Autonomous cooperative continuous low-thrust high-orbit target orbital transfer approaching method, system and equipment and medium

Abstract

The invention discloses an autonomous cooperative continuous low-thrust high-orbit target orbital transfer approaching method, system and device and a medium, and the method comprises the steps: obtaining the orbital parameters of a service satellite and a target satellite in real time, and judging the approaching type; automatically starting an on-satellite autonomous decision-making mode by the on-satellite computer, and adjusting constraint parameters of the electric propulsion system; on the basis of the approaching type and the adjusted constraint parameters, a multi-dimensional optimization model is constructed, and an optimized orbital transfer strategy is calculated according to the dynamic allocation weight; the orbital transfer strategy is executed, and the service satellite carries out an orbital transfer approaching task. The autonomous level of the system is improved through an on-satellite autonomous task planning module and an autonomous decision triggering mechanism. The system can be switched to an autonomous mode to complete approaching type judgment and multi-constraint strategy calculation and execution, and real-time dependence on ground measurement and control is avoided. The problem of high-orbit communication delay is solved, the quick response requirements of emergency tasks such as emergency observation and on-orbit disposal are met, and the independent survival and task completion capabilities of the system in a complex space environment are enhanced.

Description

Technical Field

[0001] This invention relates to the field of orbit control technology for high-orbit spacecraft, and in particular to an autonomous, cooperative, continuous low-thrust method, system, equipment, and medium for orbit change and approach to high-orbit targets, which can be applied to space missions such as satellite on-orbit servicing, space target observation, and emergency response to faulty satellites. Background Technology

[0002] Orbit maneuvering and approach technology for high-orbit satellites (such as geostationary orbit and geosynchronous orbit satellites) is a core supporting technology for realizing on-orbit space services. Continuous low-thrust orbit maneuvering technology has become one of the mainstream technical approaches for high-orbit target approach missions due to its advantages such as high fuel utilization efficiency and stable thrust output.

[0003] Currently, there are some related technical solutions in this field. For example, existing invention application CN113636106A discloses a method and system for approaching high-orbit targets with continuous low thrust. This technical solution divides the high-orbit target approach scenarios into three categories: coplanar, non-planar with small inclination angle, and non-planar with large inclination angle, and designs corresponding orbit-changing strategies for different types, thus achieving high-orbit approach in continuous low thrust mode to a certain extent. However, this technology still has obvious limitations in practical engineering applications and in meeting the needs of complex tasks, mainly in the following aspects:

[0004] (1) Lack of autonomous decision-making capability. Relying on the ground to complete the inclination vector calculation, approach type judgment and strategy solution, when faced with sudden situations such as ground communication delay or ground station offline, the orbit change is passive and waiting, which cannot meet the emergency mission requirements such as emergency observation of faulty satellites; (2) Limited adaptability to multiple constraints. A multi-objective collaborative optimization mechanism has not been formed. The core is still to minimize fuel consumption as the primary goal. There is a lack of dynamic balance design for the key energy constraints (conflict between solar power supply and propulsion working period), attitude constraints (thrust direction blocks the field of view of observation payload) and time constraints (differentiated requirements between emergency and conventional approach) of high-orbit satellites; (3) Lack of dynamic obstacle avoidance mechanism. The interference risk of high-orbit space debris and other satellites is not covered. There are more than 3,000 trackable targets (including abandoned satellites and debris) in the geosynchronous orbit area. There are many orbital intersection points when approaching at large inclination angles, and the probability of collision is significantly increased; (4) Single scene adaptability. The design strategy is only for general high-orbit targets and cannot meet the needs of specific scenarios such as geostationary satellite fixed-point drift correction and multi-target cooperative approach; (5) Performance evaluation closed loop is missing. There is no quantitative evaluation mechanism for orbit change effect, so it is impossible to determine whether indicators such as fuel efficiency and approach accuracy meet the standards, and it is also difficult to support subsequent strategy optimization.

[0005] In addition, other related technologies, such as invention application document CN115072007A, disclose an all-electric propulsion orbit transfer method based on autonomous mission planning. Although this method improves the ability of satellites to autonomously execute missions, it does not specifically optimize the classification characteristics of different orbit configurations (coplanar, non-coplanar, etc.) in high-orbit approach missions. The targeting and efficiency of its strategy still have room for improvement in high-orbit approach scenarios.

[0006] Therefore, existing technologies lack a comprehensive solution for continuous low-thrust approach maneuvers to high-orbit targets that can simultaneously consider autonomous decision-making, multi-constraint balancing, dynamic obstacle avoidance, scenario expansion, and performance evaluation. Thus, a new technological solution is needed to overcome these shortcomings and improve the autonomy, efficiency, safety, and adaptability of high-orbit approach missions. Summary of the Invention

[0007] To address the aforementioned problems, the present invention aims to provide an autonomous and collaborative continuous low-thrust high-orbit target maneuvering approach method, system, equipment, and medium. This addresses the lack of comprehensive solutions for autonomous decision-making, multi-constraint balancing, dynamic obstacle avoidance, scenario expansion, and performance evaluation in existing high-orbit target continuous low-thrust maneuvering approach processes, thereby improving the autonomy, efficiency, safety, and adaptability of high-orbit approach missions.

