|\right|$

${\hat{b}}_1={\hat{b}}_2\×{\hat{b}}_3$

Satellite position vector (the P that P provides for almanac data _X, P _Y, P _Z), the satellite velocity vector (V that V provides for almanac data _X, V _Y, V _Z), || || be the compute sign of the mould of vector.

7) with the measurement vector under track system Convert the observation vector under the satellite body system of axes to

$\hat{u}\mathrm{SAT}=T_{\mathrm{SAT}/\mathrm{ORB}}\×\hat{u}\mathrm{ORB}$

T wherein _SAT/ORBBe tied to the transition matrix of satellite body system for track,

$T_{\mathrm{ORB}/\mathrm{SAT}}=\left[\begin{array}{ccc}\cos {\mathrm{\&xi;}}_Y& \sin {\mathrm{\&xi;}}_Y& 0\\ -\sin {\mathrm{\&xi;}}_Y& \cos {\mathrm{\&xi;}}_{\mathrm{<figure-callout\; id="0"\; label="Y"\; filenames="HDA00002868491900022.png,HDA00002868491900031.png"\; state="\{\{state\}\}">Y</figure-callout>}}& 0\\ 0& 0& 1\end{array}\right]\left[\begin{array}{ccc}1& 0& 0\\ 0& \cos {\mathrm{\&xi;}}_R& \sin {\mathrm{\&xi;}}_R\\ 0& -\sin {\mathrm{\&xi;}}_R& \cos {\mathrm{\&xi;}}_R\end{array}\right]\left[\begin{array}{ccc}\cos {\mathrm{\&xi;}}_P& 0& -\sin {\mathrm{\&xi;}}_{\mathrm{<figure-callout\; id="0"\; label="P"\; filenames="HDA00002868491900022.png,HDA00002868491900031.png"\; state="\{\{state\}\}">P</figure-callout>}}\\ 0& 1& 0\\ \sin {\mathrm{\&xi;}}_{\mathrm{<figure-callout\; id="0"\; label="P"\; filenames="HDA00002868491900022.png,HDA00002868491900031.png"\; state="\{\{state\}\}">P</figure-callout>}}& 0& \cos {\mathrm{\&xi;}}_P\end{array}\right]$

8) find the solution attitude error value (Δ ξ _Y, Δ ξ _R, Δ ξ _P)

$\hat{u}\mathrm{SAT}=R(\mathrm{\&Delta;}{\mathrm{\&xi;}}_Y,\mathrm{\&Delta;}{\mathrm{\&xi;}}_R,\mathrm{\&Delta;}{\mathrm{\&xi;}}_P)u_{\mathrm{SAT}}$

Wherein R is by attitude error R (Δ ξ _Y, Δ ξ _R, Δ ξ _P) the matrix that forms of function,

$R=\left[\begin{array}{ccc}\cos \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_Y\right)& -\sin \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_Y\right)& 0\\ \sin \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_Y\right)& \cos \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_Y\right)& 0\\ 0& 0& 1\end{array}\right]\left[\begin{array}{ccc}1& 0& 0\\ 0& \cos \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_R\right)& -\sin \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_R\right)\\ 0& \sin \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_R\right)& \cos \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_R\right)\end{array}\right]\left[\begin{array}{ccc}\cos \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_P\right)& 0& \sin \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_P\right)\\ 0& 1& 0\\ -\sin \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_P\right)& 0& \cos \left(\mathrm{\&Delta;}{\mathrm{\&xi;}}_P\right)\end{array}\right]$

The compensation of 5 Optical remote satellite attitude angle

Satellite attitude angle compensation in this step is when accuracy requirement is not high, can adopt the attitude error value of a scape image that calculates in above-mentioned four steps to compensate, need to determine that in whole rail, each attitude data is measured attitude angle compensation value constantly this moment according to the attitude error value of calculating, each is measured attitude angle compensation value constantly be added on corresponding attitude angle constantly, complete the compensation of Optical remote satellite attitude angle.In whole rail, each attitude data measurement attitude angle compensation value constantly can be identical with the attitude error value of calculating.

