A method for simulating target motion trajectory based on on-board payload

Abstract

This invention relates to a target motion trajectory simulation method based on an on-board payload, comprising the following steps: using the observation satellite, the target satellite, and a star as simulation objects, combining satellite motion simulation and star background simulation, acquiring the position information of the visible target satellite and visible star in the camera coordinate system over a continuous time period to construct a continuous motion scene for on-orbit observation; based on the position information, generating a target observation image with a star background through coordinate conversion to a pixel coordinate system, pixel size calculation, and grayscale value conversion; generating multiple frames of simulation images within the continuous observation period and marking the target position frame by frame to visualize the target's motion trajectory from entering the field of view to leaving the field of view, generating a continuous motion trajectory map of the target; and converting the multiple frames of simulation images into data files to complete the simulation of the on-board payload data telemetry transmission process, enabling the satellite ground support software to directly analyze and view the target's dynamic motion trajectory. This invention improves the algorithm's security and flexibility.

Description

Technical Field

[0001] This invention relates to the field of space point target observation technology, and to a method for simulating target motion trajectory based on on-board payloads. Background Technology

[0002] Space target surveillance systems are the foundation of space security systems, and their capabilities constrain the effectiveness of space offensive and defensive operations. The core tasks of space target surveillance are to detect, track, and identify space targets, thereby determining their threat level, monitoring for space collisions, and providing security alerts. Space target surveillance can employ both ground-based and space-based observation methods. Compared to ground-based observation, space-based observation is not limited by the Earth's atmosphere, station location, or observation time, and has significant advantages in terms of airspace coverage and monitoring timeliness. Currently, space-based space target observation technology has become a cutting-edge technology in the space field. Space-based space target observation technology relies on onboard cameras to acquire target information, perform target location estimation, monitoring, and rapid response. Observation technologies mainly include visible light, infrared, and microwave radar. Visible light detection can effectively detect targets in sunlight-exposed areas and has a stronger detection capability for distant targets compared to infrared detection. The technology is also more mature and is a popular choice for payloads on currently operational satellites.

[0003] The Space Midcourse Experiment (MSX) satellite, launched by the United States in 1996, carried a space-based visible light sensor (SBV), pioneering space-based space surveillance and playing a crucial role in monitoring geostationary orbit satellites. Building on the success of the SBV, the United States began developing the Space-Based Space Surveillance System (SBSS) in 2002, which will improve the United States' tracking capability of geostationary orbit (GEO) satellites by 5%. Currently, many scholars and research institutions have conducted a series of studies on key technologies in space target surveillance simulation. For example, based on the theory of bidirectional reflectance distribution function (BRDF), various model characterization methods for the surface reflectance of materials have been proposed. Imaging simulation calculation methods for space targets have been developed, such as rasterization rendering technologies such as OpenGL imaging engines and ray tracing radiation calculation rendering methods based on physical models.

[0004] Simulation of space targets and star backgrounds plays a crucial role in the development of space-based space target monitoring systems, providing essential simulation data sources for payload parameter optimization and key technology verification. Existing work has several shortcomings: First, the onboard payload imaging settings are relatively simplistic, neglecting the presence of stellar backgrounds in the images during actual target observation. Second, it only studies imaging simulation techniques under static conditions, failing to consider the relative motion of the remote sensing satellite, target satellite, and stars, and neglecting continuous onboard payload imaging during operation. Third, it primarily considers the optical reflection characteristics of the target, ignoring the imaging differences at different observation distances and failing to identify the target trajectory for continuous imaging. Fourth, it does not consider the telemetry data transmission process; most studies generate image data in .png and .jpg formats, which do not conform to the transmission methods between the onboard payload and the ground. Summary of the Invention

