Spacecraft orbit safety intelligent planning method and system

Abstract

The invention discloses a safe and intelligent planning method for a spacecraft orbit. The safe and intelligent planning method comprises the following steps: S1, constructing an orbit safe and intelligent planning model; s2, analyzing a space debris orbit change event; s3, selecting and determining a space debris removal sequence; s4, calculating a track safety intelligent planning result; s5, formulating an optimized detailed orbit maneuvering strategy; s6, a planning report and a scene graph are generated through one key, the invention further discloses a corresponding system, electronic equipment and a computer readable storage medium condition, the safety intelligent planning precision and speed of the spacecraft orbit can be improved, and the planning scheme and simulation scene generation time can be shortened; combined application of various task elements is considered, hierarchical and hierarchical task planning from coarse granularity to fine granularity is completed, and actual task requirements are met; intelligent task planning is deepened, the algorithm application range is expanded, and task planning method research under systematic complex scenes is supported.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and in particular to a method and system for intelligent planning of spacecraft orbital safety based on reinforcement learning. Background Art

[0002] With the development of technology and the deepening of space applications, the threat of space debris and other space debris to on-orbit spacecraft is increasing, and the potential risks in specific environments are gradually increasing. There is an urgent need for the innovative application of fast, reliable, high-precision and intelligent mission planning methods and technologies to improve orbital safety capabilities against space debris and other space debris.

[0003] After searching, the existing technologies include the following categories:

[0004] (1) A Chinese patent application (application number: CN2013103145506, publication number: CN103438888A) discloses a relative navigation method for autonomous rendezvous with a non-cooperative target in space. The relative orbital motion equation of the spacecraft is used as the navigation state equation, the relative line of sight angle information measured by the onboard CCD (Charge Coupled Device) camera, the absolute positioning information output by the GNSS (Global Navigation Satellite System) receiver, and the relative distance ρ information constructed by geometric constraints are used as measurement quantities, and the UKF (Unscented Kalman Filter) filtering algorithm is used to accurately estimate the relative position and relative velocity between the service satellite and the non-cooperative target.

[0005] (2) A Chinese patent application (application number: CN2015102889151, publication number: CN104977594A) discloses a codeless Doppler orbit determination method based on non-cooperative navigation satellite signals, comprising the following steps: sampling a received navigation satellite signal to obtain a digital intermediate frequency signal after digital down-conversion, eliminating the confidential modulation code of the digital intermediate frequency signal, and calculating an estimated value of the carrier frequency based on the signal after code elimination; using the estimated value of the carrier frequency obtained in step (1) as the initial frequency of the carrier tracking loop to generate a local oscillator signal of the carrier tracking loop, and ... The signal after the mid-elimination code is used as the input signal of the carrier tracking loop to recover the carrier signal, and the Doppler frequency shift of each navigation satellite signal is measured and extracted; the prior value of each navigation satellite signal is calculated, and combined with the measured value of the Doppler frequency shift obtained in step (2), an identification and matching algorithm containing the measured value and the prior value of the Doppler frequency shift of the receiver frequency difference is established to complete the identification and matching of the navigation satellite; the statistical orbit determination algorithm is used to realize orbit measurement, the orbit dynamics equation is used to establish the state equation, the carrier phase measurement value is used to establish the phase difference measurement equation, and then the Kalman filter is used to estimate the orbit parameters of the user satellite.

[0006] However, the above-mentioned existing technologies are difficult to achieve rapidity, high precision and standardization in the intelligent planning of orbital safety of space debris, which limits their application in complex working conditions.

[0007] In addition, during orbital safety operations on space debris, there are still outstanding problems such as high cost of operations, low level of intelligence, and incomplete processes.

[0008] The workflow problems caused by the low level of intelligence include: serious empiricism among task commanders, the level of command methods depends on the commander's task experience, and the command effects of different commanders vary greatly; the level of the command team is not fixed, the task planning level of the support team is uneven, and the task planning effects vary greatly; the support team learns slowly, making it difficult to quickly cultivate a team with strong task planning capabilities and effectively support task planning.

