Space target collision early warning method and system based on mass orbit data

Abstract

The invention relates to the technical field of domestic commercial satellite measurement and control application, provides a space target collision early warning method and system based on mass orbit data, and is widely applied to the related field of space target monitoring. Through carrying out collision early warning calculation on the space target, a user can rapidly know whether the current concerned target has the risk of collision with other space targets or not, so that a response is rapidly made, and a related avoidance strategy is formulated in advance. From the perspective of calculating the accuracy of a space target collision early warning risk, an object identification optimization algorithm combining different object track heights with an interpolation algorithm is provided for space target identification by using ground-based radar observation data, so that a set of calculation method with both calculation efficiency and accuracy under massive calculation data is found. And calculating collision risk data, supporting in-orbit operation safety of the spacecraft, and finally calculating an observed space target.

Description

Technical Field

[0001] This invention relates to the technical field of domestic commercial satellite telemetry, tracking, and command applications, and particularly to a space target collision early warning method and system based on massive orbital data, which can be widely used in the field of space target surveillance. By performing collision early warning calculations on space targets, users can quickly understand whether the target of their interest is at risk of colliding with other space targets, and thus react quickly and formulate relevant avoidance strategies in advance. Background Technology

[0002] The number of global space launches has shown a significant year-on-year increase, with the growth rate continuing to accelerate. Behind this trend are the continuous investment of space agencies in various countries in deep space exploration and space science research, as well as the vigorous development of the commercial space sector—from the large-scale deployment of low-Earth orbit communication satellite constellations to the intensive launches of small scientific research satellites and CubeSats, the participants in space exploration are becoming increasingly diverse, and the number of spacecraft launches is repeatedly setting new records.

[0003] As more and more spacecraft are sent into space, the amount of debris in the space environment is also increasing dramatically. This debris includes large pieces such as rocket final stages and defunct satellites, as well as tiny particles such as metal fragments and coating peelings from spacecraft disintegration. Statistics show that there are currently more than 23,000 trackable pieces of debris larger than 10 centimeters in diameter in Earth orbit, while millions more are between 1 millimeter and 10 centimeters in diameter. These debris travel at speeds of several kilometers per second, posing a potential threat to spacecraft in orbit.

[0004] Against this backdrop, limited orbital resources are facing increasingly severe congestion challenges: the density of spacecraft in the golden orbital ranges such as Low Earth Orbit (LEO) and Geosynchronous Orbit (GEO) continues to rise, and spacecraft and debris at different orbital altitudes and inclinations are interspersed, making the space traffic environment increasingly complex. This complexity directly leads to a significant increase in the probability of spacecraft colliding with other space targets (including other spacecraft or space debris)—even centimeter-sized debris can cause structural damage and functional failure of spacecraft due to high-speed impacts, or even trigger catastrophic "chain reaction" effects, further exacerbating the deterioration of the space environment.

[0005] To effectively address this critical issue concerning the sustainability of space activities, there is an urgent need to develop a method for calculating collision early warning risks for spacecraft in orbit that can adapt to large computational loads. This method must be capable of processing massive amounts of orbital data, quickly and accurately identifying potential collision risks among tens of thousands of space targets, and providing timely early warning information to spacecraft operators. This allows them to formulate evasive maneuvers and orbital adjustments in advance, fundamentally ensuring the operational safety of spacecraft in orbit and maintaining the long-term stability of the space environment. Summary of the Invention

[0006] To address the aforementioned problems, the present invention aims to provide a space target collision early warning method and system based on massive orbital data. From the perspective of calculating the accuracy of space target collision early warning risks, and for space target identification using ground-based radar observation data, an optimized object identification algorithm is proposed that combines interpolation algorithms with different object orbital altitudes. This provides a calculation method that combines computational efficiency and accuracy under massive computational data, calculates collision risk data, supports the safe on-orbit operation of spacecraft, and ultimately calculates the observed space targets.

