CN112816184A - Uncontrolled calibration method and device for optical remote sensing satellite - Google Patents

Uncontrolled calibration method and device for optical remote sensing satellite Download PDF

Info

Publication number
CN112816184A
CN112816184A CN202011496811.7A CN202011496811A CN112816184A CN 112816184 A CN112816184 A CN 112816184A CN 202011496811 A CN202011496811 A CN 202011496811A CN 112816184 A CN112816184 A CN 112816184A
Authority
CN
China
Prior art keywords
ccd
image
parameters
rpc
virtual
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202011496811.7A
Other languages
Chinese (zh)
Inventor
方舟
陈付亮
李龙飞
李岩
许萌
汪松
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Space Star Technology Co Ltd
Original Assignee
Space Star Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Space Star Technology Co Ltd filed Critical Space Star Technology Co Ltd
Priority to CN202011496811.7A priority Critical patent/CN112816184A/en
Publication of CN112816184A publication Critical patent/CN112816184A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
    • G01M11/02—Testing optical properties
    • G01M11/0242—Testing optical properties by measuring geometrical properties or aberrations
    • G01M11/0257—Testing optical properties by measuring geometrical properties or aberrations by analyzing the image formed by the object to be tested
    • G01M11/0264—Testing optical properties by measuring geometrical properties or aberrations by analyzing the image formed by the object to be tested by using targets or reference patterns
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/20—Integrity monitoring, fault detection or fault isolation of space segment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Theoretical Computer Science (AREA)
  • Geometry (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Manufacturing & Machinery (AREA)
  • Image Processing (AREA)

Abstract

The invention discloses an uncontrolled calibration method and a device of an optical remote sensing satellite, wherein the method comprises the following steps: respectively acquiring imaging parameters of each CCD, wherein the imaging parameters comprise: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters; establishing virtual CCD imaging parameters according to the imaging parameters of each CCD; performing sensor correction according to the imaging parameters of each CCD and the virtual CCD imaging parameters to obtain an image and RPC parameters after the sensor correction; and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters. The uncontrolled calibration method of the optical remote sensing satellite disclosed by the invention can improve the positioning accuracy of the optical remote sensing satellite.

