Optical observation space debris short arc correlation method and system
By using genetic algorithms and orbit improvement processes, the problem of large orbital errors in short-arc correlation of space debris in optical observations was solved, improving the accuracy and reliability of correlation and reducing the error rate.
Patent Information
- Application Number
- CN202610000995.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-04
- Publication Date
- 2026-05-15
AI Technical Summary
Existing optical observation methods for short-arc correlation of space debris suffer from large orbital errors due to the lack of initial orbital calculations, which can easily lead to a high correlation error rate.
A genetic algorithm-based correlation judgment process and orbit improvement process are adopted. By combining the genetic algorithm and orbit improvement method, the correlation judgment of short arcs of space debris observed by optical observation is carried out by iteratively solving the objective function minimum value through the genetic algorithm, and the orbital state is evaluated by using the Lambert problem.
It effectively improved the accuracy of short-arc correlation of space debris in optical observations, reduced the correlation error rate, and improved the accuracy and reliability of the correlation.
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Figure CN122045312A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of space exploration technology, specifically to a method and system for optical observation of short-arc correlation of space debris. Background Technology
[0002] Current space debris monitoring equipment includes radar and optical telescopes. While radar observation equipment is not limited by atmospheric or lighting conditions, it is constrained by the geographical location and ranging range of the station. Optical telescopes, on the other hand, can acquire relatively higher angular measurement information and, due to their passive observation, consume less power. In particular, space-based optical telescopes can effectively improve the observation coverage of space debris. When optical telescopes observe space debris, the orbital data they acquire is typically in the form of short or very short arcs, with each arc segment having a relatively short observation duration.
[0003] Space debris observations are typically sparse. When processing short arcs of space debris obtained from optical observations, if historical orbital data of the space debris is available, the observed arc segment can be correlated with the historical orbital data before processing. However, if there is no historical orbital data of the space debris, or if it is a new space debris, it is necessary to correlate only the arc segments. Only after correctly correlating multiple arc segments from the same space debris can more accurate orbital information of the space debris be obtained.
[0004] To address the correlation problem between short arcs observed in optical observation, which only contain angular information, the literature "Correlation of Initial Orbits of Very Short Arcs of Low-Earth Orbit Space Targets" (Journal of Wuhan University (Information Science Edition), 2020, 45(10)) proposes a distance search and geometric method for the correlation of optical arcs. First, the initial orbits of the two very short arcs are calculated separately. Then, the orbits are extrapolated to the midpoint, the difference between the two initial orbits at that moment is calculated, and the initial orbits are iteratively adjusted. The possibility of correlation is determined based on the difference between the adjusted initial orbits. In the literature "Research on Initial Orbit Correlation of Very Short Arcs of Space Debris Based on Only Angle" (Acta Geodaetica et Cartographica Sinica, 2021, 50(2)), the initial orbits of the two very short arcs are calculated separately. Then, the orbits are extrapolated to the midpoint, and the long radius of one set is adjusted. If the difference in the position along the orbit at the midpoint is close to zero, it is confirmed that the two sets of initial orbits belong to the same target. The literature "A Robust Method for Short Arc Correlation of Low-Earth Orbit Targets" (Space Control Technology and Application, 2020, 46(5)) and "A Short Arc Correlation Analysis Method Based on Optical Observations Only" (China Space Science and Technology, 2021, 41(3)) use the AR (Admissible Region) method to fit the optimal orbits of multiple sets of observation data. Based on the residuals corresponding to the optimal orbits, the correlation between arc segments is determined by the chi-square test. In the literature "Research on the Correlation Problem of Arc Segments in Optical Observations of Space Debris Based on Mean Drift Clustering Method" (2021 Annual Meeting of the Chinese Astronomical Society), the orbit residuals are evaluated based on the orbital elements within the mean drift clustering framework.
