Service-oriented task and remote sensing satellite bilateral matching method and system

Abstract

The application provides a task and remote sensing satellite double-sided matching method, system, storage medium and electronic equipment for service satisfaction, and relates to the technical field of satellite task planning.The application provides a task and satellite double-sided matching method for service satisfaction, which establishes a structured and standardized system of remote sensing satellites, establishes a double-sided matching relationship between tasks and remote sensing satellites, and proposes a remote sensing satellite cluster concept.The remote sensing satellite cluster improves the use efficiency of remote sensing satellites on one hand, and on the other hand, when the environment changes, the remote sensing satellite cluster that meets the current common task demand can be quickly formed, and real-time dynamic adjustment of remote sensing satellite configuration can be made according to the change of the environment.A task-remote sensing satellite matching model is designed, and a distributed collaborative task assignment method is used to complete remote sensing satellite cluster task planning.The remote sensing satellite can be allocated to complete tasks more quickly, the time cost is reduced, and the optimization efficiency of satellite task completion is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of satellite mission planning technology, and more specifically to a bilateral matching method, system, storage medium, and electronic device for missions and remote sensing satellites oriented towards service fulfillment. Background Technology

[0002] In recent years, with the continuous advancement of aerospace technology, the amount of on-orbit satellite data has increased rapidly, and satellite capabilities have also undergone a qualitative leap. As a result, users' demands for completing satellite missions have also increased significantly. Traditional mission planning methods for single satellites can no longer meet the growing user needs.

[0003] Meeting mission requirements inevitably involves mapping various types of remote sensing satellites, such as those for acquisition, transmission, distribution, and processing. However, the mission's requirements for these different types of remote sensing satellites are combinable, and these satellites often have a high degree of coupling, making the establishment of a mapping relationship between requirements and remote sensing satellites quite complex.

[0004] To improve the overall efficiency of satellite systems and meet mission requirements, and to make efficient use of a limited number of remote sensing satellites, it is necessary to provide a mission-satellite bilateral matching scheme oriented towards service fulfillment. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a bilateral matching method, system, storage medium, and electronic device for service-oriented missions and remote sensing satellites, solving the technical problem that existing technologies cannot meet the combinatorial requirements of missions for various types of remote sensing satellites.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A service-fidelity-oriented bilateral matching method between tasks and remote sensing satellites includes:

[0010] S1. Based on the task set and satellite resources, obtain remote sensing satellite clusters for jointly completing the tasks, wherein the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks;

[0011] S2. Based on the task set, satellite resources and remote sensing satellite cluster, construct a task-remote sensing satellite matching model with the goal of minimizing overall energy consumption;

[0012] S3. Based on the task-remote sensing satellite matching model, a distributed collaborative task assignment method is used to complete the task planning for the remote sensing satellite cluster.

[0013] Preferably, the mission-remote sensing satellite matching model in S2 includes:

[0014] The objective function is to minimize the overall energy consumption.

[0015]

[0016] Where S represents the set of satellites in a distributed satellite system, S = {s1, s2, ..., s} w};

[0017] s j Let $j$ represent the $j$-th satellite, where $j = {1, 2, ..., w} and $w$ is the total number of satellites.

[0018] F represents the set of tasks to be observed, F = {f1, f2, ..., f} v}, where v is the total number of tasks;

[0019] S i Indicates the use of f to jointly complete the task. i The remote sensing satellite cluster, S i ∈S;

[0020] p ji Indicates satellite s j Complete task f i The energy consumed;

[0021] For decision variables, if the task and tasks All of them will occupy satellites j And the task Follow the mission Then execute, otherwise in

[0022] Preferably, the mission-remote sensing satellite matching model in S2 further includes:

[0023] Constraints:

[0024] (1) A task can only occupy one satellite when it is executed, and the task can only be executed once. If a task is scheduled to be executed, there can only be one follow-up task. The task can be a virtual task.