Description

Uncontrolled calibration method and device for optical remote sensing satellite
Technical Field
The invention belongs to the technical field of spaceflight, and particularly relates to an uncontrolled calibration method of an optical remote sensing satellite.
Background
The system geometry correction algorithm mainly calculates the longitude and latitude of the grid points based on an imaging collinear equation according to the track parameters, the attitude parameters and the camera imaging parameters, and compares the positioning accuracy by using the image points and the control points after resampling the product.
In an ideal flight state of the satellite platform, the platform is parallel to the ground and has a certain flight height, and at the moment, the imaging area of the camera on the platform is rectangular and has the same resolution as that set by the image matching system. However, the platform suffers from images of various interference factors in the flying process, so that the platform has certain attitude deviation and flying height deviation, and the attitude deviation and the flying height deviation appear in the imaging of the camera, so that the imaging area of the camera deviates from the ideal condition, and the shot image generates geometric distortion. Therefore, accurate attitude parameters are obtained, which is the core of the system geometric correction algorithm, and high-precision geometric positioning precision can be obtained.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the existing optical remote sensing satellite calibration method has the problem of low positioning accuracy.
In order to solve the technical problem, the invention discloses an uncontrolled calibration method of an optical remote sensing satellite, wherein the method comprises the following steps:
respectively acquiring imaging parameters of each CCD, wherein the imaging parameters comprise: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters;
establishing virtual CCD imaging parameters according to the imaging parameters of each CCD;
performing sensor correction according to the imaging parameters of each CCD and the virtual CCD imaging parameters to obtain an image and RPC parameters after the sensor correction;
and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters.
Optionally, the step of performing sensor correction according to the imaging parameters of each CCD and the imaging parameters of the virtual CCD to obtain an image after sensor correction and RPC parameters includes:
constructing an imaging model of each CCD according to the imaging parameters of each CCD;
positioning the ground positions of four corner points of a virtual CCD scanning scene to acquire the elevation range of an imaging area;
respectively establishing a forward and backward calculation model between the image point on each CCD and the ground point;
constructing an imaging model of each virtual CCD based on the virtual CCD imaging parameters;
establishing an RPC model of the virtual CCD, and resolving RPC parameters;
and establishing a positive and negative calculation model between the image point of the virtual CCD and the ground.
Optionally, the step of calculating the ground coordinates according to the image and the RPC parameters corrected by the sensor includes:
establishing a back calculation model between each CCD image point and the virtual CCD image point coordinates;
acquiring the scanning start time and the scanning end time of the virtual CCD, and determining the height of a virtual scene;
acquiring original image data acquired by each CCD;
respectively determining an original CCD film number and an image point coordinate corresponding to each pixel in the virtual CCD, and generating a report file;
and calculating the ground coordinates according to the report file and the RPC file.
Optionally, the step of calculating the ground coordinates according to the report file and the RPC file includes:
acquiring image width and height information from the report file;
obtaining a PFM coefficient from the RPC file;
calculating the longitude and latitude of four corner points and the longitude and latitude of a center of the image based on the image width and height information and the PFM coefficient;
establishing a conversion relation between longitude and latitude and the projection X, Y;
establishing the size of an output image and the conversion relation between the row and column numbers of the output image and the coordinates of a projection X, Y according to the X, Y coordinates of the projections at the four corners of the image and the resampling resolution;
calculating the projection X, Y and longitude and latitude of each pixel for each row and column of the output image;
and aiming at each pixel, calculating the row and column number of the pixel in the input image by using RPC according to the longitude and latitude and the average elevation of the pixel.
In order to solve the technical problem, the invention discloses an uncontrolled calibration device of an optical remote sensing satellite, wherein the device comprises:
the acquiring module is used for respectively acquiring imaging parameters of each CCD, wherein the imaging parameters comprise: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters;
the first establishing module is used for establishing virtual CCD imaging parameters according to the imaging parameters of each CCD;
the correction module is used for correcting the sensor according to the imaging parameters of each CCD and the imaging parameters of the virtual CCD to obtain an image and RPC parameters after the sensor is corrected;
and the calculation module is used for calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters.
Optionally, the correction module includes:
the first sub-module is used for constructing an imaging model of each CCD according to the imaging parameters of each CCD;
the second sub-module is used for positioning the ground positions of four corner points of the virtual CCD scanning scene and acquiring the elevation range of the imaging area;
the third sub-module is used for respectively establishing a forward and backward calculation model between the image point and the ground point on each CCD;
the fourth sub-module is used for constructing an imaging model of each virtual CCD based on the virtual CCD imaging parameters;
the fifth sub-module is used for establishing an RPC model of the virtual CCD and resolving RPC parameters;
and the sixth submodule is used for establishing a positive and negative calculation model between the image point of the virtual CCD and the ground.
Optionally, the calculation module includes:
the seventh sub-module is used for establishing a back calculation model between each CCD image point and the virtual CCD image point coordinates;
the eighth submodule is used for acquiring the scanning start time and the scanning end time of the virtual CCD and determining the height of a virtual scene;
a ninth sub-module, configured to obtain original image data obtained by each CCD;
the tenth submodule is used for respectively determining an original CCD film number and an image point coordinate corresponding to each pixel element in the virtual CCD and generating a report file;
