Multi-station and multi-satellite TT&C resource scheduling optimization method and system under complex constraints

Abstract

The present invention relates to a multi-station multi-satellite measurement and control resource scheduling optimization method and system under complex constraint conditions. The optimization method obtains task information and arc information within the scheduling period according to forecasts, equipment attribute tables, task attribute tables, satellite attribute tables and task planning tables, and constructs task matching sets, arc matching sets and arc conflict sets according to the task information and arc information, calculates arc priority and task priority, selects the task with the smallest arc allocation priority and the arc with the smallest task priority corresponding to it, and allocates the selected arc to the selected task to generate a measurement and control resource scheduling plan. The present invention, by classifying and sorting various constraint conditions, introduces measurement and control task measurement and control arc matching sets, measurement and control arc conflict sets, and measurement and control arc task matching sets, starts from the global optimum, obtains the best measurement and control resource allocation and scheduling plan through simple data calculation, and has high resource allocation efficiency.

Description

Technical Field

[0001] The present invention relates to the field of aerospace measurement and control technology, and in particular to a method and system for optimizing multi-station and multi-satellite measurement and control resource scheduling under complex constraint conditions. Background Art

[0002] Due to the fact that satellites are constantly orbiting the Earth and the measurement and control range of their equipment, satellite tracking and prediction determine the "time window" for ground stations to measure and control satellites. For medium and low orbit satellites, this window period is about a few minutes. In the early days of space activities, there were very few satellites in orbit, so it was not difficult to allocate and dispatch ground equipment to serve different satellites. However, with the maturity of space technology, the number of satellites in orbit currently ranges from dozens to hundreds or even thousands. In this case, how to effectively allocate and dispatch limited ground measurement and control equipment is to solve the optimization combination problem under multiple constraints.

[0003] The difficulty of the problem lies in that with the increase in the number of satellites in orbit, the "observation arcs" between satellites will inevitably overlap. Since the "measurement and control" of satellites must be carried out within the "time window" that can be observed and controlled, the overlap of observation arcs between different satellites will inevitably cause "measurement and control conflicts". Therefore, during the measurement and control cycle of more than ten days, how to allocate and schedule dozens or even hundreds of measurement and control equipment according to the measurement and control mission needs of each satellite has always been a difficult problem because it involves the optimization combination of huge amounts of data. In the aerospace field, this problem is usually called the Satellite Measurement and Control Resource Scheduling (SatelliteTT$C Resource Scheduling) problem, referred to as the STRS problem. Summary of the invention

[0004] In order to solve the technical problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a multi-station and multi-satellite measurement and control resource scheduling optimization method and system under complex constraints, which has the characteristics of simple optimization method, easy implementation and good optimization effect.

[0005] To achieve the above-mentioned object of the invention, the present invention provides a multi-station and multi-satellite measurement and control resource scheduling optimization method under complex constraints, comprising the following steps:

[0006] Step S1, obtaining task information and arc information within the scheduling period according to the forecast, the equipment attribute table, the task attribute table, the satellite attribute table and the task planning table;

[0007] Step S2, correcting the tracking start time and tracking end time of the device in the forecast;

[0008] Step S3: construct a task matching set, an arc matching set and an arc conflict set according to the task information and the arc information;

[0009] Step S4, scanning the task matching set of each arc segment, if the task matching set of a certain arc segment is empty, then deleting the arc segment from the conflict set of other arc segments;

[0010] Step S5, calculating arc segment priority and task priority according to the task matching set, the arc segment matching set and the arc segment conflict set, and the currently remaining arc segments and tasks, and selecting the task with the smallest arc segment allocation priority and the arc segment with the smallest task priority corresponding thereto;

[0011] Step S6, assigning the selected arc segment to the selected task;

[0012] Step S7, clearing the current task arc matching set, arc task matching set, and arc conflict set;

[0013] Step S8, determine whether all tasks within the scheduling period have been planned, if so, execute step S9, otherwise repeat steps S5 to S7;

[0014] Step S9: Save and output the results, and generate a measurement and control resource scheduling plan.