[0005] Patent CN111578950A discloses an autonomous arc segment association and orbit determination method for GEO targets in space-based optical monitoring. It uses two initial orbits to solve the Lambert equation, assigns distance values to the angle measurement data using the near-circular assumption, and then improves the orbit using a perturbation-considered orbit determination model, using the observation residual slope as a judgment threshold. Patent CN113204917B discloses a space-based optical angle measurement arc segment initial orbit determination and association method for GEO targets. Based on the initial orbit, it calculates the nadir point trajectory, using the difference in the average longitude of the nadir points in two arc segments as a judgment threshold. Patent CN114396953B discloses a method for association of space-based short-arc optical orbit measurement data. It performs association verification based on phase difference, combines pairs of data, and then performs three-arc segment verification to finally confirm the target. Patent CN117664146A discloses a trajectory determination method based on optical short-arc track association. It constructs an allowable region between tracks, solves the Lambert problem, calculates the Mahalanobis distance between observed and predicted values of two tracks for screening, and then uses clustered unscented particle filtering for further screening. Patent CN119047136A discloses a spatial target optical arc segment association method based on control metrics. It obtains initial values from two arc segments through an allowable region, and then iteratively calculates the actual control metric value and a relevant threshold to determine the association status.
[0006] In summary, existing optical observation methods for associating short arcs of space debris are mostly based on initial orbits. Since the initial orbit calculation is directly performed using the short arcs of optically observed space debris, the orbital error is usually large. This is due to the insufficient geometric constraints imposed by the optical short arcs on the orbit. Further associating short arcs based on these large initial orbits easily leads to a high association error rate.
[0007] This invention proposes an association method. On one hand, it provides an association judgment process based on a genetic algorithm for two independent arc segments. On the other hand, it provides an association judgment process based on orbit improvement for combinations of independent arc segments and existing arc segments. This method does not involve initial orbit calculations for individual short arcs of optical observation space debris, thus effectively improving the accuracy of short arc association. Summary of the Invention
[0008] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for optical observation of short-arc correlation of space debris.
[0009] According to the present invention, a method for short-arc association of space debris in optical observation includes the following steps: Step S1, setting up an inter-arc association database, including independent arc segment data and arc segment combination data, both types of data are initialized to empty; Step S2, inputting a set of angle-only observation arc segment data, including: sampling time sequence, angle measurement data sequence of space debris relative to the optical observation station in the geocentric celestial coordinate system, and position data sequence of the optical observation station itself in the geocentric celestial coordinate system; Step S3, preprocessing the angle-only observation arc segment data, converting all sampling time data into a line-of-sight unit vector in the geocentric celestial coordinate system and the position of the optical observation station in the geocentric celestial coordinate system; Step S4, if the arc segment combination data in the inter-arc association database is not empty, proceed to Step S5, if the inter-arc association data... If the arc segment combination data in the database is empty, proceed to step S7; Step S5: Associate the current arc segment with the arc segment combination. If an association is found, proceed to step S6; otherwise, proceed to step S7; Step S6: Update the corresponding arc segment combination information in the arc segment association database; Step S7: Associate the current arc segment with the independent arc segment. If an association is found, proceed to step S8; otherwise, proceed to step S9; Step S8: Delete the corresponding independent arc segment information from the arc segment association database and add a new arc segment combination information; Step S9: Add a new independent arc segment information to the arc segment association database; Step S10: Input a new set of optical observation short arc data and repeat steps S2-S9 until all pending optical observation short arc data has been processed.
[0010] Preferably, in step S1, an inter-arc association database is set up, including independent arc segment data and arc segment combination data. Both types of data are initialized to empty. The inter-arc association database stores preprocessed angle-only observation data for independent arc segments and multiple preprocessed angle-only observation data for arc segment combinations, as well as multiple historical orbit information. The orbit information includes the epoch time and orbital element number corresponding to the orbit.
