Large-scale curved surface phased array multi-beam scheduling method and system based on subset decomposition

Abstract

The invention discloses a large-scale curved surface phased array multi-beam scheduling method and system based on subset decomposition, and belongs to the field of aircraft measurement and control, and the method comprises the steps: S1, building a satellite measurement and control task set and a task execution interval set; s2, decomposing the measurement and control task into task subsets and scheduling the task subsets; s3, conflict tasks after different task subsets are scheduled are judged, and a conflict task set is formed; s4, further distributing the tasks in the conflict task set, and judging that the tasks cannot be distributed in the conflict task set; and S5, distributing the tasks which cannot be distributed in the next channel, and repeating the steps S2 to S4 until the distribution is completed or the channel is used. According to the method, beams can be reasonably allocated to execute satellite measurement and control tasks, array resource conflicts are reduced, and the multi-beam measurement and control performance of a phased array system is improved.

Description

Technical Field

[0001] The present invention relates to the field of aircraft measurement and control, and more specifically, to a large-scale curved phased array multi-beam scheduling method and system based on subset decomposition. Background Art

[0002] At present, the beam scheduling method of large-scale phased arrays is to schedule the large-scale phased array antenna with N beam synthesis channels equivalent to N parabolic antennas. This simplifies the complexity of beam scheduling, allows the system to use the existing antenna scheduling algorithm, and realizes the rapid integration of equipment into the existing network.

[0003] However, such equivalent processing causes a waste of large-scale phased array resources. At the same time, as the number of aircraft continues to increase, the number of measurement and control tasks gradually increases, which will lead to a shortage of measurement and control resources. Therefore, under the original large-scale spherical array architecture, the design allocates the array element channels of the entire array to different measurement and control targets for a single DBF circuit resource, realizes co-array multi-beam synthesis, and improves the capacity of the phased array measurement and control system. When performing beam scheduling for large-scale satellite constellation measurement and control tasks, considering the mobility of satellites, "empty window sliding" is usually used for target tracking. Therefore, the activation of array elements at different time beams is determined by the visible time window and its corresponding visible arc segment. When tracking multiple targets simultaneously, there will be conflicts in the activation of array elements at certain times, so reasonable beam scheduling is required to improve the system capacity while avoiding conflicts. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a large-scale curved phased array multi-beam scheduling method and system based on subset decomposition, which can reasonably allocate beams to perform satellite measurement and control tasks, reduce array resource conflicts, and improve the multi-beam measurement and control performance of the phased array system.

[0005] The object of the present invention is achieved through the following solutions:

[0006] A large-scale curved phased array multi-beam scheduling method based on subset decomposition comprises the following steps:

[0007] S1. Establish satellite measurement and control task set and task execution interval set;

[0008] S2, decomposing the measurement and control tasks into task subsets and scheduling each task subset;

[0009] S3, determining the conflicting tasks after scheduling different task subsets to form a conflicting task set;

[0010] S4, further assigning tasks in the conflicting task set, and determining that no tasks can be assigned in the conflicting task set;

[0011] S5. Allocate the tasks that cannot be allocated to the next channel, and repeat steps S2 to S4 until the allocation is completed or the channel is used up.

[0012] Furthermore, in step S1, the measurement and control task set specifically includes the following variables: task sequence number, satellite ID, task duration and task execution status.

[0013] Furthermore, in step S1, the task execution interval set specifically includes the following variables: satellite id, satellite model, execution interval, start time, end time and duration.

[0014] Furthermore, in step S1, the variables of the measurement and control task set correspond one-to-one with the variables of the task execution interval set.

[0015] Furthermore, in step S2, decomposing the measurement and control task into task subsets specifically includes the following sub-steps:

[0016] Decompose N satellite tracking and control tasks into task subsets with M tasks in each group. If the number of remaining tasks is less than M, the remaining tasks are grouped together. The specific process includes the following:

[0017] Step 1, calculate the number of complete groups: Where k is the number of complete subsets formed;

[0018] Step 2, calculate the number of remaining tasks: r = Nmod M; where r is the number of remaining tasks; if r = 0, there are no remaining tasks;

[0019] Step 3: If 0<r<M, then these r tasks constitute a separate subset;

[0020]

[0021] Furthermore, in step S2, the scheduling of each task subset specifically includes the following sub-steps:

[0022] After completing the grouping, each subset task is scheduled, and the task satisfaction rate η is measured and controlled. 1 , array element resource utilization rate η 2 , array resource conflict rate η 3 The indicator forms the objective function f = w 1 η 1 +w 2 η 2 -w 3 η 3 , and for each subset a solution is generated that maximizes the objective function:

[0023]

[0024] Furthermore, in step S3, the conflicting tasks specifically include two categories:

[0025] One type is the tasks that conflict and cannot be assigned due to constraints when scheduling task subsets; the other type is the tasks that have been assigned in the task subset and conflict with the remaining subsets under unified judgment; the above conflicting tasks are integrated into the conflicting task set.

