Space target structure modeling method and device based on luminosity characteristics of internal and external fields

Abstract

The invention discloses a space target structure modeling method and device based on internal and external field luminosity characteristics, and the method comprises the steps: carrying out the internal field test through a luminosity characteristic model, and obtaining a luminosity-angle data curve of the luminosity model; obtaining a blaze characteristic of a luminosity-angle data curve of the luminosity model, and establishing a mapping relation between a structure modeling scale and the blaze characteristic; performing an external field test on the space target to obtain a luminosity time sequence data curve of the space target, and extracting data features of the luminosity time sequence data curve; and comparing the data features with the blazed features, and determining the modeling scale of the space target structure. According to the invention, by analyzing the blazing characteristics, the size of the load or the composition structure of the external field space target causing the blazing characteristics can be determined, so that the size of the space target structure modeling is determined. The method has universality for space targets of different types and structures, and a basis is provided for further characteristic inversion and simulation analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of research on space target characteristics. Specifically, it relates to a method and device for modeling the structure of space targets based on photometric characteristics in the internal and external fields. Background Art

[0002] Ground-based optical observation systems are important means for observing space targets. For ground-based large-field-of-view optoelectronic observation systems, space targets often appear as point-source images during observation, and their observable characteristics mainly include photometry and position. The photometry of space targets itself couples characteristics such as structure, material, orbit, attitude, and motion. Therefore, photometric curves are usually used to extract the characteristics of space targets.

[0003] In terms of extracting the structural characteristics of space targets, the inversion of typical components of the target can be achieved based on the extreme value characteristics of the photometric curve. The above method can extract some structural characteristics of space targets, but only makes large-category distinctions, such as typical categories, A2100 categories, communication satellite categories, BSS702C categories, special categories, etc., or simply believes that geosynchronous orbit three-axis stabilized satellites can be simplified to a simple structure of a solar panel plus a main body.

[0004] However, communication satellites, navigation satellites, remote sensing satellites, experimental satellites, reconnaissance satellites, etc. will adopt satellite platforms of different sizes and types due to different applications, and at the same time carry payloads with different functions. Therefore, it has limited applicability to structural targets of different sizes or other types of structures, and it is impossible to determine the modeling scale of specific structural components. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and device for modeling the structure of space targets based on photometric characteristics in the internal and external fields, which can solve at least one of the above-mentioned technical problems. The specific solutions are as follows:

[0006] According to a specific embodiment of the present invention, a first aspect of the present invention provides a method for modeling the structure of space targets based on photometric characteristics in the internal and external fields, including: performing an internal field test using a photometric characteristic model to obtain a photometric-angle data curve of the photometric model;

[0007] Obtaining the flare characteristics of the photometric-angle data curve of the photometric model, and establishing a mapping relationship between the structure modeling scale and the flare characteristics; the flare characteristics include: full width at half maximum, skewness, and peak-to-valley value;

[0008] Performing an external field test on the space target to obtain a photometric time-series data curve of the space target, and extracting data characteristics of the photometric time-series data curve, the data characteristics including: external full width at half maximum, external skewness, and external peak-to-valley value;

[0009] Compare the data characteristics with the specular characteristics to determine the modeling scale of the spatial target structure.

[0010] Preferably, the in-field test is performed using the photometric feature model to obtain the photometric-angle data curve of the photometric model, including:

[0011] Establish the photometric feature model, which includes: a small surface structure scale region, a partially flat surface scale region, an independent large flat surface scale region, and a combined large flat surface scale region;

[0012] Fix the positions of the light source and the detector, and rotate the photometric feature model uniformly around the vertical axis for one week to obtain the photometric-angle data curve of the photometric feature model at different illumination angles.

