Space target temperature inversion method and device

Abstract

The present invention provides a method and device for inverting the temperature of a space target, relating to the field of data processing technology. The method comprises: obtaining infrared simulated images of a space-based satellite and a ground-based platform, respectively; performing image segmentation on the main body and the sailboard of the surface target in the infrared simulated image of the space-based satellite to obtain a first segmentation result, and performing image segmentation on the point target and celestial body in the infrared simulated image of the ground-based platform to obtain a second segmentation result, wherein the surface target is other satellites observed at close range by the space-based satellite, and the point target is other satellites observed at long distance by the ground-based platform; based on the first segmentation result and the second segmentation result, inverting the temperature of the surface target in the space-based satellite and the point target in the ground-based platform. The above-mentioned method provided by the present invention improves the accuracy and reliability of the image simulation and temperature inversion methods by segmenting the infrared images of the space-based satellite and the ground-based platform to perform temperature inversion on the space target.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and more particularly to a method and device for inverting the temperature of a space target. Background Art

[0002] The temperature of a space target can reflect its working status and other information, providing an important basis for judging the target's thermal control status, material properties and working mode. As a key technology for space situational awareness and target characteristic identification, infrared temperature inversion of space targets obtains the target surface temperature by analyzing the imaging data of infrared simulation images.

[0003] Currently, ground-based infrared observations are the main data source for temperature inversion of space targets. However, due to limitations in detector performance and special scenarios such as highly dynamic and complex structured targets, the cost of acquiring high-quality ground-based infrared images is extremely high. Key modeling factors, such as the non-uniformity of thermal noise in infrared optical systems, can easily lead to insufficient matching between the radiation characteristics of simulated images and measured data.

[0004] Due to the difficulty in calibrating on-orbit sensors on space-based platforms and the extreme lack of actually available measured data, it is difficult to support data-driven temperature inversion model training. Therefore, there is currently a lack of technical means to invert the target temperature distribution through space-based infrared simulation images.

[0005] Existing temperature inversion algorithms lack accuracy in target segmentation and detection. They rely on fixed thresholds or low robustness features in surface target segmentation and small target detection, making it difficult to effectively distinguish between targets and background radiation, which easily leads to the accumulation of temperature solution errors.

[0006] In addition, the temperature inversion results are directly affected by the radiation calibration parameters (such as the non-uniformity of the optical system response and the accuracy of the atmospheric path radiation compensation). However, the existing methods lack a closed-loop error evaluation framework from simulation to inversion, making it difficult to quantify the impact of calibration deviation, noise model and target segmentation error on the final temperature field.

[0007] Currently, there is still a lack of systematic breakthroughs in areas such as space-based and ground-based collaborative infrared image simulation and the integration of adaptive temperature inversion algorithms. Therefore, there is an urgent need to build a full-process technology system that integrates infrared simulation with intelligent temperature inversion and error verification to achieve accurate and efficient reconstruction of target temperatures in complex space environments. Summary of the Invention

[0008] In view of the above problems, the present invention provides a method and device for inverting the temperature of a spatial target.

[0009] On the one hand, the present invention provides a method for inverting the temperature of a space target, comprising: obtaining infrared simulation images of a space-based satellite and a ground-based platform respectively; performing image segmentation on the body of a surface target and the sailboard of the surface target in the infrared simulation image of the space-based satellite to obtain a first segmentation result, and performing image segmentation on the point target and the celestial body in the infrared simulation image of the ground-based platform to obtain a second segmentation result, wherein the surface target is other satellites observed at close range by the space-based satellite, and the point target is other satellites observed at long range by the ground-based platform; and based on the first segmentation result and the second segmentation result, inverting the temperature of the surface target in the space-based satellite and the point target in the ground-based platform.

[0010] According to an embodiment of the present invention, a three-dimensional geometric model of another satellite is created; an observation parameter set of the three-dimensional geometric model is set; coordinate transformation and perspective projection are performed on the body coordinate system of another satellite through the observation parameter set to obtain the plane coordinates of another satellite; the infrared radiation brightness of the body of the surface target and the sailboard of the surface target is obtained through the plane coordinates of the other satellite and the Planck equation; the infrared radiation brightness of the body of the surface target and the sailboard of the surface target is quantified to obtain an infrared simulation image of the space-based satellite.

[0011] According to an embodiment of the present invention, the observation parameter set includes: attitude parameters of the body of the surface target and the sailboard of the surface target, observation parameters of other satellite detectors, observation distance, wavelength, image noise level of other satellites, temperature of the body of the surface target and the sailboard of the surface target, material emissivity of the body of the surface target and the sailboard of the surface target, and deep space background temperature.