[0025]

[0026] (2) Ensure satellite s j There can only be one starting task in the task queue;

[0027]

[0028] (3) Ensure satellite s j Tasks in the task queue are executed sequentially, meaning their execution times do not overlap. If task f i Occupying satellites j Then its predecessor and successor missions also occupy satellite space. j ;

[0029]

[0030] (4) Determine the order of execution of the two tasks;

[0031]

[0032] (5) Ensure that the task can only be executed within a single time window;

[0033]

[0034] (6) The execution time of the task is determined to be within the corresponding time window;

[0035]

[0036]

[0037] (7)CQ i ≤sf i ≤C i ;

[0038] Among them, sf i This indicates that if task f i Occupying satellites j Task f i Let f0 = 0 be the actual start time;

[0039] lf i This indicates that if task f i Occupying satellites j Task f i Execution preparation time, lf i ≥0;

[0040] l ij Indicates task f i For satellites s j The time occupied, l ij ≥0;

[0041] D ij Indicates task f i Occupying satellites j The number of time windows allowed at any given time;

[0042] FM ij This indicates that if task f i Occupying satellites j The set of time windows allowed at any time;

[0043]

[0044]

[0045] in and They represent f respectively i Occupying satellites j Release the start and end times of the allowed h-th time window;

[0046] As a decision variable, if task f i Occupying satellites j The time window occupied during execution is but otherwise

[0047] CQ i This indicates that if task f i Occupying satellites j The time window occupied during execution is Then satellite s j Execute task f i The earliest possible start time;

[0048]

[0049] C i This indicates that if task f i Occupying satellites j The time window occupied during execution is Then satellite s j Execute task f i The latest possible start time;

[0050]

[0051] Preferably, in step S3, a distributed collaborative task assignment method is used to select a conflict-free and time-constrained visible time window for the execution of each task in the corresponding remote sensing satellite cluster, thereby completing task planning.

[0052] Define any satellite s in the remote sensing satellite cluster j The current queue of tasks to be observed is s j For task f iThe set of candidate visible time windows to be judged is

[0053] The time constraint verification algorithm includes:

[0054] S100, initialize the values ​​to h = 0, a = 0, z = 0; where h is the candidate visible time window to be judged. ij h The number; a is the insertion point position; z is a logical value indicating whether there is a visible time window that satisfies the time constraint; 1 indicates yes, 0 indicates no;

[0055] S200, if h <D ij If z = 1, then set h = h + 1 and a = 1, and proceed to S300; otherwise, set z = 1, select the optimal time window for bidding, and exit; otherwise, proceed to S900.

[0056] S300. If a > q + 1, then q = |F j If the above conditions are met, proceed to S200; otherwise, determine the task. and Is there enough free time between them to insert task f? i The judgment is as follows:

[0057] sf a -af a-1 ≥lp i +lf a q +QF i

[0058] in, For task f i Post-insertion task The new preparation time is different from the time before insertion. The original preparation time lf a QF i For task f i If the above formula holds true, proceed to S500 for the required continuous observation time; otherwise, proceed to S400.

[0059] S400, Task The earliest possible start time sf a Shift backward, minimum time length for shifting backward

[0060]

[0061] Will moving the task to the back cause task conflicts, and will this introduce new tasks? Post-shift time MF a The judgment condition is d <MF a If true, and the shift to the next position is allowed, then sfa =sf a +d; af a =af a +d; MF a =MF a -d, switch to S500; otherwise, task and There is not enough free time to insert task f i a = a + 1, then switch to S300;

[0062] S500, SF i =af a-1 +lf i ;af i =sf i +QF i ;but

[0063]

[0064]

[0065] Task f i The criterion for determining whether the earliest possible start time of execution falls within the candidate time window is: sf i ≥SF i If approved, you will be transferred to S700; otherwise, you will be transferred to S600.