[0009] Technical operational problems caused by the low level of intelligence include: difficulty in comprehensive analysis of intelligence information, inability to timely and accurately screen and anchor intelligence information that is truly useful for intelligent planning of space debris orbital safety, and inability to quantify the meaning of situation information and the mechanism and degree of its impact on subsequent mission planning; difficulty in extracting and applying mission data. When facing the problem of intelligent planning of spacecraft orbital safety, it is necessary to widely collect and organize data such as spacecraft attributes and mission environment information from multiple media, and it is impossible to achieve rapid extraction and application of systematic data; difficulty in intelligent calculation of mission planning. It is impossible to quickly apply the collected intelligence and data information to mission planning calculations including orbital safety deductions, and it is difficult to generate mission planning plans and mission scenarios that take into account multiple factors and make comprehensive conclusions; it is difficult for auxiliary decision-making to be effective. Mission command and control often requires near-real-time provision of mission planning plans to quickly assist departments in making decisions on handling spacecraft orbital safety tasks. Existing methods lack systematicity and cannot support the ability to quickly calculate and generate results, making it difficult to effectively support mission planning.

[0010] For intelligent planning of spacecraft orbital safety, existing methods and systems are difficult to balance rapidity, high precision and standardization, which limits their application under complex working conditions. These problems need to be solved urgently, and in-depth research is needed to explore and study the theory of intelligent planning methods for spacecraft orbital safety with practical benefits to assist in supporting the command and decision-making of spacecraft orbital safety missions. Summary of the invention

[0011] The purpose of the present invention is to provide a spacecraft orbital safety intelligent planning method and system, which is oriented to the needs of space debris orbital safety intelligent planning, and provides a spacecraft orbital safety intelligent planning method and system that considers intelligent algorithms such as reinforcement learning and differential evolution, serving the needs of space debris orbital safety intelligent planning, comprehensive situation analysis and task planning for the safety of cooperative spacecraft; the purpose of the spacecraft orbital safety intelligent planning method and system is to explore and study the theory of spacecraft intelligent task planning methods, propose intelligent task planning methods with practical benefits, support scientific decision-making for space mission actions, and realize accurate task command auxiliary decision-making based on actuarial calculations, so as to achieve the purpose of quickly generating feasible and accurate task planning plans. The inventive concept of the present invention is to use intelligent methods and technologies, integrate into space mission command, solve the problem of intelligent and rapid task planning for spacecraft orbital safety, complete space debris orbital change event analysis, rapid selection of orbital safety targets, orbital safety intelligent planning, task plan optimization and one-click generation of scenario reports, thereby changing the current situation of relying on manual deep participation in task analysis and planning plan writing, and improving the speed, accuracy and reliability of spacecraft orbital safety intelligent planning.

[0012] A first aspect of the present invention is to provide a spacecraft orbit safety intelligent planning method, comprising:

[0013] S1, build a spacecraft orbital safety intelligent planning model;

[0014] S2, analysis of orbit change events of space debris;

[0015] S3, rapid selection of mission targets based on quantified orbit change events;

[0016] S4, calculate the results of intelligent planning for track safety;

[0017] S5, formulate optimization detailed task strategy;

[0018] S6, generating a planning report and a scenario diagram based on the optimized task plan with one click.

[0019] Preferably, the S1 comprises:

[0020] S11, build a spacecraft orbital safety intelligent planning model architecture;

[0021] S12, establish a spacecraft orbit safety intelligent planning method flow based on the spacecraft orbit safety intelligent planning model architecture.

[0022] Preferably, S2 includes:

[0023] S21, based on the spacecraft orbit information and comprehensive intelligence information, using the spacecraft dynamics model, extrapolating and predicting the spacecraft rendezvous event, combining the historical orbit change law of space debris and the partial objective hierarchical analysis method to analyze the space debris orbit change event; the partial objective hierarchical analysis method to analyze the space debris orbit change event includes:

[0024] (1) Extrapolate the orbits of space debris before and after the orbital change, including:

[0025] Using a high-precision orbit fast integration method and an automatic step size selection algorithm, combined with the advantages of fast analytical method and high numerical method, the trajectory of space debris before and after orbit changes is extrapolated;

[0026] (2) Calculate the track change of the splicing point, including:

[0027] The orbital states of the extrapolated and calculated space debris orbit splicing points are converted into the orbital six-element numbers, and the changes of the orbital six-element numbers are compared and calculated;

[0028] (3) Analyze orbital change events based on the changes in orbital elements of space debris, including:

[0029] Determine the change in the number of orbital elements of space debris after the change relative to before the change, and preliminarily analyze the orbital control of space debris based on its control history and control laws;

[0030] (4) Extrapolating the orbits of both spacecraft to determine the proximity of space debris, including:

[0031] Extrapolate the orbits of multiple spacecraft in parallel, compare the spatial distance between space debris and spacecraft at each time point, determine whether the closest distance meets the orbital safety action conditions, and determine the orbit change events of space debris accordingly;

[0032] (5) Using the analytic hierarchy process to determine the target's orbital change events, including:

[0033] Based on the close proximity of space debris and spacecraft, the orbit change event of space debris target is obtained by using partial objective hierarchical analysis method;

[0034] S22, quantitatively express the orbit change event, and search for the corresponding response and disposal plan in the case strategy library, so as to provide the prerequisite for the subsequent task determination and the rapid selection of orbit safety task objectives.