[0013] Preferably, obtaining the photometric-angle data curve of the photometric feature model at different illumination angles includes:

[0014] Obtain the electron number image of the photometric feature model through an electron multiplying charge coupled device;

[0015] Sum up all the photoelectron numerical values in the small surface structure scale region, the partially flat surface scale region, the independent large flat surface scale region, and the combined large flat surface scale region in the electron number image respectively to obtain the total photoelectron number-angle data curve;

[0016] Map the total photoelectron number-angle curve into the magnitude coordinate system, and use software to extract the photometric-angle data curve of the small surface structure scale region, the photometric-angle data curve of the partially flat surface scale region, the photometric-angle data curve of the independent large flat surface scale region, and the photometric-angle data curve of the combined large flat surface scale region.

[0017] Preferably, the out-field test is performed on the spatial target to obtain the photometric time-series data curve of the spatial target, and the data characteristics of the photometric time-series data curve are extracted, including:

[0018] Collect at least one circle of the photometric time-series data of the spatial target to obtain the photometric time-series data curve in the photometric-time;

[0019] Use the extreme value function to obtain the photometric peak value M peak and the peak position L peak , and the adjacent valley value M valley and the valley position L valley ;

[0020] According to the photometric peak values M peak and M valley calculate the intermediate value Mhalf and record the left half-height position L of the intermediate value half_left and the right half-height position L half_right , to obtain the full width at half maximum (FWHM) of the external field, and the expression is:

[0021] FWHM = |L half_right - L half_left |;

[0022] Convert the full width at half maximum of the external field of the photometric time series data curve into the full width at half maximum FWHM of the external field under photometric-angle.

[0023] Preferably, it further includes: calculating the peak-valley value of the external field according to the photometric peak values M peak and M valley , and the expression of the peak-valley value of the external field is:

[0024] PV = M peak - M valley .

[0025] Preferably, for the external field test of the space target to obtain the photometric time series data curve of the space target and extract the data characteristics of the photometric time series data curve, it further includes:

[0026] Collect the photometric time series data of at least one circle of the space target to obtain the photometric time series data curve under photometric-time;

[0027] Obtain the skewness value of the external field according to the photometric time series data curve, and the formula is:

[0028]

[0029] where M i represents the photometric value, and n is the number of samples;

[0030] μ is the mean value of M i , and μ is the standard deviation of M i .

[0031] Preferably, the mapping relationship between the structural modeling scale and the glint feature is:

[0032] When the full width at half maximum of the glint feature < 2°, the range of the skewness value is [-0.5, 0.5], and the peak-valley value < 0.5 magnitude, the structural member scale is the surface small structure scale, and the area of the surface small structure scale is a certain percentage of the surface area of the large component, and the large component includes: the satellite body or the solar panel;

[0033] When the full width at half maximum of the flare feature < 10°, the absolute value of the skewness value is greater than 0.5, and the peak-to-valley value < 1 magnitude, the scale of the structural member is the surface partial flatness scale, and the area of the surface partial flatness scale is a fraction of the surface area of the large component;

[0034] When the full width at half maximum of the flare feature > 20°, the range of the skewness value is [-0.5, 0.5], and the peak-to-valley value > 1 magnitude, the scale of the structural member is the independent large-area flatness scale, and the area of the independent large-area flatness region scale is the surface area of the large component;

[0035] When the full width at half maximum of the flare feature > 30°, the range of the skewness value is [-0.5, 0.5], and the peak-to-valley value > 2 magnitudes, the scale of the structural member is the combined large-area flatness scale, and the area of the combined large-area flatness scale is greater than the surface area of the large component.

[0036] Preferably, after comparing the data feature and the flare feature to determine the modeling scale of the spatial target structure, it further includes:

[0037] Determine the type of load or the composition structure carried by the spatial target according to the mapping relationship between the structural modeling scale and the structural member.

