A visible light camera imaging simulation method for space targets in celestial background

Abstract

This invention discloses a visible light camera imaging simulation method for space targets against a celestial background. Addressing the specific imaging requirements of spaceborne optical cameras capturing the Sun and Moon during observation, this method first accurately calculates the positions of the Sun and Moon in the camera coordinate system based on NASA / JPL DE440s planetary ephemeris and sensor parameters, combined with a view projection matrix. Second, it performs visibility culling of the Sun and Moon through spatial geometric constraints to avoid non-physical occlusion. Then, for lunar imaging, it accurately simulates the lunar surface irradiance distribution by combining a 3D model and a Lambert diffuse reflection illumination model. For solar imaging, it calculates the solar pixel radius based on perspective projection, simulating the global overexposure and single-layer halo effect caused by strong light. Finally, it generates the final simulated image through depth testing and multi-channel synthesis. This invention's method can accurately calculate the pixel coordinates of the Sun and Moon on the imaging plane based on planetary ephemeris and sensor parameters; accurately calculate the light intensity distribution on the lunar surface to simulate actual lunar phases; and accurately simulate the overexposure effect caused by the Sun entering the camera's field of view and the backlighting effect of space targets. The method of this invention can simulate the imaging effect of a spaceborne camera in scenes including the sun, moon and backlight, providing highly reliable simulation data for spaceborne optical systems.

Description

Technical Field

[0001] This invention belongs to the field of space imaging simulation technology. Specifically, it is a visible light camera imaging simulation method for space targets against a celestial background. Background Technology

[0002] Spaceborne optical imaging simulation of space targets is a core supporting technology for aerospace system performance verification, mission planning, and image processing algorithm optimization. During the imaging process, the sun and moon are inevitably captured. Existing simulations mostly focus on constructing isolated space targets against a static stellar background, emphasizing the modeling of space target optical characteristics and stellar background imaging, but generally neglecting the introduction of strong celestial sources such as the sun and moon. Due to the lack of high-precision ephemeris calculations, effective modeling of complex spatial geometric occlusion, and strong light source sensor responses, simulated images differ significantly from real observations under complex conditions such as backlighting or the presence of the sun and moon, failing to meet the engineering application requirements of spaceborne optical imaging systems in complex lighting environments.

[0003] Existing patent CN110095767A proposes a surface occlusion method for space target imaging simulation. This method optimizes the surface occlusion judgment process through the K-nearest neighbor algorithm, divides the target surface into micro-surface meshes, and judges the visibility of each micro-surface to the solar light source and camera separately, effectively improving the computational efficiency under massive micro-surface conditions. However, this method is limited to the geometric occlusion calculation of the target body, lacks the mechanism for introducing strong celestial sources such as the sun and moon, and does not consider sensor overexposure and halo effects in backlight environments, making it difficult to meet the physical realism requirements of complex space backgrounds.

[0004] Existing patent CN116933567A proposes a method for constructing a simulation dataset of space targets in complex multi-scene scenarios. This method simulates stellar background imaging by establishing a navigation star library, and combines it with modeling the reflection characteristics of space targets and simulating noise and stray light to generate space target images in multiple scenarios. However, this method has significant shortcomings in imaging simulation under strong light source interference. It neither calculates the positions of the sun and moon based on high-precision planetary ephemeris nor establishes a physical illumination model for the characteristics of the sun and moon, resulting in insufficient simulation credibility under backlight or conditions containing the sun and moon.

[0005] Existing patent CN119672201A proposes a dynamic digital imaging simulation method for small space targets in complex scenes. This method constructs a target digital library through a two-dimensional shape feature point description method, and combines it with stellar mapping from the Hipparcos star catalog, multi-type illumination background modeling, and dynamic motion simulation to achieve imaging simulation of small space targets in complex scenes. However, this method lacks the ability to simulate the sun and moon, and cannot reproduce the sensor saturation overflow and halo diffusion phenomena caused by strong light incidence. Summary of the Invention

[0006] The purpose of this invention is to propose a visible light camera imaging simulation method for space targets under celestial background, which can accurately simulate the imaging process of space-borne cameras under strong interference from the sun / moon, and mainly solve the problems of unrealistic sun and moon simulation imaging and overexposure simulation of strong light sources in existing simulations.