[0007] The above-mentioned objective of this invention is achieved through the following technical solutions: A space target collision early warning method based on massive orbital data includes the following steps: S1: Obtain the latest full set of orbit TLE data required by the algorithm. The input conditions are: the collision target orbit TLE data set, the collision full set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size. After inputting these conditions into the system, the system adaptively performs parallel calculations based on the number of primary targets and its own computing resources. S2: Use date expiration pre-screening to remove data, filtering out targets whose epoch date distance is too close to the analysis date. S3: Perform apogee / perigee pre-screening, filtering out targets whose apogee altitude is less than the perigee altitude of another target. S4: Use orbit intersection pre-screening to filter out targets whose approach distance between two target orbits is greater than the threshold distance D. S5: Use time pre-screening to filter out targets not geometrically filtered based on the time difference between the two targets crossing the orbital plane intersection. S6: After completing the traversal, calculate the object with the smallest average spatial distance and determine it as the identified object. Perform SGP4 orbit prediction on the main target and the eliminated secondary targets, and use the prediction results to calculate whether there is a collision risk. S7: After all parallel calculations are completed, summarize all calculation results and output a collision warning result set containing information such as the collision main and secondary target numbers, approach distance, collision probability, and approach time.

[0008] Furthermore, in step S1, the algorithm preparation work requires obtaining the latest complete set of orbit TLE data; the input conditions include the collision target orbit TLE data set, the collision complete set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size; the system adaptively allocates computing tasks and carries out parallel computing based on the number of target objects and its own computing resources, including the number of CPU cores and available memory.

[0009] Furthermore, in step S2, the data removal using date expiration pre-screening specifically involves: If the epoch date of the target orbit is too far from the analysis date, it is determined that the target orbit does not meet the collision warning calculation requirements due to the expiration date, and these targets are filtered out from the calculation dataset.

[0010] Further, in step S3, apogee / neargee pre-screening is performed, specifically as follows: When the apogee of one target's orbit is less than the perigee of another target, the two target orbits have no possibility of intersecting and cannot collide, thus these targets are filtered out.

[0011] Furthermore, in step S4, pre-screening is performed using the intersection of the tracks, specifically as follows: Even if the apogee and perigee of two target orbits overlap, the two targets can only approach each other at the intersection of the two orbits or the intersection of the two orbital planes. Assuming that the two target orbits have two approach distances a and b, if the distance between them is greater than the threshold distance D, it indicates that the two targets have no chance of approaching each other, and thus these targets are filtered out.

[0012] Furthermore, in step S5, time-based pre-screening is performed, specifically as follows: For targets not selected by the geometric screening in steps S2-S4, the time difference between the two targets passing through the intersection line of the orbital plane is used for screening. Although the orbits of the two targets may intersect at close range, they can only approach each other at close range when they pass through the approach point at the same time. In this way, the time difference between the two targets passing through the intersection line of the orbital plane can be used to screen targets.

[0013] Furthermore, in step S6, after completing the traversal, the object with the smallest average spatial distance is identified as the object being identified by calculating the average spatial distance. Then, the SGP4 orbit prediction model is used on the main target and the eliminated secondary targets. The orbit parameters are input to carry out orbit prediction. The prediction results are then used in conjunction with the collision probability calculation model to determine whether there is a collision risk.

[0014] A space target collision warning system based on massive orbital data for executing the space target collision warning method based on massive orbital data as described above, characterized in that it comprises: The parallel computing initialization module is used to obtain the latest full set of orbit TLE data required by the algorithm. It takes the collision target orbit TLE data set, the collision full set orbit TLE data set, date expiration pre-screening threshold, apogee / perigee pre-screening threshold, orbit intersection pre-screening threshold, time pre-screening threshold, and calculation step size as input conditions. After inputting these conditions into the system, the system adaptively performs parallel computing based on the number of target objects and its own computing resources. The date expiration filtering module is used to remove data using date expiration pre-screening, filtering out targets whose epoch date distance is too close to the analysis date. The apogee / perigee filtering module is used to perform apogee / perigee pre-screening, filtering out targets whose apogee altitude is less than the perigee altitude of another target. The orbit intersection filtering module is used to pre-screen using orbit intersection, filtering out targets whose approach distance between two target orbits is greater than a threshold distance D. The time synchronization filtering module is used to pre-screen using time, filtering out targets that have not been geometrically filtered based on the time difference between two targets passing through the orbital plane intersection. The collision risk calculation module is used to calculate the object with the smallest average spatial distance after traversal and identify it as the identified object. It performs SGP4 orbit prediction on the main target and the eliminated secondary targets, and uses the prediction results to calculate whether there is a collision risk. The result summary and output module is used to summarize all calculation results after all parallel calculations are completed and output a collision warning result set containing information such as the collision main and secondary target numbers, approach distance, collision probability, and approach time.