[0038] Preferably, the mapping relationship between the structural modeling scale and the structural member includes:

[0039] When the scale of the structural member is the surface small structure scale, the type of load or the composition structure carried by the spatial target includes: lens barrel, antenna, micro thruster, star sensor, surface wrinkles and surface coating;

[0040] When the scale of the structural member is the surface partial flatness scale, the type of load or the composition structure carried by the spatial target includes: surface bosses, local flat surfaces, overall surface unevenness;

[0041] When the scale of the structural member is the independent large-area flatness scale, the type of load or the composition structure carried by the spatial target includes: satellite body or solar panel;

[0042] When the scale of the structural member is the combined large-area flatness scale, the type of load or the composition structure carried by the spatial target includes: the combination of the satellite body and the solar panel.

[0043] According to the specific implementation manners disclosed in the present invention, the second aspect of the present invention provides a spatial target structure modeling device based on the internal and external field photometric features, including:

[0044] An internal field data acquisition module, configured to perform internal field tests using the photometric feature model to obtain the photometric-angle data curve of the photometric model;

[0045] The flare feature extraction module is used to obtain the flare features of the photometric-angle data curve of the photometric model and establish the mapping relationship between the scale of the structural member and the flare features; the flare features include: full width at half maximum, skewness, and peak-to-valley value;

[0046] The external field data processing module is used to perform external field tests on the space target to obtain the photometric time series data curve of the space target, and extract the data features of the photometric time series data curve, where the data features include: external full width at half maximum, external skewness, and external peak-to-valley value;

[0047] The data comparison module is used to compare the data features and the flare features to determine the modeling scale of the space target structure.

[0048] Compared with the prior art, the above scheme disclosed by the present invention has at least the following beneficial effects:

[0049] By performing in-field tests on the photometric feature model, the present invention establishes the mapping relationship between the flare features and the scale of the structural member. That is, by analyzing the flare features, the scale of the payload or structural member carried by the external field space target that causes the flare features can be determined, so as to determine the scale of the space target structure modeling. This method is universal for different types and structures of space targets and provides a basis for further feature inversion and simulation analysis. Description of the Drawings

[0050] The drawings here are incorporated into the specification and form a part of this specification, showing the embodiments that conform to the disclosure of the present invention, and are used together with the specification to explain the principles of the disclosure of the present invention. Obviously, the drawings in the following description are only some embodiments of the disclosure of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0051] Figure 1 is a flowchart of a method for modeling the structure of a space target based on in-field and out-field photometric features of the present invention;

[0052] Figure 2 is a schematic structural diagram of the photometric feature model of the present invention;

[0053] Figure 3 is an in-field total photoelectron number-angle curve graph of the present invention;

[0054] Figure 4 is an in-field photometric-angle curve graph of the present invention;

[0055] Figure 5 is a photometric-angle curve graph of the in-field solar panel extracted;

[0056] Figure 6 It is a graph of the time series of the external field photometric intensity;

[0057] Figure 7 It is a graph of the photometric intensity - time series of a certain geosynchronous orbit satellite;

[0058] Figure 8 It is a schematic structural diagram of a spatial target structure modeling device based on the internal and external field photometric characteristics of the present invention.

[0059] Reference numerals:

[0060] 1 Photometric characteristic model, 2 Photometer, 3 Light source. Specific implementation manners

[0061] In order to make the purpose, technical solutions and advantages of the disclosure of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments disclosed by the present invention, rather than all of the embodiments. Based on the embodiments disclosed in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the disclosure of the present invention.

[0062] The terms used in the embodiments of the disclosure of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the disclosure of the present invention. The singular forms "a", "the" and "said" used in the embodiments of the disclosure of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0063] It should be understood that the term " / and / " used herein is only a description of the associated relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " herein generally represents an "or" relationship between the front and rear associated objects.

[0064] It should be understood that although terms such as first, second, third, etc. may be used in the embodiments of the disclosure of the present invention, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the disclosure of the present invention, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0065] Depending on the context, as used herein, the terms "if" and "when" may be interpreted as "when", "while", "in response to determining", or "in response to detecting". Similarly, depending on the context, the phrases "if determined" or "if detecting (stated condition or event)" may be interpreted as "when determined", "in response to determining", "when detecting (stated condition or event)", or "in response to detecting (stated condition or event)".