[0008] This invention provides an autonomous, collaborative, continuous low-thrust high-orbit target maneuvering approach method, system, equipment, and medium.

[0009] First aspect: A method for autonomous, coordinated, continuous low-thrust approach to a high-orbit target using orbital maneuvering, including:

[0010] S1. Obtain the orbital parameters of the service satellite and the target satellite in real time, calculate the inclination vector adjustment based on the orbital parameters, and make a preliminary judgment on the approach type;

[0011] S2. The onboard computer monitors orbital parameter deviations and ground command status in real time. When preset trigger conditions are met, it automatically starts the onboard autonomous decision-making mode and dynamically adjusts the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the service satellite.

[0012] S3. Based on the approach type and adjusted constraint parameters, a multi-dimensional optimization model including fuel efficiency, energy matching degree, attitude compatibility and time compliance rate is constructed. The optimized orbit change strategy is obtained by solving the dynamically allocated weights.

[0013] S4. Execute the orbit change strategy and perform the orbit change approach mission.

[0014] In one embodiment of the present invention, it further includes:

[0015] Before executing the orbit change strategy, the real-time detection data of the service satellite is integrated with the pre-stored obstacle database on the ground to identify obstacles on the orbit change path and classify them by risk. Based on the risk level, the original orbit change strategy is maintained, fine-tuned, or replanned.

[0016] In one embodiment of the present invention, identifying obstacles on the trajectory change path and classifying their risks includes:

[0017] Low risk: Maintain the original strategy and record the obstacle positions;

[0018] Medium risk: Fine-tuning the operating phase angle of the electric propulsion system;

[0019] High risk: Suspend the original strategy, calculate the emergency obstacle avoidance trajectory, calculate the obstacle avoidance deviation after avoiding the obstacle, re-determine the approach type, and calculate a new trajectory change strategy.

[0020] In one embodiment of the present invention, it further includes:

[0021] After the orbital maneuver and approach mission is completed, a quantitative assessment report is generated, and the assessment results are stored and downloaded to the ground database.

[0022] In one embodiment of the present invention, the evaluation report evaluates one or more of the following indicators: fuel efficiency, approach accuracy, time compliance rate, and obstacle avoidance success rate. If an indicator fails to meet the standard, the report automatically backtracks to analyze the cause and generates optimization suggestions.

[0023] In one embodiment of the present invention, the optimized trajectory-changing strategy obtained in S3 based on dynamically allocated weights includes:

[0024] When approaching each other on the same plane, an in-plane phasing strategy is adopted. If it is an emergency mission, the weight of time target achievement rate is increased and the weight of fuel efficiency is increased.

[0025] When approaching at a small tilt angle, the orbital plane is adjusted first, and then the phase adjustment within the orbital plane is performed. During the adjustment process, the attitude-thrust linkage algorithm is used to ensure that the angle between the thrust direction and the field of view of the observation camera is greater than 90° to avoid load obstruction.

[0026] When approaching at a large inclination angle, the approach should be carried out at the ascending / descending intersection point, and the solar illumination angle should be predicted simultaneously to avoid the shadow area of ​​the geosynchronous orbit.

[0027] In one embodiment of the present invention, the trajectory-changing strategy further includes a scenario-based sub-strategy, comprising:

[0028] For the scenario of fixed-point drift correction of geostationary satellites, the small-step iterative phase-tuning strategy is invoked to decompose a single orbit change into multiple small-thrust operations;

[0029] For emergency observation scenarios of faulty satellites, the multi-orbit rendezvous sub-strategy is invoked to plan subsequent rendezvous observation windows when a single rendezvous observation is not completed.

[0030] For multi-target cooperative approach scenarios, the orbital plane clustering algorithm is used to group the targets, and the continuous phase modulation strategy is used to approach the targets on the same orbital plane in sequence.

[0031] The second aspect: an autonomous, cooperative, continuous low-thrust high-orbit target maneuvering and approach system, comprising:

[0032] The onboard navigation module is used to acquire the orbital parameters of the service satellite and the target satellite in real time.

[0033] The onboard autonomous mission planning module calculates the inclination vector adjustment based on the acquired orbital parameters to preliminarily determine the approach type;

[0034] The onboard computer module is equipped with a computer system for real-time monitoring of orbital parameter deviations and ground command status. When preset trigger conditions are met, it automatically starts the onboard autonomous decision-making mode and dynamically adjusts the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the serving satellite.

[0035] The multi-objective optimization module, connected to the onboard computer, is used to construct a multi-dimensional optimization model and solve the multi-constraint cooperative orbit change strategy by dynamically assigning weights based on the approach type and adjusted constraint parameters.

[0036] The dynamic obstacle avoidance module is used to integrate real-time detection data from the service satellite with a pre-stored obstacle database on the ground before the orbit change is performed, identify obstacles on the orbit change path and classify their risks.

[0037] The performance evaluation module is used to generate a quantitative evaluation report after the orbit change mission is completed.

[0038] Third aspect: An electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, performs the steps of the method provided in the first aspect.