[0005] This invention provides a target motion trajectory simulation method based on on-board payloads, comprising: First, given a standard star catalog and satellite motion information, calculating the relative motion of the observation satellite, target satellite, and star at consecutive time intervals to construct a complete on-orbit observation mission scenario; Second, fusing a stellar background image into the target satellite image to make the target observation image conform to the actual on-board imaging situation, optimizing the visualization effect of the target observation image, calculating the grayscale values ​​and pixel sizes of the target and star based on magnitude information and observation distance, and marking the target in the image according to the target position information to adapt to ground observation needs; Third, a complete on-orbit observation mission will generate a set of image datasets for consecutive time periods, capable of presenting the target being captured. The entire process from the target entering the field of view to its exiting the field of view at the end of the observation is simulated. Given a continuous observation time, multiple frames of target observation images are generated and the target position is marked to form a star map of the target's motion trajectory, simulating the complete execution result of the observation mission. Finally, the simulated images are generally in .png or .jpg format, but after the actual onboard payload completes the target detection, it uses hexadecimal storage to generate a .raw format file, and then the observation data is transmitted via telemetry. Ground-based analysis software is used for visualization. Therefore, to fully simulate the onboard payload's target monitoring mission, it is also necessary to simulate the onboard data telemetry transmission process, convert the simulated star map into a data file, and then use the satellite's ground-based software for analysis and viewing, thus expanding the applicability of the invention method. This method uses C++ programming for algorithm implementation, improving the algorithm's security and flexibility.

[0006] This invention provides a method for simulating the trajectory of a target based on an on-board payload, comprising the following steps: Sp10 uses observation satellites, target satellites, and stars as simulation objects. Combining satellite motion simulation and star background simulation, it obtains the position information of visible target satellites and visible stars in the camera coordinate system over a continuous period of time, so as to construct a continuous motion scene for on-orbit observation. Sp20, based on the location information, a target observation image with a stellar background is generated by converting coordinates to a pixel coordinate system, calculating pixel size, and converting grayscale values. Multiple simulated images are generated within a continuous observation period, and the target position is marked frame by frame to visualize the target's motion trajectory from entering the field of view to leaving the field of view, generating a continuous target motion trajectory map; and Sp30. Convert the multi-frame simulation images into data files to complete the simulation of the on-board payload data telemetry transmission process, enabling the satellite ground software to directly analyze and view the target's dynamic motion trajectory, and complete the full-process simulation implementation.

[0007] Furthermore, in step Sp10, the satellite motion simulation includes the following steps: Establishing a camera coordinate system based on the onboard payload of the observation satellite; and Given the motion states of the observation satellite and the target satellite, calculate their relative positional relationship to obtain the position information of the target satellite in the camera coordinate system, and obtain the target satellite within the field of view based on the payload pointing and the field of view.

[0008] Furthermore, in step Sp10, the stellar background simulation includes the following steps: Based on the standard star catalog, the star background observed at any observation time and any observation location is simulated, and stellar data is stored using an octree structure. Based on the pointing and field of view of the observation satellite payload, stellar targets within the observation satellite camera's field of view that meet the preset magnitude range requirements are selected. Luminosity parameters are extracted to provide information on the position and luminosity of these stellar targets for subsequent generation of stellar background images; and The selected stars are sorted by magnitude, and the stars are automatically converted from their mean position at the reference epoch to the observation time. The position information of the stars in the camera coordinate system is calculated to complete the star background modeling.

[0009] Furthermore, the standard stellar catalogue includes information such as right ascension and declination, apparent magnitude, proper motion of stars, and trigonometric parallax.

[0010] Furthermore, the camera coordinate system is O C -X C -Y C -Z C With the optical center of the load as the origin O C With the optical axis of the load as Z C Axis, X C Axis, Y C The axis is parallel to the two sides of the observation satellite body.

