A method and system for estimating the area-mass ratio of space objects based on historical TLE data

Abstract

The application discloses a space target surface-mass ratio estimation method and system based on historical TLE data, and the method comprises the following steps: obtaining historical TLE data of a space target, and screening TLE data with the longest semi-major axis descending over time within a time period; extrapolating ephemeris from the TLE data within the selected time period to perform precise orbit determination, and simultaneously solving an atmospheric resistance coefficient; inversely calculating a satellite surface-mass ratio according to the atmospheric resistance coefficient; and processing the satellite surface-mass ratio, and outputting the processed satellite surface-mass ratio. The application inversely deduces the surface-mass ratio without the cooperation of the target by screening the effective data section with the descending semi-major axis, combining the precise orbit determination and the solution of the atmospheric resistance coefficient, solves the problem that it is difficult to obtain the surface-mass ratio of a non-cooperative target, improves the feasibility of obtaining the surface-mass ratio, and expands the application range of space target monitoring.

Description

Technical Field

[0001] This invention relates to the field of space target surface mass ratio estimation technology, and in particular to a method and system for estimating space target surface mass ratio based on historical TLE data. Background Technology

[0002] In recent years, with the advancement of technologies such as rockets and satellites and the continuous development of commercial spaceflight, the number of space targets in orbit has been increasing. Not only are the number of active spacecraft growing daily, but the vast number of defunct satellites and debris—"space junk"—has also led to an exponential increase in the probability of space target collisions. This has made space target collision safety a high-risk issue requiring real-time monitoring. To protect the normal operation of valuable space targets, it is necessary to accurately estimate their collision probability with other space targets in their orbits and to promptly detect approach events, enabling control satellites to maneuver and avoid collisions in a timely manner.

[0003] Estimating the probability of collisions with space targets relies heavily on high-precision calculations of their orbits. Commonly used methods include the SGP4 prediction model based on TLE data, the High Precision Orbit Propagator (HPOP), and precise orbit determination based on observational data (such as GNSS position and velocity information, radar ranging and angle measurement information). The SGP4 method, based on periodically released TLE data, has good availability but lower accuracy, especially in scenarios with small-scale targets like collision warnings, where the distribution of its error ellipsoid may be too dispersed. Precise orbit determination requires cooperation with the target or sufficient observation capabilities, which is often difficult to guarantee in practical applications. HPOP, on the other hand, is based on a complex perturbation model, offering high accuracy and good independence, making it suitable for calculating the orbits of space targets.

[0004] Within the current altitude range of 460km-610km, where space targets are most densely distributed, the maximum perturbation force J2 experienced by the satellite is approximately 10 times that of Earth's gravity. 3 The magnitude is second only to atmospheric drag, which is about 10 times that of gravity. 6The magnitude of atmospheric drag is significant. Atmospheric drag can cause orbital errors on the order of kilometers within three days, making its accurate estimation crucial. Calculating atmospheric drag perturbations requires satellite surface-to-mass ratio (SMR). For example, the paper "A Spherical MicroSatellite Design and Detection Method for Upper Atmospheric Density Estimation" (DOI 10.1155 / 2019 / 1758956) calculates the SMR directly from the satellite's design shape, size, and mass. Another example is the paper "Atmospheric density determination using high-accuracy satellite GPS data" (DOI 10.1007 / s11431-016-9096-6), which uses GPS data for precise orbit determination and, combined with an atmospheric model, can invert the satellite's SMR.

[0005] However, the above methods are limited by observation capabilities and it is difficult to obtain reliable data for non-cooperative targets. TLE data, on the other hand, is publicly released after observing and determining the orbit of space targets. It contains the trend of satellite orbit changes and, as a square root information, filters out the instantaneous root influence caused by J2 perturbation. Therefore, the changes in TLE orbit are mainly affected by atmospheric drag. Information on atmospheric drag experienced by the satellite can be extracted from historical TLE data, and the satellite's surface-to-mass ratio can be retrieved using a defined atmospheric model. Summary of the Invention

[0006] To address the aforementioned problems, the present invention aims to provide a method and system for estimating the surface mass ratio (SMR) of space targets based on historical TLE data, solving the problem that the SMR of non-cooperative space targets is difficult to obtain through traditional observation methods. This method utilizes historical TLE data to analyze the time-varying trend of satellite orbits and extract orbital attenuation information caused by atmospheric drag.

