Air target optical image real-time simulation method and system suitable for approaching operation

Abstract

The invention discloses an air target optical image real-time simulation method and system suitable for approaching operation. The method comprises the following steps: receiving target and observation star motion orbit data generated by an orbit or attitude generator in real time; calculating a camera optical axis direction; screening out fixed stars which can be detected by the camera from the SAO star catalogue by combining the limit detection capability of the camera, and completing fixed star simulation; calculating the relative pose of the observation star and the target according to the data; performing imaging simulation on the target according to the characteristics of the space target; whether the moon appears in the visual field or not is judged, and the situation that the moon exists in the visual field is simulated; adding noise and stray light in the image; and outputting in a UDP transmission mode through an Ethernet port. According to the method, various space targets can be simulated, relative change of space illumination is considered, calculation is real-time and efficient, rapid image generation and transmission capacity is achieved, and vivid target image input can be provided for ground semi-physical performance verification of a space visual navigation system.

Description

Technical Field

[0001] The present invention belongs to the field of satellite technology, and particularly relates to a method and system for real-time simulation of optical images of space targets applicable to proximity operations. Background Art

[0002] In the fields of space technology and space exploration, the observation, identification, and analysis of space targets are of crucial significance. Ground stations play a key role in acquiring image data of space targets, and this data can provide basic information for various applications such as orbit determination, shape analysis, attitude estimation, and fault diagnosis of space targets. With the increasing frequency of space activities, the demand for high-precision and high-fidelity space target imaging simulation technology has become more urgent.

[0003] Traditional space target imaging mainly relies on actual optical observation equipment. However, these devices are restricted by various factors, such as weather conditions, observation time windows, equipment costs, and equipment maintenance. In addition, it is often difficult to flexibly adjust parameters and reproduce scenarios under various preset conditions in real observations, which brings great difficulties to algorithm development, system testing, and verification of new imaging technologies. Currently, some software-based imaging simulation methods can, to a certain extent, simulate the imaging process of space targets, but most of them do not consider the integration with the ground semi-physical joint simulation environment. These pure software simulations lack the ability to interact with actual hardware systems (such as sensor models, signal processing hardware, etc.), resulting in a significant reduction in the accuracy and effectiveness of simulation results in actual application scenarios. When applying the simulation results to the optimization of actual devices and verification of new algorithms, there are large deviations and it is impossible to accurately reflect the imaging effects in the real semi-physical joint simulation situation. Therefore, a method for real-time simulation of visible light images of space targets for ground semi-physical verification of satellite vision navigation systems is needed, which can solve technical problems such as the difficulty in obtaining real-time on-orbit images of existing targets and the difficulty in restoring complex space environments and the states of targets in orbit by optical cameras on the ground. Summary of the Invention

[0004] Object of the Invention: The present invention provides a method and system for real-time simulation of optical images of space targets applicable to proximity operations, forming stable and coherent full-course image output, and achieving the real-time performance and dynamics required for joint simulation.

[0005] Technical Solution: A method for real-time simulation of optical images of space targets applicable to proximity operations according to the present invention specifically includes the following steps:

[0006] S1. Real-time receive the motion orbit data of the target and the observation star generated by the orbit or attitude generator;

[0007] S2. Calculate the pointing direction of the camera optical axis based on the received motion orbit data;

[0008] S3. According to the calculated pointing of the camera optical axis and combined with the limit detection ability of the camera, select the stars that can be detected by the camera from the SAO star catalog to complete the star simulation;

[0009] S4. Calculate the relative pose between the observed star and the target according to the data received in S1;

[0010] S5. Perform imaging simulation on the target according to the characteristics of the space target;

[0011] S6. Judge whether the moon will appear in the field of view according to the orbital motion data, and simulate the situation where the moon exists in the field of view;

[0012] S7. Add noise and stray light to the image simulated in S5;

[0013] S8. Output the image after adding noise and stray light in S7 through the Ethernet port in UDP transmission mode.

[0014] Further, the motion orbit data of the target and the observed star described in step S1 are:

[0015] The position and velocity vector of the target in the ECI coordinate system, the position and velocity vector of the observed star in the ECI coordinate system, the body attitude quaternion of the observed star in the ECI coordinate system, the position vector of the moon in the ECI, and the direction vector of the sunlight in the ECI.

[0016] Further, the step S2 includes the following steps:

[0017] S201. Calculate the rotation matrix M1 from the ECI coordinate system to the body coordinate system of the observed star according to the body attitude quaternion of the observed star in the ECI coordinate system in the received data;

[0018] S202. Define the camera installation matrix M2, and calculate the rotation matrix M3 from the ECI coordinate system to the observation camera by the rotation matrix M1 and the camera installation matrix M2.

