Space target temperature inversion method and device

Abstract

The invention provides a space target temperature inversion method and device, and relates to the technical field of data processing. The method comprises the following steps: respectively obtaining infrared simulation images of a space-based satellite and a foundation platform; image segmentation is carried out on a body of a surface target and a sailboard of the surface target in the infrared simulation image of the space-based satellite to obtain a first segmentation result, image segmentation is carried out on a point target and a celestial body in the infrared simulation image of the foundation platform to obtain a second segmentation result, the surface target is other satellites observed by the space-based satellite in a close range, and the point target is other satellites observed by the foundation platform in a close range. The point targets are other satellites observed by the foundation platform in a long distance; according to the first segmentation result and the second segmentation result, the temperature of the space-based satellite middle surface target and the temperature of the foundation platform middle point target are inverted. According to the method provided by the invention, the temperature inversion is carried out on the space target by segmenting the infrared images of the space-based satellite and the foundation platform, and the accuracy and reliability of the image simulation and temperature inversion method are improved.

Description

Technical Field

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

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

[0003] At present, ground-based infrared observation is the main data source for space target temperature inversion. However, limited by the detector performance and special scenarios such as high-dynamic and complex-structured targets, the cost of obtaining high-quality ground-based infrared images is extremely high. Due to key modeling factors such as the non-uniformity of the thermal noise of the infrared optical system, it is easy to result in insufficient matching of the radiation characteristics between the simulation image and the measured data.

[0004] Due to the great difficulty in calibrating on-orbit sensors for space-based platforms, the actual available measured data is extremely scarce, making it difficult to support the training of data-driven temperature inversion models. Therefore, there is a lack of technical means for inverting the target temperature distribution through space-based infrared simulation images at present.

[0005] Existing temperature inversion algorithms have insufficient interpretation accuracy in target segmentation and detection. In the segmentation of surface targets and the detection of small and weak targets, they rely on fixed thresholds or low-robustness features, making it difficult to effectively distinguish the target from the background radiation and easily leading to the accumulation of temperature calculation errors.

[0006] In addition, the temperature inversion result is directly affected by radiation calibration parameters (such as the non-uniformity of the optical system response and the accuracy of 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 transfer effects of calibration deviation, noise model, and target segmentation error on the final temperature field.

[0007] At present, there is still a lack of systematic breakthroughs in aspects such as space / ground collaborative infrared image simulation and the integration of adaptive temperature inversion algorithms. Therefore, it is urgent to construct a full-process technical system that integrates infrared simulation, intelligent temperature inversion, and error verification to achieve accurate and efficient reconstruction of the target temperature in a complex space environment. 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 space target.

[0009] On the one hand, the present invention provides a method for retrieving the temperature of a space target, including: obtaining infrared simulation images of a space-based satellite and a ground-based platform respectively; performing image segmentation on the main 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 performing image segmentation on the point target and celestial bodies in the infrared simulation image of the ground-based platform to obtain a second segmentation result, where the surface target is another satellite observed closely by the space-based satellite, and the point target is another satellite observed remotely by the ground-based platform; retrieving 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.

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

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

[0012] According to an embodiment of the present invention, a first rotation matrix and a translation matrix are constructed through the attitude parameters of the surface target and the sailboard in the set of observation parameters, and the body coordinate system of the other satellite is transformed into the world coordinate system through the first rotation matrix and the translation matrix; a second rotation matrix is constructed through the observation parameters of the detector in the set of observation parameters, and the world coordinate system is transformed into the camera coordinate system through the second rotation matrix, where the camera is used for the detector to observe the other satellite; perspective projection is performed on the camera coordinate system to obtain the planar coordinates of the other satellite.

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

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

[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; corresponding error equations are established respectively 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 respectively 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 simulation temperatures.

[0017] According to an embodiment of the present invention, the temperature of the first mask region 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 region of the infrared simulation image of the ground-based platform is statistically analyzed, wherein there are connected regions with different areas in the second mask region, and the connected region with a larger area is used as the point target region; the high-temperature average value of the connected region with a larger area is taken as the temperature of the point target; the temperatures of the point target and the surface target are respectively calculated with the simulation temperature to obtain an error evaluation result.