[0011] Preferably, in step S5, the association judgment between the current arc segment and the arc segment combination includes: Step S5.1, obtaining angle-only observation data of multiple arc segments in the arc segment combination whose time is less than a preset threshold and historical orbit information; if there is less than one arc segment, the data of the arc segment with the closest time is taken; Step S5.2, using the last record in the historical orbit information as the initial value, and using the angle-only observation data of multiple arc segments in the arc segment combination and the angle-only observation data of the current arc segment as observation data, performing orbit improvement; Step S5.3, if the orbit improvement fails, output "not associated"; otherwise, obtain the orbit improvement result, compare the orbit improvement residual with the threshold; if it exceeds the threshold, output "not associated"; if it meets the threshold, proceed to step S5.4; Step S5.4, obtain the eccentricity in multiple historical orbit information, calculate the mean and standard deviation of the historical eccentricity; if the eccentricity of the current orbit improvement result is within the 3sigma criterion of the historical eccentricity, output "associated" and output the current orbit improvement result; otherwise, output "not associated".
[0012] Preferably, in step S6, updating the corresponding arc segment combination information in the inter-arc segment association database includes: adding the time series corresponding to the current arc segment, the line-of-sight unit vector in the geocentric celestial coordinate system, the position of the optical observatory in the geocentric celestial coordinate system, and adding the current orbit improvement result to the historical orbit information, based on the original record.
[0013] Preferably, in step S7, the association determination between the current arc segment and the independent arc segment includes: step S7.1, retrieving the observation data of the independent arc segment and the observation data of the current arc segment, merging these two data segments in chronological order to form observation data, if the independent arc segment contains... The next sample, the current arc segment contains The second sampling results in the observation data being composed of arc segment combinations and the current arc segment arranged sequentially, i.e., the first sampling of the combined data. Each sample value, These originate sequentially from the original independent arc segment and the current arc segment; Step S7.2, set the two-dimensional solution space as... ,in, The distance measurement corresponding to the first sampled value of the observation data. For the distance measurement corresponding to the Sth sample value of the observation data, the input parameters of the genetic algorithm are set, including the initial population value, upper search limit, lower search limit and maximum number of iterations; Step S7.3, the genetic algorithm is used to iteratively solve the problem and output the minimum value of the objective function and the corresponding distance measurement estimate sequence for all times of the combined data; Step S7.4, the minimum value of the objective function is compared with the threshold. If the threshold is met, the correlation is output; otherwise, the non-correlation is output.
[0014] Preferably, in step S7.2, the initial population value is generated by uniformly distributed random numbers within the upper and lower limits of the search.
[0015] Preferably, a genetic algorithm is used to iteratively solve the problem, outputting the minimum value of the objective function and the corresponding sequence of distance estimates for all time steps of the combined data, including: step S7.3.1, according to The position values of the space debris are calculated based on the angle measurement values and station position values at the two corresponding time points; Step S7.3.2: Solve the Lambert problem based on the position values and time at the two time points. If the solution converges, output the velocity value and execute step S7.3.3; otherwise, set the objective function value to inf; Step S7.3.3: Recursively derive the position estimates for all time points of the combined data from the position and velocity values, calculate the angle estimates based on the position estimates, and calculate the objective function; Step S7.3.4: After the genetic algorithm iteration is completed, output the minimum value of the objective function and the corresponding sequence of distance estimates for all time points of the combined data.
[0016] Preferably, in step S7.3.3, calculating the objective function includes: the objective function being the average angle difference between the measured angle corresponding to the orbital estimate and the measured angle.
[0017] Here, mean() represents the mean function, and arccos() represents the inverse cosine function. Denotes the vector dot product function. This is the estimated value of the k-th angle measurement in the combined data. This represents the k-th measured value of the combined data.
[0018] Preferably, in step S8, the corresponding independent arc segment information is deleted from the inter-arc segment association database, and an arc segment combination information is added. The added arc segment combination information includes: the time series corresponding to the two arc segments currently involved in the association judgment, the line-of-sight unit vector in the geocentric celestial coordinate system, the position of the optical observatory in the geocentric celestial coordinate system, and the current orbit improvement result is stored in the historical orbit information.