[0019] Further, the step S3 includes the following steps:

[0020] S301. According to the detection ability of the camera, select the stars with sufficient brightness to be detected from the SAO star catalog, and the screening conditions are:

[0021] Stars = {VM i ≤VM 0 , i = 1, 2, 3... N}

[0022] where Stars is the set of stars that can be detected within the limit detection range of the camera in the SAO star catalog, and VM i is the apparent magnitude of the i-th star in the SAO star catalog, VM0 The faintest stellar apparent magnitude that can be detected by the detection limit of the camera;

[0023] S302. According to the right ascension and declination information of the stars in the SAO star catalog, calculate the azimuth vector Vector of the stars in Stars obtained in S301 in the camera coordinate system:

[0024]

[0025] where Vector is the direction vector of the star in the camera coordinate system, and RA and RD are the right ascension and declination information of the star respectively;

[0026] S303. According to the result Vector obtained in S302, further screen the stars Stars-In-Img within the camera field of view in the Stars obtained in S301. The screening conditions are as follows:

[0027]

[0028] where FOV x is the field of view angle of the camera in the x direction, and FOV y is the field of view angle of the camera in the y direction;

[0029] S304. Calculate the pixel coordinates of the stars Stars-In-Img screened out in S303 in the image. The calculation formula is:

[0030]

[0031] where (N x , N y ) are the pixel coordinates of the star in the image, f is the focal length of the camera used, and d x and d y are the pixel sizes of the camera in the x and y directions respectively;

[0032] S305. The simulated camera detection ability range is from magnitude -1 to 5. Set the total gray value of the stars with the faintest magnitude that the camera can detect in the image Then the total gray value of the stars with the remaining magnitudes is:

[0033]

[0034] where, is the total gray value of the star with magnitude VM i in the image, and is the total gray value of the star with magnitude VM 0 in the image;

[0035] S306. With the stellar pixel coordinates obtained in S304 as the center, perform gray-scale diffusion on the stellar spots within the pixel range of 3×3 to 7×7 around it. The diffusion formula is as follows:

[0036]

[0037] where A is the total gray value of the star, δ is the Gaussian diffusion radius, (x 0 , y 0 ) is the diffusion center coordinate, and I(x, y) is the gray value at the pixel (x, y).

[0038] Furthermore, the step S4 includes the following steps:

[0039] S401. Based on the target star position vector R Tar and the observed star position vector R Cha in the ECI coordinate system, calculate the relative position between the target and the observation platform in the camera coordinate system;

[0040] S402. Based on the position vector R Tar and the velocity vector V Tar of the target star in the ECI, calculate the rotation matrix M4 from the target body coordinate system to the observed star body coordinate system;

[0041] S403. Use the rotation matrix M4 to calculate the attitude angles δ 1 , δ 2 , δ 3 of the target relative to the observation camera, and obtain the relative attitude of the target.

[0042] Furthermore, the step S5 includes the following steps:

[0043] S501. Combine the three-dimensional geometric configuration of the target, select a certain number of feature points to reflect its own structural characteristics, obtain the coordinates of these feature points in the target body coordinate system according to the target size information, and convert the coordinates of the feature points in the target body coordinate system to pixel coordinates in the camera coordinate system through the rotation matrix M4;

[0044] S502. Analyze the reflection characteristics of the target surface, and use different reflection models to describe it according to the different materials selected for different parts of the target;

[0045] S503. Regard the sun as blackbody radiation, calculate the radiant emittance M within the effective wavelength range λ 1 to λ 2 of the visible light camera, and calculate the spectral irradiance E sun of the sunlight on the surface of the target at a distance D Tar-sun from the sun according to the inverse square law of distance.; Divide the target surface into surface elements according to the feature points selected in S501, and calculate the spectral irradiance dE radiated outward by each surface element Tar ; Set the visual magnitude VM of the sun Sun , and calculate the equivalent visual magnitude VM of the surface element dA dA-Tar ; According to the total gray value of the stars with magnitude 5 Further calculate the total gray value I of the surface element dA-Tar ;

[0046] S504. Obtain the number of pixels occupied by the surface element according to the pixel coordinates of the feature points in S501, and divide I dA-Tar evenly among the surface elements to obtain the gray value of the target in the image.

[0047] Further, the step S6 includes the following steps:

[0048] S601. According to the lunar orbit operation data, calculate its position relative to the observed star in the camera coordinate system, determine whether the angles between the moon and the camera optical axis in the x and y directions are greater than the camera field of view angle, and whether the angle formed by the geocenter-camera-moon center is less than the angle formed by the geocenter-camera-the tangent point of the camera and the earth's edge, so as to judge the visibility of the moon;

[0049] S602. After judging that the moon is within the field of view, simulate the moon: according to the relative position relationship between the moon and the earth, the observed star, and the change of the angle θ between the vector perpendicular to the sunlight vector and the position vector of the moon relative to the observed star, determine the calculation method of the bright surface area of the moon in the simulation image, and select the corresponding method according to θ to calculate the imaging area S of the moon in the image; further calculate the number of pixels S it occupies in the image according to the pinhole imaging principle of the camera Pic :

[0050]

[0051] Among them, S Pic is the number of pixels occupied by the moon in the image, S is the imaging area of the moon in the image, and R Cam-moon is the relative position between the observation camera and the moon;

[0052] S603. Calculate the moon's visual magnitude according to the imaging area of the moon in the image and its visual magnitude in the full moon state, and further calculate the total gray value and gray distribution of the moon.