[0066] S600, Judgment Task f i Is there enough leeway for MF to move back? i Can guarantee sf i If it falls within the candidate time window, the judgment condition is sf i +MF i ≥SF i If the condition is met, proceed to S700; otherwise, if a = a - 1, proceed to S300.

[0067] S700, Mission F i The criterion for determining whether the earliest possible completion time falls within the candidate time window is af. i ≤AF i If true, proceed to S800; otherwise, a = a + 1, proceed to S300.

[0068] S800, satellite j The h-th candidate time window satisfies the task time constraint. If z = 0, then set z = 1 and go to S200.

[0069] S900, such as task f i None of the candidate time windows to be judged meet the task constraints. j Bid rejected, withdrawal.

[0070] Preferably, if there are multiple candidate time windows that meet the time constraints, the best satellite is selected for observation according to the preset optimization objective. The optimization objective is to minimize the difference between the energy required to complete the task and the energy consumed before the task is inserted. If they are the same, the selection continues with minimizing the actual completion time of the task as the objective.

[0071] A service-metrization-oriented mission-to-remote-sensing-satellite bilateral matching system includes:

[0072] The acquisition module is used to acquire remote sensing satellite clusters used to jointly complete the tasks based on the task set and satellite resources, wherein the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks;

[0073] The construction module is used to build a task-remote sensing satellite matching model based on the task set, satellite resources and remote sensing satellite cluster, with the goal of minimizing overall energy consumption.

[0074] The solution module is used to complete the task planning of the remote sensing satellite cluster using a distributed collaborative task assignment method based on the task-remote sensing satellite matching model.

[0075] A storage medium storing a computer program for bilateral matching of tasks with remote sensing satellites for service fulfillment, wherein the computer program causes a computer to perform the bilateral matching method of tasks with remote sensing satellites as described above.

[0076] An electronic device, comprising:

[0077] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the tasks described above and bilateral matching methods with remote sensing satellites.

[0078] (III) Beneficial Effects

[0079] This invention provides a method, system, storage medium, and electronic device for bilateral matching of tasks and remote sensing satellites oriented towards service satisfaction. Compared with the prior art, it has the following advantages:

[0080] This invention provides a task-satellite bilateral matching method oriented towards service fulfillment. This method establishes a structured and standardized system for remote sensing satellites, establishes a bilateral matching relationship between tasks and remote sensing satellites, and proposes the concept of remote sensing satellite clusters. Remote sensing satellite clusters improve the efficiency of remote sensing satellite utilization and, when the environment changes, can quickly form clusters that meet the current common task requirements, and can dynamically adjust the remote sensing satellite configuration in real time to adapt to environmental changes. A task-satellite matching model is designed, and a distributed collaborative task assignment method is used to complete the remote sensing satellite cluster task planning. This method can quickly complete the remote sensing satellite task allocation, reduce time costs, and effectively improve the optimization efficiency of satellites in completing tasks. Attached Figure Description

[0081] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0082] Figure 1 This is a flowchart illustrating a bilateral matching method between a service-oriented task and a remote sensing satellite, provided as an embodiment of the present invention. Detailed Implementation

[0083] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0084] This application provides a bilateral matching method, system, storage medium, and electronic device for service-oriented missions and remote sensing satellites, solving the technical problem that existing technologies cannot meet the combinatorial requirements of missions for various types of remote sensing satellites.

[0085] The technical solution in this application is to solve the above-mentioned technical problems, and the general idea is as follows:

[0086] In the existing satellite technology landscape, mission-satellite matching is mostly unilateral, and this matching may not be optimal. Under such a mission-satellite matching method, one-way communication between the mission and the platform may not be the most efficient or suitable approach.

[0087] For joint observation missions, multiple satellites are required to work together to meet the mission requirements because a single satellite cannot complete the task. Without loss of generality, this embodiment of the invention considers multiple observation missions. To complete these missions, a set of remote sensing satellites must be determined for each joint mission. The remote sensing satellites in the set constitute the remote sensing satellite cluster corresponding to that mission, and bidirectional matching of remote sensing satellite missions is performed through the remote sensing satellite cluster approach.