[0007] The technical solution to achieve the purpose of this invention is: a visible light camera imaging simulation method for space targets against a celestial background, comprising the following steps:

[0008] Step (1): Import the target satellite 3D model using OpenGL 3D rendering method, parse the vertex coordinates, mesh patches and material parameters of each component in the target satellite 3D model, load the Hipparcos star catalog and NASA / JPLDE440s planetary ephemeris data, and generate target satellite image and star background image.

[0009] Step (2): Based on planetary ephemeris data, simulation time, the position and attitude of the observed spacecraft and camera field of view parameters, calculate the positions of the sun and moon in the camera coordinate system, perform field of view detection and space occlusion detection on the sun and moon, and obtain the visibility judgment results of the sun, the visibility judgment results of the moon and the corresponding space occlusion relationship.

[0010] Step (3): Based on visibility judgment, combined with the lunar 3D model and the direction of sunlight, calculate lunar rendering data and generate lunar images;

[0011] Based on visibility assessment, the pixel radius of the sun on the imaging plane is calculated, and the sensor overexposure and halo effect caused by strong light are simulated to generate a solar image.

[0012] Step (4): Perform depth tests on the star background image, lunar image, target satellite image and solar image corresponding to the same simulation time, determine the image data to be retained at each pixel position based on the spatial occlusion relationship and the depth data of each image, and perform pixel mixing on the retained image data to generate a visible light camera simulation image.

[0013] Compared with the prior art, the significant advantages of this invention are: (1) It can accurately calculate the pixel coordinates of the sun and moon on the imaging plane based on planetary ephemeris and combined with sensor parameters; (2) It can accurately calculate the light intensity distribution on the lunar surface and simulate the actual lunar phase; (3) It can accurately simulate the overexposure effect caused by the sun entering the camera's field of view and the backlight imaging effect of space targets. Attached Figure Description

[0014] Figure 1 This is a flowchart of a visible light camera imaging simulation method for space targets against a celestial background, according to the present invention.

[0015] Figure 2 In this embodiment of the invention, the target star is about 0.3km away from the observation star, the camera's field of view is 5°, and the observation star simultaneously captures an image of the target star and the moon.

[0016] Figure 3 In this embodiment of the invention, the target star is about 0.15km away from the observation star, the camera's field of view is 5°, and the observation star simultaneously captures an image of the target star and the sun. Detailed Implementation

[0017] This invention addresses the specific imaging requirements of spaceborne optical cameras capturing the Sun and Moon during observation. First, based on NASA / JPL DE440s planetary ephemeris and sensor parameters, the positions of the Sun and Moon in the camera coordinate system are accurately calculated using a view projection matrix. Second, spatial geometric constraints are used to eliminate visibility of the Sun and Moon, avoiding non-physical occlusion. Then, for lunar imaging, a 3D model and a Lambert diffuse reflection illumination model are combined to accurately simulate the lunar surface irradiance distribution. For solar imaging, perspective projection is used to calculate the solar pixel radius, simulating global overexposure and single-layer halo effects caused by strong light. Finally, depth testing and multi-channel synthesis generate the final simulated image. The specific implementation steps are as follows:

[0018] Step (1): Using mature technical solutions in the field of space target optical imaging, complete the satellite 3D modeling, star background construction and basic rendering process;

[0019] Step (2): Determine the visibility of the sun and moon based on spatial geometric constraints;

[0020] Step (3): Based on visibility judgment, combined with the three-dimensional model of the moon and the direction of sunlight, calculate the moon rendering data; based on visibility judgment, calculate the pixel radius of the sun on the imaging plane, and simulate the sensor overexposure and halo effect caused by strong light;

[0021] Step (4): Apply depth testing to process occlusion relationships, perform image synthesis, and realize simulated optical imaging.

[0022] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0023] like Figure 1 As shown, this invention provides a visible light camera imaging simulation method for space targets against a celestial background, comprising the following steps:

[0024] Step (1): Using mature technical solutions in the field of space target optical imaging, complete the satellite 3D modeling, star background construction and basic rendering process;

[0025] Step 1.1: Import the satellite model using a standard 3D modeling workflow, analyze the geometric structure and material properties (such as reflectivity and albedo) of components such as the satellite body, solar panels, and antennas, extract vertex, edge, and face information, calculate the model's bounding box, and determine the overall size range. This process is implemented based on a general-purpose 3D graphics interface (such as OpenGL).

