A cataloging method and system for building multi-target tracking requirements

Abstract

This invention discloses a cataloging method and system for constructing multi-target tracking requirements, relating to the field of space multi-target tracking requirements analysis technology. The method includes: creating a simulation scenario for space multi-target observation and operation; then creating observation tasks based on the simulation scenario, covering various types such as orbit measurement and optical imaging; different observation tasks correspond to different observation equipment, and observation equipment requirement constraints can be set; finally, selecting observation equipment according to the observation tasks, and automatically scheduling resources for the observation equipment according to the observation requirements, including requirement merging, visibility calculation, conflict resolution, and arc segment optimization, and cataloging to form an observation plan for the observation tasks. This invention solves the problems of low accuracy and poor stability in existing multi-target tracking cataloging methods under complex scenarios, improves the performance and reliability of multi-target tracking, and can effectively guide various observation equipment to perform observation and tracking tasks.

Description

Technical Field

[0001] This invention relates to the field of spatial multi-target tracking requirements analysis technology, and in particular to a cataloging method and system for constructing multi-target tracking requirements. Background Technology

[0002] In the fields of space information analysis and spacecraft tracking, telemetry, and command (TT&C), ground station equipment and space surveillance satellites play a crucial role as the number of spacecraft increases. In multi-target tracking, accurate cataloging of multiple targets is fundamental to effective tracking and management. Traditional multi-target tracking cataloging methods often fail to meet the needs of diverse observation tasks. Users cannot simulate observation equipment to track and perform tasks according to their specific requirements, making accurate cataloging difficult and impacting tracking performance.

[0003] Specifically, when it comes to the coordinated tracking of multiple observation devices such as single-target radar, phased array radar, optical imaging and radar imaging, traditional methods are difficult to coordinate the performance parameters and operational constraints of different observation devices, cannot reasonably combine multiple needs such as orbit measurement and optical imaging, and cannot effectively handle problems such as resource conflicts of observation devices and changes in target visibility. This makes the observation plan lack scientific rigor and feasibility, and it is difficult to support efficient multi-target tracking in complex scenarios.

[0004] For example, application number 202310065442.3 discloses a method, device, and storage medium for cataloging and locating space targets based on optical observation. This solution can use mainstream astronomical equipment on the market to achieve target discovery and location, compared to methods that rely on radar systems to identify and locate space targets. However, this solution also has its limitations: it is only designed for optical equipment and cannot be compatible with other equipment such as single-target radar and phased array radar, making it difficult to handle multi-device collaborative tracking scenarios. Furthermore, this solution does not address key aspects such as merging observation requirements and resolving equipment resource conflicts, and it cannot generate a comprehensive observation plan when there are multiple mission requirements such as orbit measurement and radar imaging.

[0005] Therefore, for the cataloging problem of multi-target tracking requirements in complex scenarios, there is an urgent need for a method and system that can improve the accuracy and stability of cataloging, so as to optimize the observation plan and improve the performance and reliability of multi-target tracking. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides a cataloging method and system for constructing multi-target tracking requirements, solving the cataloging problem of multi-target tracking requirements in complex scenarios. By creating an observation task scenario and defining multiple tracking requirements, the multiple requirements of the observation task are merged according to requirement constraints; target visibility is calculated, automatic observation task planning is performed, and an observation plan is generated.

[0007] Firstly, embodiments of the present invention provide a cataloging method for constructing multi-target tracking requirements, including:

[0008] S1. Create a simulation scenario for multi-target observation and operation in space;

[0009] S2. Based on the simulation scenario, create observation tasks;

[0010] S3. Select observation equipment based on the observation task, and automatically schedule the resources of the observation equipment according to the observation requirements of the observation task, and catalog to form an observation plan for the observation task.

[0011] In one embodiment of the present invention:

[0012] Observation mission types include: orbit measurement, optical imaging, radar imaging, and airspace search;

[0013] The types of observation equipment include: precision tracking radar, phased array radar, optical imaging observation equipment, and radar observation equipment;

[0014] Matching observation task type with observation equipment type includes:

[0015] The type of observation equipment used for orbit measurement is precision tracking radar and / or phased array radar;

[0016] The type of observation equipment corresponding to optical imaging is optical imaging observation equipment;

[0017] The type of observation equipment corresponding to radar imaging is radar observation equipment;

[0018] The type of observation equipment corresponding to the airspace search is phased array radar.