[0088] To address the aforementioned technical problems, this invention provides a bilateral matching method for missions and satellites oriented towards service fulfillment. This method establishes a remote sensing satellite cluster and performs reasonable matching based on the satellite mission-remote sensing satellite problem, minimizing matching ambiguity and reducing conflicts between different types of capabilities of the same remote sensing satellite. Through bilateral matching of missions and remote sensing satellites, the optimal pairing method is identified, maximizing mission execution efficiency. This shortens mission completion time, improves mission efficiency, and also enhances the utilization efficiency of remote sensing satellites.

[0089] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0090] Example:

[0091] like Figure 1 As shown, this embodiment of the invention provides a bilateral matching method between a task and a remote sensing satellite for service satisfaction, including:

[0092] S1. Based on the task set and satellite resources, obtain remote sensing satellite clusters for jointly completing the tasks, wherein the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks;

[0093] S2. Based on the task set, satellite resources and remote sensing satellite cluster, construct a task-remote sensing satellite matching model with the goal of minimizing overall energy consumption;

[0094] S3. Based on the task-remote sensing satellite matching model, a distributed collaborative task assignment method is used to complete the task planning for the remote sensing satellite cluster.

[0095] This invention establishes a remote sensing satellite cluster to rationally match satellite missions with remote sensing satellites, minimizing ambiguity and conflicts between different capabilities of the same remote sensing satellite. Through bilateral matching of missions and remote sensing satellites, the optimal pairing is identified, maximizing mission execution efficiency. This shortens mission completion time, improves mission efficiency, and enhances the utilization efficiency of remote sensing satellites.

[0096] The following will detail each step of the above technical solution:

[0097] In step S1, based on the task set and satellite resources, a cluster of remote sensing satellites is obtained to jointly complete the task, and the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks.

[0098] A remote sensing satellite cluster is a form of remote sensing satellite organization. It is a loosely structured, distributed cluster capable of collaboratively completing complex Earth observation tasks, and each satellite belongs to a different satellite management system. Different types of satellites can cooperate and coordinate through satellite management, enabling them to accomplish observation tasks that individual satellites cannot.

[0099] Due to the dynamic uncertainty of missions and mission environments, the satellite remote sensing clusters for various missions are constantly changing. When common missions need to be processed simultaneously, the virtual constellation, through consultation with the satellite center, dynamically selects appropriate remote sensing satellites to form a remote sensing satellite cluster to complete the Earth observation mission. Therefore, there is a one-to-one correspondence between the dynamic remote sensing satellite clusters in the remote sensing satellite pool and the current common missions; the number of remote sensing satellite clusters equals the number of common missions.

[0100] In step S2, based on the task set, satellite resources, and remote sensing satellite cluster, a task-remote sensing satellite matching model is constructed with the goal of minimizing overall energy consumption.

[0101] The mission-remote sensing satellite matching model includes:

[0102] The objective function is to minimize the overall energy consumption.

[0103]

[0104] Where S represents the set of satellites in a distributed satellite system, S = {s1, s2, ..., s} w};

[0105] s j Let $j$ represent the $j$-th satellite, where $j = {1, 2, ..., w} and $w$ is the total number of satellites.

[0106] F represents the set of tasks to be observed, F = {f1, f2, ..., f} v}, where v is the total number of tasks;

[0107] S i Indicates the use of f to jointly complete the task. i The remote sensing satellite cluster, S i ∈S;

[0108] p ji Indicates satellite s j Complete task fi The energy consumed;

[0109] For decision variables, if the task and tasks All of them will occupy satellites j And the task Follow the mission Then execute, otherwise in

[0110] and constraints:

[0111] (1) A task can only occupy one satellite when it is executed, and the task can only be executed once. If a task is scheduled to be executed, there can only be one follow-up task. The task can be a virtual task. The virtual task refers to the task that needs to be completed by negotiating with the satellite center through a virtual constellation when there are collaborative tasks that need to be processed at the same time, and selecting the corresponding resources to complete the required Earth observation task.