[0012] According to an embodiment of the present invention, a first rotation matrix and a translation matrix are constructed by the attitude parameters of the surface target and the sailboard in the observation parameter set, and the body coordinate system of other satellites is converted to the world coordinate system through the first rotation matrix and the translation matrix; a second rotation matrix is ​​constructed by the observation parameters of the detector in the observation parameter set, and the world coordinate system is converted to the camera coordinate system through the second rotation matrix, wherein the camera is used for the detector to observe other satellites; the camera coordinate system is perspective projected to obtain the plane coordinates of other satellites.

[0013] According to an embodiment of the present invention, a three-dimensional geometric model is simplified; an observation parameter set is modified; coordinate transformation and perspective projection are performed based on the modified observation parameter set to obtain the plane coordinates of a point target; the radii of multiple celestial bodies are randomly generated within a preset observation field of view, the plane coordinates of multiple celestial bodies are specified, and a temperature value is randomly assigned to each celestial body; the infrared radiation brightness of multiple celestial bodies, deep space background, and point targets is calculated using the Planck equation using the plane coordinates and temperature values ​​of the multiple celestial bodies and point targets; the infrared radiation brightness of the multiple celestial bodies, deep space background, and point targets is superimposed using the observation parameter set; the superimposed infrared radiation brightness is quantified after adding a diffraction effect, to obtain an infrared simulation image of a ground-based platform.

[0014] According to an embodiment of the present invention, modifying the observation parameter set includes modifying the observation distance, image noise level, and atmospheric transmittance parameters of other satellites.

[0015] According to an embodiment of the present invention, the infrared radiation brightness measurement value of the surface target and the infrared radiation brightness measurement value of the point target are obtained through the first segmentation result and the second segmentation result; the corresponding error equations are established based on the Planck equation through the infrared radiation brightness measurement value of the surface target and the infrared radiation brightness measurement value of the point target; the error equations are iteratively optimized to invert the infrared simulation image temperature of the surface target in the space-based satellite and the point target in the ground-based platform.

[0016] According to an embodiment of the present invention, the infrared simulation images of the space-based satellite and the ground-based platform are both provided with simulated temperatures.

[0017] According to an embodiment of the present invention, a histogram of the temperature of the first mask area is statistically analyzed to obtain a temperature histogram; the peak value of the temperature histogram is calculated to obtain the temperature of the sailboard of the surface target and the body of the surface target, wherein the temperature of the sailboard of the surface target is higher than the temperature of the body of the surface target during the day; the temperature of the second mask area of ​​the infrared simulation image of the ground-based platform is statistically analyzed, wherein the second mask area has connected domains of different areas, and the connected domains with larger areas are used as point target areas; the high temperature average of the connected domains with larger areas is taken as the temperature of the point target; and the temperatures of the point target and the surface target are respectively subjected to error calculation with the simulation temperature to obtain an error evaluation result.

[0018] Another aspect of the present invention provides a space target temperature inversion device, including: an image acquisition module for obtaining infrared simulation images of space-based satellites and ground-based platforms; an image segmentation module for performing image segmentation on the body of a surface target and the sailboard of the surface target in the infrared simulation image of the space-based satellite to obtain a first segmentation result, and performing image segmentation on point targets and celestial bodies in the infrared simulation image of the ground-based platform to obtain a second segmentation result, wherein the surface targets are other satellites observed at close range by the space-based satellite, and the point targets are other satellites observed at long range by the ground-based platform; a temperature inversion module for inverting the temperatures of the surface targets in the space-based satellite and the point targets in the ground-based platform based on the Planck equation according to the first segmentation result and the second segmentation result.

[0019] The spatial target temperature inversion method and device provided by the present invention can achieve the following beneficial effects:

[0020] (1) Aiming at the characteristics of space target imaging systems of space-based satellites and ground-based platforms, it supports rapid simulation of infrared images of space-based and ground-based platforms, provides data support, and can generate high-quality images in a short time by building three-dimensional geometric models and setting observation parameters, effectively enhancing the application flexibility and efficiency of the system;

[0021] (2) An algorithm and process for inverting the temperature of a space target based on infrared simulation images was proposed. By using Planck's radiation law and the least squares method, a high-precision method for inverting the temperature of a space target was provided, filling the current technical gap.

[0022] (3) It covers the complete technical process from infrared image simulation to temperature inversion and then to error evaluation. Through inversion and error analysis, it can optimize the inversion accuracy and ensure the accuracy and reliability of image simulation and temperature inversion methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0024] Figure 1 A flowchart of a spatial target temperature inversion method according to an embodiment of the present invention is schematically shown;

[0025] Figure 2 The principle diagram of the spatial target temperature inversion method according to an embodiment of the present invention is schematically shown.