and the eleventh submodule is used for calculating the ground coordinates according to the report file and the RPC file.
Optionally, the eleventh sub-module is specifically configured to:
acquiring image width and height information from the report file;
obtaining a PFM coefficient from the RPC file;
calculating the longitude and latitude of four corner points and the longitude and latitude of a center of the image based on the image width and height information and the PFM coefficient;
establishing a conversion relation between longitude and latitude and the projection X, Y;
establishing the size of an output image and the conversion relation between the row and column numbers of the output image and the coordinates of a projection X, Y according to the X, Y coordinates of the projections at the four corners of the image and the resampling resolution;
calculating the projection X, Y and longitude and latitude of each pixel for each row and column of the output image;
and aiming at each pixel, calculating the row and column number of the pixel in the input image by using RPC according to the longitude and latitude and the average elevation of the pixel.
The invention has the following advantages:
the embodiment of the invention discloses an inter-band calibration method of an optical remote sensing satellite, which respectively obtains imaging parameters of each CCD (Charge Coupled Device); establishing virtual CCD imaging parameters according to the imaging parameters of each CCD; performing sensor correction according to the imaging parameters of each CCD and the imaging parameters of the virtual CCD to obtain an image after the sensor correction and RPC (Rational Polynomial Coefficient) parameters; and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters. The method carries out uncontrolled positioning on the remote sensing image based on the double-vector attitude determination algorithm, and can improve the positioning precision.
Drawings
FIG. 1 is a flowchart illustrating steps of an uncontrolled calibration method for an optical remote sensing satellite according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of a method for uncontrolled calibration of an optical remote sensing satellite according to another embodiment of the present invention;
fig. 3 is a block diagram of an uncontrolled calibration apparatus for an optical remote sensing satellite according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to specific embodiments and with reference to the attached drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The vector attitude sensor is an attitude measurement component widely applied to the aircraft, and the attitude of the aircraft can be determined by utilizing vector observation information. Common algorithms for solving the three-axis attitude based on vector observation include a TRIAD algorithm and a QUEST algorithm, but the algorithms are rarely applied to remote sensing satellite image processing, and effective paper and work research is not found in the application. In the implementation of the method, whether the satellite uncontrolled geometric positioning precision (plane) meets the index requirement is tested by calibrating external orientation elements (bias matrixes) of all cameras of the satellite. The attitude of the aircraft is directly determined by utilizing two or more vector observations, the attitude of the aircraft is determined by utilizing the two vector observations in a sampling TRIAD algorithm according to the characteristics of a certain satellite, vector observation information containing the attitude condition of the aircraft is obtained by measuring the direction of a selected reference celestial body relative to the aircraft, and the attitude of the aircraft can be determined by utilizing the vector observation information.
An algorithm for solving the three-axis attitude based on vector observations utilizes two or more vector observations to directly determine the attitude of the aircraft. According to the characteristics of a certain satellite, the attitude of the aircraft is determined by utilizing two vector observations in a sampling TRIAD algorithm. The specific principle of the algorithm is as follows:
the TRIAD is an algorithm for solving the three-axis attitude based on vector observation, which is simple in calculation and high in calculation speed, and is known to have two non-parallel unit reference vectors r1 and r2 in a reference coordinate system, the unit observation vectors measured in a body coordinate system are b1 and b2 respectively, and new orthogonal coordinate systems L, S are established in the reference coordinate system and the body coordinate system respectively, and the unit vectors of all coordinate axes in the L and S coordinate systems are as follows:
Figure RE-GDA0003008147630000051
then there is a unique orthogonal attitude matrix a that satisfies:
Figure RE-GDA0003008147630000061
according to the principle of satellite photogrammetry, taking the flight direction as the X direction, the basic model of image positioning can be expressed as:
Figure RE-GDA0003008147630000062
in the formula
Figure RE-GDA0003008147630000063
Coordinates of a feature point P corresponding to the image point P in a WGS84 coordinate system;
Figure RE-GDA0003008147630000064
coordinates of the satellite in the WGS84 coordinate system when imaging the feature point P; λ is the scale factor; rEOIs a transformation matrix from an orbit coordinate system to a WGS84 coordinate systemAs a function of time t, the specific expression is:
Figure RE-GDA0003008147630000065
wherein
Figure RE-GDA0003008147630000066
Figure RE-GDA0003008147630000067
The speeds of the satellite motion in the X, Y and Z axial directions when the ground object point P is imaged;
ROBthe transformation matrix from the body coordinate system to the orbit coordinate system is a function of time t and can be expressed as:
Figure RE-GDA0003008147630000068
wherein
Figure RE-GDA0003008147630000069
Is pitch angle, omega is roll angle, kappa is yaw angle;
RBCthe method is characterized in that the method is a conversion matrix from a camera coordinate system to a body coordinate system, namely an installation matrix of a camera relative to a satellite, and can be considered as a unit matrix under an ideal condition;
RCDis a transformation matrix from the sensor coordinate system to the camera coordinate system, i.e. a position matrix of the camera optical axis relative to the camera, which matrix can be understood as the yaw ψ of the sensor in the track directionxAngle imaging, which can be specifically expressed as:
RCD＝R1(-ψx) (4)
in the formula: x is the coordinate of an image point p on the CCD array; (x)0 y0) The coordinates of the image principal point in an image plane coordinate system are obtained; f is the sensor focal length.
According to the basic image localization model described by the foregoing localization theory, equation (3) can be transformed as follows:
Figure RE-GDA0003008147630000071
namely:
Figure RE-GDA0003008147630000072
Figure RE-GDA0003008147630000073