[0019] This invention also provides an optical observation short-arc correlation system for space debris. This system can be implemented by executing the steps of the optical observation short-arc correlation method. That is, those skilled in the art can understand the optical observation short-arc correlation method as a preferred embodiment of the optical observation short-arc correlation system. The system includes: Module M1 sets up an inter-arc relationship database, including independent arc segment data and arc segment combination data. Both types of data are initialized to empty. Module M2 takes as input a set of angle-measuring observation arc data only, including: sampling time sequence, angle measurement data sequence of space debris relative to the optical observatory in the geocentric celestial coordinate system, and position data sequence of the optical observatory itself in the geocentric celestial coordinate system; Module M3 preprocesses the angle-only observation arc data, converting all sampling time data into a line-of-sight unit vector in the geocentric celestial coordinate system and the position of the optical observatory in the geocentric celestial coordinate system; Module M4: If the arc segment combination data in the inter-arc segment association database is not empty, module M5 is triggered to work; if the arc segment combination data in the inter-arc segment association database is empty, module M7 is triggered to work. Module M5 performs association judgment between the current arc segment and the arc segment combination. If an associated object is found, module M6 is triggered; if no associated object is found, module M7 is triggered. Module M6 updates the corresponding arc segment combination information in the inter-arc segment association database; Module M7 determines the association between the current arc segment and independent arc segments. If an associated object is found, module M8 is triggered; otherwise, module M9 is triggered. Module M8 deletes the corresponding independent arc segment information from the arc segment association database and adds a new arc segment combination information; Module M9 adds a new independent arc segment information to the inter-arc segment association database; Module M10 inputs a new set of optical observation short arc data, repeatedly triggering modules M2, M3, M4, M5, M6, M7, M8, and M9 to work until all pending optical observation short arc data has been processed.
[0020] Compared with existing technologies, this invention has the following advantages: This invention proposes a method and process for associating short arcs of space debris in optical observations. For independent arc segments and combinations of arc segments, a correlation judgment process based on orbit improvement is designed; for independent arc segments, a correlation judgment process based on a genetic algorithm is designed. Furthermore, this invention also proposes a corresponding arc segment correlation database maintenance method, which can be applied to effectively determine the association of short arcs of space debris in optical observations even without prior knowledge. Attached Figure Description
[0021] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 The flowchart illustrates a method for optical observation of short-arc correlation of space debris provided by this invention. Detailed Implementation
[0022] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.
[0023] To determine the correlation between observation arcs, traditional methods typically employ an observation-calculation approach. This involves propagating the trajectory determined by one or more observation arcs to the observation time of the current arc and comparing the predicted and measured values. However, while traditional methods maintain relatively accurate historical data and orbital information for confirmed space debris, they suffer from significant prediction errors when faced with a lack of prior information or a large number of newly emerging space debris, directly impacting the accuracy of correlation. For situations where no other prior information is available, and only short-arc data from optical observations (including sampling time sequences, angular measurement data sequences of space debris relative to optical observatories, and positional data sequences of the optical observatories themselves) is available, this invention considers the rationality of the trajectory and attempts to search for a reasonable trajectory that conforms to the existing observation data; that is, the difference between the estimated and measured angular values corresponding to this trajectory is within the range of angular measurement error.
[0024] Figure 1 A flowchart of a method for optically observing short-arc correlation of space debris provided by the present invention is shown below. Figure 1 As shown, it includes: First, the short-arc data from optical observations are unified into the same spatial coordinate system. In this embodiment, the geocentric celestial coordinate system is selected. Therefore, in the data preprocessing, all data at all sampling times are converted into the line-of-sight unit vector in the geocentric celestial coordinate system and the position of the optical observatory in the geocentric celestial coordinate system.