[0007] This invention provides a method and system for estimating the surface-to-mass ratio of spatial targets based on historical TLE data.

[0008] First aspect: A method for estimating the spatial target surface quality ratio based on historical TLE data, including the following steps:

[0009] S1. Obtain historical TLE data of the space target and filter out the TLE data with the longest duration where the semi-major axis decreases over time.

[0010] S2. For TLE data within the selected time period, extrapolate to ephemeris for precise orbit determination, and simultaneously solve for atmospheric drag coefficient;

[0011] S3. Calculate the satellite surface mass ratio based on the atmospheric drag coefficient;

[0012] S4. Process the satellite surface mass ratio and output the processed satellite surface mass ratio.

[0013] In one embodiment of the present invention, the duration of the TLE data segment selected in S1 is not less than 1 week, and the number of TLE data groups decreasing over time is not less than 5 groups.

[0014] In one embodiment of the present invention: step S2 includes the following steps:

[0015] S21. For each set of TLE data within the selected time period, generate satellite ephemeris based on the SGP4 model extrapolation.

[0016] S22. Use the extrapolated satellite ephemeris as GNSS observation values ​​and call the precise orbit determination software to determine the satellite's orbit.

[0017] S23. Set the initial satellite surface-to-mass ratio, and calculate the atmospheric drag coefficient based on the atmospheric drag perturbation equation for a unit mass satellite.

[0018] In one embodiment of the present invention, when extrapolating to generate satellite ephemeris in S21, TLE data is sampled for TLE data groups within a selected time period at time intervals not less than 1% of the total time period length.

[0019] In one embodiment of the present invention: the atmospheric drag perturbation equation for a unit mass satellite in S23 is expressed as follows:

[0020]

[0021] in, The atmospheric drag experienced by a satellite per unit mass This is the atmospheric drag coefficient. The atmospheric density at the satellite's location. For satellite speed, For the satellite's windward area, For satellite quality, The ratio of flour to tomato.

[0022] In one embodiment of the present invention: when the atmospheric drag perturbation equation is used, the initial value of the satellite surface mass ratio is 0.021m. 2 / kg, The value is 2.1, and the calculated inverse constant is 100.

[0023] In one embodiment of the present invention: the satellite surface mass ratio is obtained by back-calculating the satellite surface mass ratio based on the atmospheric drag coefficient, and the formula is expressed as:

[0024]

[0025] in, 100 is the calculated atmospheric drag coefficient, and 100 is the inverse constant.

[0026] In one embodiment of the present invention: the processing of the satellite surface-to-mass ratio in S4 includes:

[0027] S41. Filter the calculated satellite surface-to-mass ratio results and remove results with negative values;

[0028] S42. Continue to filter the remaining surface-to-texture ratio results after processing, and remove results with obviously excessively large values.

[0029] S43. Take the average value of the remaining surface-to-mass ratio results to obtain the satellite's surface-to-mass ratio.

[0030] In one embodiment of the present invention: the major axis radius of the space target is no greater than 700 km.

[0031] The second aspect: a spatial target surface quality ratio estimation system based on historical TLE data, including:

[0032] The data acquisition module is used to acquire historical TLE data of space targets and filter out the TLE data with the longest duration of semi-major axis decreasing over time.

[0033] The coefficient calculation module is used to extrapolate TLE data within a selected time period into ephemeris for precise orbit determination, and simultaneously solve the atmospheric drag coefficient.

[0034] The surface-to-mass ratio inverse calculation module is used to inversely calculate the satellite's surface-to-mass ratio based on the atmospheric drag coefficient;

[0035] The output module processes the satellite surface mass ratio and outputs the processed satellite surface mass ratio.

[0036] Third aspect: An electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, performs the steps of the method provided in the first aspect.

[0037] Fourth aspect: A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect.