[0035] Preferably, S3 includes:

[0036] S31, based on the objective information of the spacecraft orbital safety mission, quantitatively expressing the mission objective;

[0037] S32, based on the analysis results of the orbit change event, using the analytic hierarchy process, combined with the classification and grading information of the space debris target mission and importance in the comprehensive intelligence information, traverse the preliminary possible solutions for dealing with the space debris approach event;

[0038] S33, based on the preliminary possible solution, using the ephemeris matching method to quickly screen targets or determine target sequences, and selecting orbital safety mission targets based on the targets or target sequences, wherein the calculation process of the ephemeris matching method includes:

[0039] (1) Find the target star that is closest to the matching star or the mission star at any time node within the mission allowed time period through orbit ephemeris recursion;

[0040] (2) By comparing the minimum distances at all time nodes, determine the target star closest to the matching star and its corresponding time node within the allowed time period of the entire mission;

[0041] (3) According to the Lambert characteristic, the target star closest to the matching star is the one with the least transfer energy consumption, thereby determining the optimal launch window initial value and the candidate optimal detection sequence.

[0042] Preferably, S4 includes:

[0043] S41, obtaining spacecraft orbit information, force application rule information, comprehensive intelligence information, mission purpose information and spacecraft dynamic model information as calculation basic information;

[0044] S42, based on the initially selected orbital safety mission target and the calculation basic information, utilize the space target orbital safety intelligent planning algorithm to achieve the coarse-grained task planning results of the spacecraft orbital safety mission; wherein, the coarse-grained task planning results of the spacecraft orbital safety mission are used to determine the mission target, mission purpose and basic plan arrangements for the use of comprehensive forces.

[0045] Preferably, S5 includes:

[0046] S51, based on the coarse-grained task planning of completing the spacecraft orbital safety mission, combined with the spacecraft orbital information, calling the satellite dynamics model, and using the global optimization algorithm and the high-precision orbital integration method to perform orbital design and splicing; wherein the global optimization algorithm includes a differential evolution method, and of course, those skilled in the art should know that other differential evolution methods are also within the scope of protection of the present invention;

[0047] S52, optimize the splicing orbit based on the global optimization algorithm, determine the optimal parameters of the transfer orbit, and obtain a fine-grained task planning result.

[0048] Preferably, S6 includes:

[0049] S61, preliminarily evaluating and judging the fine-grained task planning result, if the fine-grained task planning result is feasible, calling the WORD algorithm based on MATLAB, automatically writing and filling the fine-grained task planning result, and forming a planning report with one click;

[0050] S62, based on MATLAB calling the STK algorithm, generates a scene diagram with one click that combines three-dimensional and two-dimensional scenes with task indicator graphics, visually displaying the debris removal process and task completion status.

[0051] A second aspect of the present invention is to provide a spacecraft orbit safety intelligent planning system, comprising:

[0052] Model building module, used to build a spacecraft orbital safety intelligent planning model;

[0053] Orbital change event analysis module, used to analyze orbital change events of space debris;

[0054] Mission target selection module, used to quickly select mission targets based on quantified orbit change events;

[0055] A calculation module is used to calculate the results of intelligent planning for track safety;

[0056] The optimization module is used to formulate detailed optimization task strategies;

[0057] Display module, used to generate planning reports and scenario diagrams with one click.

[0058] A third aspect of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores a plurality of instructions, and the processor is configured to read the instructions and execute the method described in the first aspect.

[0059] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a plurality of instructions, and the plurality of instructions can be read by a processor and execute the method described in the first aspect.

[0060] Beneficial effects of the method, system, electronic device, and readable storage medium of the present invention:

[0061] This method and system take advantage of the automation and intelligence of mission data, mission planning, plan formulation, report generation and other processes, make up for the low efficiency caused by the lack of data links, and support the rapid planning of orbital safety missions for space debris. The proposed intelligent planning method and system for spacecraft orbital safety has the advantages of standardized workflow, fast calculation speed, less manual intervention, flexible deployment, low system implementation cost, and wide application. Specifically including:

[0062] 1) According to the method and system of the present invention, the accuracy and speed of intelligent planning for safe orbits of space debris can be improved, and the time for generating planning schemes and simulation scenarios can be shortened, which is in line with the development trend of intelligence;