[0015] A computer device includes a memory and one or more processors, the memory storing computer code that, when executed by the one or more processors, causes the one or more processors to perform the method described above.

[0016] A computer-readable storage medium storing computer code that, when executed, performs the method described above.

[0017] Compared with the prior art, the present invention has at least one of the following beneficial effects: (1) Balancing computational efficiency and accuracy: Through multi-step pre-screening (date expiration, apogee / perigee, orbital intersection, time pre-screening), targets that are unlikely to collide are gradually eliminated from massive orbital data, greatly reducing the amount of data for subsequent fine calculations. At the same time, combined with adaptive parallel computing, the system resources are used to improve the calculation speed, achieving a balance between the efficiency and accuracy of collision warning calculations under massive data, and providing efficient data support for the on-orbit safety of spacecraft.

[0018] (2) Accurately identify collision risks: After multiple rounds of screening to narrow down the target range, the key targets are determined by calculating the average spatial distance. Combined with the mature SGP4 orbit prediction model and collision probability calculation model, the main and secondary target orbits are accurately predicted and the collision risk is determined. This can promptly and accurately detect potential collision threats to spacecraft.

[0019] (3) Output comprehensive and effective information: After summarizing the calculation results, output a set of early warnings containing information such as the collision master and slave target number, approach distance, collision probability, and approach time, providing spacecraft operators with clear and comprehensive details of collision risks, facilitating the formulation of response strategies such as orbit adjustment in advance, and ensuring the safe operation of spacecraft in orbit. Attached Figure Description

[0020] Figure 1 This is an overall flowchart of the space target collision early warning method based on massive orbital data of the present invention; Figure 2 This is a detailed flowchart of the space target collision early warning method based on massive orbital data of the present invention; Figure 3 This is a structural diagram of the space target collision early warning system based on massive orbital data according to the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0023] First Embodiment like Figure 1 and 2 As shown, this embodiment provides a space target collision early warning method based on massive orbital data, including the following steps: S1: Obtain the latest full set of orbit TLE data required by the algorithm. Take the collision target orbit TLE data set, the collision full set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size as input conditions. After inputting into the system, the system adaptively performs parallel calculations based on the number of target objects and its own computing resources.

[0024] In step S1, the algorithm preparation work requires obtaining the latest complete set of orbit TLE data; the input conditions include the collision target orbit TLE data set, the collision complete set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size; the system adaptively allocates computing tasks and carries out parallel computing based on the number of target objects and its own computing resources, including the number of CPU cores and available memory.

[0025] The Far / Near Geometry (FG) screening module S1 is the starting and foundational step in the entire space target collision warning process, focusing on data preparation and intelligent allocation of computing resources. Firstly, the "latest complete set of orbital FG data" is the cornerstone of accurate collision warning. This data covers key orbital information for various space targets and must be timely to provide a reliable basis for subsequent analysis. The input conditions constitute the "raw materials" and "rule constraints" of the near / far point filtering module for calculation. The collision master and the entire set of orbits are the analysis objects. Various pre-screening thresholds (expired date, near point, etc.) are like the specifications of the "filters" for the near / far point filtering module. The calculation step size determines the time accuracy of orbit prediction and analysis. Together, they define the scope and standards for collision warning calculation.