[0015] According to a technical solution of the present invention, in step S2, it also includes:

[0016] Establish a set A of all arc segments of all satellites in the scheduling period, Any arc segment a in set A i Through a four-tuple It means: it can be used at the measurement and control station Time window Satellite A task of They are the start time and end time of measurement and control respectively;

[0017] Establish a planning task set K for all satellites within the scheduling period, Any task k in set K j Through a four-tuple It means satellite In the time window Dispatch equipment required Provide yourself with a measurement and control service. is the earliest time the task can start, The latest time when the task execution ends.

[0018] According to a technical solution of the present invention, in step S3, the arc conflict set is constructed according to the arc conflict rule, and the arc conflict rule is set as:

[0019] For any arc segment a i1 and ai2 , if the relationship (1) is satisfied

[0020]

[0021] Then the two arc segments a i1 and a i2 A measurement and control conflict is formed, denoted as a i1 ∩a i2 ≠Φ;

[0022] For any arc segment a i1 ∈A, if a i1 ∩a i2 ≠Φ, then

[0023] in, For arc segment a i1 The conflict set, Stores arc segment a i1 All arcs where measurement and control conflicts occur;

[0024] The size of To express, The value of i1 The number of arcs where measurement and control conflicts occur;

[0025] when When it is equal to zero, arc segment a i1 Does not conflict with any arc segment;

[0026] For any arc segment a i1 with a i2 ,if but

[0027] According to a technical solution of the present invention, in step S3, the arc segment matching set is established according to the arc segment matching relationship; the arc segment matching relationship is set as:

[0028] For any arc segment a i and task k j , if the relationship (2) is satisfied:

[0029]

[0030] but

[0031] in, To do the task k j The arc segment matching set, arc segment matching set The size of the matching set is expressed as express;

[0032] Represents arc segment a i The device supports tasks k j Equipment required.

[0033] According to a technical solution of the present invention, in step S3, the arc segment matching set is constructed according to the arc segment matching rule; the arc segment matching rule is set as:

[0034] When an arc segment a i When multiple tasks can be met, Then define k j and k l Arc segment a i Task matching set Elements within;

[0035] if Then it must exist

[0036] According to a technical solution of the present invention, in step S5, it specifically includes:

[0037] Calculating arc state parameters according to the task matching set, the arc matching set and the arc conflict set, and calculating arc allocation priority according to the arc state parameters;

[0038] Calculating task status parameters according to the task matching set, the arc matching set and the arc conflict set, and calculating task priority according to the task status parameters;

[0039] A solution set construction algorithm is set according to the arc allocation priority and the task priority to solve the task.

[0040] According to a technical solution of the present invention, the arc segment state parameters include task matching parameters Conflict Depth Parameter and segment time window parameters

[0041] The task matching value parameter Describe arc segment a i Current task matching set a i 匹配集 The size of

[0042] The conflict depth parameter express The size of

[0043] The arc segment time window parameter For the same task k j , express Arc segment a i According to the measurement and control start time In the segment matching set The sequence number when sorting in ascending order;

[0044] The arc segment allocation priority The expression is as follows:

[0045]

[0046] According to a technical solution of the present invention, the task status parameter includes an available resource quantity parameter Resource performance parameters Task static priority parameter Satellite priority parameters Task time window parameters and mandatory parameters

[0047] The available resource quantity parameter For each task k j , which meets the task k j The number of arc segments, That is, the number of resources currently available to the task is equal to the current size of its matching set;

[0048] The resource performance parameter The value is determined according to the task tracking mode, and its definition is as follows:

[0049]

[0050] The static priority parameter of the task Indicates the priority of the task, and its value comes from the task attribute table in the system;

[0051] The satellite priority parameter Indicates the priority of the satellite to which the task belongs, and its value comes from the satellite attribute table in the system;

[0052] The task time window parameter It is expressed as: For the same satellite, the corresponding tasks are sorted in ascending order according to the earliest time when the task can start. Task k j The sequence number of the sort;

[0053] The mandatory parameters Indicates whether the task is marked as mandatory. The values ​​are defined as follows:

[0054]

[0055] The task assignment priority The expression is as follows:

[0056]

[0057] According to a technical solution of the present invention, the solution set construction algorithm is expressed as:

[0058] Let task k j The solution is k j ', the current solution set of task set K is K';

[0059] Let arc segment a i ,if

[0060]