[0011] Furthermore, in step Sp20, the coordinate transformation includes the following steps: Based on the location information, the points in the camera coordinate system are transformed to the image coordinate system through central projection. The formula for the central projection transformation from the camera coordinate system to the image coordinate system is as follows: P I =[x I y I 1] T =f / z C ×[x C y C 1] T = f / z C ×P C Wherein, P(x C ,y C ,z C P is a point in the camera coordinate system. I Let f be a point in the image coordinate system, and f be the focal length of the optical system; and The points in the image coordinate system are transformed to the pixel coordinate system to obtain the pixel coordinates of the observed object in the image. The transformation formula is as follows: u=x I / p+u0, v=y I / p+v0 Where P(u,v) is a point in the pixel coordinate system, p is the pixel size, and (u0, v0) are the coordinates of the origin of the image coordinate system in the pixel coordinate system.

[0012] Further, in step Sp20, the pixel size is calculated by combining the pixel size of the observed object and the pixel size of the optical system's point spread function (PSF) to obtain the total pixel size of the observed object in the image, including the following steps: Calculate the angular diameter θ of the observed object target : θ target =L / R Where, θ target The unit is radians, L represents the characteristic size of the observed object in meters, and R represents the distance between the observed object and the observed satellite in meters. Calculate the PSF, which is determined by the angular resolution θ of the PSF. target Decide: θ PSF =1.22·λ / D Where, θ PSF The unit is radians, λ represents the observation wavelength in meters, and D represents the camera aperture in meters. Calculate the pixel size d, d = θ·f / p, where d is in pixels and f represents the focal length of the optical system in meters; calculate the pixel size of the observed object using the formula: d pixels=θ target ·f / p Calculate the pixel size of the PSF: d PSF =θ PSF ·f / p Calculate the total pixel size: d total =(d PSF 2 + d pixels 2 ) 0.5 .

[0013] Further, in step Sp20, the grayscale value conversion includes calculating the grayscale values ​​of visible target satellites and visible stars in the image based on the correspondence between magnitude and grayscale. The conversion formula is as follows: G=255 / 2.51 Ms-5 Where Ms is the equivalent apparent star magnitude, and G is the grayscale value. It is specified that when the star magnitude is 5, the corresponding grayscale value is 255.

[0014] Further, in step Sp20, multiple frames of simulated images are generated within the continuous observation period, and the target position is marked frame by frame to visualize the target's motion trajectory from entering the field of view to leaving the field of view, generating a continuous motion trajectory map of the target, including the following steps: Based on pixel coordinates, pixel size, and grayscale values, a stellar star map and a target satellite image are generated respectively. These two images are then weighted and fused to obtain a target observation image with a stellar background. The pixel coordinates of the target satellite are marked within this image, completing the generation of a single-frame marked target observation image. Based on the continuous motion scene built by Sp10, a set of continuous target observation images is generated, and the target position of each frame image is marked, so that the target's motion trajectory is visualized during continuous observation, realizing the simulation of the observation process from the observation satellite capturing the target entering the field of view to the target jumping out of the field of view.

[0015] Furthermore, the addWeighted function of the OpenCV library is used to perform a weighted fusion of the star map and the target satellite map; after fusion, the pixel coordinates of the target satellite are marked with hollow circles.

[0016] Further, in step Sp30, the multi-frame simulated images are converted into data files to complete the simulation of the on-board payload data telemetry transmission process, enabling the satellite ground support software to directly analyze and view the target's dynamic motion trajectory. This includes the following steps: The simulation image in .png format obtained in step Sp20 is regarded as a two-dimensional matrix with N rows and M columns. The pixel unit with image coordinates (n,m) corresponds to the matrix element in the nth row and mth column. The storage content of the pixel unit is the gray value of the pixel, and the gray value range is 0-255. Use the OpenCV library to iterate through the pixel units of an image, read the grayscale value of each pixel unit sequentially, and convert it to hexadecimal format; and The converted hexadecimal data is written into a .raw format data file in pixel unit traversal order to generate a single-frame target observation data file; the above operation is performed on all simulation images within a continuous time period to generate a set of corresponding .raw format data files, thus completing the simulation of the on-board payload data telemetry transmission process.