in the formula, y is the coordinate of a pixel on a single scanning line; x is the number of0,y0F is the internal orientation element of the image; a isi,bi,ci(i ═ 1,2,3) direction cosine variables for satellite position and velocity, satellite attitude parameters, into which the orthogonal attitude matrix a obtained from the double vector constants is substituted; λ is the scale factor; xS,YS,ZSWGS-84 coordinates for the satellite at the shooting site; x, Y and Z are coordinates of the ground object point in a WGS-84 coordinate system; (x) and (y) are coordinates of the equivalent image.
The results of the uncontrolled positioning accuracy of the images before and after double-vector attitude determination are shown in the following table, and it can be seen that the satellite attitude accuracy obtained by double-vector attitude determination is higher, and the index requirements of the system on the uncontrolled positioning accuracy are met.
Figure RE-GDA0003008147630000074
The following describes an uncontrolled calibration method of the optical remote sensing satellite based on the above principle.
Fig. 1 is a flowchart illustrating steps of an uncontrolled positioning method for an optical remote sensing satellite according to an embodiment of the present invention.
The uncontrolled calibration method of the optical remote sensing satellite comprises the following steps:
step 101: and respectively acquiring the imaging parameters of each CCD.
Wherein the imaging parameters include: true internal orientation elements, down-going time, down-going trajectory, aircraft attitude determined using at least two vector observations, and installation parameters. The aircraft attitude is the descent attitude.
In the embodiment of the invention, the attitude of the aircraft is directly determined by utilizing a TRIAD double-vector attitude determination algorithm, namely two or more vectors are observed, and the external orientation elements (bias matrix) of each camera of the satellite are calibrated.
Step 102: and establishing virtual CCD imaging parameters according to the imaging parameters of each CCD.
Step 103: and correcting the sensor according to the imaging parameters of each CCD and the imaging parameters of the virtual CCD to obtain an image and RPC parameters after the sensor is corrected.
When the sensor is corrected, data splicing among CCDs in the camera and splicing among cameras are achieved through a virtual CCD splicing technology, band registration among panchromatic, multispectral and multispectral is achieved, camera distortion is removed, and high-precision RPC parameters are provided.
Step 104: and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters.
The method is carried out on the basis of the sensor correction, namely, images and RPC parameters after the sensor correction are input, and ground coordinates are calculated, wherein the ground coordinates comprise: longitude, latitude and elevation (X, Y, Z), and the image row and column numbers (r, c) corresponding to the pixels.
In the actual implementation process, the ground control points can be used for measuring the uncontrolled positioning precision of the system geometric correction image.
The method for calibrating the optical remote sensing satellite between the wave bands, provided by the embodiment of the invention, respectively obtains the imaging parameters of each CCD; establishing virtual CCD imaging parameters according to the imaging parameters of each CCD; correcting the sensor according to the imaging parameters of each CCD and the imaging parameters of the virtual CCD to obtain an image and RPC parameters after the sensor is corrected; and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters. The method carries out uncontrolled positioning on the remote sensing image based on the double-vector attitude determination algorithm, and can improve the positioning precision.
Fig. 2 is a flowchart illustrating steps of another method for uncontrolled positioning of an optical remote sensing satellite according to an embodiment of the present invention.
In the embodiment of the invention, when the uncontrolled calibration of the optical remote sensing satellite is carried out, the uncontrolled calibration precision of the optical remote sensing satellite is judged and is applied to the on-orbit geometric calibration of the satellite; directly determining the attitude of the aircraft by using two or more vector observations, calibrating external orientation elements (bias matrix) of each camera of the satellite, and measuring the uncontrolled geometric positioning accuracy (plane) of the satellite during the in-orbit period of the optical remote sensing satellite; the measurement result of the geometric positioning precision of the reaction plane meets the requirement of geometric calibration and verification of the optical remote sensing satellite.
The uncontrolled calibration method of the optical remote sensing satellite provided by the embodiment of the invention specifically comprises the following steps:
step 201: and respectively acquiring the imaging parameters of each CCD.
Wherein the imaging parameters include: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters; the aircraft attitude is the descent attitude.
Step 202: and establishing virtual CCD imaging parameters according to the imaging parameters of each CCD.
Step 203: and constructing an imaging model of each virtual CCD based on the imaging parameters of the virtual CCDs.
Step 204: and establishing an RPC model of the virtual CCD, and resolving RPC parameters.
Step 205: and establishing a positive and negative calculation model between the image point of the virtual CCD and the ground.
In steps 202 to 205, data splicing between CCDs in the camera and splicing between cameras, band registration between panchromatic and multispectral and between multispectral are realized by adopting a virtual CCD splicing technology, camera distortion is removed, and high-precision RPC parameters are provided.
Step 206: and constructing an imaging model of each CCD according to the imaging parameters of each CCD.
Step 207: and positioning the ground positions of four corner points of the virtual CCD scanning scene to acquire the elevation range of the imaging area.
Step 208: and respectively establishing a forward and backward calculation model between the image point on each CCD and the ground point.
Step 209: and establishing a back calculation model between each CCD image point and the virtual CCD image point coordinates.
Step 210: and acquiring the scanning start time and the scanning end time of the virtual CCD, and determining the height of the virtual scene.
Step 211: and acquiring original image data acquired by each CCD.
Step 212: and aiming at each pixel in the virtual CCD, solving the corresponding original CCD chip number and the pixel point coordinate.
Step 213: and pixel-by-pixel resampling processing.
Step 212 to step 213, to determine the original CCD slice number and the image point coordinates corresponding to each pixel element in the virtual CCD, respectively, to generate a specific implementation of the report file. The report file is an SC message.
Step 214: closing the file and releasing the memory.