[0053] Further, the step S7 includes the following steps:

[0054] S701. Judge the angle β between the tangent line of the observation platform and the earth's atmosphere edge and the camera optical axis and 1 / 2 of the camera field of view FOV yIf the size relationship satisfies β < FOV y / 2, it is considered that the ground - atmosphere light radiation affects the camera imaging;

[0055] S702. The ground - atmosphere light radiation is mainly the reflection of sunlight. Calculate the irradiance E of the earth's surface irradiated by sunlight SC ;

[0056] S703. According to the Lambert cosine law, consider the earth as a Lambert radiator with a constant radiance in all directions. Its radiation intensity changes with the angle θ between the observation direction and the normal of the surface source, and follows the cosine law. Divide its surface into countless surface elements, and then calculate the irradiance dE of each surface element on the earth's surface at the entrance pupil of the detection camera e-Cam ;

[0057] S704. Set the equivalent visual magnitude VM of the sun Sun , and calculate the equivalent visual magnitude VM of the surface element at the entrance pupil of the detection camera according to the quantitative relationship between the visual magnitude and the irradiance e ; Further convert the visual magnitude of the surface element into a gray - scale value, and calculate the total gray - scale value and the gray - scale distribution of the ground - atmosphere light radiation.

[0058] An optical image real - time simulation system for space targets applicable to close - range operations described in the present invention includes:

[0059] An RS422 serial - port data receiving module, which is used to connect the target optical image simulator with the orbit or attitude generator, and receive the motion data of the observed stars and space targets generated by it in real time;

[0060] A camera optical axis calculation module, which calculates the line - of - sight pointing of the observation camera according to the data received by the RS422 serial port, including the rotation matrix from the ECI coordinate system to the body coordinate system of the observed star and the rotation matrix from the ECI coordinate system to the observation camera;

[0061] A star simulation module, which screens out the stars that can be detected by the camera from the SAO star catalog and simulates them according to the calculated camera optical axis pointing and the limit detection ability of the camera;

[0062] A relative position and attitude calculation module, which calculates the relative position and attitude, including relative position and relative attitude, by using the position vectors and velocity vectors of the observed star and the target star in the ECI coordinate system in the received data;

[0063] A target simulation imaging module, which is used to calculate the feature points that can reflect the structural characteristics of the target according to the characteristics of the space target, and perform imaging simulation on the target;

[0064] The moon determination and simulation imaging module determines the visibility of the moon based on the moon's orbital operation data, whether it is within the camera's field of view, and whether it is blocked by the earth, and calculates the pixel coordinate position, the number of pixels occupied, the total gray value, and the gray distribution of the moon in the image when it is determined that the moon is within the field of view;

[0065] The noise and stray light addition module calculates the irradiance of sunlight on the earth's surface, the irradiance of each earth surface element at the entrance pupil of the detector, the equivalent visual magnitude of the surface element at the entrance pupil of the detection camera, and the total gray value and gray distribution of the earth's atmospheric light radiation according to the stray light imaging model;

[0066] The Ethernet port image transmission module outputs the simulated generated image in UDP transmission mode through the Ethernet port.

[0067] Advantages: Compared with the prior art, the advantages of the present invention are as follows:

[0068] The present invention fully considers the real deep space environment including noise and stray light. At the same time, compared with other prior arts, it considers the moon, a major interference item that may appear in the field of view of an optical camera in actual deep space exploration, and simulates it, making the simulation scenario more realistic and credible;

[0069] The present invention can simulate the whole process of the target moving from far to near during the mission, and can generate continuously updated simulated images according to the dynamic changes of the target (such as the motion orbit and attitude quaternion information of the space target), achieving full coverage of medium and long-distance and close-range images, and forming a stable and coherent full-process image output;

[0070] The present invention has strong data interaction capabilities with other links, can receive data in real time, generate the latest images in real time and send them in real time, and has a relatively high speed, meeting the real-time and dynamic requirements of joint simulation;

[0071] The present invention can be semi-physically verified on the ground, that is, in the absence of actual cameras, satellite targets and other equipment, it can simulate the motion images of space targets and apply them to subsequent attitude and orbit control analysis, etc.; this method solves the problem that it is difficult to restore the complex space environment of an optical camera on the ground in traditional simulation technologies. Description of the Drawings

[0072] Figure 1 It is a flowchart of a real-time simulation method for optical images of space targets applicable to approaching operations;

[0073] Figure 2 It is a geometric relationship diagram of the bright and dark sides of the moon in the camera;

[0074] Figure 3This is the simulation result of the on-orbit visual scene of a space target at various distances from the observation platform in the present invention. Among them, (a) shows the distance between the target and the observation platform is 2.441 km; (b) shows the distance between the target and the observation platform is 0.167 km; (c) shows the distance between the target and the observation platform is 0.019 km. Detailed implementation manner

[0075] The present invention will be further described in detail below with reference to the accompanying drawings.

[0076] The present invention proposes a real-time simulation method for the optical image of an empty target suitable for close approach operations. The specific implementation process is as follows:

[0077] S1. The RS422 serial port receives in real time the target and observation star motion orbit data generated by the orbit or attitude generator.

[0078] The received data mainly includes the position and velocity vector of the target in the ECI coordinate system, the position and velocity vector of the observation star in the ECI coordinate system, the attitude quaternion of the observation star body in the ECI coordinate system, the position vector of the moon in the ECI coordinate system, and the direction vector of the sunlight in the ECI coordinate system.

[0079] S2. Calculate the line-of-sight direction of the observation camera according to the data received by the RS422 serial port.

[0080] S201. From the attitude quaternion of the observation star body in the ECI coordinate system in the received data, calculate the rotation matrix M1 from the ECI coordinate system to the body coordinate system of the observation star. The calculation is as follows:

[0081]

[0082] Among them, Q(q 0 , q 1 , q 2 , q 3 ) is the attitude quaternion of the observation star body in the ECI coordinate system, and M1 is the rotation matrix from the ECI coordinate system to the body coordinate system of the observation star.