[0061] but

[0062] k′ j ={a i},

[0063]

[0064] According to one aspect of the present invention, a multi-station multi-satellite measurement and control resource scheduling optimization system under complex constraints is provided, which is used to implement the multi-station multi-satellite measurement and control resource scheduling optimization method under complex constraints, including:

[0065] A tracking prediction acquisition and processing unit is used to obtain the tracking time window of each satellite;

[0066] A measurement and control requirement acquisition and processing unit, used to receive measurement and control resource requirements of all satellites in the measurement and control network, wherein the measurement and control resource requirements of the satellites include the measurement and control time period for the satellites and the requirements of the satellites for the measurement and control equipment types;

[0067] A measurement and control resource scheduling scheme generating unit, configured to calculate and generate a measurement and control resource scheduling scheme within a measurement and control cycle according to the multi-station and multi-satellite measurement and control resource scheduling optimization method under the complex constraint conditions;

[0068] The plan sending unit is used to send the measurement and control resource scheduling plan to the measurement and control mission control center of each satellite and the mission control center of each measurement and control station according to the measurement and control resource scheduling plan.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The present invention proposes a multi-station multi-satellite measurement and control resource scheduling optimization method and system under complex constraint conditions, by constructing task matching sets, arc matching sets and arc conflict sets of tasks and arc segments, and calculating task priorities and arc priorities according to the task matching sets, arc matching sets and arc conflict sets, screening out tasks with the smallest arc allocation priority and their corresponding arc segments with the smallest task priority, and assigning the selected tasks to the selected arc segments, so that the conflict values ​​of the assigned tasks and arc segments with other tasks and arc segments are minimized, thereby obtaining the optimal scheduling scheme for multi-station multi-satellite measurement and control. The method provided by the present invention can achieve the allocation of the most suitable arc segment to the most suitable measurement and control task only through simple mathematical calculations, obtain the best measurement and control resource allocation and scheduling scheme, and solve the problems of multiple processing objects and complex constraint relationships faced by measurement and control resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] 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 are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0072] Figure 1 Schematically showing a flow chart of a multi-station and multi-satellite measurement and control resource scheduling optimization method under complex constraints according to an embodiment of the present invention;

[0073] Figure 2 A schematic diagram of aerospace tracking and control arc segment resource competition according to an embodiment of the present invention is schematically shown;

[0074] Figure 3 A schematic diagram schematically shows a conflict between different satellites according to an embodiment of the present invention;

[0075] Figure 4 The structure diagram of a multi-station and multi-satellite measurement and control resource scheduling optimization system under complex constraints according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0076] The description of the embodiments of this specification should be combined with the corresponding drawings, which should be considered as part of the complete specification. In the drawings, the shape or thickness of the embodiments may be enlarged and indicated for simplification or convenience. Furthermore, the parts of each structure in the drawings will be described separately. It is worth noting that the elements not shown in the drawings or not described in words are in a form known to ordinary technicians in the relevant technical field.

[0077] The description of the embodiments herein and any reference to directions and orientations are only for the convenience of description and are not to be construed as any limitation on the scope of protection of the present invention. The following description of the preferred embodiments may involve combinations of features, which may exist independently or in combination, and the present invention is not particularly limited to the preferred embodiments. The scope of the present invention is defined by the claims.

[0078] like Figure 1 As shown, an optimization combination algorithm for solving the multi-station and multi-satellite measurement and control resource scheduling problem under complex constraints of the present invention includes the following steps:

[0079] Step S1, obtaining task information and arc information within the scheduling period according to the forecast, the equipment attribute table, the task attribute table, the satellite attribute table and the task planning table;

[0080] Step S2, correcting the tracking start time and tracking end time of the device in the forecast;

[0081] Step S3: construct a task matching set, an arc matching set and an arc conflict set according to the task information and the arc information;

[0082] Step S4, scanning the task matching set of each arc segment, if the task matching set of a certain arc segment is empty, then deleting the arc segment from the conflict set of other arc segments;

[0083] Step S5, calculating arc segment priority and task priority according to the task matching set, the arc segment matching set and the arc segment conflict set, and the currently remaining arc segments and tasks, and selecting the task with the smallest arc segment allocation priority and the arc segment with the smallest task priority corresponding thereto;

[0084] In the step S5, it specifically includes:

[0085] Calculating arc state parameters according to the task matching set, the arc matching set and the arc conflict set, and calculating arc allocation priority according to the arc state parameters;

[0086] Calculating task status parameters according to the task matching set, the arc matching set and the arc conflict set, and calculating task priority according to the task status parameters;

[0087] A solution set construction algorithm is set according to the arc allocation priority and the task priority to solve the task.