After the file is closed and the memory is released, the ground coordinates can be calculated according to the report file and the RPC file. The specific calculation mode refers to the subsequent related flow.
Step 215: and acquiring image width and height information from the report file.
Step 216: and obtaining the PFM coefficient from the RPC file.
Step 217: and calculating the longitude and latitude of four corner points and the longitude and latitude of the center of the image based on the width and height information of the image and the PFM coefficient.
Step 218: a translation of latitude and longitude is established with projection X, Y.
Step 219: the size of the output image and the conversion relation between the row and column numbers of the output image and the coordinates of the projection X, Y are established according to the X, Y coordinates of the projections at the four corners of the image and the resampling resolution.
Step 220: the projection X, Y and the latitude and longitude of each pixel are calculated row by row for the output image.
Step 221: and calculating the row and column numbers in the input image by using RPC according to the longitude and latitude and the average elevation.
Step 222: the point is resampled.
Step 223: and judging whether all points are calculated.
The steps 221 to 223 are specific procedures of calculating the row and column numbers of the pixels in the input image by using RPC according to the longitude and latitude and the average elevation of the pixels for each pixel.
Step 209 to step 223 are performed on the basis of sensor correction, that is, the image and the RPC parameters after sensor correction are input, and the ground coordinates are calculated: and performing related processes of projection and image resampling through image row and column numbers (r and c) corresponding to latitude and elevation (X, Y, Z).
Step 224: and after all the points are calculated, saving the output image.
The uncontrolled positioning method of the optical remote sensing satellite provided by the embodiment of the invention has the following advantages:
(1) the method for judging the high-precision uncontrolled positioning of the optical remote sensing satellite is applied to the on-orbit geometric calibration of the satellite.
(2) And acquiring a system geometric correction image with high precision and uncontrolled positioning precision based on a TRIAD double-vector attitude determination algorithm and a virtual CCD splicing technology.
(3) The measurement result of the geometric positioning precision of the reaction plane meets the requirement of geometric calibration and verification of the optical remote sensing satellite.
Fig. 3 is a block diagram of an uncontrolled calibration apparatus for an optical remote sensing satellite according to an embodiment of the present invention.
As shown in fig. 3, the uncontrolled scaling device for an optical remote sensing satellite according to the embodiment of the present application includes the following modules:
an obtaining module 301, configured to obtain imaging parameters of each CCD, where the imaging parameters include: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters;
a first establishing module 302, configured to establish a virtual CCD imaging parameter according to the imaging parameter of each CCD;
a correction module 303, configured to perform sensor correction according to the imaging parameters of each CCD and the virtual CCD imaging parameters, to obtain an image and RPC parameters after sensor correction;
and the calculating module 304 is used for calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters.
Optionally, the correction module comprises:
the first sub-module is used for constructing an imaging model of each CCD according to the imaging parameters of each CCD;
the second sub-module is used for positioning the ground positions of four corner points of the virtual CCD scanning scene and acquiring the elevation range of the imaging area;
the third sub-module is used for respectively establishing a forward and backward calculation model between the image point and the ground point on each CCD;
the fourth sub-module is used for constructing an imaging model of each virtual CCD based on the virtual CCD imaging parameters;
the fifth sub-module is used for establishing an RPC model of the virtual CCD and resolving RPC parameters;
and the sixth submodule is used for establishing a positive and negative calculation model between the image point of the virtual CCD and the ground.
Optionally, the calculation module comprises:
the seventh sub-module is used for establishing a back calculation model between each CCD image point and the virtual CCD image point coordinates;
the eighth submodule is used for acquiring the scanning start time and the scanning end time of the virtual CCD and determining the height of a virtual scene;
a ninth sub-module, configured to obtain original image data obtained by each CCD;
the tenth submodule is used for respectively determining an original CCD film number and an image point coordinate corresponding to each pixel element in the virtual CCD and generating a report file;
and the eleventh submodule is used for calculating the ground coordinates according to the report file and the RPC file.
Optionally, the eleventh submodule is specifically configured to:
acquiring image width and height information from the report file;
obtaining a PFM coefficient from the RPC file;
calculating the longitude and latitude of four corner points and the longitude and latitude of a center of the image based on the image width and height information and the PFM coefficient;
establishing a conversion relation between longitude and latitude and the projection X, Y;
establishing the size of an output image and the conversion relation between the row and column numbers of the output image and the coordinates of a projection X, Y according to the X, Y coordinates of the projections at the four corners of the image and the resampling resolution;
calculating the projection X, Y and longitude and latitude of each pixel for each row and column of the output image;
and aiming at each pixel, calculating the row and column number of the pixel in the input image by using RPC according to the longitude and latitude and the average elevation of the pixel.
The inter-band calibration device of the optical remote sensing satellite provided by the embodiment of the invention respectively obtains the imaging parameters of each CCD; establishing virtual CCD imaging parameters according to the imaging parameters of each CCD; performing sensor correction according to the imaging parameters of each CCD and the virtual CCD imaging parameters to obtain an image and RPC parameters after the sensor correction; and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters. The device carries out uncontrolled positioning on the remote sensing image based on the double-vector attitude determination algorithm, and can improve the positioning precision.
The above description is only for the best mode of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Those skilled in the art will appreciate that the details of the invention not described in detail in this specification are well within the skill of those in the art.