[0039] Fourth aspect: A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect.

[0040] The beneficial effects of this invention are:

[0041] 1. This invention significantly enhances the system's autonomy through an onboard autonomous mission planning module and an autonomous decision-making triggering mechanism. When sudden changes in the target satellite's orbit or ground command timeouts occur, the system can immediately switch to autonomous mode, independently completing approach type determination, multi-constraint strategy calculation and execution, completely eliminating real-time dependence on ground telemetry and control. This effectively overcomes the passive waiting problem caused by high-orbit communication delays, reducing orbit change response time from hours to minutes or even less. It can meet the rapid response requirements for emergency tasks such as emergency observation and on-orbit handling of runaway satellites and other targets, greatly enhancing the system's independent survival and mission completion capabilities in complex space environments.

[0042] 2. This invention overcomes the limitations of existing technologies that focus solely on fuel conservation by constructing a multi-dimensional optimization model encompassing fuel, energy, attitude, and time. The system dynamically allocates weights based on mission urgency, energy status, and payload requirements, achieving collaborative optimization across multiple objectives. This enables the system not only to save fuel but also to intelligently balance energy supply and demand, ensure continuous payload operation, and meet differentiated time requirements, thereby comprehensively improving mission efficiency under complex constraints. It is particularly suitable for energy-sensitive, long-cycle, high-orbit missions with heavy observation workloads. It achieves dynamic balance across multiple constraints and optimizes mission efficiency.

[0043] 3. This invention constructs a multi-layered safety protection system for high-orbit approach missions by introducing a dynamic obstacle avoidance module and a scenario-based sub-strategy library, and expands its application scenarios. The dynamic obstacle avoidance mechanism can identify and hierarchically avoid obstacles such as space debris based on satellite-ground fusion data, significantly reducing the risk of collisions. Simultaneously, dedicated sub-strategies designed for specific scenarios such as fixed-point drift correction, emergency observation, and multi-target collaboration enable the system to flexibly and efficiently respond to diverse on-orbit service needs. This combination of safety and scenario adaptability ensures a high mission success rate, promotes the practical and intelligent development of high-orbit operation technology, and enhances space safety and mission scenario adaptability. Attached Figure Description

[0044] Figure 1 This is a schematic flowchart of the method of the present invention;

[0045] Figure 2 This is a schematic diagram of the system structure of the present invention;

[0046] Figure 3 This is a schematic diagram of the structure of the electronic device of the present invention. Detailed Implementation

[0047] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar symbols denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0048] Existing methods for approaching high-orbit targets by maneuvering have problems such as low autonomous decision-making ability, poor adaptability to multiple constraints, poor dynamic obstacle avoidance mechanism, and limited adaptability to a single scenario.

[0049] To address the aforementioned problems, this invention discloses an autonomous, collaborative, continuous low-thrust high-orbit target maneuvering approach method. To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with specific embodiments.

[0050] Example 1:

[0051] This embodiment discloses an autonomous, cooperative, continuous low-thrust high-orbit target maneuvering approach method, such as... Figure 1 As shown, the steps include:

[0052] S1. Obtain the orbital parameters of the service satellite and the target satellite in real time, calculate the inclination vector adjustment based on the orbital parameters, and make a preliminary judgment on the approach type.

[0053] Using the onboard navigation module, the orbital parameters of the target satellite and the service satellite are collected in real time. The orbital parameters include inclination i, right ascension of the ascending node Ω, semi-major axis a, eccentricity e, argument of perigee ω, mean perigee angle M, and mean motion n.

[0054] The velocity increment required for tilt vector adjustment is calculated using the onboard autonomous mission planning module, with the relevant method referring to the method disclosed in invention application document CN115072007A, to preliminarily determine the approach type (coplanar / non-planar small tilt angle / non-planar large tilt angle).

[0055] S2. The onboard computer monitors orbital parameter deviations and ground command status in real time. When preset trigger conditions are met, it automatically activates the onboard autonomous decision-making mode and dynamically adjusts the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the serving satellite.

[0056] The onboard computer monitors orbital parameter deviations and ground command status in real time. When the target satellite's orbital deviation exceeds a certain threshold or the ground command times out for a certain period of time, the autonomous decision-making mode is automatically activated.

[0057] Meanwhile, the electric propulsion constraint parameters are dynamically adjusted based on the output power of the solar array and the remaining propellant. For example, when the remaining fuel is less than a certain threshold, the fuel-efficient algorithm is used first, and when the energy reserve is less than a certain amount, the propulsion working period is adjusted to a sufficiently sunny range with a suitable solar altitude angle.

[0058] Furthermore, if the deviation between the autonomous calculation result and the pre-stored strategy on the ground is greater than a threshold, a dual-algorithm verification can be triggered, simultaneously calling the nonlinear programming algorithm and the newly added fast greedy algorithm, and executing the algorithm with the smallest deviation.

[0059] S3. Based on the approach type and adjusted constraint parameters, a multi-dimensional optimization model is constructed, which includes fuel efficiency, energy matching degree, attitude compatibility and time compliance rate. The optimized orbit change strategy is obtained by solving the dynamically allocated weights.