[0026] Further, in step S3, the conflicting tasks after scheduling of different task subsets are determined to form a conflicting task set, which specifically includes the following sub-steps:

[0027] The tasks in the conflicting task set are processed and judged pairwise to form conflicting task pairs for subsequent processing.

[0028] Further, in step S4, the step of determining that tasks cannot be assigned in the conflicting task set specifically includes the following sub-steps:

[0029] When allocating, take the conflicting task pairs as the object and judge all the conflicting task pairs in turn, which specifically includes the following process:

[0030] Step 1: Create a reserved task set and a rescheduled task set, both of which are initially empty;

[0031] Step 2: Judge each conflicting task pair in the conflicting task set, loop through all conflicting task pairs, and put the two tasks of the conflicting task pair into the reserved task set and the rescheduled task set respectively: if one of the tasks is already in the reserved set and the other is not in the rescheduled set, put it into the rescheduled set; if there is a task in the rescheduled set that is also in the reserved set, remove the task in the reserved set; the rescheduled task set and the reserved task set can only have one of the tasks of the conflicting task pair, and the tasks already in the two sets will not be put into the rescheduled task set;

[0032] Step 3: After traversing all conflicting task pairs, the final rearrangement set is the unassignable task set.

[0033] A large-scale curved phased array multi-beam scheduling system based on subset decomposition comprises a computer device, a computer program is stored in the memory of the computer device, and when the computer program is loaded by the processor of the computer device, any of the above methods is executed.

[0034] The beneficial effects of the present invention include:

[0035] Under the premise of common-plane multi-beam synthesis, the present invention completes large-scale curved phased array beam scheduling through subset decomposition from the perspective of task allocation, thereby improving the measurement and control system's ability to support measurement and control tasks.

[0036] The present invention aims at common-plane multi-beam synthesis and avoids conflicts between task time and array element activation through subset decomposition from the perspective of task allocation, thereby realizing large-scale curved phased array beam scheduling and improving the multi-beam measurement and control performance of the phased array system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0038] Figure 1 A flowchart of the implementation steps of the method of the embodiment of the present invention;

[0039] Figure 2 Optimize the process flow diagram for conflicting tasks. DETAILED DESCRIPTION

[0040] All features disclosed in all embodiments in this specification, or steps in all methods or processes implicitly disclosed, except for mutually exclusive features and / or steps, can be combined and / or expanded or replaced in any manner.

[0041] The present invention aims to solve the following technical problems: In the scenario of beam scheduling for a large number of tasks under a large-scale curved phased array, due to the large number of tasks and array resources, the conflicts between tasks are complex. A technical solution is proposed to reasonably allocate beams to perform satellite measurement and control tasks, reduce array resource conflicts, maximize task allocation, and improve the multi-beam measurement and control performance of the phased array system, such as Figure 1 As shown, the specific steps include:

[0042] Step A: Establish N satellite measurement and control task sets and all task execution interval sets;

[0043] Step B, decomposing the measurement and control task into task subsets and scheduling each task subset;

[0044] Step C: determine the conflicting tasks after scheduling different task subsets, form a conflicting task set, and form two conflicting task pairs;

[0045] Step D: Determine that the conflicting task set cannot be assigned tasks;

[0046] Step E: Assign the tasks that cannot be assigned to the next channel, and repeat steps B to D until the assignment is completed or the channel is used up.

[0047] Furthermore, the task execution interval set in step A includes variables such as satellite id (satellite_id), satellite model (Source), execution interval (IntervalNumber), start time (StartTime), end time (EndTime) and duration (Duration); the measurement and control task set includes four variables: task number (task_numbe), satellite id (satellite_id), task duration (duration) and task execution status (status), and corresponds one-to-one to the task execution interval set.

[0048] Furthermore, in step B, a method of decomposing the measurement and control tasks into task subsets is as follows: decomposing N satellite measurement and control tasks into task subsets with M tasks in each group. If the number of remaining tasks is less than M, the remaining tasks are grouped together. The specific steps are as follows:

[0049] Count the number of complete groups: Where k is the number of complete subsets that can be formed;

[0050] Calculate the number of remaining tasks: r = N mod M; where r is the number of remaining tasks; if r = 0, there are no remaining tasks;

[0051] If 0<r<M, then these r tasks constitute a separate subset;

[0052]

[0053] Step B schedules each subset task obtained after the grouping is completed, and the scheduling algorithm is not limited here.