[0112]

[0113] (2) Ensure satellite s j There can only be one starting task in the task queue;

[0114]

[0115] (3) Ensure satellite s j Tasks in the task queue are executed sequentially, meaning their execution times do not overlap. If task f i Occupying satellites j Then its predecessor and successor missions also occupy satellite space. j ;

[0116]

[0117] (4) Determine the order of execution of the two tasks;

[0118]

[0119] (5) Ensure that the task can only be executed within a single time window;

[0120]

[0121] (6) The execution time of the task is determined to be within the corresponding time window;

[0122]

[0123] (7)CQ i ≤sf i ≤C i ;

[0124] Among them, sf i This indicates that if task f i Occupying satellites j Task f i Let f0 = 0 be the actual start time;

[0125] lf i This indicates that if task f i Occupying satellites j Task f i Execution preparation time, lf i ≥0;

[0126] l ij Indicates task f i For satellites s j The time occupied, l ij ≥0;

[0127] D ij Indicates task f i Occupying satellites j The number of time windows allowed at any given time;

[0128] FM ij This indicates that if task f i Occupying satellites j The set of time windows allowed at any time;

[0129]

[0130]

[0131] in and They represent f respectively i Occupying satellites j Release the start and end times of the allowed h-th time window;

[0132] As a decision variable, if task f i Occupying satellites j The time window occupied during execution is but otherwise

[0133] CQ i This indicates that if task f i Occupying satellites j The time window occupied during execution is Then satellite sj Execute task f i The earliest possible start time;

[0134]

[0135] C i This indicates that if task f i Occupying satellites j The time window occupied during execution is Then satellite s j Execute task f i The latest possible start time;

[0136]

[0137] In step S3, based on the task-remote sensing satellite matching model, a distributed collaborative task assignment method is used to complete the task planning for the remote sensing satellite cluster.

[0138] In this embodiment of the invention, each remote sensing satellite is treated as a satellite agent. Therefore, satellite agents in a remote sensing satellite cluster are divided into two types: Management Agent (MA) and Work Agent (WA). The MA has the function of assigning observation tasks among numerous WAs and determining whether a WA is capable of completing the assigned observation task. The WA has the function of accepting or rejecting observation tasks; when a WA accepts an assigned observation task, it can image the target within a suitable visible time window.

[0139] Due to the unique nature of Earth observation missions, generally speaking, assuming that WA targets mission f within a planning cycle... i It often has many visible time windows, for |FW ij 1. To determine the execution time of a task, it is necessary to start from FW. ij We select the optimal visible time window that satisfies the time constraint and has no task conflicts. Theoretically, as long as the start and end times of the task are within the time window, the time constraint is satisfied. However, since a remote sensing satellite can only fulfill the requirements of one observation task at a time.

[0140] Therefore, this leads to when s j Pre-acceptance task f i At that time, f must also be considered i Will it affect s j The impact of previously accepted tasks, i.e., whether conflicts will occur between tasks after acceptance, and whether these conflicts can be resolved, is addressed by using only visible time windows that meet time constraints and have no task conflicts. To achieve this, we introduce the concept of shifting spare time and provide a corresponding time constraint verification algorithm.

[0141] The system selects windows based on their start times, considering them sequentially to identify all visible time windows that satisfy the constraints and are conflict-free. Without loss of generality, let's assume the time window to be judged is... If the insertion point to be determined is the a-th point, then the insertion point is located at... and between

[0142] The time constraint verification algorithm includes:

[0143] S100, initialize the values ​​to h = 0, a = 0, z = 0; where h is the candidate visible time window to be judged. ij h The number; a is the insertion point position; z is a logical value indicating whether there is a visible time window that satisfies the time constraint; 1 indicates yes, 0 indicates no;

[0144] S200, if h <D ij If z = 1, then set h = h + 1 and a = 1, and proceed to S300; otherwise, set z = 1, select the optimal time window for bidding, and exit; otherwise, proceed to S900.