[0063] 2) According to the method and system of the present invention, it is possible to take into account the combined use of various task forces and complete hierarchical task planning from coarse granularity to fine granularity, which meets the actual task requirements;

[0064] 3) Based on the method and system of the present invention, it is possible to deepen the research on intelligent task planning under the use of comprehensive forces, expand the application scope of the algorithm, and support the research on task planning methods in systematic and complex scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the related technologies, the drawings required for use in the specific embodiments or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0066] Figure 1 A schematic diagram of the structure of a spacecraft orbital safety intelligent planning model provided by an embodiment of the present invention, which is used to explain the basic logical framework and calculation and processing flow of spacecraft orbital safety intelligent planning;

[0067] Figure 2 A schematic diagram of a typical intelligent planning result for rail safety provided in an embodiment of the present invention.

[0068] in: Figure 2 (a) is a schematic diagram of the analysis results, describing the changes in the distance and illumination angle during the approach of space debris X to spacecraft Y;

[0069] Figure 2 (b) is a schematic diagram of the target selection results, describing the screening results of orbital safety targets using the hierarchical analysis and ephemeris matching methods;

[0070] Figure 2 (c) is a schematic diagram of the intelligent planning calculation results, describing the coarse-grained results of spacecraft orbital safety planning;

[0071] Figure 2 (d) is a schematic diagram of the diversion strategy results, describing the diversion path of the spacecraft to the space debris;

[0072] Figure 2 (e) is a schematic diagram of the mission scenario results, describing the mission scenario results of the spacecraft and space debris carrying out orbital safety actions;

[0073] Figure 3 This is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0074] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0076] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0077] The spacecraft orbital safety intelligent planning method and system of this embodiment include six main parts: mission planning model construction, orbital change event analysis, rapid selection of orbital safety action targets, orbital safety intelligent planning, mission plan optimization formulation, and scenario report one-key generation algorithm. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict, and the specific implementation methods of the invention are described in detail below.

[0078] Figure 1 The figure shows the structure diagram of the spacecraft orbital safety intelligent planning model, which is used to explain the basic logical framework and computational processing flow of spacecraft orbital safety intelligent planning. Based on the spacecraft orbital information, the spacecraft dynamics model is used to extrapolate and predict spacecraft rendezvous events, and the orbital change events of space debris are analyzed in combination with the historical orbital change laws of space debris; based on the mission purpose information, the key points of mission action are determined, and the orbital safety action targets are quickly selected; the spacecraft orbital safety intelligent planning algorithm based on reinforcement learning is used, combined with the situational awareness capability, force application strategy library, and orbital maneuver strategy library, and the mission planning results are calculated through orbital safety deduction; the global optimization algorithm is used to accurately calculate the spacecraft orbital change strategy, formulate the mission plan, and generate the overall mission planning plan.

[0079] This embodiment provides a spacecraft orbit safety intelligent planning method, including:

[0080] S1, build a spacecraft orbital safety intelligent planning model, including:

[0081] S11, build a spacecraft orbital safety intelligent planning model architecture;

[0082] S12, establish a spacecraft orbit safety intelligent planning method flow based on the spacecraft orbit safety intelligent planning model architecture.

[0083] S2, analysis of orbital change events of space debris, including:

[0084] S21, based on spacecraft orbit information and comprehensive intelligence information, using spacecraft dynamics models, extrapolating and predicting spacecraft rendezvous events, and analyzing space debris orbit change events in combination with the historical orbit change laws of space debris;

[0085] S22, quantitatively express the orbit change event, and search the corresponding response and disposal plan in the case strategy library to provide a prerequisite for the subsequent task determination and the rapid selection of orbit safety action targets.

[0086] In this embodiment, the judgment of satellite orbit change events using the classic analytic hierarchy process is subjective and not very reliable. Therefore, the analytic hierarchy process is appropriately improved as follows: the basic principles and steps are the same as those of the analytic hierarchy process, but if the weight vector of a certain layer of elements for the previous layer of elements can be calculated by a more objective method, it is no longer obtained by solving the eigenvector of the judgment matrix. It is called the partial objective analytic hierarchy process (POAHP). The basic method flow of using the partial objective analytic hierarchy process to judge satellite orbit change events is as follows:

[0087] (1) Extrapolate the trajectory of space debris before and after the orbital change, including:

[0088] By using a high-precision orbit fast integration method and an automatic step size selection algorithm, combined with the advantages of fast calculation speed of the analytical method and high calculation accuracy of the numerical method, the trajectory of space debris before and after the orbit change is extrapolated.