[0017] This invention has at least the following beneficial effects: 1) This invention constructs a continuous motion scenario for on-orbit observation, considering the relative motion of the observation satellite, the target satellite, and the star simultaneously. This overcomes the limitations of existing technologies that only study static imaging, simulating the complete observation process from the target satellite entering the field of view to leaving the field of view. The simulation results are more consistent with the actual on-orbit operation of the payload. 2) This invention integrates the stellar background into the target observation image, calculates the imaging pixel size based on the observation distance, and converts the grayscale value based on the magnitude. This solves the problems of simple imaging settings and single parameter design in existing technologies, improving the realism and visualization effect of the simulated image. 3) This invention visualizes the target's motion trajectory by marking the target position frame by frame, intuitively presenting the target satellite's motion process and providing a clear simulation basis for verifying space target tracking and recognition technologies. 4) This invention converts the simulated image into a raw hexadecimal storage format. The format file simulates the complete process of telemetry data transmission from the satellite payload, matching the actual data transmission method between the satellite payload and the ground. This allows the simulation results to be directly analyzed by the satellite ground software, significantly improving the practical application value of the simulation method and expanding its applicability. 5) This invention uses an octree structure to store stellar data, significantly improving the efficiency of stellar data search and processing. It uses the OpenCV library to complete image fusion, traversal, and format conversion, simplifying the implementation process and reducing development costs. In addition, this invention belongs to the specific application of innovative algorithms in a specific technical field, namely, spatial point target observation. The algorithm is implemented using the C++ programming language, and the resulting technical effect is to improve the security and flexibility of the algorithm. Attached Figure Description

[0018] To further illustrate the above and other advantages and features of the various embodiments of the present invention, a more specific description of the embodiments of the invention will be presented with reference to the accompanying drawings. It is to be understood that these drawings depict only typical embodiments of the invention and are therefore not intended to limit its scope. In the drawings, identical or corresponding parts will be indicated by identical or similar reference numerals for clarity.

[0019] Figure 1 The flowchart of the target motion trajectory simulation method for on-board payloads in some embodiments of the present invention is shown; Figure 2 The flowcharts illustrating the construction of continuous on-orbit observation continuous motion scenarios in some embodiments of the present invention are shown. Figure 3 The following diagrams illustrate the transformation between the camera coordinate system and the image coordinate system in some embodiments of the present invention; Figure 4 The flowcharts for generating continuous motion trajectory maps of targets in some embodiments of the present invention are shown. Figure 5 The following diagrams illustrate the transformation between the image coordinate system and the pixel coordinate system in some embodiments of the present invention; Figure 6 The following are some embodiments of the present invention: a) simulation results of stellar background images; b) simulation results of target observation images; Figure 7 The diagram shows the continuous motion trajectory of the target in some embodiments of the present invention. Detailed Implementation

[0020] It should be noted that the components in the accompanying drawings may be shown exaggerated for illustrative purposes and may not be to scale.

[0021] In this invention, the various embodiments are merely intended to illustrate the solutions of the invention and should not be construed as limiting.

[0022] In this invention, unless otherwise specified, the quantifiers “a” and “one” do not exclude scenarios involving multiple elements.

[0023] It should also be noted that, in the embodiments of the present invention, only a portion of the parts or components may be shown for clarity and simplicity. However, those skilled in the art will understand that, under the teachings of the present invention, the required parts or components can be added as needed for specific scenarios.

[0024] It should also be noted that within the scope of this invention, the terms "same", "equal", and "equal to" do not mean that the two values ​​are absolutely equal, but allow for a certain reasonable error. In other words, the terms also cover "substantially the same", "substantially equal", and "substantially equal to".

[0025] It should also be noted that in the description of this invention, the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not explicitly or implicitly suggest that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] Furthermore, the embodiments of the present invention describe the process steps in a specific order. However, this is only for the convenience of distinguishing each step, and is not a limitation on the order of each step. In different embodiments of the present invention, the order of each step can be adjusted according to the process.