[0066] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the commodity or device comprising said element.

[0067] The following combines the attached Figure 1 - Detailed description of the alternative embodiments disclosed in the present invention.

[0068] Embodiment 1

[0069] Figure 1 is a flowchart of a method for modeling the spatial target structure based on the photometric characteristics of the internal and external fields of the present invention. As Figure 1 shown, it includes the following steps:

[0070] Step S1: Use the photometric characteristic model for internal field testing to obtain the photometric-angle data curve of the photometric model, including the following steps:

[0071] Step S101: Establish the photometric characteristic model.

[0072] Specifically, the photometric characteristic model can be a scaled-down model, which is used to simulate the morphological scale when a space satellite carries various payloads. Due to different payloads, the satellite body or the composition structure of the satellite itself, such as the different scales of solar panels, under the illumination of the light source, it is reflected as regions with different luminosities. In this embodiment, the luminosity is measured in apparent magnitude. Therefore, by measuring the light characteristic model in the internal field multiple times and obtaining the typical characteristic values until the model converges, it can be used as a benchmark for matching with the external field test data.

[0073] In a preferred embodiment of the present invention, the constructed photometric characteristic model includes: a surface small structure scale region, a surface partial flat scale region, an independent large area flat scale region, and a combined large area flat scale region.

[0074] Among them, the area of the small surface structure scale region is a certain percentage of the surface area of the large component, and the large component includes: the satellite body or the solar panel;

[0075] The area of the partially flat surface scale region is a fraction of the surface area of the large component; the area of the independent large flat surface scale region is equivalent to the surface area of the large component;

[0076] The area of the combined large flat surface scale region is larger than the surface area of the large component, that is, larger than the surface area of the satellite body or the solar panel.

[0077] Step S102: Fix the positions of the light source and the detector, rotate the photometric feature model uniformly around the vertical axis for one week, and obtain the photometric-angle data curve of the photometric feature model at different irradiation angles.

[0078] As Figure 2 shown, the light source 3 is used to simulate the sun, the detector is the photometer 2, keep the positions of the light source 3 and the photometer 2 unchanged, rotate the photometric feature model 1 uniformly around the vertical axis for one week, and record the photometric data Q i ={θ i ,N i};

[0079] Among them, θ i is the i-th angle; N i is the photometric data obtained at the θ i angle.

[0080] Specifically, use a high-resolution electron multiplying charge-coupled device (EMCCD) to perform ultra-low electron noise imaging on the photometric feature model to obtain the electron number image of the photometric feature model.

[0081] Add up the photoelectron values in the surface small structure scale region, the surface partially flat scale region, the independent large flat surface scale region, and the combined large flat surface scale region in the electron number image of the photometric feature model to obtain the total photoelectron number-angle data curve as Figure 3 shown.

[0082] Since the actual application examines its characteristics in the magnitude coordinate system, it needs to be converted to the magnitude coordinate. Assume that when the total photoelectron number = 1, it corresponds to the reference star equivalent value of 30 (which can be arbitrarily taken). According to the Pogson formula for magnitude calculation, convert the photoelectron number into the relative magnitude value to examine its scintillation characteristics, rather than focusing on its absolute photometric value.

[0083] The relative magnitude N i is calculated as follows:

[0084] N i = 30 - 2.5×log 10 (E)

[0085] Among them, E represents the total number of photoelectrons.

[0086] Therefore, it is further possible to obtain Figure 4 the total luminosity - angle curve as shown.

[0087] Finally, the Andor Solis software for analyzing in - field test data can be used to extract the total luminosity - angle curve, and obtain the luminosity - angle data curves of the small - scale surface structure area, the partially flat - scale surface area, the independent large - area flat - scale area, or the combined large - area flat - scale area.