[0088] Step S6, assigning the selected arc segment to the selected task;

[0089] Step S7, clearing the current task arc matching set, arc task matching set, and arc conflict set;

[0090] Step S8, determine whether all tasks within the scheduling period have been planned, if so, execute step S9, otherwise repeat steps S5 to S7;

[0091] Step S9: Save and output the results, and generate a measurement and control resource scheduling plan.

[0092] The basic idea of ​​the algorithm of the present invention is to decompose a large-scale problem into smaller-scale sub-problems, which are independent of each other and have the same properties as the original problem. Since the scale of the sub-problem is already small, it is easier to solve. By analogy, when the scale of the sub-problem is small enough, it can be solved directly. The specific algorithm principle is as follows:

[0093] All tasks to be planned The arcs that meet the task are sorted in ascending order and grouped. The same number of arcs is grouped together. j Indicates the group number, assuming j = 1, ... n, use Represents G j The number of arc segments of the task elements in the task, it is obvious that the following inequality holds:

[0094] Because different tasks of the same satellite compete for the same arc resources and arc conflicts may occur between different tasks, if a task in any group on the left side of the inequality obtains an arc, it may cause a reduction in the arc resources available to the tasks on the right side of the inequality. Because each task only needs to obtain one arc, if any task on the left side of the inequality obtains an arc, the number of arcs available to all tasks on its right side will be reduced by at most one. In this way, we focus the scope of problem solving on group G1. If an arc is assigned to any task in group G1, then all G j In the worst case, tasks in the group (j=2,..n) lose at most one available arc segment (due to the orbital characteristics of near-Earth satellites, arc segments of different satellites will conflict at most once on the same device). Therefore, we choose to process tasks in the G1 group.

[0095] The elements in group G1 are further separated. Since the number of elements is the same, they are sorted according to the number of tasks that can be adapted to the arcs in the task. The basis for grouping each task is to take the arc with the least number of tasks that can be adapted. j Indicates grouping, using Indicates the conflict caused by this arc segment. Obviously, the smaller the conflict value, the less impact the task has on solving other tasks when it obtains this arc segment.

[0096] The above algorithm idea can be conveniently used in the arrangement of class timetables in the education industry, the arrangement of duty schedules for various units, etc.

[0097] The present invention classifies and sorts various constraints, introduces the concepts of "measurement and control task measurement and control arc segment matching set", "measurement and control arc segment conflict set" and "measurement and control arc segment task matching set", focuses on the global optimum, and uses simple mathematical calculations to allocate the most suitable arc segment to the most suitable measurement and control task, and uses simple mathematical calculations to obtain the best measurement and control resource allocation and scheduling plan.

[0098] The present invention is described in detail below by way of examples.

[0099] 1. Problem Description

[0100] The solution to the multi-station and multi-satellite measurement and control resource scheduling problem under complex constraints provided by the present invention includes two parts: one is the competition for the same arc segment among different tasks of the same satellite, and the other is the "measurement and control conflict" caused by the overlap of arc segments among different satellite measurement and control tasks.

[0101] (1) Competition between different missions of the same satellite for the same arc segment: Figure 2 As shown, the large ellipse K j Indicates different measurement and control tasks of the same satellite. The small circle a i Indicates different observation arcs. If the icon representing the arc is within the ellipse representing the task, we say that the arc supports the task. Indicates that task k is satisfied j The arc segment set is:

[0102]

[0103] (2) “T&C conflicts” caused by overlapping arcs of different satellite T&C missions: Figure 2 As shown, ellipses of different colors represent the measurement and control tasks of different satellites, and circles of the same color within the ellipses represent the measurement and control arcs that meet the tasks. If two circles of different colors overlap, it means that there is a measurement and control conflict in the measurement and control tasks of different satellites.