[0018] Another aspect of the present invention provides a device for inverting the temperature of a space target, including: an image acquisition module for acquiring infrared simulation images of a space-based satellite and a ground-based platform; an image segmentation module for performing 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 performing image segmentation on the point target and celestial bodies in the infrared simulation image of the ground-based platform to obtain a second segmentation result, wherein the surface target is another satellite observed closely by the space-based satellite, and the point target is another satellite observed remotely by the ground-based platform; a temperature inversion module for inverting 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.

[0019] The method and device for inverting the temperature of a space target provided by the present invention can achieve the following beneficial effects:

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

[0021] (2) A spatial target temperature inversion algorithm and process based on infrared simulation images are proposed. By using Planck's radiation law and the least squares method, a high-precision spatial target temperature inversion method is provided, filling the current technical gap.

[0022] (3) It covers a complete technical process from infrared image simulation to temperature inversion and then to error evaluation. Through inversion and error analysis, the inversion accuracy can be optimized to ensure the accuracy and reliability of the image simulation and temperature inversion methods. Description of the Drawings

[0023] Through the following description of the embodiments of the present invention with reference to the drawings, the above and other objects, features, and advantages of the present invention will become clearer. In the drawings:

[0024] Figure 1 Schematically shows the flowchart of the spatial target temperature inversion method according to an embodiment of the present invention;

[0025] Figure 2 Schematically shows the principle diagram of the spatial target temperature inversion method according to an embodiment of the present invention.

[0026] Figure 3 Schematically shows the flowchart of generating infrared simulation images of space-based satellites and ground-based platforms according to an embodiment of the present invention;

[0027] Figure 4 Schematically shows the flowchart of converting the body coordinate system of other satellites into a plane coordinate according to an embodiment of the present invention;

[0028] Figure 5 Schematically shows the flowchart of constructing an error equation to invert the temperature of a spatial target;

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

[0030] Figure 7 Schematically shows the block diagram of the spatial target temperature inversion device according to an embodiment of the present invention.

[0031] Description of the Reference Numerals in the Drawings:

[0032] 100 - Space-based satellite; 200 - Other satellites; 201 - The solar panel of other satellites / solar panel of the surface target; 202 - The body of other satellites / body of the surface target; 300 - Ground-based platform; 400 - Celestial body; 500 - Deep space background; 600 - Observation field of view. Detailed Embodiments

[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 merely exemplary and are not intended to limit the scope of the present invention. In the following detailed description, for the sake of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present invention. However, it is obvious that one or more embodiments can be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concepts of the present invention.

[0034] The terms used herein are merely for describing specific embodiments and are not intended to limit the present invention. The terms "including", "comprising", 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 the specific embodiments of the present invention in detail, technical terms are first explained to facilitate a better understanding of the present invention.

[0037] Surface target: refers to a target that occupies multiple pixels and has obvious spatial expansion characteristics in remote sensing or infrared imaging. The size and shape of the surface target are clearly visible in the image, and its sub-structures can be further segmented and analyzed, such as the solar panels and the main body of a satellite. By segmenting the solar panel area, it can be analyzed whether the temperature distribution of the satellite is abnormal.

[0038] Point target: refers to a tiny target that only occupies 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 its geometric shape or internal structure details cannot be presented in the image. Identification mainly relies on its radiation intensity, motion trajectory, or spectral characteristics, rather than morphological information. For example, a geostationary earth orbit (GEO) satellite appears as a single-pixel bright spot in a low-resolution optical image.

[0039] Perspective projection: is a key geometric transformation from a three-dimensional scene to a two-dimensional image. In the infrared simulation of spatial 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 temperature inversion of spatial targets.