[0026] Step 1.2: Load the Hipparcos star catalog, extract parameters such as star ID, right ascension, declination, and apparent star, and construct a stellar background database; planetary ephemeris is constructed based on the NASA / JPL DE440s planetary ephemeris system, and provides high-precision positions of solar system objects through SPICE kernel files.

[0027] Step 1.3: Establish the Lambert lighting model to determine whether the target has entered the camera's field of view. If it has entered the field of view, combine the incident light direction, normal vector, and Lambert model to calculate the lighting intensity of each grid cell of the target.

[0028] Step 1.3.1: Calculate the horizontal and vertical boundaries of the camera's spherical field of view. To determine whether a spatial target has entered the field of view, it is necessary to determine the right ascension and declination ranges covered by the camera's field of view, i.e., to model the camera's field of view. The formulas for calculating the right ascension and declination boundaries are as follows:

[0029]

[0030] in, This is the right ascension offset; Right ascension is the center point to which the optical axis points; This is the horizontal field of view of the camera.

[0031]

[0032] in, The declination is the center point to which the optical axis points. This is the camera's vertical field of view.

[0033] Step 1.3.2: Determine whether the target has entered the camera's field of view.

[0034] Step 1.3.3: When the target enters the field of view, the Lambert diffuse reflection model is used to calculate the illumination intensity on the satellite surface. The formula is:

[0035]

[0036] in, This represents the intensity of diffuse reflection. The incident light intensity; The diffuse reflectance coefficient of the surface; The surface unit normal vector; This is the unit vector representing the direction of the light source.

[0037] Step 1.4: Output the satellite surface illumination intensity for subsequent target image data rendering.

[0038] Step (2): Determine the visibility of the sun and moon based on spatial geometric constraints;

[0039] Step 2.1: To ensure the physical authenticity of the imaging data, the target source needs to be culled for visibility before rendering. The judgment logic comprehensively considers the occlusion relationship between celestial bodies and the constraints of the observation field of view. First, the visibility of the Moon is judged.

[0040] For the moon to be visible in the camera's field of view, three geometric conditions must be met simultaneously: it must not be in the Earth's shadow, it must not be obscured by any physical entity on Earth, and it must not be backlit.

[0041] Step 2.1.1: Ground shadow occlusion detection.

[0042] To determine whether the moon enters the Earth's umbra cone, i.e., whether a lunar eclipse occurs.

[0043] Earth's umbra for:

[0044]

[0045] in, The radius of the Earth; The radius of the sun is; This represents the Earth-Sun distance.

[0046] Angle between observation vectors for:

[0047]

[0048] in, The Earth-Moon vector; This is the Earth-Sun vector.

[0049] like If the moon is in Earth's shadow, it is considered invisible.

[0050] Step 2.1.2: Earth entity occlusion detection.

[0051] To determine whether the Earth's sphere blocks the observer's view of the Moon.

[0052] Angle between line of sight and the Earth's center for:

[0053]

[0054] in, The observer's (camera) position; This indicates the position of the moon.

[0055] Earth's critical angle of obstruction for:

[0056]

[0057] in, The distance between the Earth and the Moon; This represents the distance from the observer to the moon.

[0058] like and If it is obscured by the Earth, it will be considered invisible.

[0059] Step 2.1.3: Backlight detection.

[0060] Determine if the sun is on the far side of the moon (i.e., the moon is crescent-shaped and cannot be illuminated).

[0061] The angular size of the sun relative to the observer for:

[0062]

[0063] The angle between the observer's line of sight and the line connecting the sun and the moon for:

[0064]

[0065] in, This indicates the position of the sun.

[0066] like If the moon is in a backlit state, it is considered invisible.

[0067] Step 2.1.4: Determine the visibility of the moon.

[0068]

[0069] Once the moon enters the camera's field of view, it is only considered visible if it is neither in the Earth's shadow, nor obscured by the Earth, nor backlit.

[0070] Step 2.2: Determine the visibility of the sun. The visibility of the sun is mainly affected by the moon's obstruction (solar eclipse) and the earth's obstruction.

[0071] Step 2.2.1: Solar eclipse detection.

[0072] To determine whether the moon is blocking sunlight, a solar eclipse occurs.

[0073] half moon shadow for:

[0074]

[0075] in, The radius of the moon; This represents the distance between the Sun and the Moon.