[0104] The occurrence of measurement and control conflict indicates that there is temporal overlap when satellites pass through the observable area of ​​the measurement and control equipment, or that one satellite appears within the observable range of another satellite when one satellite has not yet left the observable area of ​​a specific device.

[0105] 2. Constraints

[0106] The algorithm constraints are as follows:

[0107] (1) A single set of antenna equipment can only serve one satellite at a time;

[0108] (2) When the device is tracking, the arc segment cannot be interrupted;

[0109] (3) When the arc segments of several satellites conflict with the same device, the device can only serve one satellite;

[0110] (4) When a satellite has all its missions matched in the mission planning table, no arc will be assigned;

[0111] (5) The time window for each task planning should not exceed 24 hours.

[0112] 3. Data Definition

[0113] 1. Observable arc segment dataset

[0114] definition is the set of all arc segments of all satellites in a certain scheduling period. Any element a in the set i A quadruplet is available It means: it can be used at the measurement and control station Time window Satellite A task of They are the start time and end time of measurement and control respectively.

[0115] 2. Observation arc conflict

[0116] For any arc segment a i1 and a i2 , if the relationship (1) is satisfied:

[0117]

[0118] These two arcs are said to form a measurement and control conflict. i1 ∩a i2 ≠Φ.

[0119] 3. Observation arc conflict set

[0120] For any arc segment a i1 ∈A, if a i1 ∩a i2 ≠Φ, then Arc segment a i The conflict set stores the conflict with arc a i All arcs where measurement and control conflicts occur.

[0121] in, For arc segment a i1 The conflict set, Stores arc segment a i1 All arcs where measurement and control conflicts occur. When it is equal to zero, arc segment a i1 Does not conflict with any arcs.

[0122] Obviously, for any arc segment a i1 with a i2 ,if but

[0123] 4. Mission Planning Set

[0124] definition is the set of all tasks planned for all satellites within a certain scheduling period. Any element k in the set j A quadruplet is available It means satellite Time Window Dispatch equipment required Provide yourself with a measurement and control service. is the earliest time the task can start, The latest time when the task execution ends.

[0125] 5. Task Matching Set

[0126] For any arc segment a i and task k j , if the relationship (2) is satisfied:

[0127]

[0128] but It is called task k j The arc segment matching set, task k j The size of the arc segment matching set is expressed as express.

[0129] Represents arc segment a i The device supports tasks k j Required device. For devices, if the device specifies a device identifier, the identifiers are equal, otherwise the device types are equal. When implementing software, the function code of each device and the function code of the task can be defined by binary bits. The same position identifies the same function. If the value of the task function code and the device function code remains unchanged after the bitwise logical multiplication operation, it means that the device fully supports the task function.

[0130] Obviously, if task k j of is equal to 0, then the calculation result k j There must be no resources to allocate.

[0131] 6. Arc segment matching set

[0132] When an observation arc a i When multiple tasks can be met, Then define k j and kl All are observation arc segment a i Task matching set Obviously, if Then it must exist

[0133] Obviously, if is equal to 0, then arc segment a i It is a useless arc segment.

[0134] 7. Arc state parameters

[0135] 1) Task matching value parameters

[0136] Task matching value parameters Describe arc segment a i Current task matching set a i 匹配集 The size of

[0137] 2) Conflict depth parameter

[0138] Conflict Depth Parameter express The size of

[0139] 3) Segment time window parameters

[0140] For the same task k j , express Arc segment a i According to the measurement and control start time In the segment matching set The sequence number when sorting in ascending order.

[0141] 8. Arc segment allocation priority

[0142] Define segment allocation priorities The expression is:

[0143]

[0144] Arc allocation priority The bitmap is as follows:

[0145]

[0146] 9. Task status parameters

[0147] 1) Available resource quantity parameters

[0148] For each task k j , which meets the task k j The number of arcs is defined as the number of available resources Apparently That is, the number of resources currently available to the task is equal to the current size of its matching set.

[0149] 2) Resource efficiency parameters

[0150] Resource performance parameters The value is determined according to the task tracking mode and is defined as follows:

[0151]

[0152] 3) Task priority parameter

[0153] Task static priority parameter Indicates the priority of the task, and its value comes from the task attribute table in the system.