Claims (8)

1. An uncontrolled calibration method for an optical remote sensing satellite is characterized by comprising the following steps:
respectively acquiring imaging parameters of each CCD, wherein the imaging parameters comprise: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters;
establishing virtual CCD imaging parameters according to the imaging parameters of each CCD;
performing sensor correction according to the imaging parameters of each CCD and the virtual CCD imaging parameters to obtain an image and RPC parameters after the sensor correction;
and calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters.
2. The method of claim 1, wherein the step of performing sensor calibration according to the imaging parameters of each CCD slice and the imaging parameters of the virtual CCD to obtain a sensor-calibrated image and RPC parameters comprises:
constructing an imaging model of each CCD according to the imaging parameters of each CCD;
positioning the ground positions of four corner points of a virtual CCD scanning scene to acquire the elevation range of an imaging area;
respectively establishing a forward and backward calculation model between the image point on each CCD and the ground point;
constructing an imaging model of each virtual CCD based on the virtual CCD imaging parameters;
establishing an RPC model of the virtual CCD, and resolving RPC parameters;
and establishing a positive and negative calculation model between the image point of the virtual CCD and the ground.
3. The method of claim 2, wherein the step of calculating ground coordinates from the sensor corrected image and RPC parameters comprises:
establishing a back calculation model between each CCD image point and the virtual CCD image point coordinates;
acquiring the scanning start time and the scanning end time of the virtual CCD, and determining the height of a virtual scene;
acquiring original image data acquired by each CCD;
respectively determining an original CCD film number and an image point coordinate corresponding to each pixel in the virtual CCD, and generating a report file;
and calculating the ground coordinates according to the report file and the RPC file.
4. The method of claim 3, wherein the step of calculating ground coordinates from the report file and the RPC file comprises:
acquiring image width and height information from the report file;
obtaining a PFM coefficient from the RPC file;
calculating the longitude and latitude of four corner points and the longitude and latitude of a center of the image based on the image width and height information and the PFM coefficient;
establishing a conversion relation between longitude and latitude and the projection X, Y;
establishing the size of an output image and the conversion relation between the row and column numbers of the output image and the coordinates of a projection X, Y according to the X, Y coordinates of the projections at the four corners of the image and the resampling resolution;
calculating the projection X, Y and longitude and latitude of each pixel for each row and column of the output image;
and aiming at each pixel, calculating the row and column number of the pixel in the input image by using RPC according to the longitude and latitude and the average elevation of the pixel.
5. An uncontrolled scaling device for optical remote sensing satellites, characterized in that it comprises:
the acquiring module is used for respectively acquiring imaging parameters of each CCD, wherein the imaging parameters comprise: real internal orientation elements, a downlink time, a downlink track, an aircraft attitude determined by observing at least two vectors and installation parameters;
the first establishing module is used for establishing virtual CCD imaging parameters according to the imaging parameters of each CCD;
the correction module is used for correcting the sensor according to the imaging parameters of each CCD and the imaging parameters of the virtual CCD to obtain an image and RPC parameters after the sensor is corrected;
and the calculation module is used for calculating the ground coordinates according to the image corrected by the sensor and the RPC parameters.
6. The apparatus of claim 5, wherein the correction module comprises:
the first sub-module is used for constructing an imaging model of each CCD according to the imaging parameters of each CCD;
the second sub-module is used for positioning the ground positions of four corner points of the virtual CCD scanning scene and acquiring the elevation range of the imaging area;
the third sub-module is used for respectively establishing a forward and backward calculation model between the image point and the ground point on each CCD;
the fourth sub-module is used for constructing an imaging model of each virtual CCD based on the virtual CCD imaging parameters;
the fifth sub-module is used for establishing an RPC model of the virtual CCD and resolving RPC parameters;
and the sixth submodule is used for establishing a positive and negative calculation model between the image point of the virtual CCD and the ground.
7. The apparatus of claim 6, wherein the computing module comprises:
the seventh sub-module is used for establishing a back calculation model between each CCD image point and the virtual CCD image point coordinates;
the eighth submodule is used for acquiring the scanning start time and the scanning end time of the virtual CCD and determining the height of a virtual scene;
a ninth sub-module, configured to obtain original image data obtained by each CCD;
the tenth submodule is used for respectively determining an original CCD film number and an image point coordinate corresponding to each pixel element in the virtual CCD and generating a report file;
and the eleventh submodule is used for calculating the ground coordinates according to the report file and the RPC file.
8. The apparatus of claim 7, wherein the eleventh submodule is specifically configured to:
acquiring image width and height information from the report file;
obtaining a PFM coefficient from the RPC file;
calculating the longitude and latitude of four corner points and the longitude and latitude of a center of the image based on the image width and height information and the PFM coefficient;
establishing a conversion relation between longitude and latitude and the projection X, Y;
establishing the size of an output image and the conversion relation between the row and column numbers of the output image and the coordinates of a projection X, Y according to the X, Y coordinates of the projections at the four corners of the image and the resampling resolution;
calculating the projection X, Y and longitude and latitude of each pixel for each row and column of the output image;
and aiming at each pixel, calculating the row and column number of the pixel in the input image by using RPC according to the longitude and latitude and the average elevation of the pixel.
CN202011496811.7A 2020-12-17 2020-12-17 Uncontrolled calibration method and device for optical remote sensing satellite Pending CN112816184A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011496811.7A CN112816184A (en) 2020-12-17 2020-12-17 Uncontrolled calibration method and device for optical remote sensing satellite