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

[0042] As shown Figure 1 in the figure, the space 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 the space-based satellite 100 is realized through the construction of the three-dimensional geometric model of other satellites 200, the setting of observation parameters, coordinate transformation and perspective projection, and the calculation and generation of the infrared radiation of the surface target. The infrared image simulation of the ground-based platform is realized by simplifying the three-dimensional geometric model, modifying the observation parameters and 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, 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 are segmented to obtain a first segmentation result, and the point target and the celestial body 400 in the infrared simulation image of the ground-based platform 300 are segmented to obtain a second segmentation result.

[0046] Read the infrared simulation image of the space-based satellite 100, and sequentially segment the sailboard 201 and the body components of the surface target of the satellite through the secondary segmentation method in the predefined clustering algorithm to generate a first mask area. Read the infrared simulation image of the ground-based platform 300, and detect the point target and each celestial body 400 through the reconstruction and suppression of the predefined deep space background 500 to generate a second mask area.

[0047] For example, the clustering algorithm can adopt the K-means algorithm: classify pixels according to color or intensity values; the MeanShift algorithm: find dense regions in the color space through density gradients; the DBSCAN algorithm: separate the foreground and background based on density; the spectral clustering algorithm: perform graph partitioning on the pixel similarity matrix. To avoid repetition, only one clustering algorithm for image segmentation is described in this embodiment.

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

[0049] Obtain the calibration constant to convert the infrared simulation image into an infrared radiance measurement value, establish an error equation based on the Planck equation through the infrared radiance measurement value, and invert the target temperature by optimizing the error equation through least squares iteration in the first mask area and the second mask area.

[0050] Figure 2 Schematically shows the principle diagram of the space target temperature inversion method according to an embodiment of the present invention; Figure 3Schematically shows a 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.

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

[0052] In step S111, create a three-dimensional geometric model of the other satellite 200.

[0053] Create a cube combination such as the body 202 of the surface target and the solar panel 201 of the surface target in the body coordinate system of the other satellite 200, or import a parsed general three-dimensional geometric model of the other satellite 200 (.obj,.fbx,.stl format, etc.). Among them, 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, the Z-axis direction is the direction pointing to the Earth's centroid, and X, Y, and Z form a right-handed rectangular coordinate system.

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

[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 solar panel 201 of the surface target, the observation parameters of the detector, the observation distance, the wavelength, the image noise level, the temperatures of the body 202 of the surface target and the solar panel 201 of the surface target, the material emissivities of the body 202 of the surface target and the solar panel 201 of the surface target, the temperature of the deep space background 500, and the atmospheric transmittance parameter. Among them, the surface target is the other satellite 200 observed closely by the space-based satellite 100, and the point target is the other satellite 200 observed remotely by the ground-based platform 300.

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

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

[0058] Based on the observation parameters, establish a rotation matrix and perspective projection to convert the other satellite 200 from the three-dimensional body coordinate system to two dimensions;

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

[0060] For example, by setting the simulation temperature of other satellites 200 and the emissivity parameters of the materials of other satellites 200, etc., based on the Planck equation the infrared radiation brightness of different components of the satellite is obtained, and the Planck equation is established according to the following formula:

[0061]

[0062] In the formula, is the emissivity of the materials of the surface target and the sailboard 201 of other satellites, is the Planck 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 the infrared simulation image of the space-based satellite 100.

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

[0065]

[0066] In the formula, 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] Given that the distance between the ground-based infrared system and the target is relatively far, generally ranging from several hundred kilometers to several thousand kilometers, the point targets in the infrared image observation field 600 are 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 set of observation parameters is modified.

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

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

[0072] The conversion method for converting the three-dimensional coordinates of the point target into planar coordinates is the same as that of the above-mentioned other satellites 200, and thus will not be elaborated further here.

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

[0074] Radii of celestial bodies 400 (1 - 3 pixels), planar coordinates of celestial bodies 400, and temperatures are randomly generated within a bounded range. The conversion method for converting the three-dimensional coordinates of celestial bodies 400 into planar coordinates is the same as that of the above-mentioned other satellites 200, and similarly, it will not be elaborated further here. In step S125, using the planar coordinates and temperature values of the multiple celestial bodies 400 and the point target, the infrared radiation brightnesses of the multiple celestial bodies 400, the deep space background 500, and the point target are calculated through the Planck equation.