[0027] The following embodiments provide a method for simulating the trajectory of a target based on an on-board payload. Figure 1 The flowchart of the target motion trajectory simulation method for on-board payload is shown, including: Sp10, constructing a continuous motion scene for on-orbit observation; Sp20, generating a continuous motion trajectory map of the target; Sp30, generating a target trajectory data file.

[0028] The main task of Sp10 is to construct a continuous motion scenario for on-orbit observation, considering the observation satellite, target satellite, and stars as simulation objects. Figure 2 A flowchart for constructing a continuous motion scenario for continuous on-orbit observation is shown.

[0029] ① Satellite motion simulation: Establishing a camera coordinate system O based on the payload of the observed satellite. C -X C -Y C -Z C As shown in Figure 3, which illustrates the transformation between the camera coordinate system and the image coordinate system, the origin O is taken as the optical center of the payload. C With the optical axis of the load as Z C Axis, X C Axis, Y C The axes are parallel to the two sides of the observation satellite body; given the motion states of the observation satellite and the target satellite, the relative positional relationship between the two is calculated, thereby obtaining the position information of the target satellite in the camera coordinate system, and the target satellite within the range is obtained according to the payload pointing and the field of view; ②Stellar background simulation, Figure 6 a) Shows the simulation results of the stellar background image; Figure 6(b) shows the simulation results of the target observation image. While the observation satellite detects the target satellite, its onboard payload passively detects the deep-space background, primarily targeting natural celestial bodies such as stars. Based on a standard star catalog, the simulation simulates the star background observed at any observation time and location. The catalog contains information such as stellar right ascension, declination, apparent magnitude, proper motion, and trigonometric parallax. To improve the efficiency of star search within the catalog, an octree structure is used to store stellar data. After calculating the stellar position information, each star is sequentially placed into the corresponding node of the octree according to its spatial position and subsequent calculations are performed. Based on the payload pointing and field of view, stellar targets that will appear within the observation satellite's camera's field of view and meet the set magnitude range requirements are selected, and luminosity parameters are extracted to provide information on the stellar target position and luminosity for the subsequent generation of stellar background images. After sorting the selected stars by magnitude, stars that meet the set magnitude are selected, and their positions are converted from their mean positions at the reference epoch to the observation time based on their proper motion. The position information of the stars in the camera coordinate system is calculated. Using the star background modeling results, the star background at different observation times and locations can be drawn.

[0030] ③ Constructing a continuous motion scene for on-orbit observation: Constructing a continuous motion scene for on-orbit observation refers to the relative motion state of stars, observation satellites, and target satellites over a continuous period of time. Given a continuous time and a continuous motion state, the continuous position information of the target satellite in the camera coordinate system can be obtained based on method ①, and the continuous position information of the stars in the camera coordinate system can be obtained based on method ②, thus completing the construction of a continuous motion scene for on-orbit observation. Given the camera's pointing direction and field of view, the position information of visible stars and visible target satellites can be obtained.

[0031] The main task of Sp20 is to take visible targets and stars in Sp10 as the observation objects, generate observation images and mark the trajectory of the target's centroid motion within a continuous observation period. Figure 4 A flowchart for generating a continuous motion trajectory map of a target is shown.