[0089] (2) Calculate the track change of the splicing point, including:

[0090] The extrapolated and calculated orbital state quantities of the space debris orbit splicing point (the closest point) are converted into the form of six orbital numbers, and the changes of the six orbital numbers are compared and calculated.

[0091] (3) Analyze orbital change events based on the changes in orbital elements of space debris, including:

[0092] Determine the change in the orbital elements of space debris after the change relative to before the change, and combine its control history and control laws to preliminarily analyze the orbital control of space debris.

[0093] (4) Extrapolating the orbits of both spacecraft to determine the proximity of space debris, including:

[0094] Extrapolate the orbits of multiple spacecraft in parallel, compare the spatial distance between space debris and spacecraft at each time point, determine whether the closest distance meets the orbital safety action conditions, and determine the orbital change events of space debris accordingly.

[0095] (5) Using the analytic hierarchy process to determine the target's orbital change events, including:

[0096] After obtaining the proximity situation between space debris and spacecraft, the partial objective hierarchical analysis method is used to comprehensively determine the orbit change event of the space debris target.

[0097] S3, quickly selects mission targets based on quantified orbit change events, including:

[0098] S31, based on the objective information of the spacecraft orbital safety mission, quantitatively expressing the mission objective;

[0099] S32, based on the analysis results of the orbital change event, using the analytic hierarchy process, combined with the classification and grading information of the orbital safety action objectives, missions and importance in the comprehensive intelligence information, traverse the preliminary possible solutions for dealing with the space debris approach event;

[0100] S33, based on the preliminary possible solutions, using an ephemeris matching method to quickly screen targets or determine target sequences, and selecting orbital safety mission targets based on the targets or target sequences.

[0101] In this embodiment, the basic calculation process of the ephemeris matching method in S33 includes:

[0102] (1) First, find the target star closest to the matching star (task star) at any time node within the mission allowed time period through orbit ephemeris recursion;

[0103] (2) Then, by comparing the minimum distances at all time nodes, determine the target star closest to the matching star and its corresponding time node within the allowed time period of the entire task;

[0104] (3) Finally, according to the Lambert characteristic, the target star closest to the matching star is the one with the least transfer energy consumption, thus finding the optimal launch window initial value and the candidate optimal detection sequence.

[0105] From the analysis of Lambert's problem, we know that when the departure time t0 or the arrival time t f Target Star t The closer the position is to the matching star p (here refers to the mission star) (equivalent to the bias δ x The smaller the size), the spacecraft is transferred by Lambert from the matching star p to f Fly to the target star t The less energy is consumed, the more likely it is that the target star p t The degree of closeness (or matching degree) to the ephemeris (position and velocity) of the matching star p at each moment can measure the relative size of the energy Δv consumed by the spacecraft transfer between the matching star and the target star. The mathematical model is expressed as formula (1):

[0106] Δv=f(rpt (τ)-r p (τ),v pt (τ)-v p (τ)) (1)

[0107] Among them, f(·) is a monotonically increasing function; r p , v p are the position and velocity vector of the matching star p; r pt , v pt The target star p t The position and velocity vector of f .

[0108] The goal of the ephemeris matching method is to find the maneuvering time and target star that satisfy the minimum Δv, which is equivalent to finding a solution that satisfies the following conditions (2) and (3):

[0109]

[0110] Where k is the candidate target star number; Δt is the time period for distance calculation and comparison at a certain time point t; ΔT stay_m is the minimum rendezvous dwell time; T p is the orbital period of the matching star (here refers to the mission star).

[0111] The ephemeris matching method replaces large-scale numerical search with a semi-analytical method. The results show that this method can quickly and accurately solve the optimal initial value of the maneuvering time of the mission satellite and the optimal task sequence of the candidate target satellite. Its solution efficiency is much higher than that of large-data traversal search methods such as the branch and bound method, which improves the solution efficiency of orbital safety action target selection.

[0112] S4, calculates the results of intelligent rail safety planning, including:

[0113] S41, obtaining spacecraft orbit information, force application rule information, comprehensive intelligence information, mission purpose information and spacecraft dynamic model information as calculation basic information;

[0114] S42, based on the initially selected orbital safety mission target and the calculation basic information, utilize the space target orbital safety intelligent planning algorithm to achieve the coarse-grained task planning results of the spacecraft orbital safety mission; wherein, the coarse-grained task planning results of the spacecraft orbital safety mission are used to determine the mission target, mission purpose and basic plan arrangements for the use of comprehensive forces.