[0025] The ultimate goal of arc segment association is to group observed arc segments belonging to the same fragment together, while arc segments from different fragments are stored separately. For ease of maintenance, this embodiment sets up an inter-arc segment association database containing two types of data: independent arc segments and arc segment combinations. Independent arc segments temporarily store individual arc segments not associated with other arc segments, and the final fragment confirmation is determined by filtering from arc segment combinations. When there is no prior information, both types of data are initialized to empty.
[0026] When a single arc segment is input, it is first matched against objects in the arc segment combination database. If a related object is found, the corresponding arc segment combination database entry is updated. If no arc segment combination is matched, the single arc segment is matched against entries in the independent arc segment database. If a related object is found, the current arc segment and its corresponding entry in the independent arc segment database are removed from the arc segment combination database; otherwise, the current arc segment is saved as an independent arc segment in the independent arc segment database. In addition to storing pre-processed observation data, the arc segment combination database also stores historical orbit information. This historical orbit information serves as initial values for subsequent orbit improvements and also as a basis for detecting whether the orbits of space debris have undergone abrupt changes during correlation assessment.
[0027] Specifically, when associating the current arc segment with arc segment combinations, multiple arc segment data points from the arc segment combination whose time is less than a given threshold are retrieved. If there is less than one arc segment, the arc segment data point with the closest time is retrieved. If the retrieved arc segment combination contains... Each independent arc segment ( Each arc segment contains Samples (n=1, 2, ..., The current arc segment contains The next sampling constructs the observation data, which is composed of arc segment combinations and the current arc segment arranged sequentially, i.e., the k-th sample value of the combined data (k=1, 2, ...). , , ..., ……, The data originates sequentially from the arc segment combination and the current arc segment. Historical orbit information provides the last orbital information as the initial value. Orbit improvement is performed based on the constructed observation data. If the current arc segment and the arc segment combination do not originate from the same space debris's observation data, the improvement may fail to converge or converge but with a large orbital residual. In this case, the improvement results can be used to determine arc segment association: For space debris with very similar orbits, especially those on the same orbital plane, if their angle-only arc segments show convergence in the improvement results and meet the orbital residual threshold, further analysis using historical orbital information can be conducted to check for abrupt changes in the current improved orbit compared to historical orbital information. For space debris, where abrupt changes are unlikely, the 3sigma criterion for eccentricity is used for judgment. If the eccentricity exceeds the 3sigma criterion for historical orbital eccentricity, it is still considered unassociated.
[0028] If, after traversing all arc segments, no related arc segments are found, the search continues to explore whether they might originate from the same space debris as other independent arc segments. Since independent arc segments lack historical orbital information compared to arc segment combinations, orbital calculations are performed based on the observation data of two arc segments. If an independent arc segment contains... The next sample, the current arc segment contains The sampling is performed on the k-th sampled value of the combined data (k=1, 2, ...). The observation data for two arc segments are formed by sequentially arranging the combined arc segments and the current arc segment. , , ..., () comes from the original independent arc segment and the current arc segment in turn.
[0029] Since angle measurement data alone lacks distance measurement information, the trajectory calculation is transformed into solving for two distance measurement values. That is, the distance measurement values of the first and last samples of one arc segment constitute a two-dimensional solution space. Furthermore, by estimating the distance values, the orbital status and the rationality of the orbit can be determined.
[0030] Specifically, when evaluating whether the calculated trajectory conforms to existing observation data, an objective function is used for quantification. The objective function is defined as the average angle difference between the angular measurement corresponding to the estimated trajectory and the measured angular measurement, i.e.
[0031] Here, mean() represents the mean function, and arccos() represents the inverse cosine function. Denotes the vector dot product function. This is the estimated value of the k-th angle measurement in the combined data. This represents the k-th measured value of the combined data.
[0032] From two distance estimates When calculating the objective function, firstly by The position value of the space debris is calculated based on the angle measurement value and the station position value at the corresponding two time points. Then, the Lambert problem involving the position value and time is solved using the position value and time at the two time points. If the solution converges, the velocity value is output; otherwise, the objective function value is set to inf.