[0075] The methods for obtaining the infrared radiation brightnesses of the point target, celestial bodies 400, and deep space background 500 are the same as the above-mentioned calculation formulas based on the Planck equation and thus will not be elaborated further here.

[0076] In step S126, the infrared radiation brightnesses of the multiple celestial bodies 400, the deep space background 500, and the point target are superimposed through the set of observation parameters.

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

[0078]

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

[0080] In step S127, after adding the diffraction effect to the superimposed infrared radiation luminance, quantization is performed to obtain the 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 luminance. The specific method of adding the diffraction effect refers to the prior art and will not be elaborated in detail in this disclosure.

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

[0083]

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

[0085] Figure 4 Schematically shows a flowchart of converting the other satellite 200 from the body coordinate system to the plane coordinate system according to an embodiment of the present invention.

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

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

[0088] For example, a first rotation matrix is constructed through the attitude of the other satellite 200 and the translation matrix , and the other satellite 200 is converted from the body coordinate system to the world coordinate system. Calculate the first rotation matrix according to the following formula and the translation matrix :

[0089]

[0090]

[0091] In the formula, is the azimuth angle 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 based on the observation parameters of the detectors in the set of observation parameters, and the world coordinate system is converted to the camera coordinate system through the second rotation matrix.

[0093] For example, a second rotation matrix is constructed based on the camera attitude in the observation parameters of the detector , and the world coordinate system is converted to the camera coordinate system through the second rotation matrix, where the camera is used by the detector of the other satellite 200 to observe the other satellite 200, and the second rotation matrix is calculated according to the following formula :

[0094]

[0095] In the formula, is the azimuth angle of camera observation (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 planar coordinates of the other satellite 200.

[0097] Based on the three-dimensional coordinates in the camera coordinate system, the camera line-of-sight direction is selected and converted to planar coordinates through perspective projection.

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

[0099]

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

[0101] Figure 5 Schematically shows a flowchart of constructing an error equation to invert the temperature of a space target according to an embodiment of the present invention.

[0102] As Figure 5 shown, in this embodiment, step S3 above for inverting the temperatures 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 adopts steps S31 to S33.

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

[0104] Using the infrared simulation images of the space-based satellite 100, the 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 images of the ground-based platform 300, point targets, celestial bodies 400, and deep-space background 500 within the observation field 600 are detected and segmented to obtain a second segmentation result. The calibration constant is obtained, and through the calibration constant, the infrared simulation images of the first segmentation region and the second segmentation region are converted into infrared radiance measurement values.

[0105] For example, calculate the infrared radiance measurement value of the surface target and the infrared radiance measurement value of the point target according to the following formula :

[0106]

[0107] In the formula, is the gain amount, is the offset, and DN is the image quantization value.

[0108] In step S32, corresponding error equations are established respectively through the infrared radiance measurement value of the surface target and the infrared radiance measurement value of the point target .

[0109] For example, calculate the error equation according to the following formula :

[0110]

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

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

[0113] Figure 6 Schematically shows a flowchart of judging and calculating the temperature of a space target based on the image segmentation result according to an embodiment of the present invention.

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

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

[0116] The sailboard and the main body of other satellites 200 are successively segmented by a predefined K-means secondary segmentation method to generate a first mask region.

[0117] In step S3112, a histogram of the temperature of the first mask region is statistically calculated to obtain a temperature histogram.

[0118] A histogram of the temperature of the target mask region of the first mask region is statistically calculated to obtain a temperature histogram.

[0119] In step S3113, the temperature of the sailboard of the surface target and the main body of the surface target is obtained by calculating the peak value of the temperature histogram. Among them, the temperature of the sailboard of the surface target is higher than that of the main body of the surface target during the day. Here, the temperature refers to the surface temperature.