[0060] The multi-objective optimization module constructs a multi-dimensional optimization model of "fuel efficiency, energy matching degree, attitude compatibility, and time achievement rate".

[0061] Scenario adaptation is achieved through dynamic weight allocation, for example:

[0062] When approaching each other on the same plane, an in-plane phase adjustment strategy is adopted. If it is an emergency mission (transfer time ≤ 24 hours), the weight of time compliance rate is increased and the weight of fuel efficiency is increased.

[0063] When approaching at a small tilt angle, the orbital plane is adjusted first, and then the phase adjustment within the orbital plane is performed. During the adjustment process, the attitude-thrust linkage algorithm is used to ensure that the angle between the thrust direction and the field of view of the observation camera is greater than 90° to avoid load obstruction.

[0064] When approaching at a large inclination angle, the approach should be carried out at the ascending / descending intersection point, and the solar illumination angle should be predicted simultaneously to avoid the shadow area of ​​the geosynchronous orbit.

[0065] S4. Execute the orbit change strategy and perform the orbit change approach mission.

[0066] Based on the acquired optimized orbit-changing strategy, the service satellite executes an orbit-changing approach mission. Its propulsion system continuously outputs small thrusts according to the planned thrust magnitude, direction, and timing sequence in the strategy. The service satellite's orbital parameters and attitude information are monitored in real time and compared with the target orbit and desired attitude. A closed-loop control algorithm is used to finely correct the thrust output and attitude adjustments to compensate for deviations caused by orbital perturbations, execution errors, and other factors, ensuring that the service satellite can approach the target satellite accurately and stably along the predetermined trajectory.

[0067] Throughout the orbit change and approach phase, the service satellite maintains necessary communication with the ground station or other satellites in the cooperating constellation, reports the mission execution status in a timely manner, and receives possible instruction updates.

[0068] Furthermore, when the satellite encounters complex scenarios such as multiple obstacles, it triggers satellite-ground collaborative calculations. The satellite sends key parameters such as orbital deviation and remaining fuel to the ground. The ground combines global debris distribution data to calculate and optimize strategies. In response to geostationary orbit communication delays, it generates pre-action commands through orbital trend prediction to compensate for command lag errors.

[0069] Example 2:

[0070] Based on Example 1, this embodiment integrates real-time detection data from the service satellite with a pre-stored obstacle database on the ground before executing the orbit change strategy. It identifies obstacles on the orbit change path and performs risk classification. Based on the risk level, it maintains, fine-tunes, or re-plans the original orbit change strategy.

[0071] Specifically, obstacles on the trajectory change path are identified and risk-classified, including: low risk: maintain the original strategy and record the obstacle position; medium risk: fine-tune the working phase angle of the electric propulsion system; high risk: suspend the original strategy, calculate the emergency obstacle avoidance trajectory, calculate the obstacle avoidance deviation after avoiding the obstacle, re-determine the approach type and calculate the new trajectory change strategy.

[0072] Based on the risk level, dynamic obstacle avoidance and strategy backtracking are implemented. When the risk is determined to be low, the service satellite maintains the original orbit change strategy while recording the precise three-dimensional coordinates, velocity vector and estimated orbital drift of the obstacle in real time to the on-board obstacle log library and marking it as a potential target of concern. During subsequent orbit change processes, it is continuously tracked and observed by on-board sensors to update its dynamic parameters.

[0073] When the risk level is determined to be medium, a phase angle fine-tuning command is sent to the electric propulsion system to cause a slight shift in the actual thrust direction. This allows the service satellite's center of mass trajectory to deviate from the obstacle collision envelope by at least 500 meters without significantly changing the total orbit change time and fuel consumption.

[0074] When a high-risk condition is identified, the service satellite triggers an emergency braking procedure, suspending the execution of the original orbit change strategy. Simultaneously, the onboard high-performance processor is activated to calculate an emergency obstacle avoidance trajectory. This trajectory uses the current position and velocity as initial conditions and is constrained by maintaining a safe encounter distance of no less than 500 meters from the obstacle. A temporary avoidance path is generated, and the electric propulsion system is controlled to perform maneuvers according to the obstacle avoidance path. The service satellite calculates the position and velocity deviations introduced by the obstacle avoidance maneuver through the orbit parameter comparison module and uses these deviations as the new initial state. The approach type judgment module is called again to determine the most suitable approach type. Based on the continuous low-thrust orbit optimization model, a new orbit change strategy including thrust magnitude, direction, and action time sequence is recalculated, completing the strategy backtracking process. This ensures that the service satellite can return to the main mission orbit for approaching the target satellite after avoiding the risk.

[0075] Example 3:

[0076] Based on embodiment 1 or 2, this embodiment further includes a scenario-based sub-strategy for the trajectory-changing strategy. Specifically, the scenario-based sub-strategy includes:

[0077] For geostationary satellite point-to-point drift correction scenarios, a small-step iterative phase-tuning strategy is employed to decompose a single orbit change into multiple small-thrust operations.