[0083] S202. Define the camera installation matrix M2 as:

[0084]

[0085] From the rotation matrix M1 from the ECI coordinate system to the body coordinate system of the observation star obtained in S201 and the camera installation matrix M2, the rotation matrix M3 from the ECI coordinate system to the observation camera can be calculated. Then, the optical axis direction of the camera in the ECI coordinate system is known. The calculation is as follows:

[0086] M3 = M2 × M1

[0087] Among them, M3 is the rotation matrix from the ECI coordinate system to the observation camera.

[0088] S3. Based on the calculated pointing of the camera optical axis and combined with the camera's limit detection ability, select the stars that can be detected by the camera from the SAO star catalog to complete the star simulation.

[0089] S301. According to the detection ability of the camera, select the stars in the SAO star catalog with sufficient brightness to be detected. The selection conditions are:

[0090] Stars = {VM i ≤VM 0 , i = 1, 2, 3... N}

[0091] where Stars is the set of stars that can be detected within the camera's limit detection range in the SAO star catalog, VM i is the apparent magnitude of the i-th star in the SAO star catalog, and VM 0 is the apparent magnitude of the dimmest star that can be detected by the camera detection limit.

[0092] S302. According to the right ascension and declination information of the stars in the SAO star catalog, calculate the azimuth vector Vector of the stars in Stars obtained in S301 in the camera coordinate system:

[0093]

[0094] where Vector is the direction vector of the star in the camera coordinate system, and RA and RD are the right ascension and declination information of the star respectively.

[0095] S303. According to the result Vector obtained in S302, further select the stars Stars-In-Img within the camera field of view from the Stars obtained in S301. The selection conditions are as follows:

[0096]

[0097] where FOV x is the camera's field of view angle in the x direction, and FOV y is the camera's field of view angle in the y direction.

[0098] S304. Calculate the pixel coordinates of the stars Stars-In-Img selected in S303 in the image. The calculation formula is as follows:

[0099]

[0100] where (N x , N y ) are the pixel coordinates of the star in the image, f is the focal length of the camera used, d x and d yThey are the pixel sizes of the camera in the x and y directions respectively.

[0101] S305. The simulated camera detection ability range is from magnitude -1 to magnitude 5. Set the total gray value A of the faintest magnitude star that the camera can detect in the image VM0 to be 60. Then the total gray values of stars of other magnitudes can be calculated by the following formula:

[0102]

[0103] Where is the total gray value of a star with magnitude VM i in the image, is the total gray value of a star with magnitude VM 0 in the image.

[0104] S306. Taking the stellar pixel coordinates obtained by S304 as the center, perform gray - scale diffusion on the star points within the pixel range of 3×3 to 7×7 around. The diffusion formula is as follows:

[0105]

[0106] Where A is the total gray value of the star, δ is the Gaussian diffusion radius, (x 0 , y 0 ) is the diffusion center coordinate, and I(x, y) is the gray value at pixel (x, y). The diffusion pixel range depends on the star magnitude level, that is, its total gray value shown in the image.

[0107] Based on multiple experimental tests and data statistics, the present invention judges that: if we want to ensure that stars will not be submerged by the noise background due to too low gray values, the gray value of the star brightness center should not be lower than 30. Taking a magnitude 5 star as an example, since it belongs to a relatively dim star, it is diffused into 3×3 pixels. Therefore, more than 95% of the energy of its star point is concentrated within the 3×3 range. According to the Gaussian distribution law, the probability that the numerical distribution is within (μ - 2σ, μ + 2σ) is 95%, μ is the pixel position where the star brightness center is located, σ is the Gaussian diffusion radius δ. Since the star brightness is diffused within the 3×3 pixel range and the center of the pixel range is the star brightness center, the Gaussian diffusion radius of the star point should satisfy the following relationship at this time:

[0108]

[0109] Where δ is the Gaussian diffusion radius.

[0110] Therefore, the Gaussian dispersion radius of the star point is approximately 0.5 pixels at this time. If it is necessary to ensure that the gray value at the brightness center of a magnitude 5 star is not lower than 30, according to the gray dispersion formula, the total gray value of the magnitude 5 star can be estimated to be approximately 60. Therefore, in the present invention, the total gray value of the magnitude 5 star is set to 60. The total gray value set in the present invention is not absolute, but a relative value that can be changed within an appropriate range based on different simulation requirements and working conditions.

[0111] For stars of other magnitudes, calculate their total gray values according to S305, and determine what pixel range to use for gray dispersion. The judgment conditions are as follows:

[0112] a. When the star is relatively dim and the total gray value is less than 255×9, disperse it into pixels within a range of 3×3.

[0113] b. For bright stars with a total gray value greater than 255×9 and less than 255×49, calculate A / 255 to obtain the minimum number of pixels required for the simulation. Calculate and round up to the adjacent odd number to further calculate the pixel diameter value of the star dispersion.

[0114] c. For bright stars with a total gray value greater than 255×49, disperse them into pixels within a range of 7×7.

[0115] S4. Calculate the relative pose of the observed star and the target based on the data received in step S1.