[0026] The key to improving efficiency lies in the system's adaptive parallel computing based on the number of primary targets and its own computing resources, such as the number of CPU cores and available memory in the near / far location screening modules. Faced with massive amounts of orbital data, serial computing would result in exponentially increasing processing time, failing to meet the timeliness requirements of collision warnings. By intelligently sensing the number of primary targets in the near / far location screening modules—allocating more computing threads or processes to a larger number of modules, and simultaneously matching the CPU cores and memory resources of the near / far location screening modules—the computing tasks function like multiple parallel "data processing vehicles," each responsible for analyzing a portion of the targets. This significantly shortens the overall computing time, laying a solid foundation for the efficient operation of subsequent steps such as pre-screening and orbit prediction, ensuring the entire collision warning process can be carried out promptly and systematically in complex orbital environments.

[0027] S2: Use date expiration pre-filtering to remove data, filtering out targets whose epoch dates are close to the analysis date but too long.

[0028] In step S2, the data removal using date expiration pre-screening is as follows: if the epoch date of the target orbit is too far from the analysis date, it is determined that the target orbit does not meet the collision warning calculation requirements due to date expiration, and these targets are filtered out from the calculation dataset.

[0029] Step S2, as the first round of data screening in collision warning calculation, plays a crucial role in eliminating targets that have lost their analytical value due to outdated orbital data by judging their validity over time, thus reducing the data burden for subsequent calculations. Here, "epoch date" refers to the baseline time point of the orbital data record, while "approaching analysis date" is the target time point where collision risk needs to be assessed. Because the orbits of space targets are affected by various factors such as atmospheric drag and celestial gravity, gradually deviating from their initial orbits, the longer the interval between the epoch date and the approaching analysis date, the lower the accuracy of the prediction of the orbital state on the approaching analysis date based on the orbital data from that epoch date, and it may even produce significant deviations. Continuing to use such outdated data for collision warning calculations not only increases the amount of invalid calculations but may also lead to misjudgments due to data distortion. Therefore, by setting a reasonable pre-screening threshold for date expiration, targets with epoch dates that are too far from the approaching analysis date are filtered out from the calculation dataset, ensuring that the remaining orbital data has sufficient timeliness, laying the foundation for accurate calculations in subsequent stages, and effectively improving the overall computational efficiency of the process. S3: Perform apogee / perigee pre-screening, filtering out targets whose apogee altitude is lower than the perigee altitude of another target.

[0030] In step S3, apogee / perigee pre-screening is performed. Specifically, when the apogee height of a target orbit is less than the perigee height of another target, the two target orbits have no possibility of intersecting and cannot collide, so these targets are screened out.

[0031] Step S3, following the pre-screening for expired dates, is a crucial step in further narrowing down the calculation scope from the perspective of orbital geometry. Its core logic is based on the fundamental geometric characteristics of space target orbits. Every space target's orbit has an apogee and a perigee. The apogee is the point on the orbit farthest from Earth, and the perigee is the point closest to Earth. When the apogee altitude of one target orbit is lower than the perigee altitude of another, it means that the two orbits are "separated" in space—the former's highest operating position is still lower than the latter's lowest operating position, and their orbital ranges have no overlapping area. From a collision probability perspective, in this case, the two targets have no physical basis to meet, and a collision is impossible. Therefore, by pre-screening through apogee / perigee, targets meeting the above conditions are removed from the calculation dataset. This significantly reduces the subsequent computational workload without overlooking potential collision risks, and improves screening efficiency through rapid judgment of geometric characteristics, providing a more concise and targeted data foundation for subsequent, more refined orbital intersection analysis and other steps. S4: Use the orbital intersection line for pre-screening to filter out targets whose two target orbits are close to each other by a distance greater than the threshold distance D.

[0032] In step S4, pre-screening is performed using the orbital intersection line. Specifically, even if the apogee and perigee of two target orbits overlap, the two targets can only approach each other at the intersection of the two orbits or at the intersection of the two orbital planes. Assuming that the two target orbits have two approach distances a and b, if the distance between them is greater than the threshold distance D, it indicates that the two targets have no chance of approaching each other, and thus these targets are filtered out.