In order to submit precision to, the compensation process of attitude angle can also adopt following manner to carry out:

(5.1) choose many scapes image from whole rail image, every scape image calculates the attitude error value according to the step of step (1)～(4);

(5.2) the attitude error value of step (5.1) being calculated is carried out the validity processing, utilizes its front and back attitude error value constantly to carry out interpolation undesirable attitude error value;

Although carried out going mispairing to process, but still can not guarantee that 100% eliminates the mispairing point, need to carry out validity to the attitude error value of whole rail and process.According to the image position accuracy situation before the attitude error compensation, survey appearance, orbit measuring precision and timing tracking accuracy in conjunction with this satellite, the threshold value of setting attitude error (is made as ζ, ζ=0.1 ° for example), when attitude error is worth less than this, thinks and calculate correctly, otherwise think and calculate unsuccessfully, abandon this value during failure, before and after needing to utilize, the value of several attitude errors is constantly carried out interpolation to it.During interpolation, at first consider smooth degree interpolation method preferably, adopt linear interpolation when the failure of the method interpolation.

(5.3) the attitude error value after step (5.2) processing is carried out interpolation, obtain each attitude data measurement attitude angle compensation value constantly in whole rail image, each is measured attitude angle compensation value constantly be added on corresponding attitude angle constantly, complete the compensation of Optical remote satellite attitude angle.

Two, method validation

2.1 verification msg explanation

One-level image, almanac data and the attitude data that the present invention checking is adopted processed the digital simulation subsystem of prototype system according to the track of satellite, sensor parameters etc. by XX high-resolution optical remote sensing satellite (grinding) data, utilizes how much imaging models, radiant image model simulations to obtain; In addition, also need according to timing tracking accuracy present situation on almanac data precision, attitude data precision and the star of present satellite, almanac data, attitude data to be added error.

When the present invention is verified, the one-level image has been chosen the simulate data of the satellite of two rails (calling A rail, B rail in the following text) different technologies states: the spatial resolution of A rail data is 2 meters, the almanac data position error is 10 meters (1 σ), and attitude measurement accuracy is 0.003 ° (1 σ); The spatial resolution of B rail data is 1 meter, and the almanac data position error is 1 meter (1 σ), and attitude measurement accuracy is 0.003 ° (1 σ) °

Reference picture derives from certain high precision orthography storehouse, and accuracy of positioning is better than 5 meters; Altitude figures is STRM90, and vertical precision is about 10 meters.

2.2 verification method explanation

In a rail image, in order to improve computational efficiency, be not the calculating that each scape all participates in the attitude error value, but calculate once every some scapes.In order to verify the present invention to the optimization ability of appearance rail data, select respectively appearance rail prioritization scheme in 4: 1. every rail only calculates once, 2. calculates once, 3. calculates once, 4. calculates once every 5 scapes every 10 scapes every 20 scapes.Relatively these four kinds of schemes are to the improved situation of secondary image position accuracy.The accuracy of positioning method of measurement is: every rail is chosen arbitrarily 5 scape secondary images, chooses 6 controlling points in every scape, contrast 6 controlling points at identical point on reference picture deviations and the circular error on directions X and Y-direction.

2.3 the result

When Fig. 4 and Fig. 5 had showed respectively that with the form of scatter diagram A rail and B rail data are taked different appearance rail prioritization scheme, the secondary image was in the deviations distribution situation of X and Y-direction; Table 1 showed when A rail and B rail data are taked different appearance rail prioritization scheme, and the secondary image is in deviations (root of mean square) and the circular error (root of mean square) of X and Y-direction.

The deviations of secondary image when table 1A rail and B rail data are taked different appearance rail prioritization scheme

2.4 the result analysis and conclusion

1) the result analysis

When not doing the appearance rail and optimize, the setting circle error (root of mean square) of A rail and B rail data secondary image is respectively 483.36 meters and 398.57 meters (as shown in table 1); At the deviations of directions X and Y-direction, except having random error, also there is larger systematic error (as shown in Fig. 4 (a) and Fig. 5 (a)).