[0116] S401. Use the position vector R of the target star in the ECI coordinate system in the data received in step 1 Tar and the position vector R of the observed star Cha , and find the relative position D between the target and the observation platform in the camera coordinate system:

[0117] D = M3(R Tar - R Cha )

[0118] where D is the relative position between the target and the observation platform in the camera coordinate system, R Tar is the position vector of the target star in the ECI, and R Cha is the position vector of the observed star in the ECI coordinate system.

[0119] S402. Use the position vector R of the target star in the ECI in the data received in step 1 Tar and the velocity vector V Tar , and calculate the rotation matrix M4 from the target body system to the observed star body system. The calculation is as follows:

[0120]

[0121] where V Taris the velocity vector of the target star in ECI.

[0122] S403. Using the rotation matrix M4 obtained in S402, solve the following equation to calculate the attitude angle δ of the target relative to the observation camera. 1 , δ 2 , δ 3 , from which the relative attitude of the target can be obtained:

[0123]

[0124] S5. According to the characteristics of the space target, simulate the target image, including:

[0125] S501. Combine the three-dimensional geometric configuration of the target, select a certain number of feature points to reflect its own structural characteristics, obtain the coordinates of these feature points in the target's own coordinate system according to the target size information, and convert the coordinates of the feature points in the target's own coordinate system to pixel coordinates in the camera coordinate system through the rotation matrix M4 obtained in S402.

[0126] S502. Analyze the reflection characteristics of the target surface, and use different reflection models to describe it according to the different materials selected for different parts of the target. The main body part is approximated according to the Blinn-Phong model, and the bidirectional distribution function f Phong is as follows:

[0127]

[0128] where k d is the diffuse reflection coefficient. When k d takes 0, the model is pure specular reflection. k s is the specular reflection coefficient, n is the normal vector of the target surface, h is the half-angle vector, ω l is the light direction vector, and ω o is the observation axis direction vector.

[0129] The antenna part is approximated according to the Lambert model, and the bidirectional distribution function f Lambert is as follows:

[0130]

[0131] The solar panel part is approximated according to the AB g model, and the bidirectional distribution function f ABg is as follows:

[0132]

[0133] where β in is the scattering angle, and β outis the reflection angle, A is a scale constant reflecting the reflection energy intensity of the target, and B and g reflect the degree of concentration of the reflection energy.

[0134] S503. Regarding the sun as a blackbody radiation with a temperature of 5778 K, the radiant emittance M within the effective wavelength range λ 1 ~λ 2 of the visible light camera can be calculated. According to the inverse square law of distance, the spectral irradiance E of sunlight at the surface of the target at a distance D Tar-sun from the sun is calculated. sun .

[0135] Perform surface element division on the target surface according to the feature points selected in S501, and calculate the spectral irradiance dE Tar radiated outward by each surface element:

[0136] dE Tar = E sun × cosθ × f RBD × dA

[0137] where dE Tar is the spectral irradiance radiated outward by each surface element, E sun is the spectral irradiance of sunlight at the surface of the target at a distance D Tar-sun from the sun calculated according to the inverse square law of distance, f RBD is the bidirectional reflectance distribution function, and f RBD of different parts of the target is selected according to S502. dA is the differential area, and θ is the angle between the sun ray and the normal of the differential element.

[0138] Set the apparent magnitude VM Sun of the sun to be approximately -26.7, and calculate the equivalent apparent magnitude VM dA-Tar of the surface element dA, and the calculation is as follows:

[0139]

[0140] where dE Sun is the spectral irradiance of sunlight received by the surface element dA, VM Sun is the apparent magnitude of the sun, and VM dA-Tar is the equivalent apparent magnitude of the surface element dA.

[0141] According to the total gray value of the star with an apparent magnitude of 5, further calculate the total gray value I dA-Tar of the surface element, and the calculation is as follows:

[0142]

[0143] where VM Star-5 is the apparent magnitude, and its value is 5. is the total gray value of stars with magnitude 5, I dA-Tar is the total gray value of the pixel element.

[0144] According to the pixel coordinates of the feature points in S501, obtain the number of pixels occupied by the pixel element, and divide I dA-Tar equally into the pixel element to obtain the gray value of the target in the image. According to data such as the size information of each component of the target, the pixel coordinates of the feature points, and their gray values in the image, draw each component of the target into the image.

[0145] S6. Judge whether the moon will appear in the field of view according to the orbital data, and simulate the situation where the moon exists in the field of view.

[0146] S601. According to the moon's orbital operation data, calculate its position relative to the observed star in the camera coordinate system, judge whether the angles between the moon and the camera optical axis in the x and y directions are greater than the camera field of view angle, and whether the angle formed by the geocenter-camera-moon center is less than the angle formed by the geocenter-camera-the tangent point of the camera and the earth's edge, so as to judge the visibility of the moon.

[0147] S602. After judging that the moon is within the field of view, simulate the moon. According to the relative position relationship between the moon, the earth, and the observed star and the change of the sunlight incident direction (the angle θ between the vector perpendicular to the sunlight vector and the position vector of the moon relative to the observed star), the situation of the bright-dark interface of the moon in the imaging plane will also change, and the calculation method of the bright surface area of the moon in the simulation image is also different. Select a suitable method according to θ to calculate the imaging area S of the moon in the image.