[0026] Figure 3 The following schematically illustrates a flow chart for generating infrared simulation images of a space-based satellite and a ground-based platform according to an embodiment of the present invention;

[0027] Figure 4 A flowchart of converting other satellite body coordinate systems into plane coordinates according to an embodiment of the present invention is schematically shown;

[0028] Figure 5 Schematically shows a flow chart for constructing an error equation to invert spatial target temperature according to an embodiment of the present invention;

[0029] Figure 6 Schematically shows a flow chart for determining and calculating the temperature of a spatial target through image segmentation results according to an embodiment of the present invention;

[0030] Figure 7 A block diagram of a spatial target temperature inversion device according to an embodiment of the present invention is schematically shown.

[0031] Description of reference numerals:

[0032] 100 - Space-based satellite; 200 - Other satellites; 201 - Other satellite sailboards / surface target sailboards; 202 - Other satellite bodies / surface target bodies; 300 - Ground-based platform; 400 - Celestial body; 500 - Deep space background; 600 - Observation field of view. DETAILED DESCRIPTION

[0033] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concept of the present invention.

[0034] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise," "include," etc. used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0035] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0036] Before describing specific embodiments of the present invention in detail, technical terms are first explained to facilitate a better understanding of the present invention.

[0037] Surface targets: These are targets that occupy multiple pixels and have obvious spatial extension characteristics in remote sensing or infrared imaging. The size and shape of the surface target are clearly visible in the image, and its substructures can be further segmented and analyzed, such as the satellite's solar panels and main body. By segmenting the solar panel area, the temperature distribution of the satellite can be analyzed to see if it is abnormal.

[0038] Point target: refers to a tiny target that occupies only 1-3 pixels in a remote sensing or optoelectronic imaging system. Its spatial size is smaller than the resolution limit of the imaging system and cannot present its geometric shape or internal structure details in the image. Identification mainly relies on its radiation intensity, motion trajectory or spectral characteristics rather than morphological information. For example, a high-orbit satellite (GEO) appears as a single-pixel bright spot in a low-resolution optical image.

[0039] Perspective projection: It is a key geometric transformation from a three-dimensional scene to a two-dimensional image. In infrared simulation of space targets, perspective projection is used to convert a three-dimensional satellite model into pixel coordinates on a two-dimensional image plane.

[0040] In view of this, the present invention provides a method and device for inverting the temperature of a spatial target.

[0041] Figure 1 The flowchart of the spatial target temperature inversion method according to an embodiment of the present invention is schematically shown.

[0042] like Figure 1 As shown, the spatial target temperature inversion method according to this embodiment may include steps S1 to S3.

[0043] In step S1 , infrared simulation images of the space-based satellite 100 and the ground-based platform 300 are obtained respectively.

[0044] The infrared image simulation of space-based satellite 100 is achieved by constructing three-dimensional geometric models of other satellites 200, setting observation parameters, coordinate conversion and perspective projection, and calculating and generating infrared radiation of surface targets. The simulation of ground-based infrared image is achieved by simplifying the three-dimensional geometric model, modifying observation parameters, calculating the infrared radiation of celestial bodies 400 within the observation field of view 600, calculating the atmospheric attenuation of point targets and celestial bodies 400, and adding diffraction effects.

[0045] In step S2, image segmentation is performed on the body 202 of the surface target and the sailboard 201 of the surface target in the infrared simulation image of the space-based satellite 100 to obtain a first segmentation result, and image segmentation is performed on the point target and the celestial body 400 in the infrared simulation image of the ground-based platform 300 to obtain a second segmentation result.

[0046] The infrared simulation image of the space-based satellite 100 is read, and the sailboard 201 and the main body of the satellite's surface target are sequentially segmented by the secondary segmentation method in the predefined clustering algorithm to generate a first mask area. The infrared simulation image of the ground-based platform 300 is read, and the point targets and celestial bodies 400 are detected by reconstructing and suppressing the predefined deep space background 500 to generate a second mask area.

[0047] For example, clustering algorithms can include the K-means algorithm, which classifies pixels by color or intensity; the MeanShift algorithm, which uses density gradients to find dense regions in color space; the DBSCAN algorithm, which separates foreground and background based on density; and the spectral clustering algorithm, which performs graph partitioning on a pixel similarity matrix. To avoid redundant description, this embodiment only describes how one clustering algorithm can be used to segment an image.

[0048] In step S3, the temperatures of the surface target in the space-based satellite 100 and the point target in the ground-based platform 300 are inverted based on the first segmentation result and the second segmentation result.