[0145] S300. If a > q + 1, then q = |F j If the above conditions are met, proceed to S200; otherwise, determine the task. and Is there enough free time between them to insert task f? i The judgment is as follows:

[0146] sf a -af a-1 ≥lp i +lf a q +QF i

[0147] in, For task f i Post-insertion task The new preparation time is different from the time before insertion. The original preparation time lf a QF i For task f i If the above formula holds true, proceed to S500 for the required continuous observation time; otherwise, proceed to S400.

[0148] S400, Task The earliest possible start time sf a Shift backward, minimum time length for shifting backward

[0149]

[0150] Will moving the task to the back cause task conflicts, and will this introduce new tasks? Post-shift time MF a The judgment condition is d <MF a If true, and the shift to the next position is allowed, then sf a =sf a +d; af a =af a +d; MF a =MF a -d, switch to S500; otherwise, task and There is not enough free time to insert task f i a = a + 1, then switch to S300;

[0151] S500, SF i =af a-1 +lf i ;af i =sf i +QF i ;but

[0152]

[0153] Task f i The criterion for determining whether the earliest possible start time of execution falls within the candidate time window is: sf i ≥SF i If approved, you will be transferred to S700; otherwise, you will be transferred to S600.

[0154] S600, Judgment Task f i Is there enough leeway for MF to move back? i Can guarantee sf i If it falls within the candidate time window, the judgment condition is sf i +MF i ≥SF i If the condition is met, proceed to S700; otherwise, if a = a - 1, proceed to S300.

[0155] S700, Mission F i The criterion for determining whether the earliest possible completion time falls within the candidate time window is af. i ≤AF i If true, proceed to S800; otherwise, a = a + 1, proceed to S300.

[0156] S800, satellite j The h-th candidate time window satisfies the task time constraint. If z = 0, then set z = 1 and go to S200.

[0157] S900, such as task f i None of the candidate time windows to be judged meet the task constraints. j Bid rejected, withdrawal.

[0158] By judging the satisfaction of time constraints, the candidate time window set FW is finally selected. ij Find a visible time window sequence that satisfies the constraints, denoted as FW′. ij FW′ ij Each visible time window All correspond to satellite agents j A new set of candidate contract tasks s j The set of all new candidate contract tasks, denoted as F′ j , Now we need to optimize from F′ according to the preset optimization objective. j Choose the best one (1≤h≤u) to submit a bid.

[0159] Considering that the final goal of task allocation is to minimize the total energy consumption of the distributed satellite system in completing the observation tasks, this approach prioritizes completing... Energy required for the task and task f i The difference in energy consumption before insertion is used as the optimization objective to guide bidding decisions. However, considering that multiple candidate contract task sets with the same energy difference may still exist, task f is further selected. i The earliest completed candidate contract task set is used as the bidding task set to ensure the uniqueness of satellite bidding.

[0160] Insert task f i The new contract task set generated later Energy consumed Energy E consumed by the original contract task set before insertion j The difference is denoted as have The bidding optimization target is set as follows Further select target as Here For task f i In the candidate time window The actual completion time.

[0161] Through the above process, the bidding satellite agent can confirm its ability to complete the bidding task, thus deciding whether to submit a bid. At this point, the management agent must manage all agents capable of completing the task. iThe capabilities of the working satellite agents are evaluated, and the best working satellite agent is selected to complete the task.

[0162] Therefore, based on the principle of minimizing the energy consumed to complete the overall observation mission, the satellite agent evaluation strategy is tailored to different operational satellite agents for different mission requirements. i The bidding proposals are determined using the rule of minimizing energy consumption in the working satellite agent bidding strategy, i.e., the objective function is...