[0038] The beneficial effects of this invention are:

[0039] 1. This invention utilizes publicly available historical TLE data, filters effective data segments of semi-major axis descent, and combines precise orbit determination and atmospheric drag coefficient calculation to reverse-calculate the surface mass ratio without target cooperation. This solves the problem of difficulty in obtaining the surface mass ratio of non-cooperative targets, improves the feasibility of obtaining the surface mass ratio, and expands the application scope of space target monitoring.

[0040] 2. This invention uses the SGP4 model to extrapolate ephemeris and calculates the drag coefficient using precise orbit determination software. After data screening and averaging, atmospheric drag information is accurately extracted from historical TLE data. The inverted surface mass ratio has a small deviation from the actual satellite design parameters, making it particularly suitable for densely populated space target areas of no more than 700 km, providing reliable data support for orbit prediction and collision warning.

[0041] 3. By setting reasonable data screening criteria and fixing parameters such as initial surface-to-mass ratio and drag coefficient, this invention simplifies the calculation process and ensures the stability of the results. In addition, the method of this invention can process multi-target data in batches and is suitable for estimating the surface-to-mass ratio of large-scale space targets, which has strong engineering application value. Attached Figure Description

[0042] Figure 1 This is a flowchart illustrating the principle of the spatial target surface-to-mass ratio estimation method of the present invention;

[0043] Figure 2 This is a schematic flowchart of the spatial target surface-to-mass ratio estimation method of the present invention;

[0044] Figure 3 This is a schematic diagram of the surface-to-mass ratio calculation results of the method of the present invention;

[0045] Figure 4 This is a statistical diagram illustrating the surface-to-mass ratio calculation results of the method of the present invention;

[0046] Figure 5 This is a schematic diagram of the spatial target surface-to-mass ratio estimation system of the present invention;

[0047] Figure 6 This is a schematic diagram of the structure of the electronic device of the present invention. Detailed Implementation

[0048] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar symbols denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0049] Traditional methods can only obtain space target surface-to-mass ratio data by directly acquiring satellite design parameters or by conducting radar observations and orbit determination of space targets. They cannot obtain surface-to-mass ratio information of any non-cooperative target from publicly available TLE data, and cannot make full use of publicly available and historical TLE data.

[0050] To address the aforementioned problems, this invention discloses a method and system for estimating the spatial target surface-to-mass ratio based on historical TLE data, as illustrated in the schematic diagram below. Figure 1 As shown:

[0051] Example 1:

[0052] This embodiment provides a method for estimating the surface-to-mass ratio of spatial targets based on historical TLE data, such as... Figure 2 As shown, the steps include:

[0053] S1. Obtain historical TLE data of the space target and filter out the TLE data with the longest duration where the semi-major axis decreases over time.

[0054] Since atmospheric density decreases rapidly with increasing orbital altitude, the effective calculation of atmospheric density parameters in this embodiment is mainly applicable to space targets with an orbital semi-major axis altitude of less than 700 km. This is sufficient to cover the space region with the highest density of near-event events. However, for space targets with an orbital altitude of more than 700 km, the effect of the surface-to-mass ratio on orbital changes is not significant due to the smaller atmospheric drag. Therefore, the estimation accuracy of this method may be reduced.

[0055] In this embodiment, a satellite is used as an example of a space target:

[0056] First, obtain the satellite's historical TLE data. TLE data is released by the North American Aerospace Defense Command after observing and determining the orbits of space targets. You can filter TLE data from the satellite's historical orbit records (TLE data).

[0057] By selecting a segment of TLE data during a descent, taking one year as an example, the semi-major axis height of each TLE group is statistically analyzed. The TLE data with the longest duration of semi-major axis descent over time is identified. The main purpose of this selection is to ensure, as far as possible, that the target is not subject to active orbital maneuvers during the calculation period. The data selected in this way can more accurately reflect the impact of atmospheric drag on orbital decay, thereby improving the accuracy of the surface mass ratio estimation.