[0033] When the Lambert solution converges, the position estimate for all times is recursively derived from the position and velocity values, and the angle estimate is calculated from the position estimate.
[0034] Minimum value of objective function corresponds to Solving this problem falls under the category of optimization, and this embodiment employs a genetic algorithm. First, the input parameters for the genetic algorithm are set, including: initial population size, upper search limit, lower search limit, and maximum number of iterations. The initial population size is generated from uniformly distributed random numbers within the upper and lower search limits. Furthermore, the population size and maximum number of iterations are set larger than the arc combination size; without loss of generality, a population size of 1000 and a maximum number of iterations of 500 can be set. When the minimum value of the objective function is less than the set threshold, the result is considered as a correlation. The original independent arc segments are then deleted from the database, and new arc combination combinations are formed by combining the original independent arc segments with the current independent arc segments. The corresponding observation data and orbital information are saved to the database.
[0035] This embodiment verifies the effectiveness of the method of the present invention using simulation data. The simulation set up the orbits of 808 different space debris, and generated 5815 short optical arc segments distributed over 15 days based on the visibility of optical stations. Using the method of the present invention, the 5815 short arc segments were correlated. Arc segments of the same debris were correctly correlated 4872 times (true positives) and incorrectly judged as not correlated 162 times (false negatives). Arc segments of different debris were correctly judged as not correlated 3907959 times (true negatives) and incorrectly judged as correlated 43 times (false positives). Based on this, the accuracy rate was further statistically analyzed to be 99.11%, the false negative rate was 3.26%, and the false alarm rate was 0.0011%.
[0036] Therefore, it can be concluded that the optical observation space debris short arc correlation method provided by the present invention can achieve arc segment correlation with extremely high accuracy and extremely low false alarm rate in complex scenarios without prior information, while maintaining a low false alarm rate.
[0037] This invention also provides an optical observation short-arc correlation system for space debris. This system can be implemented by executing the steps of the optical observation short-arc correlation method. That is, those skilled in the art can understand the optical observation short-arc correlation method as a preferred embodiment of the optical observation short-arc correlation system. The system includes: Module M1 sets up an inter-arc relationship database, including independent arc segment data and arc segment combination data. Both types of data are initialized to empty. Module M2 takes as input a set of angle-measuring observation arc data only, including: sampling time sequence, angle measurement data sequence of space debris relative to the optical observatory in the geocentric celestial coordinate system, and position data sequence of the optical observatory itself in the geocentric celestial coordinate system; Module M3 preprocesses the arc data of angle-only observations, converting all data at all sampling times into line-of-sight unit vectors in the geocentric celestial coordinate system and the position of the optical observatory in the geocentric celestial coordinate system; If the arc segment combination data in the inter-arc segment association database is not empty, module M4 will trigger module M5 to work; if the arc segment combination data in the inter-arc segment association database is empty, module M7 will trigger module M7 to work. Module M5 performs association judgment between the current arc segment and the arc segment combination. If an associated object is found, module M6 is triggered; if no associated object is found, module M7 is triggered. Module M6 updates the corresponding arc segment combination information in the inter-arc segment association database; Module M7 determines the association between the current arc segment and independent arc segments. If an associated object is found, module M8 is triggered; otherwise, module M9 is triggered. Module M8 deletes the corresponding independent arc segment information from the arc segment association database and adds a new arc segment combination information; Module M9 adds a new independent arc segment information to the inter-arc segment association database; Module M10 inputs a new set of optical observation short arc data, repeatedly triggering modules M2, M3, M4, M5, M6, M7, M8, and M9 to work until all pending optical observation short arc data has been processed.
[0038] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.
[0039] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.