[0163] This invention provides a service-satisfaction-oriented bilateral matching system between missions and remote sensing satellites, comprising:

[0164] The acquisition module is used to acquire remote sensing satellite clusters used to jointly complete the tasks based on the task set and satellite resources, wherein the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks;

[0165] The construction module is used to build a task-remote sensing satellite matching model based on the task set, satellite resources and remote sensing satellite cluster, with the goal of minimizing overall energy consumption.

[0166] The solution module is used to complete the task planning of the remote sensing satellite cluster using a distributed collaborative task assignment method based on the task-remote sensing satellite matching model.

[0167] This invention provides a storage medium storing a computer program for bilateral matching of tasks and remote sensing satellites for service satisfaction, wherein the computer program causes a computer to execute the bilateral matching method of tasks and remote sensing satellites as described above.

[0168] This invention provides an electronic device, comprising:

[0169] One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the tasks described above and bilateral matching methods with remote sensing satellites.

[0170] It is understood that the service-oriented task and remote sensing satellite bilateral matching system, storage medium and electronic device provided in the embodiments of the present invention correspond to the service-oriented task and remote sensing satellite bilateral matching method provided in the embodiments of the present invention. The explanation, examples and beneficial effects of the relevant contents can be referred to the corresponding parts of the task and remote sensing satellite bilateral matching method, and will not be repeated here.

[0171] In summary, compared with existing technologies, it has the following beneficial effects:

[0172] This invention provides a task-satellite bilateral matching method oriented towards service fulfillment. This method establishes a structured and standardized system for remote sensing satellites, establishes a bilateral matching relationship between tasks and remote sensing satellites, and proposes the concept of remote sensing satellite clusters. Remote sensing satellite clusters improve the efficiency of remote sensing satellite utilization and, when the environment changes, can quickly form clusters that meet the current common task requirements, and can dynamically adjust the remote sensing satellite configuration in real time to adapt to environmental changes. A task-satellite matching model is designed, and a distributed collaborative task assignment method is used to complete the remote sensing satellite cluster task planning. This method can quickly complete the remote sensing satellite task allocation, reduce time costs, and effectively improve the optimization efficiency of satellites in completing tasks.