[0058] Find a period where the satellite's orbital altitude continuously decreases for a sufficiently long time, preferably no less than one week. The number of Time-Like (TLE) intervals during the descent should not be too few, preferably no less than five. This is because if the satellite does not actively change its orbit, the altitude decrease is mainly driven by atmospheric drag, and this record can truly reflect the impact of atmospheric drag. If the number of TLE intervals during the descent is too few (less than five) and the duration is too short (less than one week), it indicates that the satellite is still in frequent orbital maneuvers, and the calculated surface-to-mass ratio is unreliable.

[0059] Preferably, only satellites with an orbital altitude of less than 700 kilometers are selected, because atmospheric drag is significant enough to make orbital changes clearly visible.

[0060] Preferably, for each group of selected TLE data, quality screening is also required to remove abnormal or large error data points to ensure the reliability and stability of the data.

[0061] S2. For TLE data within the selected time period, extrapolate to ephemeris for precise orbit determination, and simultaneously solve for atmospheric drag coefficient.

[0062] Preferably, for multiple sets of TLE data within a selected time period, a set of TLE data is sampled at intervals of no less than 1% of the total length of the time period, which can reduce the amount of computation.

[0063] Then, satellite ephemeris is generated by extrapolation based on the sampled TLE data, and orbit determination is performed using precise orbit determination software while simultaneously solving for the atmospheric drag coefficient. Specifically:

[0064] For each set of TLE data within the selected time period, satellite ephemeris (e.g., satellite ephemeris for the next 3 days) is extrapolated from the TLE epoch based on the SGP4 model. Satellite ephemeris is the satellite's position and velocity information, with a time interval of 1 minute.

[0065] The satellite ephemeris generated by extrapolating TLE data is used as GNSS observation value, and precise orbit determination software is called to determine the satellite's orbit.

[0066] The initial orbit can be selected from the first set of observations of the ephemeris, that is, the position and velocity at the TLE epoch.

[0067] The initial satellite surface-to-mass ratio was set to 0.021 m² / kg as a parameter initialization setting during the precise orbit determination calculation. Its purpose is to provide a benchmark for calculating the atmospheric drag coefficient, thereby achieving accurate back-calculation of the surface-to-mass ratio. The initial satellite surface-to-mass ratio information was set to 0.021 m² / kg. 2 / kg provides a reasonable starting point for the solution process, ensuring that the subsequent calculation of the atmospheric drag coefficient can converge to the effective range.

[0068] During orbit determination, the precision orbit determination software needs to calculate atmospheric drag perturbation based on the initial surface-to-mass ratio and adjust the atmospheric drag coefficient to match the orbit calculation results with the extrapolated ephemeris of the TLE data.

[0069] Preferably, the calculation formula is based on the atmospheric drag perturbation experienced by a satellite per unit mass, and the formula is expressed as follows:

[0070]

[0071] in, Atmospheric drag per unit mass of a satellite is a key perturbation force affecting changes in its orbit; The atmospheric drag coefficient reflects the ability of the satellite surface to impede atmospheric particles. This refers to the atmospheric density at the satellite's location, which is related to its orbital altitude and the space environment. This is the satellite's velocity relative to the atmosphere, approximately equal to its orbital velocity.

[0072] For the satellite's windward area, For satellite quality, The surface-to-mass ratio, which is the ratio of a satellite's frontal area to its mass, directly determines the extent to which atmospheric drag affects the satellite's orbit.

[0073] S3. Calculate the satellite surface mass ratio based on the atmospheric drag coefficient.

[0074] Based on the atmospheric drag perturbation formula for a satellite per unit mass:

[0075]

[0076] The formula for calculating the surface-to-weight ratio is derived as follows:

[0077] in, This is the result calculated by the precise orbit determination software. During the orbit determination process, the precise orbit determination software uses the extrapolated ephemeris from TLE data as the observation value, presets the surface-to-mass ratio to 0.021 m² / kg, and combines it with the atmospheric drag perturbation formula. By matching the orbital changes, the atmospheric drag coefficient is derived, reflecting the actual drag coefficient that matches the current orbital data.

[0078] This is a fixed value set artificially. In subsequent HPOP orbit extrapolation, to unify calculation standards and simplify the model, the atmospheric drag coefficient is fixed at 2.1 as the benchmark parameter for the surface-to-mass ratio back-calculation. When performing HPOP orbit extrapolation, the atmospheric drag coefficient is used. The value is fixed at 2.1 to obtain the inverse calculation constant.