[0032] ① Generate labeled target observation images: First, based on the positional information of the observed object, the pixel coordinates on the image are obtained. The following coordinate system is defined: Camera coordinate system O. C -X C -Y C -Z C ,like Figure 3 The transformation diagram between the camera coordinate system and the image coordinate system is shown. The X-axis of the camera coordinate system... C Axis, Y CThe axis is parallel to the edge of the satellite body and also parallel to the horizontal and vertical directions of the image plane; a normalized plane is defined, which is a virtual plane located in front of the camera. Its characteristic is that the Z-coordinate of all 3D points in the camera coordinate system projected onto this plane is 1, which simplifies the projection process and facilitates subsequent calculations; the image coordinate system O is defined. I -X I -Y I As shown in Figure 3, the origin O is the center of the image. I , generally the intersection of the camera's optical axis and the imaging plane, X I Axis, Y I The axes are parallel to the horizontal and vertical directions of the image plane, respectively. The unit of the image coordinate system is generally meters (m); the pixel coordinate system ouv is defined, such as... Figure 5 The transformation diagram between image coordinate system and pixel coordinate system is shown. The origin O is the top left corner of the image, and the u-axis and v-axis are parallel to the horizontal and vertical directions of the image plane, respectively. The unit of the pixel coordinate system is generally a pixel. The origin O of the image coordinate system is... I The coordinates in the pixel coordinate system are (u0, v0). Based on Sp10, the position information of the observed object in the camera coordinate system can be obtained. After coordinate transformation, its coordinates in the pixel coordinate system can be obtained. Let P(x) be a point in the camera coordinate system. C ,y C ,z C The diagram illustrates the transformation process as follows: The camera coordinate system is transformed to the image coordinate system, a central projection is performed, and P is calculated using similar triangles. I =[x I y I 1] T =f / z C ×[x C y C 1] T = f / z C ×P C ; Figure 5 The diagram illustrates the transformation between the image coordinate system and the pixel coordinate system. The transformation from the image coordinate system to the pixel coordinate system is as follows: for a point P(u,v) in the pixel coordinate system, u=x I / p+u0, v=y I / p+v0, where p represents the pixel size, i.e., 1 pixel = pm; based on this, a point P in the camera coordinate system can be realized. C Transformation to pixel coordinate system P. Based on the position information of the visible target and visible stars in the camera coordinate system, a scaling transformation is performed to obtain the pixel coordinates of the observed object on the image.

[0033] Secondly, based on the actual size of the observed object and the observation distance, the pixel size on the image is obtained. The total pixel size of the observed object on the image needs to take into account both the point spread function (PSF) of the optical system and the pixel size of the observed object. The detailed calculation steps and formulas are as follows: 1. Calculate the angular diameter θ of the observed object. target The angular diameter of the observed object is determined by its actual size and the observation distance, and is calculated using the formula θ. target =L / R, where θ target The unit is radians, L represents the characteristic size of the observed object in meters, and R represents the distance between the observed object and the observed satellite in meters; 2. Calculate the point spread function (PSF) of the optical system. The PSF describes the degree of blurring of a point target by the optical system, mainly determined by the angular resolution θ of the PSF. target Decision: θ PSF =1.22·λ / D, where θ PSF The units are radians, λ represents the observation wavelength in meters, and D represents the camera aperture in meters; 3. Calculate the pixel size d using the formula d = θ·f / p, where d is in pixels and f represents the focal length of the optical system in meters. Calculate the pixel size d of the observed object using this formula. pixels =θ target ·f / p, calculate the pixel size d of the PSF according to the formula. PSF d PSF =θ PSF ·f / p; 4. Calculate the total pixel size d total =(d PSF 2 + d pixels 2 ) 0.5 , where d total The unit is pixels.

[0034] Third, based on the magnitude information of the observed object, the grayscale value on the image is obtained. Under ideal conditions, the grayscale of the observed object is calculated; the digital image reflects the grayscale level. The relationship between grayscale and magnitude is: for each magnitude decrease, the brightness increases by 2.51 times. Specifically, a magnitude of 5 corresponds to a grayscale value of 255. Based on this relationship, the transformation expression from magnitude Ms to grayscale G is: G = 255 / 2.51. Ms-5 Where Ms is the equivalent apparent magnitude and G is the gray value, the gray values ​​of the star and the target satellite in the image are obtained based on the magnitude information.

[0035] Fourth, generate a star map and a target satellite image. Use the addWeighted function of the OpenCV library to perform weighted fusion of the two images to generate a target observation image with a star background. In order to distinguish the target from the stars and visualize the position of the target, use hollow circles to mark the target in the image, thus completing the generation of a frame of marked target observation image.