[0078] The thrust magnitude of each operation is dynamically adjusted based on the target satellite's drift rate, orbital inclination deviation, and the longitude difference between the current orbit and the target's fixed position. Fine-grained correction of the orbital phase is achieved through multiple rounds of small-step propulsion, avoiding the adverse effects of a single large thrust adjustment on satellite attitude stability and fuel consumption. During propulsion, the relative position vector and velocity vector between the service satellite and the target satellite are acquired in real time, and the orbital parameters are predicted and compensated using the orbital perturbation model to ensure the execution accuracy of each phase adjustment operation.

[0079] For emergency observation scenarios of faulty satellites, a multi-orbit rendezvous sub-strategy is invoked to plan subsequent rendezvous observation windows if a single rendezvous observation is not completed.

[0080] By adjusting the orbital period difference between the service satellite and the target satellite through orbital maneuvers, periodic intersection opportunities are created during their subsequent orbital operations. In practice, key observation parameters, such as the target satellite's spin period, antenna pointing, and solar panel deployment status, are first determined based on the target satellite's failure mode. These parameters then define the key tasks for each intersection observation. Immediately after the first intersection observation, the acquired observation data is rapidly processed to assess the target satellite's stability and failure evolution trends. Combined with the orbital prediction model, the time, location, and relative distance of the next optimal observation window are calculated.

[0081] During multiple rendezvous cycles, the space environment parameters of the target star, such as the distribution of space debris and the intensity of solar activity, are continuously monitored. By introducing an environmental risk coefficient to correct the priority of the observation window, priority is given to ensuring the completion of the observation tasks of key fault parameters in a low-risk environment. Ultimately, a complete observation data chain covering the fault evolution process of the target star is formed, providing accurate data support for subsequent fault diagnosis and rescue plan formulation.

[0082] For multi-target cooperative approach scenarios, the orbital plane clustering algorithm is used to group the targets, and the continuous phase modulation strategy is used to approach the targets on the same orbital plane in sequence.

[0083] By sharing orbital parameters during phasing, fuel consumption redundancy is reduced when targets in the same group approach each other. Orbital plane similarity is calculated based on parameters such as the target star's orbital inclination and right ascension of the ascending node. Targets with orbital plane differences less than a preset threshold are grouped into the same cluster, ensuring that targets within the cluster have similar orbital characteristics.

[0084] For the first approaching target within the cluster, initial phasing is completed through continuous small thrusts, establishing a predetermined relative distance between the target star and the target. When transferring to the next target in the same orbital plane, only the thrust direction and duration need to be finely adjusted, utilizing the residual orbital kinetic energy from the previous phasing to achieve efficient energy utilization.

[0085] An optimization model for target approach sequences within a cluster is established, with the dual objective functions of minimizing total fuel consumption and shortening approach time. The sequence is ordered by combining target priority weights to avoid fuel waste caused by frequent orbital changes. For target clusters in different orbital planes, an orbital plane precession control strategy is adopted. By continuously adjusting the orbital inclination or right ascension of the ascending node of the serving satellite with small thrusts, orbital plane matching is gradually achieved. During this process, the fuel cost and time cost of orbital plane transitions are dynamically evaluated to select the optimal cluster approach sequence, ensuring the maximization of the overall efficiency of the multi-target collaborative mission.

[0086] Example 4:

[0087] Based on Examples 1, 2, or 3, this embodiment generates a quantitative evaluation report after the orbital maneuvering and approach mission is completed, and stores and downloads the evaluation results to the ground database.

[0088] Specifically, the evaluation report assesses one or more of the following indicators: fuel efficiency, approach accuracy, time compliance rate, and obstacle avoidance success rate. If an indicator fails to meet the standard, the report automatically backtracks to analyze the reasons and generates optimization suggestions.

[0089] Fuel efficiency assessment quantitatively analyzes the rationality of fuel utilization by comparing the difference between actual fuel consumption and theoretical minimum fuel consumption, combined with the fluctuation coefficient of thrust output and the number of orbit corrections during orbit change. Approach accuracy assessment uses the final relative position error and attitude alignment deviation between the service satellite and the target satellite as core parameters, and determines the accuracy level of the approach mission by comparing it with preset thresholds. Time achievement rate assesses the timeliness of mission execution by calculating the ratio of actual approach time to planned time, combined with the time deviation distribution of key orbit change nodes. Obstacle avoidance success rate is calculated by statistically analyzing the proportion of successful avoidance of obstacles such as space debris and other spacecraft during orbit change, and analyzing the impact of avoidance maneuvers on overall mission efficiency.

[0090] When any indicator fails to meet the preset standard, the system automatically retrieves raw data from the orbit change process, including thrust output logs, orbit parameter change curves, attitude adjustment records, and external environmental interference data. Through data correlation analysis and anomaly location, the system traces the specific steps that caused the indicator to fail to meet the standard. Based on the analysis results, it generates targeted optimization suggestions, such as adjusting the calibration cycle of the propulsion system, optimizing the curvature distribution of the orbit change trajectory, correcting the proportional, integral, and differential parameters of the control algorithm, or updating the trigger threshold for obstacle avoidance decisions. The suggestions, along with the evaluation report, are fed back to the ground system to provide data support for strategy optimization in subsequent missions.