[0054] When scheduling, the task satisfaction rate η is measured and controlled. 1 , array element resource utilization rate η 2 , array resource conflict rate η 3 The same index forms the objective function f = w 1 η 1 +w 2 η 2 -w 3 η 3 , and for each subset a solution is generated that maximizes the objective function:

[0055]

[0056] Furthermore, the conflicting tasks in step C are defined as tasks that have conflicts in activating array elements during the overlapping period, which mainly include two categories: one is the tasks that conflict and cannot be assigned according to the constraints when scheduling task subsets; the other is the tasks that have been assigned in the task subset and conflict with the remaining subsets under unified judgment. The above conflicting tasks are integrated into a conflicting task set. Furthermore, the tasks in the conflicting task set are processed and judged in pairs to form conflicting task pairs for subsequent processing.

[0057] Furthermore, step D further allocates the tasks in the conflicting task set to obtain unallocated tasks. When allocating, the conflicting task pairs are taken as the object, and all conflicting task pairs are judged in turn, as follows:

[0058] Step 1: Create a reserved task set (assignable tasks) and a rescheduled task set (non-assignable tasks), both of which are initially empty;

[0059] Step 2: Judge each conflicting task pair in the conflicting task set, that is, loop through all conflicting task pairs and put the two tasks of the conflicting task pair into the reserved task set and the rescheduled task set respectively:

[0060] (1) If one of the tasks is already in the reserved set and the other is not in the rescheduled set, put it into the rescheduled set;

[0061] (2) If a task in the reordered set is also in the reserved set, then the task in the reserved set needs to be removed;

[0062] The reorder set and the reserved set can only contain one of the conflicting task pairs, and tasks already in the two sets will not be added;

[0063] Step 3: After all conflicting task pairs are traversed, the final reordered set is the set of tasks that cannot be assigned. Figure 2 shown.

[0064] In another preferred embodiment of the present invention, a large-scale curved phased array multi-beam scheduling method based on subset decomposition is provided, comprising the following steps:

[0065] Step 1: Based on the Starlink Phase I constellation, establish a satellite tracking and control task set of 400 and a set of all task execution intervals.

[0066] Step 2: Decompose the measurement and control tasks into task subsets: Decompose the measurement and control task set into task subsets with 20 tasks in each group. If the number of remaining tasks is less than 20, the remaining tasks are grouped together:

[0067]

[0068] Finally, the number of initial subsets is 20. The tasks in the subset are scheduled, and beams are allocated to each task based on the task execution time and whether the activated array elements conflict.

[0069] At the same time, set the weight value w 1 =0.2, w 2 =0.4, w 3 =0.2, according to the objective function f=w 1 η 1 +w 2 η 2 -w 3 η 3 , and obtain the optimal beam scheduling results for each subset.

[0070] Step 3: Determine the conflicting tasks after scheduling different task subsets, form a conflicting task set (task_set), and form two conflicting task pairs; for example, there are tasks 1, 2, 3, and 4, and the conflict situation is as shown in Table 1:

[0071] Table 1

[0072] Task 1 2 3 4 1 / conflict conflict conflict 2 conflict / No conflict conflict 3 conflict No conflict / conflict 4 conflict conflict conflict /

[0073] There are 5 conflicting task pairs: task 1-task 2, task 1-task 3, task-task 4, task 2-task 4, and task 3-task 4.

[0074] Step 4: Determine whether the task cannot be assigned in the conflicting task set: Create a reserved task set (index_save) and a rearranged task set (index_rearrage), both of which are initially empty. Use task_num1 and task_num2 to represent the two tasks of the conflicting task pair.

[0075] Loop through all conflicting task pairs, and put the two tasks of the conflicting task pair into the reserved task set and the rescheduled task set respectively; if one of the tasks is already in the reserved set and the other is not in the rescheduled set, put it into the rescheduled set; if there is a task in the rescheduled set that is also in the reserved set, remove the task from the reserved set; the rescheduled set and the reserved set can only have one of the tasks of the conflicting task pair; tasks already in the two sets are no longer added.

[0076] Step 5: Assign the tasks that cannot be assigned to the next channel: reassign the tasks in the rearranged task set as the tasks to be tested, that is, task_set = index_rearrage. If the rearranged task set is not empty, repeat steps 2 to 4; if the rearranged task set is empty, exit the loop.