[0148] Take as an example. According to the geometric relationship as shown in Figure 2 and the moon radius r, obtain the radius R of the arc presented by the bright-dark interface of the moon in the image, and the imaging area (bright surface area) S of the moon in the image. The calculation is as follows:

[0149]

[0150] Among them, R is the radius of the arc presented by the bright-dark interface of the moon in the image, r is the moon radius, θ is the angle between the vector perpendicular to the sunlight vector and the position vector of the moon relative to the observed star, and S is the imaging area (bright surface area) of the moon in the image.

[0151] Similarly, R and S when θ is in other ranges can be obtained, as shown in Table 1:

[0152] Table 1 Imaging size of the moon in the image

[0153]

[0154] Furthermore, according to the pinhole imaging principle of the camera, the number of pixels S it occupies in the image is calculated as follows: Pic , the calculation is as follows:

[0155]

[0156] Among them, S Pic is the number of pixels occupied by the moon in the image, S is the imaging area of the moon in the image, and R Cam-moon is the relative position between the observation camera and the moon.

[0157] S603. Calculate the apparent magnitude of the moon based on the imaging area of the moon in the image and its apparent magnitude in the full moon state. Further, according to the calculation formula of the stellar brightness, calculate the total gray value and gray distribution of the moon. Draw the moon into the image based on data such as the pixel coordinates, total gray value, and gray distribution of the moon in the image.

[0158] S7. Add noise and stray light to the image.

[0159] S701. Judge the size relationship between the angle β between the tangent of the observation platform and the edge of the Earth's atmosphere and the camera's optical axis and 1 / 2 of the camera's field of view FOV y . If β < FOV y / 2, it is considered that the earth-air light radiation affects the camera imaging.

[0160] S702. The earth-air light radiation is mainly the reflection of sunlight. Calculate the irradiance E SC of the Earth's surface by sunlight, and the calculation is as follows:

[0161]

[0162] Among them, E SC is the irradiance of the Earth's surface by sunlight, A S is the surface area of the sun, λ 1 ~λ 2 is the visible light wavelength range of sunlight, h is Planck's constant, c is the speed of light, k is Boltzmann's constant, T is the temperature, and R SC is the distance between the Earth and the sun.

[0163] S703. According to Lambert's cosine law, regard the Earth as a Lambert radiator with a constant radiance in all directions. Its radiation intensity changes with the angle θ between the observation direction and the normal of the surface source and follows the cosine law. Divide its surface into countless surface elements, and thus calculate the irradiance dE e-Cam of each surface element on the Earth's surface at the entrance pupil of the detection camera.

[0164] S704. Set the equivalent apparent magnitude VM SunIt is -26.7, and the equivalent visual magnitude VM of the surface element at the entrance pupil of the detection camera is calculated according to the quantitative relationship between magnitude and irradiance. e , and the calculation is as follows:

[0165]

[0166] Where E sun is the spectral irradiance of sunlight at the surface of the target at a distance D Tar-sun from the sun, dE e-Cam is the irradiance of each surface element on the earth's surface at the entrance pupil of the detection camera, VM e is the equivalent visual magnitude of the surface element at the entrance pupil of the detection camera, and VM Sun is the equivalent visual magnitude of the sun.

[0167] Furthermore, according to the calculation formula of the stellar brightness, the visual magnitude of the surface element is converted into a gray value, and the total gray value and gray distribution of the earth-air light radiation are calculated.

[0168] S8. Send the generated image to the image processing module in the form of UDP transmission through the Ethernet port, including:

[0169] S801. Set the IP address and port number of the receiving end.

[0170] S802. Close the UDP socket that may exist before, and create a new UDP object and set the OutputBufferSize property.

[0171] S803. Open the UDP object and send the image size information, and send the image data in batches.

[0172] S804. Close the UDP object.

[0173] The present invention also provides a real-time optical image simulation system for empty targets suitable for close-range operations, including:

[0174] RS422 serial port data receiving module, which is used to connect the target optical image simulator with the orbit or attitude generator and receive in real time the motion data of the observed stars and space targets generated by them; camera optical axis calculation module, which calculates the line-of-sight pointing of the observation camera according to the data received by the RS422 serial port, including the rotation matrix from the ECI coordinate system to the body coordinate system of the observed star and the rotation matrix from the ECI coordinate system to the observation camera; star simulation module, which screens out the stars that can be detected by the camera in the SAO star catalog and simulates them according to the calculated camera optical axis pointing and the ultimate detection ability of the camera; relative pose calculation module, which calculates the relative pose including relative position and relative attitude by using the position vectors and velocity vectors of the observed star and the target star in the ECI coordinate system in the received data; target simulation imaging module, which is used to calculate the feature points that can reflect the structural characteristics of the target itself according to the characteristics of the space target and perform imaging simulation on the target; moon determination and simulation imaging module, which judges the visibility of the moon by the moon's orbital operation data, whether it is in the camera's field of view, and whether it is blocked by the earth, and calculates the pixel coordinate position, the number of pixels occupied, and the total gray value and gray distribution of the moon in the image when it is determined that the moon is in the field of view; noise and stray light adding module, which calculates the irradiance of the earth's surface by sunlight, the irradiance of each earth surface element at the entrance pupil of the detector, the equivalent visual magnitude of the surface element at the entrance pupil of the detection camera, and the total gray value and gray distribution of the earth's atmosphere light radiation according to the stray light imaging model; Ethernet port image transmission module, which outputs the simulated image through the Ethernet port in UDP transmission mode.