[0091] Example 5:

[0092] This embodiment discloses an autonomous and cooperative continuous low-thrust high-orbit target maneuvering and approach system. Based on the system of this embodiment, the methods of embodiments 1, 2, 3 or 4 can be implemented.

[0093] like Figure 2 As shown, the specific system includes: a spaceborne navigation module, a spaceborne autonomous mission planning module, a spaceborne computer module, a multi-target optimization module, a dynamic obstacle avoidance module, and a performance evaluation module, etc.

[0094] The onboard navigation module is used to acquire orbital parameters of the service satellite and the target satellite in real time, including inclination i, right ascension of the ascending node Ω, semi-major axis a, eccentricity e, argument of perigee ω, mean perigee M, and mean motion n, etc. It dynamically corrects the orbital parameters through inter-satellite links or ground telemetry and control data to ensure the real-time performance and accuracy of the orbital data, providing basic data support for subsequent mission planning and control decisions.

[0095] The onboard autonomous mission planning module, connected to the onboard navigation module, calculates the required velocity increment for inclination vector adjustment based on the acquired orbital parameters, and preliminarily determines the approach type, which includes coplanar approach, non-planar small inclination approach, and non-planar large inclination approach.

[0096] For example, when the orbital inclination difference between the service satellite and the target satellite is less than or equal to 5°, it is determined to be a coplanar approach. In this case, the approach is mainly achieved by adjusting coplanar orbital parameters such as the semi-major axis and eccentricity. When the orbital inclination difference is greater than 5° but less than or equal to 15°, it is determined to be a non-coplanar small inclination approach. While adjusting the coplanar parameters, it is necessary to make small-amplitude inclination vector adjustments through continuous small thrusts. When the orbital inclination difference is greater than 15°, it is determined to be a non-coplanar large inclination approach. This type of approach requires prioritizing the use of continuous small thrusts to complete a larger-amplitude change in the inclination vector in order to gradually reduce the orbital plane difference and lay the foundation for subsequent coplanar parameter adjustments.

[0097] The onboard computer module is equipped with a computer system and is connected to the onboard autonomous mission planning module. It is used to monitor orbital parameter deviations and ground command status, and automatically triggers the autonomous decision-making mode when preset conditions are met.

[0098] Simultaneously, the electric propulsion constraint parameters are dynamically adjusted based on the output power of the solar array and the remaining propellant. When the remaining fuel is less than a certain threshold, the fuel-efficient algorithm is prioritized. When the energy reserve is less than a certain amount, the propulsion working period is adjusted to a sufficiently sunny interval with a suitable solar altitude angle.

[0099] Furthermore, if the deviation between the onboard autonomous calculation result and the pre-stored strategy on the ground exceeds a threshold, a dual-algorithm verification is triggered, simultaneously calling the nonlinear programming algorithm and the newly added fast greedy algorithm, and executing the strategy with the smallest deviation.

[0100] The multi-objective optimization module, connected to the onboard computer, is used to construct a multi-dimensional optimization model that integrates fuel efficiency, energy matching degree, attitude compatibility and time achievement rate, and solves the multi-constraint cooperative orbit change strategy through dynamic weight allocation according to the approach type and mission requirements.

[0101] The multi-objective optimization module constructs a multi-dimensional optimization model of fuel efficiency, energy matching degree, attitude compatibility, and time compliance rate, and achieves scenario adaptation through dynamic weight allocation.

[0102] When approaching each other on the same plane, an in-plane phase adjustment strategy is adopted. If it is an emergency mission (transfer time ≤ 24 hours), the weight of time compliance rate is increased and the weight of fuel efficiency is increased.

[0103] When approaching at a small tilt angle, the orbital plane is adjusted first, and then the phase adjustment within the orbital plane is performed. During the adjustment process, the attitude-thrust linkage algorithm is used to ensure that the angle between the thrust direction and the field of view of the observation camera is greater than 90° to avoid load obstruction.

[0104] When approaching at a large inclination angle, the approach should be carried out at the ascending / descending intersection point, and the solar illumination angle should be predicted simultaneously to avoid the shadow area of ​​the geosynchronous orbit.

[0105] The dynamic obstacle avoidance module connects to the multi-target optimization module and the onboard computer module.

[0106] The dynamic obstacle avoidance module is used to integrate the space debris database on the ground with the real-time detection data of the onboard radar before the orbit change is performed, to identify obstacles on the orbit change path and to classify the risks.

[0107] The dynamic obstacle avoidance module performs corresponding operations based on the risk level, including maintaining the original strategy and recording the position for low-risk obstacles, fine-tuning the working phase angle of electric propulsion for medium-risk obstacles, and pausing the original strategy, calculating the emergency obstacle avoidance trajectory, and re-planning the approach after avoiding high-risk obstacles.

[0108] The performance evaluation module, connected to the onboard computer module, is used to generate a quantitative evaluation report after the orbit change mission is completed. The evaluation report indicators include at least fuel efficiency, approach accuracy, time target achievement rate, and obstacle avoidance success rate.