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011496811.7A CN112816184A (en) 2020-12-17 2020-12-17 Uncontrolled calibration method and device for optical remote sensing satellite

Publications (1)

Publication Number Publication Date
CN112816184A true CN112816184A (en) 2021-05-18

Family

ID=75853413

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011496811.7A Pending CN112816184A (en) 2020-12-17 2020-12-17 Uncontrolled calibration method and device for optical remote sensing satellite

Country Status (1)

Country Link
CN (1) CN112816184A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113282695A (en) * 2021-05-31 2021-08-20 国家基础地理信息中心 Vector geographic information acquisition method and device based on remote sensing image

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050147324A1 (en) * 2003-10-21 2005-07-07 Kwoh Leong K. Refinements to the Rational Polynomial Coefficient camera model
CN105374009A (en) * 2014-10-22 2016-03-02 航天恒星科技有限公司 Remote sensing image splicing method and apparatus
CN105513018A (en) * 2015-11-26 2016-04-20 航天恒星科技有限公司 Geometric correction method and apparatus for spaceborne whisk-broom imaging
CN105698764A (en) * 2016-01-30 2016-06-22 武汉大学 Error modeling compensation method and system of optical remote sensing satellite image time-varying system
CN105761228A (en) * 2016-03-09 2016-07-13 中国测绘科学研究院 Method of realizing satellite remote sensing image high precision geometric correction through slightly modifying RPC parameters
US20160259044A1 (en) * 2013-01-04 2016-09-08 National Central University Three-dimensional positioning method
CN106895851A (en) * 2016-12-21 2017-06-27 中国资源卫星应用中心 A kind of sensor calibration method that many CCD polyphasers of Optical remote satellite are uniformly processed
CN108242047A (en) * 2017-12-23 2018-07-03 北京卫星信息工程研究所 Optical satellite remote sensing image data bearing calibration based on CCD
CN110378001A (en) * 2019-07-11 2019-10-25 中国空间技术研究院 A kind of Pillarless caving remote sensing satellite geometric positioning accuracy analysis method