[0154] 4) Satellite priority parameters

[0155] Satellite priority parameters Indicates the priority of the satellite to which the task belongs. Its value comes from the satellite attribute table in the system.

[0156] 5) Task time window parameters

[0157] For the same satellite, express according to Sequence number in ascending order.

[0158] 6) Mandatory parameters

[0159] Indicates whether the task is marked as mandatory. The values ​​are defined as follows:

[0160]

[0161] 10. Task Assignment Priority

[0162] For task k j , task allocation priority The expression is as follows:

[0163]

[0164] Task Assignment Priority The bitmap is as follows:

[0165]

[0166] 11. Solution set construction algorithm

[0167] Let task k j The solution is k j ', the current solution set of task set K is K'.

[0168] Let arc segment a i ,if

[0169]

[0170] but

[0171] k′ j ={a i},

[0172]

[0173] According to one aspect of the present invention, the present invention also provides a multi-station multi-satellite measurement and control resource scheduling optimization system under complex constraints, which is used to implement the multi-station multi-satellite measurement and control resource scheduling optimization method under the above-mentioned complex constraints, including:

[0174] A tracking prediction acquisition and processing unit is used to obtain the tracking time window of each satellite;

[0175] A measurement and control requirement acquisition and processing unit, used to receive measurement and control resource requirements of all satellites in the measurement and control network, wherein the measurement and control resource requirements of the satellites include the measurement and control time period for the satellites and the requirements of the satellites for the measurement and control equipment types;

[0176] A measurement and control resource scheduling scheme generating unit, configured to calculate and generate a measurement and control resource scheduling scheme within a measurement and control cycle according to the multi-station and multi-satellite measurement and control resource scheduling optimization method under the complex constraint conditions;

[0177] The plan sending unit is used to send the measurement and control resource scheduling plan to the measurement and control mission control center of each satellite and the mission control center of each measurement and control station according to the measurement and control resource scheduling plan.

[0178] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0179] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0180] It should also be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0181] Finally, it should be noted that the above is a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, for those skilled in the art, once the basic creative concept of the present invention is known, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the present invention.

Claims

1. A multi-station and multi-satellite measurement and control resource scheduling optimization method under complex constraints, characterized in that: The following steps are involved: Step S1, obtaining task information and arc information within the scheduling period according to the forecast, the equipment attribute table, the task attribute table, the satellite attribute table and the task planning table; Step S2, correcting the tracking start time and tracking end time of the device in the forecast; Step S3: construct a task matching set, an arc matching set and an arc conflict set according to the task information and the arc information; Step S4, scanning the task matching set of each arc segment, if the task matching set of a certain arc segment is empty, then deleting the arc segment from the conflict set of other arc segments; Step S5, calculating the arc allocation priority and task priority according to the task matching set, the arc matching set and the arc conflict set, and the currently remaining arcs and tasks, and selecting the task with the smallest arc allocation priority and the arc with the smallest task priority corresponding to it; Step S6, assigning the selected arc segment to the selected task; Step S7, clearing the current task arc matching set, arc task matching set, and arc conflict set; Step S8, determine whether all tasks within the scheduling period have been planned, if so, execute step S9, otherwise repeat steps S5 to S7; Step S9, save and output the results, and generate a measurement and control resource scheduling plan; In the step S5, it specifically includes: Calculating arc state parameters according to the task matching set, the arc matching set and the arc conflict set, and calculating arc allocation priority according to the arc state parameters; Calculating task status parameters according to the task matching set, the arc matching set and the arc conflict set, and calculating task priority according to the task status parameters; According to the arc allocation priority and the task priority, a solution set construction algorithm is set to solve the task; The arc segment state parameters include task matching parameters V ai , conflict depth parameter C ai and segment time window parameter T ai , The task matching value parameter Describe arc segment a i Current task matching set a i 匹配集 The size of The conflict depth parameter express The size of The arc segment time window parameter For the same task k j , express Arc segment a i According to the measurement and control start time In the segment matching set The sequence number when sorting in ascending order; The arc segment allocation priority The expression is as follows: The task status parameters include the available resource quantity parameters Resource performance parameters Task static priority parameter Satellite priority parameters Task time window parameters and mandatory parameters The available resource quantity parameter For each task k j , which meets the task k j The number of arc segments, That is, the number of resources currently available to the task is equal to the current size of its matching set; The resource performance parameter The value is determined according to the task tracking mode, and its definition is as follows: The static priority parameter of the task Indicates the priority of the task, and its value comes from the task attribute table in the system; The satellite priority parameter Indicates the priority of the satellite to which the task belongs, and its value comes from the satellite attribute table in the system; The task time window parameter It is expressed as: For the same satellite, the corresponding tasks are sorted in ascending order according to the earliest time when the task can start. Task k j The sequence number of the sort; The mandatory parameters Indicates whether the task is marked as mandatory. The values ​​are defined as follows: The task priority The expression is as follows: in, Indicates that task k is satisfied j The set of arc segments; The solution set construction algorithm is expressed as: Let task k j The solution is k' j , the current solution set of task set K is K'; Let arc segment a i ,if but k' j ={a i }, 2. The method for optimizing multi-station and multi-satellite TT&C resource scheduling under complex constraints according to claim 1 is characterized in that: In the step S2, it also includes: Establish a set A of all arc segments of all satellites in the scheduling period, Any arc segment a in set A i Through a four-tuple It means: it can be used at the measurement and control station Time window Satellite arrangement inside A task of They are the start time and end time of measurement and control respectively; Establish a planning task set K for all satellites within the scheduling period, Any task k in set K j Through a four-tuple It means satellite In the time window Dispatch equipment required Provide yourself with a measurement and control service. is the earliest time the task can start, The latest time when the task execution ends.