[0077] Step 6: After all task beam scheduling is completed, according to the objective function f = w 1 η 1+w 2 η 2 -w 3 η 3 The results are as follows:

[0078] Table 2

[0079] Task 1 2 3 4 1 / conflict conflict conflict 2 conflict / No conflict conflict 3 conflict No conflict / conflict 4 conflict conflict conflict /

[0080] Because of w 1 =0.2, w 2 =0.4, w 3 =0.2, so when the measurement and control task satisfaction rate is 1 (that is, all tasks are successfully measured and controlled), the array resource utilization rate is 1 (that is, all array resource are used), and the array resource conflict rate is 0, the objective function f=0.6. From the simulation results, based on the embodiment of the present invention, the objective function can reach 0.6, achieving the goal of zero conflict, and all tasks successfully complete beam scheduling.

[0081] The units involved in the embodiments of the present invention may be implemented by software or hardware, and the units described may also be arranged in a processor. The names of these units do not, in some cases, limit the units themselves.

[0082] According to one aspect of an embodiment of the present invention, a computer program product or a computer program is provided, the computer program product or the computer program includes a computer instruction, and the computer instruction is stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method provided in the above various optional implementations.

[0083] As another aspect, an embodiment of the present invention further provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

Claims

1. A large-scale curved phased array multi-beam scheduling method based on subset decomposition, characterized in that: It includes the following steps: S1. Establish a satellite TT&C task set and a task execution interval set; S2. Decompose the TT&C tasks into task subsets and schedule each task subset; S3. Judge the conflicting tasks after scheduling different task subsets to form a conflicting task set; S4. Further allocate the tasks in the conflicting task set and judge the tasks that cannot be allocated in the conflicting task set; S5. Allocate the tasks that cannot be completed to the next channel, and repeat steps S2 to S4 until the allocation is completed or the channel usage is completed.

2. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 1 is characterized in that: In step S1, the TT&C task set specifically includes the following variables: task serial number, satellite id, task duration, and task execution status.

3. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 1, characterized in that: In step S1, the task execution interval set specifically includes the following variables: satellite id, satellite model, execution interval, start time, end time, and duration.

4. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 1, characterized in that: In step S1, the variables of the TT&C task set correspond one by one to the variables of the task execution interval set.

5. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 1, characterized in that: In step S2, the decomposition of the TT&C tasks into task subsets specifically includes the following sub-steps: Decompose N satellite TT&C tasks into task subsets with M tasks in each group. If the number of remaining tasks in the end is less than M, the remaining tasks form a group. The specific process is as follows: Step 1, calculate the number of complete groups: Where k is the number of complete subsets formed; Step 2. Calculate the number of remaining tasks: r = N mod M; where r is the number of remaining tasks. If r = 0, there are no remaining tasks; Step 3. If 0 < r < M, these r tasks form a separate subset; 6. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 5 is characterized in that: In step S2, the scheduling of each task subset specifically includes the following sub-steps: Schedule each subset task obtained after grouping. Through the TT&C task satisfaction rate η1, array element resource utilization rate η2, and array element resource conflict rate η3 indicators, form an objective function f = w1η1 + w2η2 - w3η3, and generate a solution that maximizes the objective function for each subset; 7. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 1, characterized in that: In step S3, the conflicting tasks specifically include two categories: One category is the tasks that cannot be allocated due to conflicts according to the constraint conditions during the scheduling of task subsets; the other category is the tasks that have been allocated in the task subsets and are in conflict after unified judgment with the rest of the subsets; The above conflicting tasks are integrated into a conflicting task set.

8. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 7 is characterized in that: In step S3, the judgment of the conflicting tasks after scheduling different task subsets to form a conflicting task set specifically includes sub-steps: Process the tasks in the conflicting task set, judge them pairwise to form conflicting task pairs for subsequent processing.

9. The large-scale curved phased array multi-beam scheduling method based on subset decomposition according to claim 1, characterized in that: In step S4, the judgment of the tasks that cannot be allocated in the conflicting task set specifically includes the following sub-steps: When performing allocation, take the conflicting task pairs as objects and judge all conflicting task pairs in turn. The specific process is as follows: Step 1. Create a reserved task set and a rearranged task set, both of which are initially empty; Step 2: Judge each conflicting task pair in the conflicting task set, loop through all conflicting task pairs, and put the two tasks of the conflicting task pair into the reserved task set and the rescheduled task set respectively: if one of the tasks is already in the reserved set and the other is not in the rescheduled set, put it into the rescheduled set; if there is a task in the rescheduled set that is also in the reserved set, remove the task in the reserved set; the rescheduled task set and the reserved task set can only have one of the tasks of the conflicting task pair, and the tasks already in the two sets will not be put into the rescheduled task set; Step 3: After traversing all conflicting task pairs, the final rearrangement set is the unassignable task set.

10. A large-scale curved phased array multi-beam scheduling system based on subset decomposition, comprising a computer device, characterized in that: A computer program is stored in the memory of the computer device, and when the computer program is loaded by the processor of the computer device, the method according to any one of claims 1 to 9 is executed.

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