[0175] Figure 3 It is the simulation result of the on-orbit visual scene of the space target with the change of the distance between the target and the observation platform from far to near. Among them, (a) is the distance between the target and the observation platform of 2.441 km; (b) is the distance between the target and the observation platform of 0.167 km; (c) is the distance between the target and the observation platform of 0.019 km; the part within the red square is some stars. The simulation results show that the simulation method involved in the present invention can clearly and truly reflect the external structure, motion process of the target and the relative position relationship between the target and the stars in the background, indicating that the present invention can simulate the whole process of the target moving from far to near during the mission.

[0176] After testing, the method proposed by the present invention is applicable to the image simulation of different satellite targets and different moving trajectories. According to the different position, velocity and attitude quaternion information of the target star and the observed star, the pixel coordinates of the target feature points can be changed to achieve the purpose of simulating different relative poses and moving trajectories. According to the different camera parameters and the different target sizes, the position, number and pixel area occupied by the feature points of the target reflected on the imaging plane are also different, so as to achieve the purpose of simulating different target satellites.

[0177] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention. Any other corresponding changes and variations made according to the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A real-time simulation method for an empty target optical image suitable for approaching operation, characterized in that: The following steps are involved: S1, receiving the target and observation star motion orbit data generated by the orbit or attitude generator in real time; S2, calculating the camera optical axis direction according to the received motion trajectory data; S3. According to the calculated camera optical axis direction and the camera's extreme detection capability, the stars that can be detected by the camera are selected from the SAO star catalog to complete the star simulation. S4, calculating the relative position and posture of the observation star and the target according to the data received in S1; S5. Perform imaging simulation on the target according to the characteristics of the space target; S6. judging whether the moon will appear in the field of view according to the orbital motion data, and simulating the situation where the moon exists in the field of view; S7, adding noise and stray light to the image simulated in S5; S8, outputting the image after adding noise and stray light in S7 through the Ethernet port in UDP transmission mode.

2. The real-time simulation method of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The target and observation star motion orbit data described in step S1 are: The position and velocity vector of the target in the ECI coordinate system, the position and velocity vector of the observed star in the ECI coordinate system, the quaternion of the observed star's body attitude in the ECI coordinate system, the position vector of the moon in the ECI system, and the direction vector of sunlight in the ECI system.

3. The real-time simulation method of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The step S2 comprises the following steps: S201, calculating the rotation matrix M1 from the ECI coordinate system to the observation star body system based on the observation star body attitude quaternion in the ECI coordinate system in the received data; S202, define the camera installation matrix M2, and calculate the rotation matrix M3 from the ECI coordinate system to the observation camera based on the rotation matrix M1 and the camera installation matrix M2.

4. The real-time simulation method of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The step S3 comprises the following steps: S301. Based on the detection capability of the camera, select stars in the SAO star catalog that are bright enough to be detected. The selection conditions are: Stars={VM i ≤VM0,i=1,2,3...N} Stars is the set of stars in the SAO star catalog that can be detected within the camera's detection range, VM i is the apparent magnitude of the ith star in the SAO star catalog, VM0 is the apparent magnitude of the faintest star that can be detected by the camera detection limit; S302. According to the right ascension and declination information of the stars in the SAO star catalog, calculate the azimuth vector Vector of the stars in Stars obtained in S301 in the camera coordinate system: Among them, Vector is the direction vector of the star in the camera coordinate system, RA and RD are the right ascension and declination information of the star respectively; S303, based on the result Vector obtained in S302, further filter the stars Stars-In-Img within the camera field of view from the Stars obtained in S301, and the screening conditions are as follows: Among them, FOV x is the camera's field of view in the x direction, FOV y The camera's field of view in the y direction; S304, calculate the pixel coordinates of the star Stars-In-Img selected by S303 in the image, and the calculation formula is: Among them, (N x ,N y ) is the pixel coordinate of the star in the image, f is the focal length of the camera used, d x With d y are the pixel sizes of the camera in the x and y directions respectively; S305: The simulated camera detection capability range is -1 to 5 magnitude stars, and the total grayscale value of the darkest magnitude star that the camera can detect in the image is set. Then the total gray value of stars of other magnitudes is: in, For the magnitude of VM i The total gray value of the star in the image, is the total gray value of the star with magnitude VM0 in the image; S306, taking the star pixel coordinates obtained in S304 as the center, grayscale diffusion is performed on the star point in the surrounding 3×3 to 7×7 pixel range. The diffusion formula is as follows: Among them, A is the total gray value of the star, δ is the Gaussian diffusion radius, (x0, y0) is the coordinate of the diffusion center, and I(x, y) is the gray value at the pixel (x, y).

5. The method for real-time simulation of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The step S4 comprises the following steps: S401, target satellite position vector R based on ECI coordinate system Tar and the observed star position vector R Cha , find the relative position of the target and the observation platform in the camera coordinate system; S402, based on the position vector R of the target star under ECI Tar With velocity vector V Tar , calculate the rotation matrix M4 from the target system to the observation star system; S403, using the rotation matrix M4 to calculate the attitude angles δ1, δ2, δ3 of the target relative to the observation camera, and obtain the relative attitude of the target.