[0079] The atmospheric drag coefficient was calculated using precision orbit determination software. The inverse constant 100 in the surface-to-mass ratio calculation formula is derived from an initial satellite surface-to-mass ratio of 0.021 m. 2 / kg, atmospheric drag coefficient set when extrapolating HPOP orbital. =2.1, which is derived from this.

[0080] Each set of atmospheric drag coefficients calculated by the precision orbit determination software Substitute them into the formula respectively:

[0081]

[0082] The satellite surface mass ratio for the corresponding group was calculated.

[0083] For example: if the solution is obtained =2.1, then the surface-to-mass ratio is 2.1 / 100 = 0.021 m 2 / kg; if =4.2, then the surface-to-mass ratio is 4.2 / 100 = 0.042 m 2 / kg.

[0084] S4. Process the satellite surface mass ratio and output the processed satellite surface mass ratio.

[0085] For each set of TLE data within the selected time period, the calculated satellite surface mass ratio is first discarded. Negative values ​​are discarded because atmospheric drag only lowers the satellite's altitude, and negative values ​​may be due to orbital changes performed by the satellite outside the selected time period affecting the TLE parameters. Significantly large values ​​also need to be discarded, primarily because TLE results are distorted when the satellite's orbit is too low or it has re-entered the atmosphere. The remaining surface mass ratio results are then averaged to obtain the satellite's surface mass ratio.

[0086] Example 2:

[0087] This embodiment discloses an application example of a spatial target surface-to-mass ratio estimation method based on historical TLE data:

[0088] Taking NORAD satellite 58918 as an example, this is a satellite currently in operation that frequently performs electric propulsion orbital maneuvers, but also maintains a stable orbital descent every few to several tens of days. The satellite's semi-major axis altitude is approximately 510 km, falling within the dense target region of 460 km to 610 km. Atmospheric drag has a significant impact on its orbit, making it suitable for estimating the surface-to-mass ratio using this method. The specific steps are as follows:

[0089] First, historical TLE data was acquired and filtered. TLE data for this satellite from January 22 to February 5, 2025 were selected. After analyzing the semi-major axis altitude of each data set, it was found that the satellite's semi-major axis continuously decreased during the period from January 22 to February 5, and the duration was 14 days (meeting ≥1 week). A total of 12 sets of TLE data were extracted (meeting ≥5 sets), and the orbital altitude remained between 504km and 506km.

[0090] Further verification of the satellite status records during this period confirmed that there were no active orbital maneuvers and that the data showed no significant jumps or outliers. Therefore, the TLE data for this period was selected as the basis for the calculation.

[0091] Then, the ephemeris is extrapolated and the atmospheric drag coefficient is calculated.

[0092] Five representative TLE data sets were selected from 12 sets of TLE data from January 22 to February 5. Based on the SGP4 model, each set of TLE data was extrapolated to generate satellite ephemeris (position and velocity information) for the next three days starting from the epoch, with a time interval of 1 minute.

[0093] Then, the surface mass ratio is calculated back based on the atmospheric drag coefficient.

[0094] Using the extrapolated ephemeris as GNSS observations, precise orbit determination software was called, with the initial orbit set to the position and velocity at the epoch, and the initial satellite surface mass ratio set to 0.021 m² / kg. Five sets of atmospheric drag coefficients were obtained. The values ​​are 1.05, 1.12, 1.08, 1.15, and 1.09, respectively.

[0095] Using the atmospheric drag perturbation formula:

[0096]

[0097] Using HPOP orbit extrapolation with a fixed atmospheric drag coefficient =2.1, obtain the inverse calculation constant 100, according to the formula:

[0098]

[0099] The above 5 groups Substituting the values ​​into the calculation, we obtain the corresponding surface-to-weight ratios: 0.0105 m² / kg, 0.0112 m² / kg, 0.0108 m² / kg, 0.0115 m² / kg, and 0.0109 m² / kg.