[0019] In one embodiment of the present invention, step S3, which involves automatic resource scheduling during the observation period of the observation equipment, includes the following steps:

[0020] S31. Merge multiple observation requirements in the observation task;

[0021] S32. Calculate the visibility of the target for each observation device;

[0022] S33. Statistical observation visibility quantity and observation tracking period;

[0023] S34. Automatically plan the observation equipment and observation targets in the observation task and resolve conflicts;

[0024] S35. Optimize the observation arcs after conflict resolution and output the observation plan.

[0025] In one embodiment of the present invention, when performing demand merging in S31, the following is included:

[0026] Merge observations based on their priority;

[0027] The constraints are merged based on the observation requirements.

[0028] In one embodiment of the present invention, the conflict resolution in S34 includes immediate conflict resolution or continuous conflict resolution.

[0029] In one embodiment of the present invention, the parameters for conflict resolution include the quality of the observed arc segment, the target priority, and the number of visible target tracks, and corresponding parameter weights are set.

[0030] In one embodiment of the present invention, the parameters for optimizing the observation arc include the observation plan duration, the quality of the observation arc, and the load of the observation equipment, and corresponding parameter weights are set.

[0031] The second aspect: a cataloging system for constructing multi-target tracking requirements, including:

[0032] The scene creation module supports users in creating or importing simulation scenes for multi-target observation in space.

[0033] The task creation module provides options for selecting observation task types and generates observation tasks with constraints.

[0034] The requirement merging module is used to merge multiple observation requirements according to priority and constraints to generate a preliminary observation plan.

[0035] The visibility calculation module is used to calculate the visibility of the observation equipment to the target during the observation period and to identify potential conflict points;

[0036] The conflict resolution module is used to resolve conflicts, make weighted decisions on parameters, and schedule observation equipment resources.

[0037] The arc segment optimization module is used to verify and output the observation plan, and to catalog the observation plan;

[0038] The plan output and monitoring module is used to visualize the output of the observation plan.

[0039] Third aspect: An electronic observation device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of, for example, the method provided in the first aspect.

[0040] 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, for example, the method provided in the first aspect.

[0041] The beneficial effects of this invention are:

[0042] 1. This invention effectively solves the problems of low cataloging accuracy and poor stability of existing methods in complex scenarios by creating simulation scenarios, formulating multiple tracking requirements, merging observation task requirements according to requirement constraints, and combining target visibility calculation with automatic observation task planning. It can more accurately catalog observation tasks for multiple targets, laying a solid foundation for subsequent tracking and management.

[0043] 2. The method and system of this invention support various needs such as orbit measurement, optical imaging, radar imaging, and airspace search. Different needs can correspond to different observation equipment, allowing users to set constraints on observation equipment requirements, such as minimum elevation angle and tracking duration. This enables users to flexibly create and combine observation tasks according to their own observation mission requirements, satisfying multi-demand observation mission scenarios and overcoming the limitations of traditional methods that cannot adapt to multi-demand observation missions.

[0044] 3. This invention generates a reasonable final observation plan by automatically planning observation tasks, including conflict resolution and arc segment optimization. The conflict resolution mechanism ensures efficient utilization of observation equipment resources, avoiding overlapping observation tasks and resource waste; arc segment optimization further improves the feasibility and effectiveness of the observation plan, enabling observation equipment such as optical equipment, phased array radar, and single-target radar to efficiently execute their respective tracking observation tasks, thereby improving the overall performance and reliability of multi-target tracking.

[0045] 4. This invention supports scene creation and import. Users can build simulation scenes according to their own needs, and simulate observation equipment to track observation tasks. This makes it easier to verify and adjust the observation tasks before actual execution, reducing tracking errors caused by unreasonable observation task planning and improving the success rate of observation task execution. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating the cataloging method of the present invention;

[0047] Figure 2 This is a schematic diagram illustrating the cataloging method of the present invention.