6. The real-time simulation method of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The step S5 comprises the following steps: S501, combining the three-dimensional geometric configuration of the target, selecting a certain number of feature points to reflect its own structural characteristics, obtaining the coordinates of these feature points in the target system according to the target size information, and converting the feature point coordinates in the target system into pixel coordinates in the camera coordinate system through the rotation matrix M4; S502, analyzing the reflection characteristics of the target surface, and using different reflection models to describe the different materials selected for different parts of the target; S503, the sun is regarded as a black body radiation, and the radiation emittance M within the effective wavelength range λ1 to λ2 of the visible light camera is calculated. The distance D of the sunlight from the sun is calculated according to the inverse square law of distance. Tar-sun Spectral irradiance E at the distant target surface sun ; Divide the target surface into facets according to the feature points selected in S501, and calculate the spectral irradiance dE radiated outward from each facet Tar ; Set the apparent magnitude VM of the Sun Sun , calculate the equivalent apparent magnitude VM of the surface element dA dA-Tar ; Based on the total gray value of a star with magnitude 5 Further calculation to obtain the total gray value I of the pixel dA-Tar ; S504, according to the pixel coordinates of the feature points in S501, the number of pixels occupied by the face element is obtained, and I dA-Tar Divide it evenly into surface elements to obtain the grayscale value of the target in the image.

7. The real-time simulation method of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The step S6 comprises the following steps: S601, based on the moon's orbital data, calculate its position relative to the observed star in the camera coordinate system, determine whether the angle between the moon and the camera's visual axis in the x and y directions is greater than the camera's field of view angle, and whether the angle formed by the center of the earth-camera-center of the moon is less than the angle formed by the center of the earth-camera-camera and the tangent point of the earth's edge, and then determine the visibility of the moon; S602, after determining that the moon is in the field of view, simulate the moon: determine the calculation method of the bright surface area of ​​the moon in the simulated image according to the relative position relationship between the moon, the earth, and the observation star and the change of the angle θ between the incident direction of sunlight, i.e., the vector perpendicular to the sunlight vector and the position vector of the moon relative to the observation star, and select the corresponding method to calculate the imaging area S of the moon in the image according to θ; further calculate the number of pixels S occupied by the moon in the image according to the camera pinhole imaging principle Pic ; S603, calculating the apparent magnitude of the moon according to the imaging area of ​​the moon in the image and its apparent magnitude in a full moon state, and further calculating the total gray value and gray distribution of the moon.

8. The method for real-time simulation of an empty target optical image suitable for approach operation according to claim 7, characterized in that: The number of pixels S Pic for: Among them, S Pic is the number of pixels occupied by the moon in the image, S is the imaging area of ​​the moon in the image, and R Cam-moon is the relative position of the observation camera and the moon.

9. The method for real-time simulation of an empty target optical image suitable for approach operation according to claim 1, characterized in that: The step S7 comprises the following steps: S701. Determine the angle β between the tangent line between the observation platform and the edge of the Earth's atmosphere and the camera's visual axis and 1 / 2 of the camera's field of view FOV y If β<FOV y / 2 believes that the ground-air light radiation has an impact on camera imaging; S702. The ground-air radiation is mainly the reflection of sunlight. Calculate the irradiance E of the earth's surface on sunlight. SC ; S703. According to Lambert's cosine law, the earth is regarded as a Lambert radiator with constant radiation brightness in all directions. Its radiation intensity changes with the change of the angle θ between the observation direction and the surface source normal, and obeys the cosine law. Its surface is divided into countless surface elements, so as to calculate the irradiance dE of each surface element of the earth at the entrance pupil of the detection camera. e-Cam ; S704. Set the equivalent apparent magnitude VM of the sun Sun According to the quantitative relationship between magnitude and irradiance, the equivalent apparent magnitude VM of the face element at the entrance pupil of the detection camera is calculated. e ; Further convert the apparent magnitude of the surface element into grayscale value, and calculate the total grayscale value and grayscale distribution of the ground-air light radiation.

10. A real-time simulation system for an empty target optical image suitable for approach operation using the method of claims 1 to 9, characterized in that: include: RS422 serial port receiving data module, used to connect the target optical image simulator with the orbit or attitude generator, and receive the motion data of the observation star and space target generated by it in real time; The camera optical axis calculation module calculates the visual axis direction of the observation camera according to the data received by the RS422 serial port, including the rotation matrix from the ECI coordinate system to the observation star system and the rotation matrix from the ECI coordinate system to the observation camera; The star simulation module selects stars that can be detected by the camera in the SAO star catalog and simulates them according to the calculated camera optical axis direction and the camera's extreme detection capability. The relative posture calculation module uses the position vector and velocity vector of the observation star and the target star in the ECI coordinate system in the received data to calculate the relative posture including relative position and relative posture; The target simulation imaging module is used to calculate the characteristic points that can reflect the structural characteristics of the target itself according to the characteristics of the space target, and perform imaging simulation on the target; The moon determination and simulation imaging module determines the visibility of the moon through the moon's orbit data, whether it is in the camera's field of view, and whether it is blocked by the earth. If the moon is in the field of view, it calculates the pixel coordinate position of the moon in the image, the number of pixels occupied, and the total grayscale value and grayscale distribution. The noise and stray light adding module calculates the irradiance of the earth's surface from sunlight, the irradiance of each surface element on the earth at the entrance pupil of the detector, the equivalent apparent magnitude of the surface element at the entrance pupil of the detection camera, and the total grayscale value and grayscale distribution of the ground-air light radiation according to the stray light imaging model; The Ethernet port image transmission module outputs the simulated image via the Ethernet port in UDP transmission mode.

Images