[0076] Observation line of sight angle for:

[0077]

[0078] like If the sun is blocked, a solar eclipse will occur, and the sun will be considered invisible.

[0079] Step 2.2.2: Earth occlusion detection.

[0080] To determine whether the Earth blocks the observer's line of sight to the Sun.

[0081] Earth's critical angle of obstruction for:

[0082]

[0083] Angle of sight for:

[0084]

[0085] like and If the sun is blocked by the earth, it is considered invisible.

[0086] Step 2.2.3: Make a comprehensive judgment on the visibility of the sun.

[0087]

[0088] Once the sun enters the camera's field of view, it is only considered visible if it is neither obscured by the moon nor by the earth.

[0089] Step (3): Based on visibility judgment, combined with the three-dimensional model of the moon and the direction of sunlight, calculate the moon rendering data;

[0090] Step 3.1: Based on the relative orbital dynamics model, calculate the relative position and attitude matrix of the Moon in the camera coordinate system.

[0091] The relative position vector of the moon's center in the camera coordinate system The results were obtained from quaternion rotation and translation transformations:

[0092]

[0093] in, Let be the position vector of the Moon's center in the Earth-centric inertial frame; To observe the spacecraft's position vector in the geocentric inertial frame; This is the conversion factor for distance units from kilometers (km) to meters (m); Let be the attitude quaternion of the camera coordinate system relative to the inertial frame; This represents quaternion multiplication operations.

[0094] Step 3.2: Construct the model transformation matrix and physically scale up the 3D lunar model.

[0095] The moon rendering is done using a 3D model of the moon. The 3D model used is a sphere with a radius of 1 meter. The original coordinates of its surface grid are in meters. It needs to be scaled according to the rendering scale to match the perspective effect on a cosmic scale.

[0096] scaling factor Defined as the actual radius of the moon With the original radius of the model The ratio:

[0097]

[0098] For each vertex coordinate in the model Apply scaling transformation:

[0099]

[0100] Step 3.3: Construct the complete model-view projection matrix.

[0101] To display the moon correctly on the screen, the vertex coordinates of the scaled model need to be transformed sequentially through model transformation, view transformation, and projection transformation.

[0102] Model matrix It is composed of a combination of translation and rotation:

[0103]

[0104] in, ; Let be the attitude rotation matrix of the moon relative to the camera.

[0105] Final clipping space coordinates The calculation formula is:

[0106]

[0107] in, For view matrix; This is the perspective projection matrix.

[0108] Step 3.4: Calculate the diffuse reflection component based on the Lambert illumination model to simulate the effect of sunlight.

[0109] The lunar surface is approximately an ideal diffuse reflector (Lambertian surface), and its brightness depends entirely on the sunlight received. First, the normalized normal vector is calculated. and the vector of the direction of solar incidence normal vector for:

[0110]

[0111] in, The original normals of the model facet; This is the normal matrix.

[0112] Sun incident direction vector for:

[0113]

[0114] in, This is the direction vector of the sun in the world coordinate system.

[0115] Diffuse light intensity Calculated using Lambert's cosine law:

[0116]

[0117] Final fragment output color This is a superposition of diffuse color and ambient light color.

[0118]

[0119] in, For ambient light intensity, The color represents the albedo of the lunar surface.

[0120] Step (4): Based on visibility judgment, calculate the pixel radius of the sun on the imaging plane and simulate sensor overexposure and halo effect caused by strong light;

[0121] Step 4.1: Based on the physical position and size of the sun, calculate its pixel radius on the imaging plane according to the principle of perspective projection.

[0122] Calculation of the apparent radius of the sun:

[0123]

[0124] in, The physical radius of the Sun; the distance from the observed star to the Sun is... (Unit: km).

[0125] Combined with camera vertical field of view and image height Convert the apparent radius of the sun to the screen pixel radius. :

[0126]

[0127] This is achieved by inversely inferring from the elements of the projection matrix: , This is the element in the second row and second column of the projection matrix.

[0128] Step 4.2: Due to the extremely high brightness of the sun, a spillover effect will occur on the CMOS / CCD sensor. A single-layer halo algorithm based on smooth interpolation and power-law attenuation is adopted to reduce computational overhead while ensuring visual quality, thereby constructing a halo attenuation model.