[0049] The calibration constant is obtained to convert the infrared simulation image into infrared radiation brightness measurement value. The error equation is established based on the Planck equation through the infrared radiation brightness measurement value. The target temperature is inverted by optimizing the error equation through least squares iteration in the first mask area and the second mask area.

[0050] Figure 2 A schematic diagram illustrating a principle diagram of a spatial target temperature inversion method according to an embodiment of the present invention is shown; Figure 3The flowchart of generating infrared simulation images of the space-based satellite 100 and the ground-based platform 300 according to an embodiment of the present invention is schematically shown.

[0051] like Figure 2 and Figure 3 As shown, in this embodiment, the above step S1 includes obtaining the infrared simulation image of the space-based satellite 100 using S111 to S115, and obtaining the infrared simulation image of the ground-based platform 300 using S121 to S127.

[0052] In step S111 , a three-dimensional geometric model of the other satellites 200 is created.

[0053] Create a cube combination of the surface target's body 202, the surface target's sailboard 201, etc. in the body coordinate system of the other satellite 200, or import a general analytical three-dimensional geometric model of the other satellite 200 (.obj, .fbx, .stl format, etc.), where the body coordinate system takes the geometric center of the other satellite 200 as the origin, the X-axis direction is the flight direction of the other satellite 200, the Y-axis is perpendicular to the flight direction of the other satellite 200, and the Z-axis direction is pointing to the center of mass of the earth. X, Y, and Z form a right-handed rectangular coordinate system.

[0054] In step S112, a set of observation parameters of the three-dimensional geometric model is set.

[0055] The observation parameter set of the three-dimensional geometric model includes the attitude parameters of the body 202 of the surface target and the sailboard 201 of the surface target, the observation parameters of the detector, the observation distance, the wavelength, the image noise level, the temperature of the body 202 of the surface target and the sailboard 201 of the surface target, the material emissivity of the body 202 of the surface target and the sailboard 201 of the surface target, the temperature of the deep space background 500, and the atmospheric transmittance parameters, among which the surface target is other satellites 200 observed by the space-based satellite 100 at a close distance, and the point target is other satellites 200 observed by the ground-based platform 300 at a long distance.

[0056] For example, attitude parameters include azimuth, pitch angle, and roll angle; detector observation parameters include observation azimuth and observation pitch angle; the observation distance of the space-based platform is set to 200m~2km; the infrared center wavelength is 10um; the temperature setting range of the body and sailboard is 150K~400K; the emissivity of the body and sailboard is 0.8 and 0.9 respectively; and the deep space background 500 temperature is set to 3K.

[0057] In step S113, coordinate transformation and perspective projection are performed on the body coordinate system of the other satellite 200 using the observation parameter set to obtain the plane coordinates of the other satellite 200;

[0058] A rotation matrix and a perspective projection are established based on the observation parameters to transform the other satellites 200 from a three-dimensional body coordinate system to a two-dimensional one;

[0059] In step S114, the Planck equation is established to obtain the infrared radiation brightness of the body 202 of the surface target and the sailboard 201 of the surface target;

[0060] For example, by setting the simulated temperature of other satellites 200 and the material emissivity parameters of other satellites 200, based on the Planck equation Obtain the infrared radiation brightness of different satellite components and establish the Planck equation according to the following formula:

[0061]

[0062] Where, is the material emissivity of the surface target and other satellite sail panels 201, is Planck's constant, is the speed of light, is the Boltzmann constant, is the wavelength, is the set simulation temperature.

[0063] In step S115 , the infrared radiation brightness of the main body 202 of the surface target and the sailboard 201 of the surface target is quantified to obtain an infrared simulation image of the space-based satellite 100 .

[0064] For example, the infrared radiation brightness of the surface target body 202 and the surface target sailboard 201 is quantized into a grayscale image of 0-255. , calculate the grayscale image according to the following formula :

[0065]

[0066] Where, is the infrared radiation brightness matrix, is the maximum value of the infrared radiation brightness matrix, is the minimum value of the infrared radiation brightness matrix.

[0067] In step S121 , the three-dimensional geometric model is simplified.

[0068] Since the ground-based infrared system is far away from the target, generally hundreds to thousands of kilometers, the point target in the infrared image observation field of view 600 is relatively small, and the three-dimensional geometric model can be simplified to a cube with specified length, width and height.

[0069] In step S122, the observation parameter set is modified.