[0100] Five sets of surface-to-mass ratio results were screened. All results were positive (negative values ​​were discarded), and all values ​​were within a reasonable range (no obviously excessive values). The average of the remaining results was taken, and the final surface-to-mass ratio of the satellite was: (0.0105+0.0112+0.0108+0.0115+0.0109) / 5=0.0110m² / kg.

[0101] Then, process the surface-to-weight ratio results.

[0102] The surface-to-weight ratio calculated using this TLE data is as follows: Figure 3 As shown: (The vertical axis in the figure represents the semi-major axis height, surface-to-mass ratio, B* parameter of TLE, first derivative of TLE translational motion, Kp exponent, and Ap exponent from left to right).

[0103] The calculated surface-to-mass ratio is basically proportional to the B* parameter and the first derivative of the translational motion of TLE. The B* coefficient is related to the Kp and Ap indices of geomagnetic activity, but not significantly. This indicates that the estimation of satellite orbit change trends by TLE data may be less affected by the space environment and mainly affected by changes in the satellite's own state.

[0104] The estimated satellite surface-to-mass ratio is 0.0110 m² / kg (C). d (Under the condition of 2.1), this is consistent with the satellite's design parameters for a windward area of ​​2.71m. 2 The result calculated from a mass of 235 kg is close to (2.71 ÷ 235 = 0.0115 m). 2 The result ( / kg) indicates that the algorithm can basically reconstruct the satellite's surface-to-mass ratio information from the TLE data, verifying the effectiveness of the method and making it applicable to the satellite's orbit prediction and collision warning analysis.

[0105] like Figure 4 As shown: Based on the surface-to-mass ratio calculation results of more than 10,000 space targets according to the method of the present invention, the surface-to-mass ratio of most space targets is within 0.05m. 2 The number of satellites is below / kg, which is consistent with general understanding (including a large number of early-launched satellites and debris).

[0106] Example 3:

[0107] Applying the method of Example 1, this example discloses a spatial target surface-to-mass ratio estimation system based on historical TLE data, such as... Figure 5 As shown, the system includes a data acquisition module, a coefficient calculation module, a surface-to-weight ratio inverse calculation module, and an output module.

[0108] First, the data acquisition module is activated to obtain historical TLE data for the space target, and the semi-major axis height of each TLE group is calculated. From this, the TLE data with the longest duration of semi-major axis decrease over time is selected. During the selection process, if the number of TLE groups in the decreasing segment is less than 5 and the time is less than 1 week, the surface-to-mass ratio calculation result is deemed unreliable, and re-selection is required.

[0109] Next, the coefficient calculation module processes the TLE data sets within the selected time period, sampling a set of TLE data at intervals no less than 1% of the total time period length. For each sampled TLE data set, satellite ephemeris for the next 3 days starting from the TLE epoch is extrapolated based on the SGP4 model, with a time interval of 1 minute. Subsequently, the extrapolated satellite ephemeris is used as GNSS observation values, and precise orbit determination software is called to determine the satellite's orbit. The initial orbit is selected from the first set of observation values ​​of the ephemeris, i.e., the position and velocity at the TLE epoch. The satellite surface mass ratio is set to 0.021 m² / kg, and the atmospheric drag coefficient C is calculated simultaneously. d0 .

[0110] Then, the surface-to-mass ratio inverse calculation module calculates the satellite's surface-to-mass ratio based on the atmospheric drag coefficient calculated by the coefficient calculation module, according to the formula:

[0111]

[0112] Among them, C d0 This is the atmospheric drag coefficient obtained from the solution.

[0113] Finally, the output module processes the calculated satellite surface mass ratio (SMR) results. It first removes negative and excessively large values, then averages the remaining results, and finally outputs the processed SMR. The SMR results can be output in numerical and graphical formats, supporting the display of results for single targets or batches of targets.

[0114] The present invention also provides an electronic device, Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 6 As shown, the electronic device may include a processor, a communications interface, memory, and a communication bus, wherein the processor, communications interface, and memory communicate with each other via the communication bus. The processor can invoke logical instructions from the memory, for example, to execute the following method:

[0115] S1. Obtain historical TLE data of the space target and filter out the TLE data with the longest duration where the semi-major axis decreases over time.