[0109] The performance evaluation module is also used to automatically backtrack and analyze the reasons when the indicators fail to meet the standards and generate optimization suggestions. The evaluation report is stored and downloaded to the ground database.

[0110] Furthermore, the system also includes a scenario-based policy library, which stores sub-policies corresponding to specific task scenarios.

[0111] The onboard computer module calls the corresponding sub-strategy from the scenario-based strategy library according to the current mission scenario. The specific mission scenario includes at least one of geostationary satellite fixed-point drift correction, emergency observation of faulty satellites, and multi-target cooperative approach.

[0112] The sub-strategy for correcting the point drift of geostationary satellites is a small-step iterative phasing strategy, which decomposes a single orbit change into multiple small-thrust operations; the sub-strategy for emergency observation of faulty satellites is a multi-orbit rendezvous strategy, which plans the next rendezvous observation window at preset intervals when the current rendezvous observation is not completed; the sub-strategy for multi-target cooperative approach includes an orbital plane clustering algorithm, which clusters target stars with inclination vector differences less than a second preset threshold into the same orbital plane group, and adopts a continuous phasing strategy for targets within the same orbital plane group.

[0113] Furthermore, the onboard computer module is also configured to: trigger a space-ground collaborative calculation mode when encountering complex scenarios with multiple obstacles superimposed, and send the service satellite's orbital deviation and remaining fuel key parameters to the ground station; receive optimization strategies calculated by the ground station in combination with global debris distribution data, the optimization strategies including pre-action instructions generated based on orbital trend predictions to compensate for command lag errors caused by geostationary orbit communication delays.

[0114] Example application:

[0115] Taking the coordinated close-in observation mission of a geostationary orbit service satellite for three faulty satellites as an example, satellite A is a stationary drifting satellite (close-in distance ≤ 10km), satellite B is an out-of-control tumbling satellite (requiring emergency observation, transfer time ≤ 24 hours), and satellite C is in the same orbital plane as satellite A (inclination vector difference < 0.3°).

[0116] Input data includes:

[0117] Service satellite orbital parameters: semi-major axis 42164km, inclination 0.1°, eccentricity 0.001; orbital root counts and space debris database for target satellites A / B / C (providing location information for obstacles with diameters >10cm); service satellite has 25% remaining fuel and a solar array output power of 1500W.

[0118] Implementation process:

[0119] Orbit parameter acquisition and preliminary judgment: The onboard navigation module collects data and determines that satellites A and C are coplanar targets, and satellite B is a small-inclination target with different planes;

[0120] Autonomous decision-making trigger: Because satellite B is an emergency mission, the autonomous decision-making mode is automatically activated, and the fuel-time balance algorithm is adopted based on the remaining fuel.

[0121] Multi-constraint solution: The weight of the satellite B mission time compliance rate is set to 60%, the propulsion working period is adjusted to the range of solar altitude angle > 15°, and the attitude-thrust linkage ensures that the camera field of view is unobstructed;

[0122] Dynamic obstacle avoidance: A medium-risk obstacle (0.8km away) was detected near the orbit of satellite B. The propulsion phase angle was adjusted by +5° to avoid it.

[0123] Scenario-based sub-strategy invocation: Satellite A adopts small-step iterative phase adjustment (8 small-thrust operations), Satellite B adopts multi-orbit rendezvous (2 intersection observations), and Satellite C adopts continuous phase adjustment (fine-tuning the phase angle after Satellite A completes its approach).

[0124] Performance evaluation: An evaluation report is generated, showing that fuel efficiency, approach accuracy, time compliance rate, and obstacle avoidance success rate all meet the threshold requirements.

[0125] Output result:

[0126] Within the planned hours, the service satellite completed close-in observations of three target satellites. After drift correction, the stationary deviation of satellite A decreased. Satellite B acquired images of the tumbling state. Satellite C provided complete observation data, and the evaluation report was transmitted to the ground database.

[0127] The present invention also provides an electronic device, Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 3 As shown, the electronic device may include a processor, a communications interface, memory, and a communication bus, wherein the processor, communications interface, and memory communicate with each other via the communication bus. The processor can invoke logical instructions from the memory, for example, to execute the following method:

[0128] S1. Obtain the orbital parameters of the service satellite and the target satellite in real time, calculate the inclination vector adjustment based on the orbital parameters, and make a preliminary judgment on the approach type;

[0129] S2. The onboard computer monitors orbital parameter deviations and ground command status in real time. When preset trigger conditions are met, it automatically starts the onboard autonomous decision-making mode and dynamically adjusts the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the service satellite.

[0130] S3. Based on the approach type and adjusted constraint parameters, a multi-dimensional optimization model including fuel efficiency, energy matching degree, attitude compatibility and time compliance rate is constructed. The optimized orbit change strategy is obtained by solving the dynamically allocated weights.

[0131] S4. Execute the orbit change strategy and perform the orbit change approach mission.

[0132] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0133] This invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the methods provided in the above embodiments, including, for example:

[0134] S1. Obtain the orbital parameters of the service satellite and the target satellite in real time, calculate the inclination vector adjustment based on the orbital parameters, and make a preliminary judgment on the approach type;

[0135] S2. The onboard computer monitors orbital parameter deviations and ground command status in real time. When preset trigger conditions are met, it automatically starts the onboard autonomous decision-making mode and dynamically adjusts the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the service satellite.