[0120] Smooth the histogram data, search for the peak value of the histogram 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 main 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 region.

[0122] Read the infrared simulation image of the ground-based platform 300, and detect point targets and each celestial body 400 through predefined deep space background 500 reconstruction and suppression to generate a second mask region.

[0123] In step S3122, the temperature of the second mask region of the infrared simulation image of the ground-based platform 300 is statistically calculated. There are connected regions with different areas in the second mask region.

[0124] In the second mask region, the temperature within the mask connected region of the point target and the celestial body 400 is statistically calculated.

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

[0126] Take the high-temperature average value to reduce the error caused by the diffraction effect. In the second mask region, the point target and the celestial body 400 are discriminated based on the area of the connected region, and the connected region with a larger area is used as the point target region.

[0127] In step S313, the error evaluation result is obtained by calculating the error between the inversion temperatures of the point target and the surface target and the simulation temperature respectively.

[0128] The error evaluation is carried out according to the temperature set by the simulation. By taking the set temperature of the simulation image as the true value and the inverted temperature value as the measured value, the absolute error and the error percentage between the two are calculated.

[0129] In summary, the embodiments of the present invention provide a method for inverting the temperature of a space target, which has the following beneficial effects:

[0130] (1) Aiming at the characteristics of space target imaging systems on space-based satellites and ground-based platforms, it supports the 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 constructing a three-dimensional geometric model and setting observation parameters, effectively enhancing the application flexibility and efficiency of the system;

[0131] (2) A space target temperature inversion algorithm and process based on infrared simulation images are proposed. Using Planck's radiation law and the least squares method, a high-precision space target temperature inversion method is provided, filling the current technical gap;

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

[0133] Based on the method disclosed in the above embodiments, the present invention also provides a space target temperature inversion device, which will be described in detail below in combination with Figure 7 This device will be described in detail.

[0134] Figure 7 The block diagram of the space target temperature inversion device according to the embodiment of the present invention is schematically shown.

[0135] As Figure 7 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] The image acquisition module 710 is used to acquire infrared simulation images of the space-based satellite 100 and the ground-based platform;

[0137] The image segmentation module 720 is used 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 100 to obtain a first segmentation result, and 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 embodiments of the device part are similar to the embodiments of the method part, and the achieved technical effects are also similar. For specific details, please refer to the method embodiment part above and will not be elaborated here.

[0140] According to an embodiment of the present invention, any combination of the image acquisition module 710, the image segmentation module 720, and the temperature inversion module 730 may be integrated into one module, or any one of them may be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the image acquisition module 710, the image segmentation module 720, and the temperature inversion module 730 may 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-chip, a system-on-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable way of integrating or packaging circuits, etc., in hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, at least one of the image acquisition module 710, the image segmentation module 720, and the temperature inversion module 730 may be at least partially implemented as a computer program module, which can execute corresponding functions when the computer program module is run.

[0141] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices and methods according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or 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 blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

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

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

Claims

1. A method for retrieving the temperature of a space target, characterized in that, Including: Obtaining infrared simulation images of a space-based satellite and a ground-based platform respectively; Performing image segmentation on the main body of the planar target and the solar panels of the planar 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 celestial bodies in the infrared simulation image of the ground-based platform to obtain a second segmentation result, wherein, the planar target is another satellite observed by the space-based satellite at a close distance, and the point target is the other satellite observed by the ground-based platform at a long distance; Inverting the temperatures of the planar 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.

2. The method according to claim 1, wherein The obtaining of the infrared simulation image of the space-based satellite includes: Creating a three-dimensional geometric model of the other satellite; Setting a set of observation parameters for the three-dimensional geometric model; Performing coordinate transformation and perspective projection on the body coordinate system of the other satellite through the set of observation parameters to obtain the planar coordinates of the other satellite; Obtaining the infrared radiance of the main body of the planar target and the solar panels of the planar target through the planar coordinates of the other satellite and the Planck equation; Quantifying the infrared radiance of the main body of the planar target and the solar panels of the planar target to obtain the infrared simulation image of the space-based satellite.