[0116] S2. For TLE data within the selected time period, extrapolate to ephemeris for precise orbit determination, and simultaneously solve for atmospheric drag coefficient;

[0117] S3. Calculate the satellite surface mass ratio based on the atmospheric drag coefficient;

[0118] S4. Process the satellite surface mass ratio and output the processed satellite surface mass ratio.

[0119] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0120] This invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the methods provided in the above embodiments, including, for example:

[0121] S1. Obtain historical TLE data of the space target and filter out the TLE data with the longest duration where the semi-major axis decreases over time.

[0122] S2. For TLE data within the selected time period, extrapolate to ephemeris for precise orbit determination, and simultaneously solve for atmospheric drag coefficient;

[0123] S3. Calculate the satellite surface mass ratio based on the atmospheric drag coefficient;

[0124] S4. Process the satellite surface mass ratio and output the processed satellite surface mass ratio.

[0125] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0126] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for estimating the spatial target surface quality ratio based on historical TLE data, characterized in that, include: S1. Obtain historical TLE data of the space target and filter out the TLE data with the longest duration where the semi-major axis decreases over time. S2. For TLE data within the selected time period, extrapolate to ephemeris for precise orbit determination, and simultaneously solve for atmospheric drag coefficient; S3. Calculate the satellite surface mass ratio based on the atmospheric drag coefficient; S4. Process the satellite surface mass ratio and output the processed satellite surface mass ratio; S2 includes the following steps: S21. For each set of TLE data within the selected time period, generate satellite ephemeris based on the SGP4 model extrapolation. S22. Use the extrapolated satellite ephemeris as GNSS observation values ​​and call the precise orbit determination software to determine the satellite's orbit. S23. Set the initial satellite surface-to-mass ratio and calculate the atmospheric drag coefficient based on the atmospheric drag perturbation equation for a unit mass satellite. The atmospheric drag perturbation equation for a satellite per unit mass in S23 is expressed as follows: ； in, The atmospheric drag experienced by a satellite per unit mass This is the atmospheric drag coefficient. The atmospheric density at the satellite's location. For satellite speed, For the satellite's windward area, For satellite quality, The ratio of flour to texture; The satellite surface mass ratio is calculated by inversely using the atmospheric drag coefficient. The formula for obtaining the satellite surface mass ratio is as follows: ； in, 100 is the calculated atmospheric drag coefficient, and 100 is the inverse constant.

2. The method according to claim 1, characterized in that, The duration of the TLE data segment selected in S1 is no less than 1 week, and the number of TLE data groups that decrease over time is no less than 5 groups.

3. The method according to claim 1, characterized in that, In S21, satellite ephemeris generation is performed by extrapolating the data. For TLE data groups within a selected time period, TLE data is sampled at time intervals not less than 1% of the total time period length.

4. The method according to claim 1, characterized in that: When the atmospheric drag perturbation equation is used, the initial satellite surface-to-mass ratio is 0.021m. 2 / kg, The value is 2.1, and the calculated inverse constant is 100.

5. The method according to claim 1, characterized in that: The processing of satellite surface-to-mass ratio in S4 includes: S41. Filter the calculated satellite surface-to-mass ratio results and remove results with negative values; S42. Continue to filter the remaining surface-to-texture ratio results after processing, and remove results with obviously excessively large values. S43. Take the average value of the remaining surface-to-mass ratio results to obtain the satellite's surface-to-mass ratio.

6. The method according to claim 1, characterized in that: The major axis radius of the space target is no greater than 700 km.

7. A spatial target surface-to-mass ratio estimation system based on historical TLE data, applied to the method described in any one of claims 1 to 6, characterized in that, include: The data acquisition module is used to acquire historical TLE data of space targets and filter out the TLE data with the longest duration of semi-major axis decreasing over time. The coefficient calculation module is used to extrapolate TLE data within a selected time period into ephemeris for precise orbit determination, and simultaneously solve the atmospheric drag coefficient. The surface-to-mass ratio inverse calculation module is used to inversely calculate the satellite's surface-to-mass ratio based on the atmospheric drag coefficient; The output module processes the satellite surface mass ratio and outputs the processed satellite surface mass ratio.

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