[0070] For example, modifying the observation parameter set includes modifying the observation distance, image noise level, and atmospheric transmittance parameters of other satellites. The observation distance is set to 200km~1000km, and the image noise level is consistent with the above Planck equation. The atmospheric transmittance parameter is of the same order of magnitude and is a value between 0 and 1. It is an important factor affecting infrared radiation transmission. It can be accurately calculated using professional atmospheric radiation transmission software or roughly estimated based on conventional formulas.

[0071] In step S123, coordinate transformation and perspective projection are performed based on the modified observation parameter set to obtain the plane coordinates of the point target.

[0072] The conversion method used to convert the three-dimensional coordinates of the point target into the plane coordinates is the same as the conversion method of the other satellites 200 mentioned above, and no further details will be given for this.

[0073] In step S124, the radii of multiple celestial bodies 400 are randomly generated within the preset observation field 600, the plane coordinates of the multiple celestial bodies 400 are specified, and a temperature value is randomly assigned to each celestial body 400;

[0074] The radius (1-3 pixels), plane coordinates, and temperature of celestial object 400 are randomly generated within a bounded range. The conversion of the three-dimensional coordinates of celestial object 400 to plane coordinates is performed using the same conversion method as described above for the other satellites 200. Similarly, this will not be further described. In step S125, the plane coordinates and temperatures of multiple celestial objects 400 and point targets are used to calculate the infrared radiation brightness of the multiple celestial objects 400, deep space background 500, and point targets using the Planck equation.

[0075] The infrared radiation brightness acquisition method of point targets, celestial bodies 400, and deep space background 500 is based on the Planck equation The calculation formula is the same, so I will not go into details.

[0076] In step S126, the infrared radiation brightness of multiple celestial bodies 400, deep space background 500 and point targets are superimposed by observing the parameter set.

[0077] For example, the superimposed brightness of the infrared radiation brightness of multiple celestial bodies 400, deep space background 500, and point targets is calculated according to the following formula:

[0078]

[0079] Where, is the infrared radiation brightness of the superimposed image, is the atmospheric transmittance set, is the infrared radiation brightness of the point target, The infrared radiation brightness of the deep space background is 500, is the infrared radiation brightness of celestial body 400, is the image noise level.

[0080] In step S127 , the superimposed infrared radiation brightness is quantified after adding the diffraction effect to obtain an infrared simulation image of the ground-based platform 300 .

[0081] Adding the diffraction effect includes generating a diffraction-limited point spread function, simulating the diffraction effect of the infrared optical system through the point spread function, and adding diffraction blur to the superimposed infrared radiation brightness. The specific method of adding the diffraction effect refers to the existing technology and will not be repeated in this disclosure.

[0082] For example, the intensity distribution of the point spread function is calculated according to the following formula :

[0083]

[0084] Where, is the radial distance on the image plane, is a first-order Bessel function, is the wave number.

[0085] Figure 4 The flowchart of converting the body coordinate system of other satellites 200 into plane coordinates according to an embodiment of the present invention is schematically shown.

[0086] like Figure 4 As shown, in this embodiment, the above step S113 includes converting the body coordinate system of other satellites 200 into plane coordinates using steps S1131 to S1133.

[0087] In step S1131, a first rotation matrix and a translation matrix are constructed by observing the attitude parameters of the body 202 and the sailboard 201 of the surface target in the parameter set, and the other satellites 200 are converted from the body coordinate system to the world coordinate system through the first rotation matrix and the translation matrix.

[0088] For example, the first rotation matrix is ​​constructed by the attitude of the other satellite 200 and translation matrix , transform the other satellites 200 from the body coordinate system to the world coordinate system, and calculate the first rotation matrix according to the following formula and translation matrices :

[0089]

[0090]

[0091] Where, is the azimuth of the space target (around the Z axis), is the pitch angle (around the Y axis), is the roll angle (around the X axis), is the translation coefficient, is the translation unit vector.

[0092] In step S1132, a second rotation matrix is ​​constructed using the observation parameters of the detector in the observation parameter set, and the world coordinate system is converted to the camera coordinate system using the second rotation matrix.

[0093] For example, the second rotation matrix is ​​constructed by the camera pose in the detector's observation parameters , the world coordinate system is converted to the camera coordinate system through the second rotation matrix, wherein the camera is used for the other satellite 200 detector to observe the other satellite 200, and the second rotation matrix is ​​calculated according to the following formula :

[0094]

[0095] Where, is the camera observation azimuth (around the Z axis), is the pitch angle (around the Y axis).

[0096] In step S1133 , perspective projection is performed on the camera coordinate system to obtain the plane coordinates of other satellites 200 .

[0097] According to the three-dimensional coordinates in the camera coordinate system, the camera sight direction is selected and converted into plane coordinates through perspective projection.