[0115] In this embodiment, S4 includes the training and application of the intelligent agent, mainly the reinforcement learning algorithm to calculate the intelligent agent; the current state of the trained intelligent agent is applied to calculate the comprehensive force combination strategy. The specific calculation steps are as follows:

[0116] (1) Input training data:

[0117] After the calculation is started, the reinforcement learning model is initialized and the training scene data is read, including the task purpose information and task target information in the training scene;

[0118] (2) Training reinforcement learning model:

[0119] Call the reinforcement learning model to perform reinforcement learning training. When the training is completed, that is, when the success rate meets the requirements, generate the trained model parameters;

[0120] (3) Using reinforcement learning model:

[0121] Configure the reinforcement learning model with training parameters, read the current scenario mission purpose information and comprehensive intelligence information, and calculate and generate coarse-grained force application strategies and spacecraft orbit change strategies;

[0122] (4) Output application data

[0123] Organize the task planning data and pass it to the task plan optimization and formulation module according to the format requirements to generate the planning data corresponding to the fine-grained task planning results of S5.

[0124] S5, formulate optimization detailed task strategy, including:

[0125] S51, based on the coarse-grained task planning of completing the spacecraft orbital safety mission, combined with the spacecraft orbital information, calling the satellite dynamics model, and using the global optimization algorithm and the high-precision orbital integration method to perform orbital design and splicing; wherein the global optimization algorithm includes a differential evolution method, and of course, those skilled in the art should know that other differential evolution methods are also within the scope of protection of the present invention;

[0126] S52, optimize the splicing orbit based on the global optimization algorithm, determine the optimal parameters of the transfer orbit, and obtain a fine-grained task planning result.

[0127] In this embodiment, a global optimization algorithm is used to optimize the orbit change strategy and calculate the precise orbit change time point and the corresponding orbit change amount. According to the mission target type, the orbit change requirements are analyzed, and the value search range near the characteristic points such as the perigee, apogee, ascending node, and descending node is set to avoid the problem of excessive calculation caused by blind optimization. A high-precision orbit integration method is used to calculate each transfer orbit containing multiple perturbation factors, and the pulse transfer orbits of each orbit are spliced ​​according to the principle of position continuity and velocity change to construct an overall transfer orbit. The global optimization algorithm is used to optimize the total velocity increment required for the transfer orbit and the weighted sum of the total flight time to obtain the optimal transfer orbit that meets the constraints.

[0128] Among them, the global optimization method can use the differential evolution algorithm to perform iterative optimization calculations. The two basic steps of the global optimization process are as follows:

[0129] (1) Given the initial value of the optimization parameter X0, the objective function is calculated as shown in formula (4):

[0130] J=f(X0) (4)

[0131] (2) Using global optimization algorithm to improve the initial value of parameter X i , calculate the objective function, and perform multiple iterations until the global minimum is found.

[0132] As a preferred embodiment, the method further comprises:

[0133] S6, one-click generation of planning reports and scenario diagrams, including:

[0134] S61, preliminarily evaluating and judging the fine-grained task planning result, if the fine-grained task planning result is feasible, calling the WORD algorithm based on MATLAB, automatically writing and filling the fine-grained task planning result, and forming a planning report with one click;

[0135] S62, based on MATLAB calling the STK algorithm, generates a scene diagram with one click that combines three-dimensional and two-dimensional scenes with task indicator graphics, visually displaying the debris removal process and task completion status.

[0136] In this embodiment, the process of MATLAB calling WORD and STK is as follows:

[0137] (1) Set the Word / STK path

[0138] In the Matlab environment, set the Word / STK calling path to ensure that the program can initialize, open, edit and write Word / STK files;

[0139] (2) Create Word / STK environment

[0140] Program operation opens Word / STK software, returns Word / STK handle and sets the page in accordance with the space mission planning format or sets the scene in accordance with the mission scenario format to meet relevant requirements;

[0141] (3) Write Word / STK content

[0142] According to the space mission planning process, write the content and planning calculation result data in a solidified format, and construct the planning report and the main content of the mission scenario;

[0143] (4) Clean up the Word / STK environment

[0144] After completing the writing of the space mission planning content or the construction of the mission scenario, the program command deletes the Word / STK handle and closes the Word / STK software.

[0145] S1 of this embodiment solves the problem of constructing a spacecraft orbital safety intelligent planning method architecture; S2 solves the problem of analyzing space debris orbital change events; S3 solves the problem of rapid selection of orbital safety action targets; S4 solves the problem of coarse-grained orbital safety intelligent planning; S5 solves the problem of fine-grained task plan optimization and formulation; S6 solves the problem of rapid one-click generation of task scenarios and planning reports.