[0048] Figure 3 This is a schematic diagram of the resource scheduling process of the present invention;

[0049] Figure 4 A schematic diagram of the requirement interface is created for an embodiment of the present invention;

[0050] Figure 5 This is a schematic diagram of the interface required for merging in an embodiment of the present invention;

[0051] Figure 6 This is a schematic diagram of the visibility analysis interface according to an embodiment of the present invention:

[0052] Figure 7This is a schematic diagram of the automatic planning interface according to an embodiment of the present invention;

[0053] Figure 8 The figure shown is a schematic diagram of the output observation plan interface according to an embodiment of the present invention;

[0054] Figure 9 This is a schematic diagram of the list-style output observation plan interface according to an embodiment of the present invention;

[0055] Figure 10 This is a schematic diagram of the cataloging system of the present invention;

[0056] Figure 11 This is a schematic diagram of the structure of the electronic device of the present invention. Detailed Implementation

[0057] 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.

[0058] Traditional multi-target tracking cataloging methods suffer from low accuracy and poor stability in complex scenarios, failing to effectively handle tracked targets. They cannot meet the needs of multi-target observation tasks, preventing users from simulating equipment tracking tasks according to their own requirements, hindering accurate cataloging, and impacting tracking performance.

[0059] To address the above problems, this invention provides a cataloging method and system for constructing multi-target tracking requirements. Figure 2 The flowchart illustrates the principle of the cataloging method for constructing multi-target tracking requirements provided in this embodiment of the invention.

[0060] Example 1:

[0061] This embodiment discloses a cataloging method for constructing multi-target tracking requirements, for example... Figure 1 As shown, the steps include:

[0062] S1. Create a simulation scenario for multi-target observation and operation in space.

[0063] Simulation scenario parameters can include: start time, end time, satellite targets (including low Earth orbit, medium Earth orbit, and high Earth orbit) and ground observation equipment (including precision tracking radar, phased array radar, and optical equipment). Scenario import is also supported.

[0064] S2. Based on the simulation scenario, create observation tasks.

[0065] The observation tasks include a variety of requirements such as orbit measurement, optical imaging, radar imaging, and airspace search, meeting the diverse observation needs of users; the types of observation equipment include: precision tracking radar, phased array radar, optical imaging observation equipment, and radar observation equipment.

[0066] Different observation equipment has equipment constraints on observation requirements, including minimum elevation angle, tracking duration, number of ascent orbits, and number of descent orbits.

[0067] The resulting observation tasks and corresponding observation equipment types are shown in Table 1, for example:

[0068] Table 1. Table of Observation Equipment Types Corresponding to Task Types

[0069]

[0070] As can be seen from Table 1, different observation tasks, such as orbit measurement, optical imaging, radar imaging, and airspace search, correspond to specific types of observation equipment, and each observation equipment has clear parameter constraints.

[0071] For example, orbit measurement and observation tasks can be undertaken by precision tracking radar (elevation range 3-90 degrees, tracking range 40,000 km) and phased array radar (azimuth range -60-60 degrees, elevation range 3-90 degrees, etc., number of tracked targets ≤50); optical imaging observation tasks correspond to optical imaging observation equipment, which has unique constraints such as solar altitude angle and ground shadow; radar imaging observation tasks are handled by radar observation equipment; and airspace search and observation tasks are adapted to phased array radar (elevation range -90-90 degrees, etc., number of tracked targets ≤100).

[0072] These correspondences and observation equipment parameters provide a foundation for subsequent observation task scheduling, resource allocation, and conflict resolution. This ensures that observation tasks are accurately matched with the capabilities of the observation equipment, guaranteeing the feasibility and effectiveness of the observation tasks. It also facilitates the rapid selection of suitable observation equipment based on observation needs in the multi-target tracking cataloging process, thus promoting the cataloging of observation plans from creation to implementation.

[0073] S3. Select observation equipment based on the observation task, and automatically schedule the resources of the observation equipment according to the observation requirements of the observation task, and catalog to form an observation plan for the observation task.

[0074] Based on the type of observation task, matching observation equipment is selected. Observation equipment resources are automatically allocated based on the constraints of the observation task (e.g., tracking duration, elevation angle range, target priority) and the capabilities of the observation equipment (e.g., tracking distance, maximum number of targets tracked). Finally, the scheduling results are integrated to output an observation plan containing the observation equipment, target, and time window, clearly defining when each observation equipment tracks which target and the observation conditions that must be met, providing clear guidance for observation execution.