[0036] ② Target trajectory marking based on continuous motion images: Based on the on-orbit continuous motion scene constructed by Sp10, a set of continuous target observation images is generated, and the target position in each frame is marked, making the target's motion trajectory visible during continuous observation. This realizes the simulation of the observation process from the observation satellite capturing the target entering the field of view to the target jumping out of the field of view. Figure 7 The continuous motion trajectory of the target is shown.

[0037] The main functions of Sp30 are: to convert target observation images into data files, to analyze and view them using the satellite's ground-based software, and to simulate the telemetry and distribution of onboard payload data.

[0038] In this embodiment, the generated image is in .png format. The format conversion from image to data file essentially involves storing the image's data content in hexadecimal format into the data file. Taking an N×M resolution image as an example, this two-dimensional image can be viewed as an N x M matrix. The pixel unit with image coordinates (n, m) corresponds to the matrix element in the nth row and mth column. The stored content of the pixel unit is its grayscale value, ranging from 0 to 255. Starting from the first row and first column of the two-dimensional image and ending at the Nth row and Mth column, the OpenCV library is used to traverse the image's pixel units, sequentially reading the grayscale values ​​and converting them to hexadecimal, then writing them sequentially into a .raw format file to generate the target observation data file, thus achieving format conversion. For a set of simulation images generated over a continuous time period, a set of corresponding data files is generated after format conversion. When the satellite-compatible ground software is used to parse the data files, the observation images representing the target's dynamic motion trajectory can be dynamically viewed.

[0039] While some embodiments of the present invention have been described in this application, those skilled in the art will understand that these embodiments are merely illustrative. Numerous variations, alternatives, and improvements will arise in those skilled in the art under the teachings of this invention without departing from its scope. The appended claims are intended to define the scope of the invention and thereby cover methods and structures within the scope of the claims themselves and their equivalents.

Claims

1. A method for simulating the trajectory of a target based on an onboard payload, characterized in that, Includes the following steps: Sp10 uses observation satellites, target satellites, and stars as simulation objects. Combining satellite motion simulation and star background simulation, it obtains the position information of visible target satellites and visible stars in the camera coordinate system over a continuous period of time, so as to construct a continuous motion scene for on-orbit observation. Sp20. Based on the location information, the target observation image with a star background is generated by converting coordinates into pixel coordinates, calculating pixel size, and converting grayscale values. Multiple frames of simulated images are generated within a continuous observation period, and the target position is marked frame by frame to visualize the target's motion trajectory from entering the field of view to leaving the field of view, and a continuous motion trajectory map of the target is generated. as well as Sp30. Convert the multi-frame simulation images into data files to complete the simulation of the on-board payload data telemetry transmission process, enabling the satellite ground support software to directly analyze and view the target's dynamic motion trajectory.

2. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp10, the satellite motion simulation includes the following steps: Establishing a camera coordinate system based on the onboard payload of the observation satellite; and Given the motion states of the observation satellite and the target satellite, calculate their relative positional relationship to obtain the position information of the target satellite in the camera coordinate system, and obtain the target satellite within the field of view based on the payload pointing and the field of view.

3. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp10, the stellar background simulation includes the following steps: Based on the standard star catalog, the star background observed at any observation time and any observation location is simulated, and stellar data is stored using an octree structure. Based on the pointing and field of view of the observation satellite payload, stellar targets within the observation satellite camera's field of view that meet the preset magnitude range requirements are selected, and their luminosity parameters are extracted; and The selected stars are sorted by magnitude, and the stars are automatically converted from their mean position at the reference epoch to the observation time. The position information of the stars in the camera coordinate system is calculated to complete the star background modeling.

4. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, The camera coordinate system is O. C -X C -Y C -Z C With the optical center of the load as the origin O C With the optical axis of the load as Z C Axis, X C Axis, Y C The axis is parallel to the two sides of the observation satellite body.

5. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp20, the coordinate transformation includes the following steps: Based on the location information, the points in the camera coordinate system are transformed to the image coordinate system through central projection. The formula for the central projection transformation from the camera coordinate system to the image coordinate system is as follows: P I =[x I y I 1] T =f / z C ×[x C y C 1] T = f / z C ×P C Wherein, P(x C ,y C ,z C P is a point in the camera coordinate system. I Let f be a point in the image coordinate system, and f be the focal length of the optical system; and The points in the image coordinate system are transformed to the pixel coordinate system to obtain the pixel coordinates of the observed object in the image. The transformation formula is as follows: u=x I / p+u­0,v=y I / p+v­0 Where P(u,v) is a point in the pixel coordinate system, p is the pixel size, and (u0, v0) are the coordinates of the origin of the image coordinate system in the pixel coordinate system.

6. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp20, the pixel size is calculated by combining the pixel size of the observed object and the pixel size of the optical system's point spread function (PSF) to obtain the total pixel size of the observed object in the image, including the following steps: Calculate the angular diameter θ of the observed object target : i target =L / R Where, θ target The unit is radians, L represents the characteristic size of the observed object in meters, and R represents the distance between the observed object and the observed satellite in meters. Calculate the PSF, which is determined by the angular resolution θ of the PSF. target Decide: i PSF =1.22 l / D Where, θ PSF The unit is radians, λ represents the observation wavelength in meters, and D represents the camera aperture in meters. Calculate the pixel size d, d = θ·f / p, where d is in pixels and f represents the focal length of the optical system in meters; calculate the pixel size of the observed object using the formula: d pixels =θ target ·f / p Calculate the pixel size of the PSF: d PSF =θ PSF ·f / p Calculate the total pixel size: d total =(d PSF 2 + d pixels 2 ) 0.5 。 7. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp20, the grayscale value conversion includes calculating the grayscale values ​​of visible target satellites and visible stars in the image based on the correspondence between magnitude and grayscale. The conversion formula is as follows: G=255 / 2.51 Ms-5 Where Ms is the equivalent apparent star magnitude, and G is the grayscale value. It is specified that when the star magnitude is 5, the corresponding grayscale value is 255.

8. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp20, multiple frames of simulated images are generated within a continuous observation period, and the target position is marked frame by frame to visualize the target's motion trajectory from entering the field of view to leaving the field of view, generating a continuous motion trajectory map of the target. This includes the following steps: Based on pixel coordinates, pixel size, and grayscale values, a stellar star map and a target satellite image are generated respectively. These two images are then weighted and fused to obtain a target observation image with a stellar background. The pixel coordinates of the target satellite are marked within this image, completing the generation of a single-frame marked target observation image. Based on the continuous motion scene built by Sp10, a set of continuous target observation images is generated, and the target position of each frame image is marked, so that the target's motion trajectory is visualized during continuous observation, realizing the simulation of the observation process from the observation satellite capturing the target entering the field of view to the target jumping out of the field of view.

9. The target motion trajectory simulation method based on on-board payload according to claim 8, characterized in that, The star map and the target satellite map are weighted and fused using the addWeighted function of the OpenCV library; the pixel coordinates of the target satellite are marked with hollow circles after fusion.

10. The target motion trajectory simulation method based on on-board payload according to claim 1, characterized in that, In step Sp30, the multi-frame simulated images are converted into data files to complete the simulation of the on-board payload data telemetry transmission process, enabling the satellite ground software to directly analyze and view the target's dynamic motion trajectory. This includes the following steps: The simulation image in .png format obtained in step Sp20 is regarded as a two-dimensional matrix with N rows and M columns. The pixel unit with image coordinates (n,m) corresponds to the matrix element in the nth row and mth column. The storage content of the pixel unit is the gray value of the pixel, and the gray value range is 0-255. Use the OpenCV library to iterate through the pixel units of an image, read the grayscale value of each pixel unit sequentially, and convert it to hexadecimal format; and The converted hexadecimal data is written into a .raw format data file in pixel unit traversal order to generate a single-frame target observation data file; the above operation is performed on all simulation images within a continuous time period to generate a set of corresponding .raw format data files, thus completing the simulation of the on-board payload data telemetry transmission process.

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