[0033] Step S4 is a crucial step in the preliminary screening process, further refining the selection based on the spatial intersection characteristics of the orbits. It aims to eliminate targets whose orbits may overlap significantly but offer no actual opportunity for approach. Even if the apogee and perigee of two target orbits overlap, theoretically meeting the height requirement for intersection, an actual approach event can only occur at the intersection point of the two orbits or the intersection line of their orbital planes. This is determined by the geometric characteristics of the orbital planes; two non-coplanar orbits will only have spatial intersection at the intersection line. Therefore, the distances between the two targets at these potential approach points (let's say a and b) need to be calculated and compared with a preset threshold distance D. If both distances are greater than the threshold distance D, it means that even if the two targets reach the orbital intersection line, the spatial distance between them exceeds the range where a collision or close approach is possible, and there is no actual opportunity for approach. Through this orbital intersection pre-screening, such targets can be removed from the calculation dataset. While retaining targets with genuine approach risks, this further reduces the amount of data for subsequent calculations, improving the targeting and efficiency of collision warning calculations, and laying a solid foundation for subsequent time-dimensional screening and refined risk assessment. S5: Using time pre-screening, targets that have not been geometrically screened are screened based on the time difference between the two targets passing through the intersection line of the orbital plane.

[0034] In step S5, time pre-screening is used, specifically: for targets that were not selected by geometry in steps S2-S4, the time difference between the two targets passing through the intersection line of the orbital plane is used for screening; although the orbits of the two targets may intersect at close range, they can only approach each other at close range when the two targets pass through the approach point at the same time. In this way, the time difference between the two targets passing through the intersection line of the orbital plane can be used to screen targets.

[0035] The S5 far / near location screening module is a crucial step in eliminating targets with no collision risk from a temporal synchronization perspective, following geometric screenings such as date expiration, far location, near location, and orbital intersection. It focuses on excluding targets whose orbital spatial positions may be close but whose time synchronization is impossible. For targets not eliminated by the preceding geometric screening, their orbits may have a point of close intersection in space (i.e., at the orbital plane intersection). However, collisions or close approaches require not only spatial overlap but also temporal synchronization. The far / near location screening module indicates that actual close contact is only possible when two targets pass this approach point at the same time. Therefore, by calculating the time difference between the two targets passing the orbital plane intersection and judging based on a preset time pre-screening threshold, if the time difference exceeds the threshold, it indicates that the two targets cannot reach the approach point simultaneously, and naturally, there is no collision risk. This time-based pre-screening introduces constraints in the time dimension, retaining targets that meet the potential collision conditions in both spatial location and temporal synchronization while further eliminating invalid data. This ensures the comprehensiveness of the screening and improves computational efficiency through precise time difference judgment, providing a more concise and targeted dataset for subsequent refined risk calculations. S6: After completing the traversal, calculate the object with the smallest average spatial distance and determine it as the identified object. Perform SGP4 orbit prediction on the main target and the eliminated secondary targets, and use the prediction results to calculate whether there is a collision risk.

[0036] In step S6, after completing the traversal, the object with the smallest average spatial distance is identified as the object being identified by calculating the average spatial distance. Then, the SGP4 orbit prediction model is used on the main target and the eliminated secondary targets. The orbit parameters are input to carry out orbit prediction. The prediction results are then used in conjunction with the collision probability calculation model to determine whether there is a collision risk.

[0037] Step S6, following multiple rounds of pre-screening, is the core stage of refined calculation and risk assessment. Its aim is to accurately identify high-risk targets from the remaining targets and complete a collision risk assessment. First, by traversing all previously screened target combinations, the average spatial distance between them is calculated. The target with the smallest average distance is identified as the key focus – this process quantifies spatial proximity, focusing on target pairs most likely to collide, thus locking in the core analysis targets for subsequent risk calculations. Then, for the primary target and the remaining secondary targets, a mature SGP4 orbit prediction model is used, inputting orbital parameters (such as key parameters from orbital TLE data) to conduct high-precision orbit predictions, obtaining dynamic information such as position and velocity over a future period. Based on these prediction results, combined with a collision probability calculation model, and considering factors such as orbit prediction error and target size, a final determination is made as to whether there is a collision risk between the primary and secondary targets. This step, through a progressive process from spatial distance screening to dynamic orbit prediction and then to risk quantification assessment, ensures the relevance of the analysis targets and leverages professional models to improve the accuracy of collision risk assessment, providing crucial evidence for the final reliable early warning results. S7: After all parallel computations are completed, summarize all computation results and output a set of collision warning results containing information such as the collision master and slave target numbers, approach distance, collision probability, and approach time.