[0136] S3. Based on the approach type and adjusted constraint parameters, a multi-dimensional optimization model including fuel efficiency, energy matching degree, attitude compatibility and time compliance rate is constructed. The optimized orbit change strategy is obtained by solving the dynamically allocated weights.

[0137] S4. Execute the orbit change strategy and perform the orbit change approach mission.

[0138] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0139] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An autonomous cooperative continuous low-thrust high-orbit target orbit transfer and proximity approach method, characterized in that, Comprise: S1, real-time acquisition of the orbit parameters of the service satellite and the target satellite, calculation of the inclination vector adjustment amount based on the orbit parameters, and preliminary determination of the approaching type; S2, real-time monitoring of the orbit parameter deviation and the ground command state by the on-board computer, automatic start of the on-board autonomous decision mode when the preset triggering condition is met, and dynamic adjustment of the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the service satellite; S3, construction of a multi-dimensional optimization model including fuel efficiency, energy matching degree, attitude compatibility and time compliance rate based on the approaching type and the adjusted constraint parameters, and obtaining of the optimized orbit transfer strategy based on the dynamically allocated weights; S4, execution of the orbit transfer strategy and execution of the orbit transfer approaching task.

2. The method of claim 1, wherein, Further comprise: Before executing the orbit transfer strategy, fusion of the real-time detection data of the service satellite and the pre-stored obstacle database on the ground, identification of the obstacles on the orbit transfer path and risk grading, and maintenance, fine tuning or re-planning of the original orbit transfer strategy according to the risk level.

3. The method of claim 2, wherein, Identification of the obstacles on the orbit transfer path and risk grading comprise: Low risk: maintain the original strategy and record the obstacle position; Medium risk: fine tune the electric propulsion system working phase angle; High risk: suspend the original strategy, calculate an emergency obstacle avoidance orbit, avoid the obstacle, re-determine the approaching type and calculate a new orbit transfer strategy.

4. The method of claim 1, wherein, Further comprise: After the completion of the orbit transfer approaching task, generate a quantitative evaluation report and store the evaluation results for transmission to the ground database.

5. The method of claim 4, wherein, The evaluation report evaluates one or more indicators of fuel efficiency, approaching accuracy, time compliance rate and obstacle avoidance success rate, and automatically traces back to analyze the reasons and generates optimization suggestions if the indicators do not meet the requirements.

6. The method of claim 1, wherein, The obtaining of the optimized orbit transfer strategy based on the dynamically allocated weights in S3 comprises: For coplanar approaching, adopt the in-plane phase adjustment strategy, and if it is an emergency task, increase the time compliance rate weight and the fuel efficiency weight; For out-of-plane small inclination approaching, first perform orbit plane adjustment, and then perform in-plane phase adjustment, and during the adjustment process, use the attitude-thrust linkage algorithm to make the thrust direction and the observation camera field of view angle > 90° to avoid load shielding; For out-of-plane large inclination approaching, select the ascending / descending intersection point for approaching, simultaneously predict the sunlight angle and avoid the shadow area of the geosynchronous orbit.

7. The method of claim 6, wherein, The orbit transfer strategy further comprises scenario-based sub-strategies, including: For the stationary orbit satellite fixed-point drift correction scenario, call the small-step iterative phase adjustment sub-strategy to divide the single orbit transfer into multiple small-thrust operations; For the emergency observation scenario of the failed satellite, call the multi-circle intersection sub-strategy to plan the subsequent intersection observation window when the single intersection observation is not completed; For the multi-target cooperative approaching scenario, use the orbit plane clustering algorithm to group the targets, and use the continuous phase adjustment sub-strategy to sequentially approach the targets on the same orbit plane.

8. The method according to any one of claims 1 to 7, characterized in that, An autonomous and cooperative continuous small-thrust high-orbit target orbit transfer approaching system, comprising: An on-board navigation module for real-time acquisition of the orbit parameters of the service satellite and the target satellite; An on-board autonomous task planning module for calculation of the inclination vector adjustment amount based on the acquired orbit parameters and preliminary determination of the approaching type; The satellite computer module is configured with a computer system for real-time monitoring of orbital parameter deviation and ground command state, and when a preset trigger condition is met, automatically starts the on-board autonomous decision mode, and dynamically adjusts the constraint parameters of the electric propulsion system according to the real-time energy and fuel constraints of the service satellite; The multi-target optimization module is connected with the satellite computer and is used for constructing a multi-dimensional optimization model and solving a multi-constraint cooperative orbit transfer strategy through dynamic weight distribution according to the approaching type and the adjusted constraint parameters; The dynamic obstacle avoidance module is used for fusing real-time detection data of the service satellite and a ground pre-stored obstacle database before orbit transfer execution, identifying obstacles on the orbit transfer path and performing risk grading; The performance evaluation module is used for generating a quantitative evaluation report after the orbit transfer task is completed.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the steps of the method of any one of claims 1 to 7. 10.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

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