[0098] For example, the plane coordinates of the other satellites 200 are calculated according to the following formula ( , ):

[0099]

[0100] Where, is the three-dimensional coordinate of the camera coordinate system after conversion, is the camera focal length.

[0101] Figure 5 The flowchart of constructing an error equation to invert the spatial target temperature according to an embodiment of the present invention is schematically shown.

[0102] like Figure 5 As shown, in this embodiment, the above step S3 inverts the temperature of the surface target in the space-based satellite 100 and the point target in the ground-based platform 300 according to the first segmentation result and the second segmentation result using steps S31 to S33.

[0103] In step S31 , the infrared radiation brightness measurement value of the area target and the infrared radiation brightness measurement value of the point target are obtained through the first segmentation result and the second segmentation result.

[0104] Using the infrared simulation image of the space-based satellite 100, the main body 202 of the surface target and the sailboard 201 of the surface target are detected and segmented to obtain a first segmentation result. Using the infrared simulation image of the ground-based platform 300, the point target, celestial body 400 and deep space background 500 within the observation field of view 600 are detected and segmented to obtain a second segmentation result. The calibration constant is obtained, and the infrared simulation images of the first segmented area and the second segmented area are converted into infrared radiation brightness measurement values ​​through the calibration constant.

[0105] For example, the infrared radiation brightness measurement value of the surface target and the infrared radiation brightness measurement value of the point target are calculated according to the following formula: :

[0106]

[0107] Where, is the gain, is the offset, and DN is the image quantization value.

[0108] In step S32, the infrared radiation brightness measurement value of the surface target is The corresponding error equations are established for the infrared radiation brightness measurement values ​​of the point target .

[0109] For example, the error equation is calculated as follows: :

[0110]

[0111] Where, is the material emissivity, is the Planck equation, is the wavelength.

[0112] In step S33 , the error equation is iteratively optimized to invert the infrared simulation image temperatures of the surface target in the space-based satellite 100 and the point target in the ground-based platform 300 .

[0113] Figure 6 The flowchart of determining and calculating the temperature of a spatial target through image segmentation results according to an embodiment of the present invention is schematically shown.

[0114] like Figure 6 As shown, in this embodiment, the above-mentioned step S31 includes obtaining the temperatures of the sailboard 201 of the surface target and the body 202 of the surface target using steps S3111~S3113, obtaining the temperature of the point target using steps S3121~S3123, and performing error evaluation on the temperatures of the surface target and the point target using step S313.

[0115] In step S3111 , the first segmentation result includes a first mask area.

[0116] The panels and bodies of other satellites 200 are segmented in sequence using a predefined K-means two-level segmentation method to generate a first mask region.

[0117] In step S3112, histogram statistics are performed on the temperature of the first mask area to obtain a temperature histogram.

[0118] Histogram statistics are performed on the temperatures of the target mask area of ​​the first mask area to obtain a temperature histogram.

[0119] In step S3113, the temperature histogram peak is calculated to obtain the temperature of the sailboard and the body of the area target, wherein the temperature of the sailboard of the area target is higher than the temperature of the body of the area target during the day, and the temperature here refers to the surface temperature.

[0120] The histogram data is smoothed, and the histogram peak is found to obtain the corresponding target temperature. Since the temperature of the sailboard 201 (solar panel) of the surface target is higher than that of the body 202 of the surface target during the day, the higher peak temperature during the day is the temperature of the sailboard 201 of the surface target.

[0121] In step S3121 , the second segmentation result includes a second mask area.

[0122] The infrared simulation image of the ground-based platform 300 is read, and the point targets and celestial bodies 400 are detected by reconstructing and suppressing the predefined deep space background 500 to generate a second mask area.

[0123] In step S3122, the temperature of the second mask area of ​​the infrared simulation image of the ground-based platform 300 is counted, and there are connected domains of different areas in the second mask area.

[0124] In the second mask area, the temperatures in the mask connection area between the point target and the celestial body 400 are counted.

[0125] In step S3123, the connected domain with a larger area is used as the point target area, and the high temperature average of the connected domain with a larger area is taken as the temperature of the point target.

[0126] The high temperature average is taken to reduce the error caused by the diffraction effect. In the second mask area, point targets and celestial bodies 400 are distinguished based on the area of ​​the connected regions, and the connected regions with larger areas are regarded as point target regions.

[0127] In step S313, the inverted temperatures of the point target and the surface target are respectively subjected to error calculations with the simulated temperatures to obtain error evaluation results.

[0128] The error evaluation is performed according to the set temperature of the simulation image. The set temperature of the simulation image is taken as the true value and the inverted temperature value is taken as the measured value. The absolute error and error percentage of the two are calculated.