[0088] In this embodiment, since the luminosity obtained in the in - field experiment is the relative magnitude, which is different from the apparent magnitude calibrated by stars in the out - field, the processing of in - field data is mainly reflected in the extraction of the flare characteristics, rather than the quantitative characteristics of the absolute luminosity value.

[0089] Step S2: Obtain the flare characteristics of the luminosity - angle data curve of the luminosity model, and establish the mapping relationship between the structural modeling scale and the flare characteristics. Among them, the flare characteristics include: full width at half maximum, skewness value, and peak - to - valley value.

[0090] In the present invention, for regions with different structural modeling scales, when measuring them, multiple different characteristic peaks will be reflected in the luminosity - angle curve. By analyzing the characteristic peaks, the structural modeling scale of the region can be determined. Therefore, the information characteristics contained within the characteristic peaks are defined as flare characteristics, and different degrees of flare characteristics correspond to different structural modeling scales.

[0091] Step S201: Obtain the full width at half maximum of the luminosity - angle data curve in the in - field test data.

[0092] Full width at half maximum: Mainly consider the shape of the luminosity - angle data curve, without paying attention to the absolute value of the luminosity. The smaller the luminosity value, the higher the brightness of the space target.

[0093] Select the luminosity peak M peak (minimum value) and the intermediate value position of the adjacent luminosity valley value M valley (maximum value) as the half - height position. When the left and right adjacent valley values are not equal, select the smaller value for calculating the intermediate value M half . The distance between the left half - height position and the right half - height position is defined as the full width at half maximum.

[0094] Specifically, find the luminosity peak M peak and the peak position L peak in the luminosity - angle data curve, as well as the adjacent valley value M valley and the valley position L valley ;

[0095] According to the photometric peak value M peak and M valley calculate the intermediate value M half , and record the left half-height position L half_left and the right half-height position L half_right of the intermediate value, to obtain the full width at half maximum (FWHM) of the external field, and the expression is:

[0096] FWHM = |L half_right - L half_left |;

[0097] If there are multiple peaks in the photometric-angle data curve, extract multiple full widths at half maximum, which is expressed as:

[0098] FWHM = {FWHM 1 , FWHM 2 ,..., FWHM n}.

[0099] Step S202, obtain the skewness value of the photometric-angle data curve.

[0100] Skewness: It can be used to measure the asymmetry of the probability distribution of a random variable, and the formula is:

[0101]

[0102] where M i represents the photometric value, and n is the number of samples;

[0103] μ is the mean of M i , and μ is the standard deviation of M i .

[0104] If there are multiple peaks in the photometric-angle data curve, extract multiple skewness values, which is expressed as:

[0105] S = {S 1 , S 2 ,..., S n}.

[0106] Step S203, obtain the peak-to-valley value of the photometric-angle data curve.

[0107] Peak-to-valley (PV) value: The visual magnitude difference corresponding to the peak-to-valley value; use the extreme value function to find the photometric peak value M peak and M valley to calculate the external field peak-to-valley value, and the expression of the external field peak-to-valley value is:

[0108] PV = M peak - M valley .

[0109] If there are multiple peaks in the photometric - angle data curve, extract multiple peak - valley values, expressed as:

[0110] PV = {PV 1 , PV 2 ,..., PV n}.

[0111] The extracted flare characteristics can be expressed as: Q = {FWHW, S, PV}.

[0112] According to the in - field test results, in the case of a known photometric characteristic model structure, the flare characteristic values corresponding to different structural modeling scales can be obtained, that is, the mapping relationship between the structural modeling scale and the said flare characteristics.