[0038] Step S7 is the final stage of the entire collision warning calculation process. It integrates the results of all parallel computing tasks and forms the final output information, providing users with a clear and comprehensive collision risk reference. After the preceding parallel computing, multiple rounds of pre-screening, and refined collision risk assessment, the system generates a large number of calculation results for different master-slave target pairs. At this point, after all parallel computing tasks are completed, these scattered results need to be summarized and integrated to ensure that no potential collision risk information is missed. The final output collision warning result set includes key information such as the collision master and slave target numbers (to identify the specific objects involved in the risk), proximity distance (quantifying the degree of spatial proximity), collision probability (assessing the likelihood of the risk occurring), and proximity time (marking the time when the risk may occur). This information is interrelated and together constitutes the complete warning content, which can intuitively present the core elements of potential collision risks, making it easy for users to quickly understand the risk situation and formulate corresponding avoidance strategies, thereby effectively leveraging the collision warning to ensure the on-orbit safety of spacecraft.

[0039] Second Embodiment like Figure 3 As shown, this embodiment provides a space target collision warning system based on massive orbital data for executing the space target collision warning method based on massive orbital data as described in the first embodiment, comprising: Parallel computing initialization module 1 is used to obtain the latest full set of orbit TLE data required by the algorithm. The collision target orbit TLE data set, the collision full set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size are used as input conditions. After input into the system, the system adaptively performs parallel computing according to the number of target objects and its own computing resources. Date expiration filtering module 2 is used to pre-filter data by date expiration, filtering out targets whose epoch date distance is close to the analysis date but too long. The apogee / perigee filtering module 3 is used to perform apogee / perigee pre-filtering, filtering out targets whose apogee altitude is lower than the perigee altitude of another target. Track intersection filtering module 4 is used to perform pre-screening using track intersections, filtering out targets whose close proximity between two target tracks is greater than a threshold distance D. The time synchronization filtering module 5 is used to pre-filter targets that have not been geometrically filtered based on the time difference between the two targets passing through the intersection line of the orbital plane. Collision risk calculation module 6 is used to calculate the object with the smallest average spatial distance after traversal, and determine it as the identified object. It performs SGP4 orbit prediction on the main target and the eliminated secondary targets, and uses the prediction results to calculate whether there is a collision risk. The result summary output module 7 is used to summarize all calculation results after all parallel calculations are completed, and output a set of collision warning results containing information such as the collision master and slave target numbers, approach distance, collision probability, and approach time.

[0040] A computer-readable storage medium stores computer code that, when executed, performs the methods described above. Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0041] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

[0042] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0043] It should be noted that the above embodiments can be freely combined as needed. The above description is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A space target collision early warning method based on massive orbital data, characterized in that, Includes the following steps: S1: Obtain the latest full set of orbit TLE data required by the algorithm. The input conditions are: the collision target orbit TLE data set, the collision full set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size. After inputting these conditions into the system, the system adaptively performs parallel calculations based on the number of target objects and its own computing resources. S2: Use date expiration pre-screening to remove data, filtering out targets whose epoch date distance is too close to the analysis date. S3: Perform apogee / perigee pre-screening, filtering out targets whose apogee altitude is less than the perigee altitude of another target. S4: Use orbit intersection pre-screening to filter out targets whose two target orbits are closer together than the threshold distance D. S5: Utilize time pre-screening to filter targets that have not been geometrically screened based on the time difference between the two targets passing through the intersection line of the orbital plane; S6: After completing the traversal, calculate the object with the smallest average spatial distance and determine it as the identified object. Perform SGP4 orbit prediction on the main target and the eliminated secondary targets, and use the prediction results to calculate whether there is a collision risk. S7: After all parallel computations are completed, summarize all computation results and output a set of collision warning results containing information such as the collision master and slave target numbers, approach distance, collision probability, and approach time.