[0129] Step 4.2.1: Calculate the normalized distance and the smoothing decay factor.

[0130] First, calculate the normalized distance from each pixel to the center of the sun. :

[0131]

[0132] in, The Euclidean distance from the pixel to the center of the sun; Where is the radius of the halo. This is the multiplier of the halo radius.

[0133] To avoid jagged, hard cutoff edges at the halo, a cubic smoothing interpolation function (smoothstep) is used to calculate the fundamental attenuation factor.

[0134]

[0135] in, The cubic smooth interpolation function is defined as follows:

[0136]

[0137] Step 4.2.2: To simulate the physical characteristics of the sun's extremely high brightness at the center and rapid decay at the edges, the basic decay factor is nonlinearly enhanced.

[0138] The nonlinear enhancement is as follows:

[0139]

[0140] Among them, exponentiation operation It effectively enhances the weight of the central area, allowing the halo to exhibit a natural energy distribution.

[0141] Step 4.2.3: The final halo intensity is combined with the preset intensity coefficient and color, and then additively mixed and superimposed onto the original scene.

[0142] Halo intensity calculation:

[0143]

[0144] in, This is the halo intensity coefficient; The color of the halo.

[0145] Step 4.3: Based on the actual halo effect, the core area of ​​the halo needs to be brightened, and dynamic range truncation is required for the final effect.

[0146] For the core region of the sun (typically within 50% of the central radius), forced brightening is performed to simulate the "white core" phenomenon caused by sensor saturation:

[0147]

[0148] in, These are the original scene color values.

[0149] To prevent floating-point color values ​​from overflowing, the final color is truncated to preserve highlight details:

[0150] The cutoff limit is set to 3.0, which allows the highlight area to exceed the display threshold, enhancing the realism.

[0151] Step (5): Apply depth testing to process occlusion relationships, perform image synthesis, and realize simulated optical imaging.

[0152] Step 5.1: Implement multi-channel off-screen rendering compositing using Frame Buffer Objects (FBOs). The compositing order is: star background → moon → space object → sun. Geometric occlusion relationships are automatically handled using depth testing. The alpha blending formula is:

[0153]

[0154] in, The color of the mixed pixels; The transparency of the current segment; The color value of the currently rendered fragment; The target color.

[0155] Step 5.2: Transfer the rendered image data from the device's video memory back to the host memory, and save the final composite image in a standard format (such as JPEG).

[0156] Step 5.3: Release OpenGL rendering resources: Delete framebuffer objects, renderbuffer objects, texture objects, shader programs, and vertex array objects. Clean up model material textures and properly shut down the GLFW rendering context.

[0157] To demonstrate the effectiveness of the algorithm of this invention and fully showcase its ability to simulate the generation of the moon and the sun entering the camera's field of view, thus triggering a global overexposure effect, the following experiments were conducted:

[0158] (1) Initial conditions and parameter settings of the experiment

[0159] The simulation experiment consisted of two sets of experiments. The first set tested the imaging effect when the observed star simultaneously captured images of the moon and the satellite; the second set tested the overexposure imaging effect when the observed star, the target star, and the sun were backlit.

[0160] (2) Analysis of experimental results

[0161] Test 1

[0162] The scene includes two satellites operating in medium orbit. Both satellites are equipped with optical sensors, and the field of view of the optical sensors is set to 5°. The generated image resolution is 2K×2K.

[0163] Figure 2 This is an image of the target star at a distance of approximately 0.3 km from the observed star. The Moon is located at the center of the imaging plane. The imaging time is 0:52:12:094 UTC on January 15, 2026, when the Moon is a new moon.

[0164] Test 2

[0165] The scene includes two satellites operating in medium orbit. The target satellite is about 0.15km away from the observation satellite, and the observation satellite, the target satellite, and the sun are in a straight line. The observation satellite is equipped with an optical sensor with a field of view of 5°, and the generated image resolution is 2K×2K.

[0166] Figure 3 This is a backlit imaging effect. At this time, the target star is located in the direction of the sun's apparent disk, causing direct sunlight to fill most of the camera's field of view, resulting in saturation overexposure, and the target itself presents a backlit silhouette imaging effect.