[0113] Since the types of loads carried in each area of the known photometric characteristic model or the composition structure in each area are known, the mapping relationship between the structural modeling scale and the structural components can be established, that is, through Figure 4 the in - field photometric - angle curve to further extract Figure 5 the photometric - angle curve of the solar panel shown

[0114] The mapping relationship between the structural modeling scale and the flare characteristics and the mapping relationship between the structural modeling scale and the structural components are shown in Table 1:

[0115] Table 1 Mapping relationship between flare characteristics, modeling scale, and load

[0116]

[0117] Among them, the locally flat surface, the overall surface unevenness, and the specific structure are not directly related, representing various possible structural surfaces.

[0118] In other embodiments of the present invention, rich test data can further converge the above - mentioned flare characteristic values.

[0119] The present invention examines the photometric morphology rather than the absolute value, avoiding the problem of over - large photometric values caused by the limited dynamic range of the in - field test detector, resulting in the photometric value in the in - field test being greater than the actual photometric value.

[0120] Step S3: Conduct an out - field test on the space target to obtain the photometric time - series data curve of the space target, and extract the data characteristics of the photometric time - series data curve, including the following steps:

[0121] Step S301: Collect at least one - turn photometric time - series data of the space target to obtain the photometric time - series data curve P i = {t i , M i}, the photometric value is measured in magnitudes, and obtain as Figure 6The photometric time curve is shown.

[0122] Among them, t i is the i-th collection moment, M i t i The target apparent magnitude at the moment;

[0123] The horizontal axis is time and the vertical axis is apparent magnitude.

[0124] Step S302: Use the 3σ rule to remove abnormal values ​​from the photometric time series data.

[0125] Step S303: extracting data features of the photometric time series data curve.

[0126] The data features of the photometric time series data curve include: the full width at half maximum of the external field, the skewness of the external field, and the peak-to-valley value of the external field. Specifically, the acquisition method of the full width at half maximum of the external field, the skewness of the external field, and the peak-to-valley value of the external field is the same as the acquisition method of the glare characteristics. In order to be consistent with the photometric-angle data of the indoor test, the outdoor measured photometric-time data can be converted into photometric-angle data. For geosynchronous orbit targets, the angle change in a short period of time is mainly caused by the rotation of the earth. The FWHM represented by time is multiplied by the angular velocity of rotation to obtain the FWHM represented by angle.

[0127] Step S4: Compare the data features with the blaze features Q = {FWHM, S, PV} to determine the modeling scale of the space target structure and the type of payload carried by the space target.

[0128] Figure 7 Based on the luminosity-time curve obtained from the data of a geosynchronous orbit satellite collected in the field test, the glare characteristics are extracted and the following results are obtained:

[0129]

[0130]

[0131] According to the above results and the mapping relationship in Table 1, the following simulation results can be obtained:

[0132] The modeling scale of the Shining 1 position is the combined large-area flat scale, and its corresponding structural components are the combination of the satellite body and the solar panels;

[0133] The modeling scale of the flash 2 position is the flat surface scale, and the corresponding structural component may be a boss;

[0134] The modeling scale of the blaze 3 position is the scale of small surface structures, which may correspond to the telescope tube or star sensor.

[0135] Therefore, the modeling scale for this geosynchronous orbit satellite should be limited to the scale of small surface structures.

[0136] Due to the limitation of dynamic range of detectors used in indoor field tests, especially when multiple components contribute to luminosity together, some areas of the detector may be saturated, resulting in the situation that the amplitude of luminosity change in indoor field tests is smaller than the actual measurement. At this time, the selection of glare features is mainly based on half-maximum full width and skewness, supplemented by peak and valley values.

[0137] In summary, according to the space target structure modeling method based on internal and external field photometric characteristics of the present invention, by conducting internal field testing on the photometric characteristic model, a mapping relationship between the scale of structural components and the glare characteristics and structural components is established, thereby determining the scale of space target structure modeling.

[0138] Example 2

[0139] The present invention also provides an apparatus embodiment that is consistent with the above embodiment, which is used to implement the method steps described in the above embodiment. The explanation based on the same name meaning is the same as the above embodiment, and has the same technical effect as the above embodiment, which will not be repeated here.