[0146] A second aspect of the present invention is to provide a spacecraft orbit safety intelligent planning system, comprising:

[0147] Model building module, used to build a spacecraft orbital safety intelligent planning model;

[0148] Orbital change event analysis module, used to analyze orbital change events of space debris;

[0149] Track safety action target selection module, used to quickly select mission targets based on quantified track change events;

[0150] A calculation module is used to calculate the results of intelligent planning for track safety;

[0151] The optimization module is used to formulate detailed optimization task strategies;

[0152] Display module, used to generate planning reports and scenario diagrams with one click.

[0153] The present invention has been successfully applied to the space mission planning system. In the event of a space debris XX approaching the spacecraft YY, the spacecraft orbital safety intelligent planning method of the present invention was used to carry out intelligent mission planning, formulate an action plan, and the action plan adopted for the subsequent action is consistent with the planning plan generated by the algorithm. It takes a total of 4.51 minutes to form an orbital safety intelligent planning report, and a total of 6.35 minutes to form an orbital safety action mission scenario. The calculation accuracy meets the task requirements, which proves the superiority of the spacecraft orbital safety intelligent planning method in calculation accuracy and speed.

[0154] Figure 2 It is a typical result of intelligent planning for rail safety: Figure 2(a) is a schematic diagram of the intention analysis results, describing the change process of the distance and illumination angle indicators during the approach of space debris X to spacecraft Y. It can be seen that spacecraft X will approach spacecraft Y at a close distance in the next few days (the closest distance is 4.37 km, corresponding to an illumination angle of 161.63 degrees), and the illumination conditions can be improved by orbital fine-tuning, so that spacecraft Y is at risk of being photographed; Figure 2 (b) is a schematic diagram of the target selection results, describing the screening results of orbital safety action targets using the hierarchical analysis and ephemeris matching method. It can be seen that the algorithm used can comprehensively consider factors such as mission purpose, mission environment, and target characteristics to achieve rapid and optimal selection of orbital safety action targets (the closest target in the figure is the selected target); Figure 2 (c) is a schematic diagram of the intelligent planning calculation results, describing the coarse-grained results of the spacecraft orbital safety planning. It can be seen that the use of other forces and the spacecraft orbit planning should be carried out alternately to achieve the optimal orbital safety action of multi-force coordination; Figure 2 (d) is a schematic diagram of the transfer strategy results, describing the transfer path of the spacecraft to the space debris. It can be seen that considering the two factors of fuel consumption and transfer time, the spacecraft needs two maneuvers to achieve the optimal transfer; Figure 2 (e) is a schematic diagram of the mission scenario results, which describes the mission scenario results of the spacecraft and space debris conducting orbital safety actions. After completing the above steps, it takes a total of 6.35 minutes to generate the report and mission scenario. The scenario contains all the elements and supports customized scenario display and revision, meeting the needs of visually presenting the mission scenario.

[0155] The present invention also provides a memory storing a plurality of instructions, wherein the instructions are used to implement the method as in the first embodiment.

[0156] like Figure 3 As shown, the present invention also provides an electronic device, including a processor 301 and a memory 302 connected to the processor 301, the memory 302 stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the method as in the first embodiment.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A spacecraft orbital safety intelligent planning method, characterized in that: include: S1, building a rail safety intelligent planning model; S2, analysis of space debris orbit change events; S3, selecting and determining a space debris removal sequence; S4, calculate the results of intelligent planning for track safety; S5, formulate and optimize detailed orbital maneuvering strategies; S6, generate planning reports and scenario diagrams with one click.

2. A spacecraft orbital safety intelligent planning method according to claim 1, characterized in that: The S1 includes: S11, build a spacecraft orbital safety intelligent planning model architecture; S12, establish a spacecraft orbit safety intelligent planning method flow based on the spacecraft orbit safety intelligent planning model architecture.