[0167] In summary, this invention possesses the capability to accurately simulate and generate the moon when the optical sensor captures the moon, and to simulate the global overexposure effect caused by the sun entering the camera's field of view when the sensor captures the sun in spaceborne optical imaging simulation. It addresses the lack of realistic rendering of the sun and moon and the simulation of overexposure from strong light sources in existing space target imaging simulations.

[0168] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for simulating visible light camera imaging of space targets against a celestial background, characterized in that, Includes the following steps: Step (1): Import the target satellite 3D model using OpenGL 3D rendering method, parse the vertex coordinates, mesh patches and material parameters of each component in the target satellite 3D model, load the Hipparcos star catalog and NASA / JPL DE440s planetary ephemeris data, and generate target satellite image and star background image. Step (2): Based on planetary ephemeris data, simulation time, the position and attitude of the observed spacecraft and camera field of view parameters, calculate the positions of the sun and moon in the camera coordinate system, perform field of view detection and space occlusion detection on the sun and moon, and obtain the visibility judgment results of the sun, the visibility judgment results of the moon and the corresponding space occlusion relationship. Step (3): Based on visibility judgment, combined with the lunar 3D model and the direction of sunlight, calculate lunar rendering data and generate lunar images; Based on visibility assessment, the pixel radius of the sun on the imaging plane is calculated, and the sensor overexposure and halo effect caused by strong light are simulated to generate a solar image. Step (4): Perform depth tests on the star background image, lunar image, target satellite image and solar image corresponding to the same simulation time, determine the image data to be retained at each pixel position based on the spatial occlusion relationship and the depth data of each image, and perform pixel mixing on the retained image data to generate a visible light camera simulation image.

2. The visible light camera imaging simulation method for space targets against a celestial background according to claim 1, characterized in that, The specific implementation method of step (1) is as follows: Step 1.1: Import the satellite model using OpenGL 3D rendering method, analyze the geometry of the body, solar panels, and antenna components, extract vertex coordinates, edges and mesh patches, read the reflectivity and albedo of each component, calculate the bounding box of the target satellite 3D model, and obtain the target satellite 3D model data. Step 1.2: Load the Hipparcos star catalog, extract star IDs, right ascension, declination, apparent star, etc., and construct a stellar background database; Load NASA / JPL DE440s planetary ephemeris data and SPICE kernel files, extract ephemeris data, leap second data and planetary constant data from the SPICE kernel files, and build a planetary ephemeris database. Step 1.3: Establish the Lambert lighting model to determine whether the target has entered the camera's field of view. If it has entered the field of view, combine the incident light direction, normal vector, and Lambert model to calculate the lighting intensity of each grid cell of the target. Step 1.4: Input the target satellite 3D model data and the illumination intensity of each mesh facet into the OpenGL shader. After coordinate transformation, material sampling, illumination calculation and grayscale conversion, the target satellite image is generated. Based on the camera's field of view, stars are selected from the star background database. The selected stars are projected onto the imaging plane, and the pixel grayscale values ​​are calculated based on the apparent magnitude of the stars to generate the star background image.

3. The visible light camera imaging simulation method for space targets against a celestial background according to claim 1, characterized in that, The specific implementation method of step (2) is as follows: Step 2.1: Based on the Moon's position in the camera coordinate system and the camera's field of view, determine whether the Moon has entered the camera's field of view; for the Moon that has entered the camera's field of view, perform Earth shadow occlusion detection, Earth entity occlusion detection, and backlight detection respectively; when the detection results are that the Moon is not in Earth's shadow, not occluded by Earth entities, and not in a backlight state, output the Moon's visibility judgment result as visible; otherwise, output the Moon's visibility judgment result as invisible. Step 2.2: Determine whether the sun has entered the camera's field of view based on the sun's position in the camera coordinate system and the camera's field of view angle; perform lunar occlusion detection and Earth occlusion detection on the sun that has entered the camera's field of view; when the sun is not occluded by the moon or the earth, output the sun's visibility judgment result as visible, otherwise output the sun's visibility judgment result as invisible.