[0140] like Figure 2 As shown, the present invention discloses a spatial target structure modeling device based on internal and external field photometric characteristics, comprising:

[0141] An infield data acquisition module 302 is used to perform an infield test using a photometric characteristic model to obtain a photometric-angle data curve of the photometric model;

[0142] The glitter feature extraction module 304 is used to obtain the glitter feature of the luminosity-angle data curve of the luminosity model and establish a mapping relationship between the scale of the structural component and the glitter feature; the glitter feature includes: half-height full width, skewness and peak-to-valley value;

[0143] The field data processing module 306 is used to perform field testing on the space target, obtain the photometric time series data curve of the space target, and extract data features of the photometric time series data curve, wherein the data features include: field half-height full width, field skewness, and field peak-to-valley value;

[0144] The data comparison module 308 is used to compare the data features with the glitter features to determine the modeling scale of the spatial target structure.

[0145] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments disclosed in the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code, which 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 that 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 and / or flowchart, as well as the combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0146] The units described in the embodiments disclosed in the present invention can be implemented in software or in hardware. Among them, the name of the unit does not constitute a limitation on the unit itself in some cases.

Claims

1. A spatial target structure modeling method based on internal and external field photometric characteristics, characterized in that: include: Performing an in-field test using a photometric characteristic model to obtain a photometric-angle data curve of the photometric model; Obtaining the sparkle characteristics of the luminosity-angle data curve of the luminosity model, and establishing a mapping relationship between the structural modeling scale and the sparkle characteristics; the sparkle characteristics include: full width at half maximum, skewness, and peak-to-valley value; Performing an outdoor test on a space target to obtain a photometric time series data curve of the space target, and extracting data features of the photometric time series data curve, wherein the data features include: outdoor field half-height full width, outdoor field skewness, and outdoor field peak-to-valley value; The data features and the glint features are compared to determine the modeling scale of the spatial target structure.

2. The method according to claim 1, characterized in that The method of performing an infield test using a photometric characteristic model to obtain a photometric-angle data curve of the photometric model includes: Establishing the photometric characteristic model, the photometric characteristic model includes: a surface small structure scale region, a surface partially flat scale region, an independent large area flat scale region and a combined large area flat scale region; The positions of the light source and the detector are fixed, and the photometric characteristic model is rotated around the vertical axis at a uniform speed for one cycle to obtain the photometric-angle data curves of the photometric characteristic model at different illumination angles.

3. The method according to claim 2, characterized in that Obtaining the luminosity-angle data curve of the luminosity characteristic model at different illumination angles, including: Acquiring an electron number image of the photometric characteristic model through an electron multiplying charge coupled device; The photoelectron values ​​in the surface small structure scale area, the surface partially flat scale area, the independent large area flat scale area and the combined large area flat scale area in the electron number image are added together to obtain a total photoelectron number-angle data curve; The total photoelectron number-angle curve is mapped into the magnitude coordinate system, and the software is used to extract the luminosity-angle data curve of the surface small structure scale area, the luminosity-angle data curve of the partially flat scale area of ​​the surface, the luminosity-angle data curve of the independent large area flat scale area, and the luminosity-angle data curve of the combined large area flat scale area.

4. The method according to claim 1, characterized in that: The method of performing an outdoor test on the space target to obtain a photometric time series data curve of the space target and extracting data features of the photometric time series data curve includes: Collecting at least one lap of photometric time series data of the space target to obtain the photometric time series data curve under photometric-time; Obtain at least one luminosity peak value M in the luminosity time series data curve using an extreme value function peak and the peak position L peak , and the adjacent valley value M valley and valley position L valley ; According to the luminosity peak M peak and M valley Calculate the middle value M half , and record the left half height position L of the middle value half_left and right half height position L half_right , and get the full width at half maximum FWHM of the external field, the expression is: FWHM=|L half_right -L half_left |; The external field half-maximum full width of the photometric time series data curve is converted into the external field half-maximum full width FWHM under the photometric angle.