[0129] In summary, the embodiment of the present invention provides a method for inverting the temperature of a spatial target, which has the following beneficial effects:

[0130] (1) Aiming at the characteristics of space target imaging systems of space-based satellites and ground-based platforms, it supports rapid simulation of infrared images of space-based and ground-based platforms, provides data support, and can generate high-quality infrared images in a short time by building three-dimensional geometric models and setting observation parameters, effectively enhancing the application flexibility and efficiency of the system;

[0131] (2) An algorithm and process for inverting the temperature of a space target based on infrared simulation images was proposed. By using Planck's radiation law and the least squares method, a high-precision method for inverting the temperature of a space target was provided, filling the current technical gap.

[0132] (3) It covers the complete technical process from infrared image simulation to temperature inversion and then to error evaluation. Through intelligent inversion and error analysis, it can optimize the inversion accuracy and ensure the accuracy and reliability of image simulation and temperature inversion algorithms.

[0133] Based on the method disclosed in the above embodiment, the present invention also provides a space target temperature inversion device, which will be combined with Figure 7 The device is described in detail.

[0134] Figure 7 A block diagram of a spatial target temperature inversion device according to an embodiment of the present invention is schematically shown.

[0135] like Figure 7 As shown, the space target temperature inversion device 700 according to this embodiment includes an image acquisition module 710 , an image segmentation module 720 and a temperature inversion module 730 .

[0136] An image acquisition module 710 is used to obtain infrared simulation images of the space-based satellite 100 and the ground-based platform;

[0137] An image segmentation module 720 is configured to perform image segmentation on the body of the area target and the sailboard of the area target in the infrared simulation image of the space-based satellite 100 to obtain a first segmentation result, and to perform image segmentation on the point target and the celestial body 400 in the infrared simulation image of the ground-based platform to obtain a second segmentation result;

[0138] The temperature inversion module 730 is used to invert the measured temperatures of the surface target in the space-based satellite 100 and the point target in the ground-based platform according to the first segmentation result and the second segmentation result.

[0139] It should be noted that the embodiment of the device part is similar to the embodiment of the method part, and the technical effects achieved are also similar. For specific details, please refer to the above-mentioned method embodiment part, which will not be repeated here.

[0140] According to embodiments of the present invention, any multiple of the image acquisition module 710, image segmentation module 720, and temperature inversion module 730 can be combined into a single module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in a single module. According to embodiments of the present invention, at least one of the image acquisition module 710, image segmentation module 720, and temperature inversion module 730 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented in hardware or firmware through any other suitable means of circuit integration or packaging, or can be implemented in any one of software, hardware, and firmware, or any suitable combination of these. Alternatively, at least one of the image acquisition module 710, image segmentation module 720, and temperature inversion module 730 can be at least partially implemented as a computer program module that, when executed, performs the corresponding functionality.

[0141] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architectures, functions and operations of the devices and methods according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0142] The features described in the various embodiments of the present invention may be combined or coupled in various ways, even if such combinations or couplings are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention may be combined or coupled in various ways without departing from the spirit and teachings of the present invention. All such combinations or couplings fall within the scope of the present invention.

[0143] The above describes embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be advantageously used in combination. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for inverting the temperature of a spatial target, characterized in that: include: Obtain infrared simulation images of space-based satellites and ground-based platforms respectively; Performing image segmentation on the body of the area target and the sailboard of the area target in the infrared simulation image of the space-based satellite to obtain a first segmentation result, and performing image segmentation on the point target and the celestial body in the infrared simulation image of the ground-based platform to obtain a second segmentation result, The area targets are other satellites observed by the space-based satellite at close range, and the point targets are other satellites observed by the ground-based platform at long range; Inverting the temperatures of the surface target in the space-based satellite and the point target in the ground-based platform according to the first segmentation result and the second segmentation result, Wherein, inverting the temperature of the surface target in the space-based satellite and the point target in the ground-based platform according to the first segmentation result and the second segmentation result includes: Obtaining an infrared radiation brightness measurement value of the area target and an infrared radiation brightness measurement value of the point target through the first segmentation result and the second segmentation result; Establishing corresponding error equations based on the Planck equation using the infrared radiation brightness measurement value of the area target and the infrared radiation brightness measurement value of the point target; The error equation is iteratively optimized to invert the infrared simulation image temperature of the surface target in the space-based satellite and the point target in the ground-based platform respectively.