Claims
1. A method for optically observing short-arc correlation of space debris, characterized in that, include: Step S1: Set up the inter-arc relationship database, including independent arc segment data and arc segment combination data. Both types of data are initialized to empty. Step S2: Input a set of angle-only observation arc data, including: sampling time sequence, angle measurement data sequence of space debris relative to the optical observatory in the geocentric celestial coordinate system, and position data sequence of the optical observatory itself in the geocentric celestial coordinate system; Step S3: Preprocess the angle-only observation arc data by converting all sampling time data into a line-of-sight unit vector in the geocentric celestial coordinate system and the position of the optical observation station in the geocentric celestial coordinate system. Step S4: If the arc segment combination data in the inter-arc segment association database is not empty, proceed to step S5; if the arc segment combination data in the inter-arc segment association database is empty, proceed to step S7. Step S5: Perform an association judgment between the current arc segment and the arc segment combination. If an associated object is found, proceed to step S6; otherwise, proceed to step S7. Step S6: Update the corresponding arc segment combination information in the arc segment association database; Step S7: Associate the current arc segment with independent arc segments. If an associated object is found, proceed to step S8; otherwise, proceed to step S9. Step S8: Delete the corresponding independent arc segment information from the arc segment association database and add a new arc segment combination information; Step S9: Add a new independent arc segment information to the inter-arc segment association database; Step S10: Input a new set of optical observation short arc data, and repeat steps S2-S9 until all optical observation short arc data to be processed is completed.
2. The optical observation method for short-arc correlation of space debris according to claim 1, characterized in that, In step S1, an inter-arc segment association database is set up, including independent arc segment data and arc segment combination data. Both types of data are initialized to empty, including: In the inter-arc association database, independent arc segments store preprocessed angle-only observation data, while arc segment combinations store preprocessed angle-only observation data for multiple arc segments, as well as multiple historical orbit information, including the epoch time and orbital elements corresponding to the orbit.
3. The optical observation method for short-arc correlation of space debris according to claim 1, characterized in that, In step S5, the current arc segment and the arc segment combination are associated and judged, including: Step S5.1: Obtain angle-only observation data and historical orbit information of multiple arc segments in the arc segment combination whose time is less than a preset threshold. If there is less than one arc segment, take out the data of the arc segment with the closest time. Step S5.2: Using the last record in the historical orbit information as the initial value, and using the angle-only observation data of multiple arc segments in the arc segment combination and the angle-only observation data of the current arc segment as the observation data, perform orbit improvement; Step S5.3: If the orbit improvement fails, output "not associated"; otherwise, obtain the orbit improvement result, compare the orbit improvement residual with the threshold, and if it exceeds the threshold, output "not associated"; if it meets the threshold, proceed to step S5.
4. Step S5.4: Obtain the eccentricity from multiple historical orbit information, calculate the mean and standard deviation of the historical eccentricity, and if the eccentricity of the current orbit improvement result is within the 3sigma criterion of the historical eccentricity, output correlation and output the current orbit improvement result; otherwise, output no correlation.
4. The optical observation method for short-arc correlation of space debris according to claim 1, characterized in that, In step S6, updating the corresponding arc segment combination information in the inter-arc segment association database includes: Based on the original record, the time series corresponding to the current arc segment, the line-of-sight unit vector in the geocentric celestial coordinate system, the position of the optical observatory in the geocentric celestial coordinate system, and the current orbit improvement results are added to the historical orbit information.
5. The optical observation method for short-arc correlation of space debris according to claim 1, characterized in that, In step S7, the association determination between the current arc segment and independent arc segments includes: Step S7.1: Extract the observation data of the independent arc segment and the observation data of the current arc segment, and merge these two data segments in chronological order to form the observation data. If the independent arc segment contains... The next sample, the current arc segment contains The second sampling results in the observation data being composed of arc segment combinations and the current arc segment arranged sequentially, i.e., the first sampling of the combined data. Each sample value, These originate sequentially from the original independent arc segment and the current arc segment; Step S7.2, set the two-dimensional solution space as ,in, The distance measurement corresponding to the first sampled value of the observation data. To measure the distance corresponding to the Sth sample value of the observation data, the input parameters of the genetic algorithm are set, including the initial population value, upper search limit, lower search limit, and maximum number of iterations; Step S7.3: Use a genetic algorithm to iteratively solve the problem and output the minimum value of the objective function and the corresponding sequence of distance estimates for all times of the combined data. Step S7.4: Compare the minimum value of the objective function with the threshold. If the threshold is met, output correlation; otherwise, output non-correlation.