4. The visible light camera imaging simulation method for space targets against a celestial background according to claim 1, characterized in that, The specific implementation method for generating lunar images in step (3) is as follows: Step 3.1: Based on the relative orbital dynamics model, calculate the relative position and attitude matrix of the Moon in the camera coordinate system; The relative position vector of the moon's center in the camera coordinate system The results were obtained from quaternion rotation and translation transformations: in, Let be the position vector of the Moon's center in the Earth-centric inertial frame; To observe the spacecraft's position vector in the geocentric inertial frame; This is the conversion factor for distance units from kilometers to meters; Let be the attitude quaternion of the camera coordinate system relative to the inertial frame; This represents quaternion multiplication. Step 3.2: Construct the model transformation matrix and physically scale up the 3D lunar model; The moon rendering is performed using a 3D model of the moon. The 3D model used is a sphere with a radius of 1 meter. The original coordinates of the surface mesh are in meters. The coordinates of each vertex are scaled according to the ratio of the actual radius of the moon to the original radius of the 3D model of the moon. scaling factor Defined as the actual radius of the moon With the original radius of the model The ratio: For each vertex coordinate in the model Apply scaling transformation: Step 3.3: Construct the complete model-view projection matrix; The vertex coordinates of the scaled lunar 3D model are sequentially transformed by model transformation, view transformation, and projection transformation to obtain the clipping space coordinates of each vertex of the lunar 3D model. Model matrix It is composed of a combination of translation and rotation: in, ; This is the attitude rotation matrix of the moon relative to the camera; Final clipping space coordinates The calculation formula is: in, For view matrix; For perspective projection matrix; Step 3.4: Calculate the diffuse reflection components of each mesh surface of the lunar 3D model based on the Lambert lighting model; For each mesh patch of the lunar 3D model, the original normals of the mesh patches are transformed using the normal matrix and then normalized to obtain the normal vectors. : in, The original normals of the model facet; The normal matrix; Normalize the solar direction vector in the world coordinate system to obtain the solar incident direction vector. : in, This is the solar direction vector in the world coordinate system; Diffuse light intensity Calculated using Lambert's cosine law: Final fragment output color This is a superposition of diffuse color and ambient light color. in, For ambient light intensity, The color represents the albedo of the lunar surface.

5. The visible light camera imaging simulation method for space targets against a celestial background according to claim 1, characterized in that, The specific implementation method for generating the solar image in step (3) is as follows: Step 3.1: Calculate the pixel radius of the sun on the imaging plane based on the sun's physical position, physical radius, camera vertical field of view, and image height; Calculation of the apparent radius of the sun: in, The physical radius of the Sun; the distance from the observed star to the Sun is... (Unit: km); Combined with camera vertical field of view and image height Convert the apparent radius of the sun to the screen pixel radius. : This is achieved by inversely inferring from the elements of the projection matrix: , The element in the second row and second column of the projection matrix; Step 3.2: For each pixel with the sun center pixel coordinates as the center and the halo radius as the range of action, calculate the normalized distance from the pixel to the sun center, use the cubic smooth interpolation function to calculate the basic attenuation factor, perform a power operation on the basic attenuation factor, and multiply the calculation result with the preset halo intensity coefficient and halo color to obtain the halo intensity of each pixel. Step 3.3: Compare the original scene color value of each pixel in the core region of the sun with the preset saturation value, and take the larger value as the color value of the core region of the sun; add the original scene color value of each pixel outside the core region of the sun to the obtained halo intensity, and truncate the dynamic range of the addition result to obtain the sun image. Pixels located less than 0.5 times the radius of the solar pixel at the center of the sun are defined as the solar core region, and the color value of the solar core region is calculated according to the following formula: in, The original scene color value; The superposition result of the color values ​​of the solar core region and the halo intensity is truncated according to the following formula: The lower cutoff limit is 0.0, and the upper cutoff limit is set to 3.

0.

6. The visible light camera imaging simulation method for space targets against a celestial background according to claim 1, characterized in that, The specific implementation method of step (4) is as follows: Step 4.1: Create a Frame Buffer Object (FBO) to achieve multi-channel off-screen rendering compositing; the compositing order is: star background → moon → space target → sun; use depth testing to automatically handle geometric occlusion relationships, and the alpha blending formula is: in, The color of the mixed pixels; The transparency of the current segment; The color value of the currently rendered fragment; The target color; Step 4.2: Transfer the synthesized image data obtained in Step 4.1 from the device's video memory back to the host memory, and save the synthesized image data as a JPEG format visible light camera simulation image; Step 4.3: Release OpenGL rendering resources: Delete framebuffer objects, renderbuffer objects, texture objects, shader programs, and vertex array objects; clean up model material textures, and properly shut down the GLFW rendering context.