3. A spacecraft orbital safety intelligent planning method according to claim 2, characterized in that: The S2 includes: S21, based on the spacecraft orbit information and comprehensive intelligence information, using the spacecraft dynamics model, extrapolating and predicting the spacecraft rendezvous event, combining the historical orbit change law of space debris and the partial objective hierarchical analysis method to analyze the space debris orbit change event; the partial objective hierarchical analysis method to analyze the space debris orbit change event includes: (1) Extrapolate the orbits of space debris before and after the orbital change, including: Using a high-precision orbit fast integration method and an automatic step size selection algorithm, combined with the advantages of fast calculation speed of analytical methods and high calculation accuracy of numerical methods, the orbits of space debris before and after orbit changes are extrapolated; (2) Calculate the track change of the splicing point, including: The orbital states of the extrapolated and calculated space debris orbit splicing points are converted into the orbital six-element numbers, and the changes of the orbital six-element numbers are compared and calculated; (3) Analyze orbital change events based on the changes in orbital elements of space debris, including: Determine the change in the number of orbital elements of space debris after the change relative to before the change, and preliminarily analyze the orbital control of space debris based on its control history and control laws; (4) Extrapolating the orbits of both spacecraft to determine the proximity of space debris, including: Parallel extrapolation of multiple spacecraft orbits, comparison of the spatial distance between space debris and spacecraft at each time point, determination of whether the closest distance meets the rendezvous condition, and determination of the orbit change event of space debris accordingly; (5) Using the analytic hierarchy process to determine the target's orbital change events, including: Based on the close proximity of space debris and spacecraft, the orbit change event of space debris target is obtained by using partial objective hierarchical analysis method; S22, quantitatively express the orbit change event, and search for the corresponding response and disposal plan in the case strategy library, so as to provide a prerequisite for the subsequent task determination and rapid selection of task objectives.

4. A spacecraft orbital safety intelligent planning method according to claim 3, characterized in that: The S3 includes: S31, based on the objective information of the spacecraft orbital safety mission, quantitatively expressing the mission objective; S32, based on the analysis results of the orbit change event, using the analytic hierarchy process, combined with the classification and grading information of the mission and importance of space debris in the comprehensive intelligence information, traverse the preliminary possible solutions for dealing with the space debris approach event; S33, based on the preliminary possible solution, using the ephemeris matching method to quickly screen targets or determine target sequences, and selecting orbital safety mission targets based on the targets or target sequences, wherein the calculation process of the ephemeris matching method includes: (1) Find the target star that is closest to the matching star or the mission star at any time node within the mission allowed time period through orbit ephemeris recursion; (2) By comparing the minimum distances at all time nodes, determine the target star closest to the matching star and its corresponding time node within the allowed time period of the entire mission; (3) According to the Lambert characteristic, the target star closest to the matching star is the one with the least transfer energy consumption, thereby determining the optimal launch window initial value and the candidate optimal detection sequence.

5. A spacecraft orbital safety intelligent planning method according to claim 4, characterized in that: The S4 includes: S41, obtaining spacecraft orbit information, force application rule information, comprehensive intelligence information, mission purpose information and spacecraft dynamic model information as calculation basic information; S42, based on the initially selected orbital safety mission target and the calculation basic information, the space target orbital safety intelligent planning algorithm is used to achieve the coarse-grained task planning results of the spacecraft orbital safety mission; wherein the coarse-grained task planning results of the spacecraft orbital safety mission are used to determine the mission target, mission purpose and basic plan arrangements for comprehensive force actions.

6. A spacecraft orbital safety intelligent planning method according to claim 5, characterized in that: The S5 includes: S51, based on the coarse-grained task planning of completing the spacecraft orbital safety mission, combined with the spacecraft orbital information, calling the satellite dynamics model, and using the global optimization algorithm and the high-precision orbital integration method to perform orbital design and splicing; wherein the global optimization algorithm includes a differential evolution method, and of course, those skilled in the art should know that other differential evolution methods are also within the scope of protection of the present invention; S52, optimize the splicing orbit based on the global optimization algorithm, determine the optimal parameters of the transfer orbit, and obtain a fine-grained task planning result.

7. A spacecraft orbital safety intelligent planning method according to claim 6, characterized in that: The S6 includes: S61, preliminarily evaluating and judging the fine-grained task planning result, if the fine-grained task planning result is feasible, calling the WORD algorithm based on MATLAB, automatically writing and filling the fine-grained task planning result, and forming a planning report with one click; S62, based on MATLAB calling the STK algorithm, generates a scene diagram with one click that combines three-dimensional and two-dimensional scenes with task indicator graphics, visually displaying the debris removal process and task completion status.

8. A spacecraft orbital safety intelligent planning system, used to implement any of the methods of claims 1-7, characterized in that: include: Model building module, used to build a spacecraft orbital safety intelligent planning model; Orbital change event analysis module, used to analyze orbital change events of space debris; Track safety target selection module, used to quickly select mission targets based on quantified track change events; A calculation module is used to calculate the results of intelligent planning for track safety; The optimization module is used to formulate detailed optimization task strategies; Display module, used to generate planning reports and scenario diagrams with one click.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a plurality of instructions, and the processor is used to read the instructions and execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the plurality of instructions can be read by a processor to execute the method according to any one of claims 1 to 7.

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