6. The optical observation method for short-arc correlation of space debris according to claim 5, characterized in that, In step S7.2, the initial population value is generated by uniformly distributed random numbers within the upper and lower limits of the search.
7. The optical observation method for short-arc correlation of space debris according to claim 1, characterized in that, In step S7.3, a genetic algorithm is used iteratively to solve the problem, outputting the minimum value of the objective function and the corresponding sequence of distance estimates for all time steps of the combined data, including: Step S7.3.1, according to And calculate the position value of the space debris based on the angle measurement value and the station position value at the corresponding two moments; Step S7.3.2: Solve the perturbed Lambert problem based on the position and time values at two time points. If the solution converges, output the velocity value and proceed to step S7.3.3; otherwise, set the objective function value to inf. Step S7.3.3: Based on the position and velocity values, recursively calculate the position estimate for all times in the combined data, calculate the angle estimate based on the position estimate, and calculate the objective function; Step S7.3.4: After the genetic algorithm has completed the iteration, output the minimum value of the objective function and the corresponding sequence of distance estimates for all times of the combined data.
8. The optical observation method for short-arc correlation of space debris according to claim 7, characterized in that, In step S7.3.3, the objective function is calculated, including: The objective function is the average angle difference between the estimated angle measurement and the actual measured angle measurement. Here, mean() represents the mean function, and arccos() represents the inverse cosine function. Denotes the vector inner product function. This is the estimated value of the k-th angle measurement in the combined data. This represents the k-th measured value of the combined data.
9. The optical observation method for short-arc correlation of space debris according to claim 1, characterized in that, In step S8, the corresponding independent arc segment information is deleted from the inter-arc segment association database, and an arc segment combination information is added. The added arc segment combination information includes: the time series corresponding to the two arc segments currently involved in the association judgment, the line-of-sight unit vector in the geocentric celestial coordinate system, the position of the optical observation station in the geocentric celestial coordinate system, and the current orbit improvement result is stored in the historical orbit information.
10. A short-arc correlation system for optical observation of space debris, characterized in that, include: Module M1 sets up an inter-arc relationship database, including independent arc segment data and arc segment combination data. Both types of data are initialized to empty. Module M2 takes as input a set of angle-measuring observation arc data only, including: sampling time sequence, angle measurement data sequence of space debris relative to the optical observatory in the geocentric celestial coordinate system, and position data sequence of the optical observatory itself in the geocentric celestial coordinate system; Module M3 preprocesses the angle-only observation arc data, converting all sampling time data into a line-of-sight unit vector in the geocentric celestial coordinate system and the position of the optical observatory in the geocentric celestial coordinate system; Module M4: If the arc segment combination data in the inter-arc segment association database is not empty, module M5 is triggered to work; if the arc segment combination data in the inter-arc segment association database is empty, module M7 is triggered to work. Module M5 performs association judgment between the current arc segment and the arc segment combination. If an associated object is found, module M6 is triggered; if no associated object is found, module M7 is triggered. Module M6 updates the corresponding arc segment combination information in the inter-arc segment association database; Module M7 determines the association between the current arc segment and independent arc segments. If an associated object is found, module M8 is triggered; otherwise, module M9 is triggered. Module M8 deletes the corresponding independent arc segment information from the arc segment association database and adds a new arc segment combination information; Module M9 adds a new independent arc segment information to the inter-arc segment association database; Module M10 inputs a new set of optical observation short arc data, repeatedly triggering modules M2, M3, M4, M5, M6, M7, M8, and M9 to work until all pending optical observation short arc data has been processed.