3. The method according to claim 2, wherein The set of observation parameters includes: attitude parameters of the main body of the planar target and the solar panels of the planar target, observation parameters of the detector of the other satellite, observation distance of the other satellite, wavelength, image noise level, temperatures of the main body of the planar target and the solar panels of the planar target, material emissivity of the main body of the planar target and the solar panels of the planar target, deep space background temperature.

4. The method according to claim 2, wherein The performing of coordinate transformation and perspective projection on the body coordinate system of the other satellite to obtain the planar coordinates of the other satellite includes: Constructing a first rotation matrix and a translation matrix through the attitude parameters of the main body of the planar target and the solar panels of the planar target in the set of observation parameters, and converting the other satellite from the body coordinate system to the world coordinate system through the first rotation matrix and the translation matrix; Constructing a second rotation matrix through the observation parameters of the detector in the set of observation parameters, and converting the world coordinate system to the camera coordinate system through the second rotation matrix, where the camera is used for the detector to observe the other satellite; Performing perspective projection on the camera coordinate system to obtain the planar coordinates of the other satellite.

5. The method according to claim 2, characterized in that, The obtaining of the infrared simulation image of the ground-based platform includes: Simplifying the three-dimensional geometric model; Modifying the set of observation parameters; Performing coordinate transformation and perspective projection based on the modified set of observation parameters to obtain the planar coordinates of the point target; Randomly generating the radii of multiple celestial bodies within a preset observation field of view, specifying the planar coordinates of the multiple celestial bodies, and randomly assigning temperature values to each celestial body; Using the planar coordinates and the temperature values of the multiple celestial bodies and the point target, and calculating the infrared radiance of the multiple celestial bodies, the deep space background and the point target through the Planck equation; Superimposing the infrared radiance of the multiple celestial bodies, the deep space background and the point target through the set of observation parameters. Quantify the infrared radiance after adding the diffraction effect to the superimposed infrared radiance to obtain the infrared simulation image of the ground-based platform.

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

7. The method according to claim 1, characterized in that The inversion of the temperatures of the mid-plane target of the space-based satellite and the mid-point target of the ground-based platform according to the first segmentation result and the second segmentation result includes: Obtaining the infrared radiance measurement value of the plane target and the infrared radiance 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 through the infrared radiance measurement value of the plane target and the infrared radiance measurement value of the point target respectively; Iteratively optimizing the error equations to invert the infrared simulation image temperatures of the mid-plane target of the space-based satellite and the mid-point target of the ground-based platform respectively.

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

9. The method according to claim 7, characterized in that, The first segmentation result includes a first mask region, and the second segmentation result includes a second mask region; the method further includes: Performing a histogram statistics on the temperature of the first mask region to obtain a temperature histogram; Calculating the peak value of the temperature histogram to obtain the temperatures of the sailboard of the plane target and the body of the plane target, wherein the temperature of the sailboard of the plane target is higher than the temperature of the body of the plane target during the day; Statistical analysis of the temperature of the second mask region of the infrared simulation image of the ground-based platform, wherein there are connected regions with different areas in the second mask region, and the connected region with a larger area is used as the point target region; Taking the high-temperature average value of the connected region with a larger area as the temperature of the point target; Calculating the error between the temperatures of the point target and the plane target and the simulation temperature respectively to obtain an error evaluation result.

10. A spatial target temperature inversion device, characterized in that, Including: An image acquisition module for acquiring the infrared simulation images of the space-based satellite and the ground-based platform; An image segmentation module for segmenting the body of the plane target and the sailboard of the plane target in the infrared simulation image of the space-based satellite to obtain a first segmentation result, and segmenting 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 plane target is another satellite observed closely by the space-based satellite, and the point target is the other satellite observed remotely by the ground-based platform; A temperature inversion module for inverting the temperatures of the mid-plane target of the space-based satellite and the mid-point target of the ground-based platform based on the Planck equation according to the first segmentation result and the second segmentation result.

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