[0075] Example 2:

[0076] Building upon Example 1, this example discloses a cataloging method for constructing multi-target tracking requirements, optimizing the automatic resource scheduling process in observation tasks. Specifically, for example... Figure 3 As shown, the steps include:

[0077] First, the multiple observation requirements in the observation mission are merged.

[0078] One observation task can correspond to multiple observation requirements, such as the observation requirement for a target area of ​​XX within a certain time period. Different observation requirements may correspond to different observation equipment.

[0079] Based on the observation needs, the required observation equipment for different time periods and different observation areas is merged, and the resulting observation plan can be regarded as a preliminary observation plan.

[0080] The initial observation plan may have conflicting requirements regarding time periods and observation targets, which could affect its implementation.

[0081] Observational needs can be merged based on their priority and / or on the constraints they impose, thus enabling efficient scheduling of observational tasks. For example, some observational needs may have higher priority and need to be met first, while other needs can be scheduled as resources allow.

[0082] Meanwhile, constraints on observation requirements, such as observation time, observation angle, and observation equipment, can also serve as a basis for merging, ensuring that the merged observation plan can meet the requirements of all observation needs, while avoiding resource and time conflicts and improving the execution efficiency and accuracy of observation tasks.

[0083] Then, the visibility of the target to be observed by each observation device is calculated separately.

[0084] To effectively resolve conflicts, the visibility of each observation device to the target during the observation period is calculated to identify potential conflict points. Conflicts may arise from overlapping needs of multiple observation devices for the same target within the same time period, or from the inability of the observation devices to meet specific observation requirements.

[0085] Then, the number of observations and the observation tracking period were statistically analyzed.

[0086] The statistical analysis of the number of observation visibilitys and the observation tracking period is for the purpose of more precise management of observation resources. The number of times each observation device is visible to the observation target within a specific time period reflects the availability of the observation device during that time period.

[0087] Then, the system automatically plans the observation equipment and targets in the observation task and resolves conflicts.

[0088] The conflict type is determined, and conflict resolution includes immediate conflict resolution or continuous conflict resolution. Conflict resolution parameters include the quality of the observed arc segment, target priority, and the number of visible target tracks, and corresponding parameter weights are set.

[0089] The quality of the observation arc refers to the effectiveness of the observation equipment for the observation period of the target, such as the integrity of the arc and the lighting conditions; the target priority refers to the ranking of the observation targets according to the importance of the observation task; the visible target tracking number is the maximum number of targets that the observation equipment can stably track per unit time.

[0090] Immediate conflict refers to a situation where the same observation equipment is assigned multiple target observation tasks simultaneously, leading to resource contention and requiring immediate handling. Immediate conflict resolution applies to resource contention at the same point in time, and the steps include:

[0091] The system monitors the observation task assignment of observation equipment in real time. When an observation device is assigned ≥2 targets in the same time period, an immediate conflict is triggered.

[0092] By calculating the observation arc quality score for each conflict observation task (e.g., 10 points for a complete arc and 3 points for a broken arc); and the target priority (e.g., the target for an emergency observation task is set to level 5, and the target for a normal observation task is set to level 2); the number of currently visible observation targets tracked by the observation equipment is confirmed (e.g., when the number of targets that a single target radar can currently track is 1, a new observation task is considered a conflict).

[0093] The weighted comprehensive score is calculated as follows: Comprehensive score = (segment quality score × weight 1) + (target priority × weight 2) + ((rated number of tracks - current number of tracks) × weight 3). Then, the observation task with the highest comprehensive score is retained, and the remaining observation tasks are marked as pending assignment and transferred to other idle observation equipment or processed later.

[0094] Continuous conflict refers to the overlap in the observation tasks of observation equipment within consecutive time periods. For example, the next observation task has started before the previous one has ended, requiring an overall adjustment of the time period.

[0095] Continuous conflict resolution addresses overlapping observation tasks within consecutive time periods, requiring overall optimization of the time window, including:

[0096] Traverse the observation task list of the observation equipment and identify consecutive observation tasks that overlap in time (e.g., the end time of observation task A > the start time of observation task B).