2. The space target collision early warning method based on massive orbital data according to claim 1, characterized in that, In step S1, the algorithm preparation work requires obtaining the latest complete set of orbit TLE data; the input conditions include the collision target orbit TLE data set, the collision complete set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size; the system adaptively allocates computing tasks and carries out parallel computing based on the number of target objects and its own computing resources, including the number of CPU cores and available memory.

3. The space target collision early warning method based on massive orbital data according to claim 1, characterized in that, In step S2, the data removal using date expiration pre-filtering is specifically as follows: If the epoch date of the target orbit is too far from the analysis date, it is determined that the target orbit does not meet the collision warning calculation requirements due to the expiration date, and these targets are filtered out from the calculation dataset.

4. The space target collision early warning method based on massive orbital data according to claim 1, characterized in that, In step S3, apogee / neargee pre-screening is performed, specifically as follows: When the apogee of one target's orbit is less than the perigee of another target, the two target orbits have no possibility of intersecting and cannot collide, thus these targets are filtered out.

5. The space target collision early warning method based on massive orbital data according to claim 1, characterized in that, In step S4, pre-screening is performed using the track intersection line, specifically as follows: Even if the apogee and perigee of two target orbits overlap, the two targets can only approach each other at the intersection of the two orbits or the intersection of the two orbital planes. Assuming that the two target orbits have two approach distances a and b, if the distance between them is greater than the threshold distance D, it indicates that the two targets have no chance of approaching each other, and thus these targets are filtered out.

6. The space target collision early warning method based on massive orbital data according to claim 1, characterized in that, In step S5, time-based pre-screening is performed, specifically as follows: For targets not selected by the geometric screening in steps S2-S4, the time difference between the two targets passing through the intersection line of the orbital plane is used for screening. Although the orbits of the two targets may intersect at close range, they can only approach each other at close range when they pass through the approach point at the same time. In this way, the time difference between the two targets passing through the intersection line of the orbital plane can be used to screen targets.

7. The space target collision early warning method based on massive orbital data according to claim 1, characterized in that, In step S6, after completing the traversal, the object with the smallest average spatial distance is identified as the object being identified by calculating the average spatial distance. Then, the SGP4 orbit prediction model is used on the main target and the eliminated secondary targets. The orbit parameters are input to carry out orbit prediction. The prediction results are then used in conjunction with the collision probability calculation model to determine whether there is a collision risk.

8. A space target collision warning system based on massive orbital data for executing the space target collision warning method based on massive orbital data as described in any one of claims 1-7, characterized in that, include: The parallel computing initialization module is used to obtain the latest full set of orbit TLE data required by the algorithm. It takes the collision target orbit TLE data set, the collision full set orbit TLE data set, the date expiration pre-screening threshold, the apogee / perigee pre-screening threshold, the orbit intersection pre-screening threshold, the time pre-screening threshold, and the calculation step size as input conditions. After inputting these conditions into the system, the system adaptively performs parallel computing based on the number of target objects and its own computing resources. The date expiration filtering module is used to remove data by using date expiration pre-screening, filtering out targets whose epoch date distance is close to the analysis date but too long. The apogee / perigee filtering module performs apogee / perigee pre-screening, filtering out targets whose apogee altitude is less than the perigee altitude of another target. The orbital intersection filtering module uses orbital intersections for pre-screening, filtering out targets whose approach distance between two target orbits exceeds a threshold distance D. The time synchronization filtering module uses time pre-screening, filtering out targets not geometrically filtered based on the time difference between two targets passing through the orbital intersection line. The collision risk calculation module, after traversal, calculates the object with the smallest average spatial distance, identifies it as a recognized object, performs SGP4 orbit prediction on the primary target and the removed secondary targets, and uses the prediction results to calculate whether a collision risk exists. The result summary output module is used to summarize all calculation results after all parallel calculations are completed, and output a set of collision warning results containing information such as the collision master and slave target numbers, approach distance, collision probability, and approach time.

9. A computer device comprising a memory and one or more processors, the memory storing computer code that, when executed by the one or more processors, causes the one or more processors to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer code, wherein when the computer code is executed, the method of any one of claims 1 to 7 is performed.

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