7. The visible light camera imaging simulation method for space targets against a celestial background according to claim 2, characterized in that, The specific implementation method of step 1.3 is as follows: Step 1.3.1: Calculate the horizontal and vertical boundaries of the camera's spherical field of view to determine the right ascension and declination ranges covered by the camera's field of view; the formulas for calculating the right ascension and declination boundaries are as follows: in, This is the right ascension offset; Right ascension is the center point to which the optical axis points; This refers to the horizontal field of view of the camera; in, The declination is the center point to which the optical axis points. The vertical field of view of the camera; Step 1.3.2: Determine whether the target has entered the camera's field of view; Step 1.3.3: When the target enters the field of view, the Lambert-Lambert diffuse reflection model is used to calculate the illumination intensity on the satellite surface. The formula is: in, This represents the intensity of diffuse reflection. The incident light intensity; The diffuse reflectance coefficient of the surface; The surface unit normal vector; This is the unit vector representing the direction of the light source.

8. The visible light camera imaging simulation method for space targets against a celestial background according to claim 3, characterized in that, The specific implementation method of step 2.1 is as follows: Step 2.1.1: Ground shadow occlusion detection; Determining whether the Moon has entered the Earth's umbra cone; Earth's umbra for: in, The radius of the Earth; The radius of the sun; The distance between the Earth and the Sun; Angle between observation vectors for: in, The Earth-Moon vector; The Earth-Sun vector; like If the moon is in Earth's shadow, it is considered invisible. Step 2.1.2: Earth entity occlusion detection; To determine whether the Earth's sphere blocks the observer's view of the Moon; Angle between line of sight and the Earth's center for: in, To observe the position of the camera on the spacecraft; The position of the moon; Earth's critical angle of obstruction for: in, The distance between the Earth and the Moon; The distance from the observer to the moon; like and If it is blocked by the Earth, it will be determined to be invisible. Step 2.1.3: Backlight detection; Calculate the angle between the line of sight from the observation spacecraft to the moon and the line of sight from the observation spacecraft to the sun, and determine whether the moon is in a backlit state based on the angle; The angular size of the sun relative to the observer for: The angle between the observer's line of sight and the line connecting the sun and the moon for: in, The position of the sun; like If the moon is in a backlit state, it is determined to be invisible. Step 2.1.4: Comprehensively determine the visibility of the moon; Once the moon enters the camera's field of view, it is considered visible only if it is neither in the Earth's shadow, nor obscured by the Earth, nor backlit.

9. The visible light camera imaging simulation method for space targets against a celestial background according to claim 3, characterized in that, The specific implementation method of step 2.2 is as follows: Step 2.2.1: Solar eclipse detection; To determine whether the moon is blocking sunlight, i.e., whether a solar eclipse is occurring; half moon shadow for: in, The radius of the moon; The distance between the sun and the moon; Observation line of sight angle for: like If the sun is blocked, a solar eclipse will occur, and the sun will be considered invisible. Step 2.2.2: Earth occlusion detection; To determine whether the Earth blocks the observer's line of sight to the Sun; Earth's critical angle of obstruction for: Angle of sight for: like and If the sun is blocked by the earth, it is considered invisible. Step 2.2.3: Comprehensively determine the visibility of the sun Once the sun enters the camera's field of view, it is only considered visible if it is neither obscured by the moon nor by the earth.

10. The visible light camera imaging simulation method for space targets against a celestial background according to claim 5, characterized in that, The specific implementation method of step 3.2 of step (3) in generating the solar image is as follows: Step 3.2.1: Calculate the normalized distance and the smoothing decay factor. First, calculate the normalized distance from each pixel to the center of the sun. : in, The Euclidean distance from the pixel to the center of the sun; Where is the radius of the halo. The radius multiplier is the halo radius multiplier. The fundamental attenuation factor is calculated based on the normalized distance using the cubic smoothing interpolation function smoothstep. in, The cubic smooth interpolation function is defined as follows: Step 3.2.2: Nonlinearly enhance the basic attenuation factor; The nonlinear enhancement is as follows: Where 0.5 is the power-law decay exponent; Step 3.2.3: The final halo intensity is combined with the preset intensity coefficient and color, and then additively mixed and superimposed onto the original scene; Halo intensity calculation: in, This is the halo intensity coefficient; The color of the halo.

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