[0097] Evaluate the arc quality of each observation task within the overlapping period (e.g., the smaller the overlap, the higher the quality score); sort by target priority (observation tasks with higher priority are retained in the core period); and calculate the theoretical maximum number of tracks by the observation equipment during the conflict period.

[0098] If an observation task with a high overall score can be split, divide it into multiple sub-time periods, avoiding overlap. If an observation task cannot be split, discard the observation task with the lower overall score, or postpone its start time until the previous observation task has finished. After adjustment, check the continuity of time periods again to ensure that no new conflicts arise.

[0099] Finally, the observation arcs are optimized based on the results after conflict resolution, and an observation plan is output.

[0100] After conflict resolution, the rationality of the observation plan and the utilization rate of the observation equipment are further improved through observation arc optimization, ultimately outputting a clear and executable observation plan. Observation arc optimization parameters include observation plan duration, observation arc quality, and observation equipment load, with corresponding parameter weights set. This includes:

[0101] Arc segment optimization is based on the conflict-resolved observation task list. Its goals are to eliminate invalid observation periods, merge redundant arc segments, and improve the tracking efficiency of observation equipment. The basis for this optimization includes:

[0102] Observation equipment parameter constraints, such as the minimum elevation angle of precision tracking radar and the azimuth range of phased array radar; observation mission requirement constraints, such as tracking duration ≥ 5 minutes, number of orbital ascent / descent, and other user-defined constraints; target visibility: only retain the effective visible period of the target by the observation equipment (excluding cases where the ground shadow or solar altitude angle is not met).

[0103] After resolving conflicts, traverse the observation task arcs and eliminate time periods that do not meet the constraints: if the lowest elevation angle of a certain arc is lower than the observation equipment threshold, delete the arc directly. If the arc duration is shorter than the minimum tracking duration set by the user, mark it as invalid and discard it. For optical imaging observation tasks, exclude time periods where the solar elevation angle is <-9 degrees or the ground shadow is true.

[0104] Preferably, for continuous visible periods of the same observation equipment and the same observation target, if the interval is ≤30 minutes, they are merged into a complete arc segment to reduce the switching loss of the observation equipment. For excessively long arc segments (e.g., exceeding the continuous working limit of the observation equipment), they are split according to the fatigue threshold of the observation equipment (e.g., phased array radar is split once every 2 hours of continuous operation, with an interval of 10 minutes) to avoid overloading the observation equipment.

[0105] Preferably, the retained arc segments are sorted, prioritizing high-quality arc segments; arc segments during the target's overhead transit period (highest elevation angle, best observation accuracy) are prioritized. For multiple arc segments of the same target, they are sorted from highest to lowest according to the observed arc segment quality score, and the top 3-5 optimal arc segments are retained, adjusted according to the load of the observation equipment.

[0106] After arc segment optimization, the observation plan display format includes: grouped by observation equipment, listing the tracking time periods for each target in sequence (e.g., attached). Figure 9 The output table style of the final observation plan interface is available, and Excel download is supported. The visual interface displays the observation task schedule for each observation device on a timeline, using different colors to indicate arc type (e.g., attached). Figure 8 As shown, green represents the effective arc segment, visually presenting the load on the observation equipment.

[0107] Preferably, a verification and adjustment mechanism for the observation plan is implemented, with a final verification performed before output. This includes: checking whether there are still unresolved conflicts among the observation equipment during the same time period; calculating the total observation task duration for each observation equipment to ensure it does not exceed its working time limit; and automatically triggering supplementary planning if the number of effective arc segments for a certain target is less than the user's requirements, searching for available observation equipment in the adjacent time period.

[0108] Through the above steps, the arc-segment optimized observation plan can not only meet the constraints of the observation equipment and the target, but also maximize the utilization of observation resources. The final output plan can be directly used to guide optical equipment, phased array radar and other observation equipment to perform tracking observation tasks.

[0109] The above methods optimize the automatic resource scheduling in observation tasks, enabling multi-dimensional and full-process intelligent management, and effectively solving the problems of resource conflicts and low efficiency in multi-target tracking and cataloging in complex scenarios.