5. The method according to claim 4, characterized in that Also includes: According to the luminosity peak M peak and M valley Calculate the external field peak-to-valley value, the expression of which is: PV=M peak -M valley 。 6. The method according to claim 1, characterized in that The field test of the space target is performed to obtain a photometric time series data curve of the space target, and data features of the photometric time series data curve are extracted, and the method further includes: Collecting at least one lap of photometric time series data of the space target to obtain the photometric time series data curve under photometric-time; The external field skewness value is obtained according to the photometric time series data curve, and the formula is: Among them, M i Represents the luminosity value, n is the number of samples; μ is M i The mean value of M i The standard deviation of .

7. The method according to any one of claims 1 to 6, characterized in that: The mapping relationship between the structural modeling scale and the glitter feature is: When the full width at half maximum of the blazing feature is less than 2°, the range of the skewness value is [-0.5, O.5], and the peak-to-valley value is less than 0.5 magnitude, the scale of the structural component is the scale of the surface small structure, and the area of ​​the surface small structure scale is a few percent of the surface area of ​​the large component, and the large component includes: a satellite body or a solar panel; When the full width at half maximum of the blazing feature is less than 10°, the absolute value of the skewness value is greater than 0.5, and the peak-to-valley value is less than 1 magnitude, the scale of the structural component is the flat scale of the surface portion, and the area of ​​the flat scale of the surface portion is a fraction of the surface area of ​​the large component; When the full width at half maximum of the blazing feature is greater than 20°, the range of the skewness value is [-0.5, 0.5], and the peak-to-valley value is greater than 1 magnitude, the scale of the structural component is an independent large-area flat scale, and the area of ​​the independent large-area flat area scale is the surface area of ​​the large component; When the full width at half maximum of the blazing feature is >30°, the skewness value range is [-0.5, 0.5], and the peak-to-valley value is >2 magnitude, the scale of the structural component is a combined large-area flat scale, and the area of ​​the combined large-area flat scale is larger than the surface area of ​​the large component.

8. The method according to claim 7, characterized in that After comparing the data features with the glint features and determining the modeling scale of the space target structure, the method further includes: The type or component structure of the load carried by the space target is determined according to the mapping relationship between the structural modeling scale and the structural component.

9. The method according to claim 8, characterized in that The mapping relationship between the structural modeling scale and the structural components includes: When the scale of the structural component is a small surface structure scale, the types or component structures of the payload carried by the space target include: a lens barrel, an antenna, a micro-thruster, a star sensor, surface wrinkles and a surface coating; When the dimension of the structural member is a partially flat dimension of the surface, the types or component structures of the load carried by the space target include: surface bosses, partially flat surfaces, and uneven surfaces as a whole; When the scale of the structural component is an independent large-area flat scale, the type or component structure of the payload carried by the space target includes: a satellite body or a solar panel; When the scale of the structural component is a combined large-area flat scale, the type or component structure of the payload carried by the space target includes: a combination of a satellite body and a solar panel.

10. A spatial target structure modeling device based on internal and external field photometric characteristics, characterized in that: include: An infield data acquisition module, used to perform an infield test using a photometric characteristic model to obtain a photometric-angle data curve of the photometric model; A glitter feature extraction module is used to obtain the glitter features of the luminosity-angle data curve of the luminosity model and establish a mapping relationship between the scale of the structural component and the glitter features; the glitter features include: full width at half maximum, skewness and peak-to-valley value; An outfield data processing module is used to perform an outfield test on a space target, obtain a photometric time series data curve of the space target, and extract data features of the photometric time series data curve, wherein the data features include: outfield full width at half maximum, outfield skewness, and outfield peak-to-valley value; A data comparison module is used to compare the data features with the glitter features to determine the modeling scale of the spatial target structure.

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