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050147324A1 (en) * 2003-10-21 2005-07-07 Kwoh Leong K. Refinements to the Rational Polynomial Coefficient camera model
US20160259044A1 (en) * 2013-01-04 2016-09-08 National Central University Three-dimensional positioning method
CN105374009A (en) * 2014-10-22 2016-03-02 航天恒星科技有限公司 Remote sensing image splicing method and apparatus
CN105513018A (en) * 2015-11-26 2016-04-20 航天恒星科技有限公司 Geometric correction method and apparatus for spaceborne whisk-broom imaging
CN105698764A (en) * 2016-01-30 2016-06-22 武汉大学 Error modeling compensation method and system of optical remote sensing satellite image time-varying system
CN105761228A (en) * 2016-03-09 2016-07-13 中国测绘科学研究院 Method of realizing satellite remote sensing image high precision geometric correction through slightly modifying RPC parameters
CN106895851A (en) * 2016-12-21 2017-06-27 中国资源卫星应用中心 A kind of sensor calibration method that many CCD polyphasers of Optical remote satellite are uniformly processed
CN108242047A (en) * 2017-12-23 2018-07-03 北京卫星信息工程研究所 Optical satellite remote sensing image data bearing calibration based on CCD
CN110378001A (en) * 2019-07-11 2019-10-25 中国空间技术研究院 A kind of Pillarless caving remote sensing satellite geometric positioning accuracy analysis method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
赵银娣: "《遥感数字图像处理教程——IDL编程实现》", 31 December 2015, 测绘出版社 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113282695A (en) * 2021-05-31 2021-08-20 国家基础地理信息中心 Vector geographic information acquisition method and device based on remote sensing image
CN113282695B (en) * 2021-05-31 2024-03-15 国家基础地理信息中心 Vector geographic information acquisition method and device based on remote sensing image

Similar Documents

Publication Publication Date Title
US10798353B2 (en) Calibration apparatus, calibration method, optical apparatus, image capturing apparatus, and projection apparatus
JP6484729B2 (en) Unmanned aircraft depth image acquisition method, acquisition device, and unmanned aircraft
CN110500995B (en) Method for establishing high-resolution satellite image equivalent geometric imaging model by using RPC parameters
KR101282718B1 (en) Absolute misalignment calibration method between attitude sensors and linear array image sensor
CN106885585B (en) Integrated calibration method of satellite-borne photogrammetry system based on light beam adjustment
CN102519433B (en) Method for inverting geometric calibrating parameter of satellite-borne linear array sensor by using RPC (Remote Position Control)
CN110006452B (en) Relative geometric calibration method and system for high-resolution six-size wide-view-field camera
JP2013187862A (en) Image data processing device, image data processing method, and program for image data processing
CN108663043B (en) Single-camera-assisted distributed POS main node and sub node relative pose measurement method
CN107564057B (en) High-orbit planar array optical satellite in-orbit geometric calibration method considering atmospheric refraction correction
CN113884519B (en) Self-navigation X-ray imaging system and imaging method
CN111220120A (en) Moving platform binocular ranging self-calibration method and device
CN114593736A (en) Geographical positioning method, positioning error analysis method and system of sweep type satellite
CN113724337A (en) Camera dynamic external parameter calibration method and device without depending on holder angle
KR100520275B1 (en) Method for correcting geometry of pushbroom image using solidbody rotation model
CN110310243B (en) Unmanned aerial vehicle photogrammetry image correction method, system and storage medium
CN111561936A (en) Precise processing method and system for rotating large-breadth optical satellite
CN113436267B (en) Visual inertial navigation calibration method, device, computer equipment and storage medium
CN112816184A (en) Uncontrolled calibration method and device for optical remote sensing satellite
Zhou et al. Automatic orthorectification and mosaicking of oblique images from a zoom lens aerial camera
CN112802118A (en) On-orbit time-sharing geometric calibration method for optical satellite sensor
CN111275773A (en) Method and system for calibrating field-free geometry
CN106403906A (en) Method for improving measurement precision of resultant image shooting of multiple panoramic cameras
CN111044076B (en) Geometric calibration method for high-resolution first-number B satellite based on reference base map
Sivov et al. Computer simulation of the intrinsic parameters decalibration for the stereo system of video cameras

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20210518