[0110] Example 3:

[0111] Based on the method of Embodiment 1 or 2, this embodiment also discloses a cataloging system for constructing multi-target tracking requirements, such as... Figure 10 As shown, the system includes a scene creation module, a task creation module, a requirement merging module, a visibility calculation module, a conflict resolution module, an arc optimization module, and a plan output and monitoring module, among which:

[0112] The scenario creation module supports users in creating or importing multi-target space observation simulation scenarios, configuring start and end times, satellite target (Low Earth Orbit / Medium Earth Orbit / High Earth Orbit), and ground observation equipment (precision tracking radar, phased array radar, etc.) parameters. The system supports batch importing satellite target orbit data (including the six elements of orbit) and ground observation equipment deployment parameters (latitude and longitude, observation equipment type) from Excel. Satellite orbits and observation equipment deployment locations can be marked on 2D / 3D maps, intuitively displaying the simulation scenario coverage area.

[0113] like Figure 4 As shown, the task creation module is used to provide the selection of observation task types (orbit measurement, optical imaging, etc.), associate observation equipment constraints, and generate observation tasks with constraints.

[0114] After the system selects the observation task type (e.g., optical imaging), it automatically loads the constraints of the optical imaging observation equipment, and users can also add custom constraints; when creating an observation task, it checks for resource conflicts of the observation equipment in real time.

[0115] like Figure 5 As shown, the requirement merging module is used to merge multiple observation requirements according to priority and constraints to generate a preliminary observation plan.

[0116] The system provides a visual configuration of priorities (e.g., levels 1-5) and constraints (e.g., time / angle / observation equipment, etc.). Users can customize merging strategies (e.g., prioritize merging high-priority observation tasks with the same observation equipment); it displays the changes in the number of observation tasks and the occupancy rate of observation equipment before and after merging, assisting users in deciding whether to adopt the merging scheme.

[0117] like Figure 6 As shown, the visibility calculation module is used to calculate the visibility of the target to the observation equipment during the observation period and to identify potential conflict points.

[0118] The system is based on spherical geometry and satellite orbit prediction simulation models to calculate the visible time period of the target for the observation equipment (including constraints such as elevation angle, ground shadow, and sunlight); it displays the risk of conflict between observation equipment using a time axis or heat map and marks the number of conflicting observation tasks.

[0119] like Figure 7 As shown, the conflict resolution module is used to distinguish between immediate and continuous conflicts, and makes weighted decisions based on parameters such as arc quality and target priority to schedule observation equipment resources.

[0120] The system allows users to set the weights of arc quality, target priority, and the number of visible target tracks; it can also record the resolution history of conflict observation tasks, which facilitates troubleshooting.

[0121] The arc segment optimization module is used to remove invalid arc segments, merge or split redundant arc segments, verify and output the observation plan, and realize the cataloging of the observation plan.

[0122] Based on the continuous working threshold of the observation equipment, the system can automatically split excessively long arc segments; identify and merge continuous arc segments with an interval of ≤30 minutes, without any manual intervention throughout the process; and display the quality score of each arc segment in a bar chart to help select the optimal arc segment.

[0123] The planning output and monitoring module can output observation plans in tables and visual interfaces, and supports verification, adjustment and execution monitoring.

[0124] like Figure 9 As shown, the system can generate an Excel observation plan (including observation equipment, targets, time periods, and constraints), and can also display observation tasks on a timeline, such as... Figure 8 As shown, it connects to the control system of the observation equipment to obtain the execution status of the observation tasks in real time, and automatically triggers rescheduling of failed observation tasks.

[0125] This system is fully automated, from scenario creation to plan output, requiring no manual intervention and significantly reducing manpower. Based on quantitative parameters and weighted decision-making, the accuracy of conflict resolution is improved. It supports dynamic adjustments during the execution of observation tasks and automatically triggers replanning, making it highly valuable for application.

[0126] The present invention also provides an electronic observation device. Figure 11 This is a schematic diagram of the structure of an electronic observation device provided in an embodiment of the present invention, for example... Figure 11 As shown, the electronic observation device may include a processor, a communication interface, a memory, and a communication bus. The processor, communication 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:

[0127] S1. Create a simulation scenario for multi-target observation and operation in space;

[0128] S2. Based on the simulation scenario, create observation tasks;

[0129] S3. Select observation equipment based on the observation task, and automatically schedule the resources of the observation equipment according to the observation requirements of the observation task, and catalog to form an observation plan for the observation task.

[0130] 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 monitoring device (which may be a personal computer, server, or network monitoring 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.