3. The method for optimizing multi-station and multi-satellite measurement and control resource scheduling under complex constraints according to claim 2 is characterized in that: In step S3, the arc conflict set is constructed according to the arc conflict rule, and the arc conflict rule is set as follows: For any arc segment a i1 and a i2 , if the relationship (1) is satisfied Then the two arc segments a i1 and a i2 A measurement and control conflict is formed, denoted as a i1 ∩a i2 ≠Φ; For any arc segment a i1 ∈A, if a i1 ∩a i2 ≠Φ, then in, For arc segment a i1 The conflict set, Stores arc segment a i1 All arcs where measurement and control conflicts occur; The size of To express, The value of i1 The number of arcs where measurement and control conflicts occur; when When it is equal to zero, arc segment a i1 Does not conflict with any arc segment; For any arc segment a i1 with a i2 ,if but 4. The method for optimizing multi-station and multi-satellite TT&C resource scheduling under complex constraints according to claim 3 is characterized in that: In step S3, the arc segment matching set is established according to the arc segment matching relationship; the arc segment matching relationship is set as: For any arc segment a i and task k j , if the relationship (2) is satisfied: but in, To do the task k j The arc segment matching set, arc segment matching set The size of the matching set is expressed as express; Represents arc segment a i The device supports tasks k j Equipment required.

5. The method for optimizing multi-station and multi-satellite TT&C resource scheduling under complex constraints according to claim 4 is characterized in that: In step S3, the arc segment matching set is constructed according to the arc segment matching rule; the arc segment matching rule is set as: When an arc segment a i When multiple tasks can be met, Then define k j and k l All are arc segment a i Task matching set Elements within; if Then there must be 6. A multi-station multi-satellite measurement and control resource scheduling optimization system under complex constraints, used to implement the multi-station multi-satellite measurement and control resource scheduling optimization method under complex constraints as claimed in any one of claims 1 to 5, characterized in that: include: A tracking prediction acquisition and processing unit is used to obtain the tracking time window of each satellite; A measurement and control requirement acquisition and processing unit, used to receive measurement and control resource requirements of all satellites in the measurement and control network, wherein the measurement and control resource requirements of the satellites include the measurement and control time period for the satellites and the requirements of the satellites for the measurement and control equipment types; A measurement and control resource scheduling scheme generating unit, configured to calculate and generate a measurement and control resource scheduling scheme within a measurement and control cycle according to the multi-station and multi-satellite measurement and control resource scheduling optimization method under the complex constraint conditions; The plan sending unit is used to send the measurement and control resource scheduling plan to the measurement and control mission control center of each satellite and the mission control center of each measurement and control station according to the measurement and control resource scheduling plan.

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