2. The method according to claim 1, characterized in that The step of obtaining an infrared simulation image of a space-based satellite comprises: creating a three-dimensional geometric model of the other satellite; Setting a set of observation parameters of the three-dimensional geometric model; Performing coordinate transformation and perspective projection on the body coordinate system of the other satellites using the observation parameter set to obtain the plane coordinates of the other satellites; Obtaining the infrared radiation brightness of the body of the area target and the sailboard of the area target through the plane coordinates of the other satellites and the Planck equation; The infrared radiation brightness of the body of the area target and the sailboard of the area target is quantified to obtain an infrared simulation image of the space-based satellite.

3. The method according to claim 2, characterized in that The observation parameter set includes: attitude parameters of the body of the surface target and the sailboard of the surface target, observation parameters of the other satellite detectors, observation distance, wavelength, image noise level of the other satellites, temperature of the body of the surface target and the sailboard of the surface target, material emissivity of the body of the surface target and the sailboard of the surface target, and deep space background temperature.

4. The method according to claim 2, characterized in that The performing coordinate transformation and perspective projection on the body coordinate system of the other satellite to obtain the plane coordinates of the other satellite includes: Constructing a first rotation matrix and a translation matrix by using the body of the surface target and the attitude parameters of the sailboard of the surface target in the observation parameter set, and converting the other satellites from the body coordinate system to the world coordinate system by using the first rotation matrix and the translation matrix; constructing a second rotation matrix using the observation parameters of the probe in the observation parameter set, and converting the world coordinate system into a camera coordinate system using the second rotation matrix, wherein the camera is used by the probe to observe the other satellites; Perform perspective projection on the camera coordinate system to obtain the plane coordinates of the other satellites.

5. The method according to claim 2, characterized in that The step of obtaining an infrared simulation image of a ground-based platform includes: simplifying the three-dimensional geometric model; Modifying the observation parameter set; Performing coordinate transformation and perspective projection based on the modified observation parameter set to obtain the plane coordinates of the point target; Randomly generate the radii of multiple celestial bodies within a preset observation field, specify the plane coordinates of the multiple celestial bodies, and randomly assign a temperature value to each of the celestial bodies; Calculating the infrared radiation brightness of the multiple celestial bodies, the deep space background, and the point target using the Planck equation using the plane coordinates of the multiple celestial bodies and the point target and the temperature value; superimposing the infrared radiation brightness of the multiple celestial bodies, the deep space background, and the point target using the observation parameter set; The superimposed infrared radiation brightness is quantified after adding the diffraction effect to obtain an infrared simulation image of the foundation platform.

6. The method according to claim 5, characterized in that Modifying the observation parameter set includes modifying the observation distance, image noise level, and atmospheric transmittance parameters of the other satellites.

7. The method according to claim 1, characterized in that The infrared simulation images of the space-based satellite and the ground-based platform are both provided with simulation temperatures.

8. The method according to claim 1, characterized in that The first segmentation result includes a first mask area, and the second segmentation result includes a second mask area; the method further includes: Performing histogram statistics on the temperature of the first mask area to obtain a temperature histogram; Calculating the peak value of the temperature histogram to obtain the temperature of the sailboard of the area target and the body of the area target, wherein the temperature of the sailboard of the area target is higher than the temperature of the body of the area target during the day; Counting the temperature of a second mask area of ​​the infrared simulation image of the ground-based platform, wherein the second mask area has connected domains of different areas, and the connected domain with the larger area is used as the point target area; Taking the high temperature average of the connected domain with a larger area as the temperature of the point target; The temperatures of the point target and the surface target are respectively subjected to error calculation with the simulation temperature to obtain error evaluation results.

9. A space target temperature inversion device, characterized in that: include: Image acquisition module, used to obtain infrared simulation images of space-based satellites and ground-based platforms; An image segmentation module is configured to perform image segmentation on the body of the surface target and the sailboard of the surface target in the infrared simulation image of the space-based satellite to obtain a first segmentation result, and to perform image segmentation on the point target and celestial body in the infrared simulation image of the ground-based platform to obtain a second segmentation result. The area targets are other satellites observed by the space-based satellite at close range, and the point targets are other satellites observed by the ground-based platform at long range; a temperature inversion module, configured to invert the temperatures of the surface target in the space-based satellite and the point target in the ground-based platform based on the Planck equation according to the first segmentation result and the second segmentation result; Wherein, inverting the temperature of the surface target in the space-based satellite and the point target in the ground-based platform according to the first segmentation result and the second segmentation result includes: Obtaining an infrared radiation brightness measurement value of the area target and an infrared radiation brightness measurement value of the point target through the first segmentation result and the second segmentation result; Corresponding error equations are established based on the Planck equation using the infrared radiation brightness measurement value of the area target and the infrared radiation brightness measurement value of the point target.

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