[0131] 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:

[0132] S1. Create a simulation scenario for multi-target observation and operation in space;

[0133] S2. Based on the simulation scenario, create observation tasks;

[0134] S3. Select observation equipment based on the observation task, and automatically schedule the resources of the observation equipment according to the observation requirements of the observation task, and catalog to form an observation plan for the observation task.

[0135] 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.

[0136] 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., including several instructions to cause a computer observation device (which may be a personal computer, server, or network observation device, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cataloging method for constructing multi-target tracking requirements, characterized in that, Including the following steps: S1. Create a simulation scenario for multi-target observation and operation in space; S2. Create observation tasks based on simulation scenarios; S3. Select observation equipment based on the observation task, and automatically schedule the resources of the observation equipment according to the observation requirements of the observation task, and catalog them to form an observation plan for the observation task. Observation mission types include: orbit measurement, optical imaging, radar imaging, and airspace search; The types of observation equipment include: precision tracking radar, phased array radar, optical imaging observation equipment, and radar observation equipment; Matching observation task type with observation equipment type includes: The type of observation equipment used for orbit measurement is precision tracking radar and / or phased array radar; The type of observation equipment corresponding to optical imaging is optical imaging observation equipment; The type of observation equipment corresponding to radar imaging is radar observation equipment; The type of observation equipment corresponding to the airspace search is a phased array radar; The automatic resource scheduling in S3 during the observation period of the observation equipment includes the following steps: S31. Merge multiple observation requirements in the observation task; S32. Calculate the visibility of the target for each observation device; S33. Statistical observation visibility quantity and observation tracking period; S34. Automatically plan the observation equipment and observation targets in the observation task and resolve conflicts; S35. Optimize the observation arcs based on the results after conflict resolution and output the observation plan; The conflict resolution in S34 includes immediate conflict resolution or continuous conflict resolution; The parameters for conflict resolution include the quality of the observed arc segment, target priority, and number of visible target tracks, and corresponding parameter weights are set. The parameters for optimizing the observation arc include the observation plan duration, the quality of the observation arc, and the load on the observation equipment, and corresponding parameter weights are set. Among them, instant conflict resolution includes: the system monitors the observation task arrangement of observation equipment in real time, and when a certain observation equipment is assigned to more than or equal to two targets in the same time period, an instant conflict is triggered. Calculate the observation arc quality score and target priority for each conflict observation task, and confirm the number of currently visible observation targets tracked by the observation equipment; The overall score is calculated by weighting, and the observation task with the highest overall score is retained. The remaining observation tasks are marked as pending assignment and transferred to other idle observation equipment or processed later. Continuous conflict resolution includes: traversing the observation task list of the observation equipment to identify consecutive observation tasks that overlap in time; evaluating the arc quality of each observation task within the overlapping period; sorting by target priority; and calculating the theoretical maximum number of tracks that the observation equipment can track during the conflict period. If the observation task with the higher overall score can be split, it should be divided into multiple sub-time periods to avoid overlap. If the observation task cannot be split, the observation task with the lower overall score should be discarded, or its start time should be postponed until the previous observation task has ended. After adjustment, the continuity of time periods should be checked again to ensure that no new conflicts arise.

2. The method according to claim 1, characterized in that, When performing requirement merging in S31, the following is included: Merge observations based on their priority; The constraints are merged based on the observation requirements.

3. A cataloging system for constructing multi-target tracking requirements, characterized in that, The method according to any one of claims 1 to 2, comprising: The scene creation module supports users in creating or importing simulation scenes for multi-target observation in space. The task creation module provides options for selecting observation task types and generates observation tasks with constraints. The requirement merging module is used to merge multiple observation requirements according to priority and constraints to generate a preliminary observation plan. The visibility calculation module is used to calculate the visibility of the observation equipment to the target during the observation period and to identify potential conflict points; The conflict resolution module is used to resolve conflicts, make weighted decisions on parameters, and schedule observation equipment resources. The arc segment optimization module is used to verify and output the observation plan, and to catalog the observation plan; The plan output and monitoring module is used to visualize the output of the observation plan.

4. An electronic observation device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of, for example, the method of any one of claims 1 to 2.

5. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method, for example, any one of claims 1 to 2.

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