After adopting the present invention to carry out the optimization of appearance rail, the deviations of A rail and B rail data secondary image obviously reduces.Along with the increase of attitude error value calculated rate, the systematic error of location and random error all have further and reduce.When frequency increased to " calculating an attitude error value every 10 scapes ", the systematic error of location was eliminated substantially, and residual random error is also less, and error amount is more stable, without the larger point of deviations.

2) checking conclusion

The present invention can carry out the optimization of appearance rail to satellite data effectively, makes the accuracy of positioning of secondary image be significantly improved;

For satellite in orbit, can appearance rail data precision real according to it and the user to the requirement of accuracy of positioning with require the frequency of determining that the attitude error value is calculated computing time.

The unspecified part of the present invention belongs to general knowledge as well known to those skilled in the art.

Claims (5)

1. Optical remote satellite attitude error dynamic compensation method based on ground navigation is characterized in that step is as follows:

(1) almanac data that star is passed up and down and attitude data carry out validity to be processed, and namely rejects the outlier in data and redefines the value of this point;

(2) determine the extraction scope at controlling point from the one-level image, and determine the Control point extraction scope of reference picture according to the data after processing in this extraction scope and step (1), Control point extraction scope on above-mentioned two images is intercepted out respectively, generate one-level image subgraph and reference picture subgraph; Described one-level image is that reference picture is the orthograph picture through the image after radiant correction;

(3) utilize the one-level image subgraph and the reference picture subgraph that intercept out to carry out the controlling point Auto-matching, and go mispairing to process;

(4) at least 3 pairs of row number different controlling points of the same name of selected distance scape center Euclidean distance minimum are carried out the attitude error value and are calculated on one-level image subgraph and the reference picture subgraph;

(5) utilize the attitude error value of determining that the Optical remote satellite attitude angle is compensated.

2. a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation according to claim 1 is characterized in that: in described step (2) on the one-level image extraction scope at controlling point determine to satisfy simultaneously following three principles:

A Control point extraction scope should be take along the scape line of centers of rail direction as rotational symmetry, and the rail direction yardstick that hangs down is as far as possible little; The out to out of the rail direction of hanging down is the radial distortion of camera optics parts at the absolute value of a pixel with interior difference apart from primary optical axis pixel row farthest number and scape center point range number;

B in a scape image as far as possible little along rail direction yardstick;

The pixel number that c Control point extraction scope comprises should satisfy the needs of controlling point Auto-matching.

3. a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation according to claim 1 is characterized in that: in described step (2), the Control point extraction scope determining step of reference picture is as follows:

(2.1) ranks of four angle points of the Control point extraction scope determined on the one-level image number are extracted respectively, utilize strict imaging model to carry out forward projection, calculate the longitude and latitude of four angle points;

(2.2) use the longitude of latitude, lower-left angle point and the upper right angle point of upper left angle point and bottom right angle point to delimit a scope;

The scope of (2.3) step (2.2) being delimited extends out at least 50 meters along longitude and latitude direction, obtains the extraction scope at reference picture controlling point.

4. a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation according to claim 1, it is characterized in that: the implementation procedure of described step (5) is as follows:

Utilize the attitude error value of a scape image that calculates in step (4) to determine that in whole rail, each attitude data is measured attitude angle compensation value constantly, each is measured attitude angle compensation value constantly be added on corresponding attitude angle constantly, complete the compensation of Optical remote satellite attitude angle.

5. a kind of Optical remote satellite attitude error dynamic compensation method based on ground navigation according to claim 1, it is characterized in that: the implementation procedure of described step (5) is as follows:

(5.1) choose many scapes image from whole rail image, every scape image calculates the attitude error value according to the step of step (1)～(4);

(5.2) the attitude error value of step (5.1) being calculated is carried out the validity processing, utilizes its front and back attitude error value constantly to carry out interpolation undesirable attitude error value;

(5.3) the attitude error value after step (5.2) processing is carried out interpolation, obtain each attitude data measurement attitude angle compensation value constantly in whole rail image, each is measured attitude angle compensation value constantly be added on corresponding attitude angle constantly, complete the compensation of Optical remote satellite attitude angle.

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