[0173] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0174] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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. Such 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 bilateral matching method between a task and a remote sensing satellite for service satisfaction, characterized in that, include: S1. Based on the task set and satellite resources, obtain remote sensing satellite clusters for jointly completing the tasks, wherein the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks; S2. Based on the task set, satellite resources and remote sensing satellite cluster, construct a task-remote sensing satellite matching model with the goal of minimizing overall energy consumption; S3. Based on the task-remote sensing satellite matching model, a distributed collaborative task assignment method is used to complete the task planning of the remote sensing satellite cluster. The mission-remote sensing satellite matching model in S2 includes: The objective function is to minimize the overall energy consumption. Where S represents the set of satellites in a distributed satellite system, S={s1,s2,...,s...} w }; s j Let $j$ represent the $j$-th satellite, where $j = {1, 2, ..., w} and $w$ is the total number of satellites. F represents the set of tasks to be observed, F={f1,f2,...,f v }, where v is the total number of tasks; S i Indicates the use of f to jointly complete the task. i The remote sensing satellite cluster, S i ∈S; p ji Indicates satellite s j Complete task f i The energy consumed; For decision variables, if the task and tasks All of them will occupy satellites j And the task Follow the mission Then execute, =1, otherwise =0, where , ∈F, ; The mission-remote sensing satellite matching model in S2 also includes: Constraints: (1) A task can only occupy one satellite when it is executed, and the task can only be executed once. If a task is scheduled to be executed, there can only be one follow-up task. (2) Ensure satellite s j There can only be one starting task in the task queue; (3) Ensure satellite s j Tasks in the task queue are executed sequentially, meaning their execution times do not overlap. If task f i Occupying satellites j Then its predecessor and successor missions also occupy satellite space. j ; (4) Determine the order of execution of the two tasks; (5) Ensure that the task can only be executed within one time window; (6) The execution time of the task is determined to be within the corresponding time window; （7） ； in, This indicates that if task f i Occupying satellites j Task f i Let f0 = 0 be the actual start time; lf i This indicates that if task f i Occupying satellites j Task f i Execution preparation time, lf i ≥0; l ij Indicates task f i For satellites s j The time occupied, l ij ≥0; D ij Indicates task f i Occupying satellites j The number of time windows allowed at any given time; FM ij This indicates that if task f i Occupying satellites j The set of time windows allowed at any time; in and They represent f respectively i Occupying satellites j Release the start and end times of the allowed h-th time window; As a decision variable, if task f i Occupying satellites j The time window occupied during execution is ,but =1; otherwise =0; CQ i This indicates that if task f i Occupying satellites j The time window occupied during execution is Then satellite s j Execute task f i The earliest possible start time; C i This indicates that if task f i Occupying satellites j The time window occupied during execution is Then satellite s j Execute task f i The latest possible start time; 。 2. The task-to-remote sensing satellite bilateral matching method oriented towards service satisfaction as described in claim 1, characterized in that, The S3 method employs a distributed collaborative task assignment approach, selecting a conflict-free and time-constrained visible time window for the execution of each task within the corresponding remote sensing satellite cluster to complete task planning. Define any satellite s in the remote sensing satellite cluster j The current queue of tasks to be observed is ;s j For task f i The set of candidate visible time windows to be judged is , ; The time constraint verification algorithm includes: S100. Initialize the values ​​to h=0, a=0, z=0; where h is the candidate visible time window to be judged. The number; a is the insertion point position; z is a logical value indicating whether there is a visible time window that satisfies the time constraint; 1 indicates yes, 0 indicates no; S200, if h <D ij If z=1, then set h=h+1, a=1, and proceed to S300; otherwise, set z=1, select the optimal time window for bidding, and exit; otherwise, proceed to S900. S300, If a>q+1, If the task is not specified, proceed to S200; otherwise, determine the task. and Is there enough free time between them to insert task f? i The judgment is as follows: in, For task f i Post-insertion task The new preparation time is different from the time before insertion. The original preparation time lf a QF i For task f i If the above formula holds true, proceed to S500 for the required continuous observation time; otherwise, proceed to S400. S400, Task The earliest possible start time Shift backward, minimum time length for shifting backward Will moving the task to the back cause task conflicts, and will this introduce new tasks? Post-shift time MF a The judgment condition is d <MF a If true, and the shift to the next position is allowed, then sf a =sf a +d; af a =af a +d; MF a =MF a -d, switch to S500; otherwise, task and There is not enough free time to insert task f i a = a + 1, then switch to S300; S500, let sf i = af a-1 + lf i ; af i = sf i + QF i ; then Task f i The criterion for determining whether the earliest possible start time of execution falls within the candidate time window is: sf i ≥SF i If approved, you will be transferred to S700; otherwise, you will be transferred to S600. S600, Judgment Task f i Is there enough leeway for MF to move back? i Can guarantee sf i If it falls within the candidate time window, the judgment condition is sf i +MF i ≥SF i If the condition is met, proceed to S700; otherwise, a = a - 1, proceed to S300. S700, Mission F i The criterion for determining whether the earliest possible completion time falls within the candidate time window is af. i ≤AF i If true, proceed to S800; otherwise, a = a + 1, proceed to S300. S800, satellite j The h-th candidate time window satisfies the task time constraint. If z=0, then set z=1 and go to S200. S900, such as task f i None of the candidate time windows to be judged meet the task constraints. j Bid rejected, withdrawal.

3. The task-to-remote sensing satellite bilateral matching method oriented towards service satisfaction as described in claim 2, characterized in that, If there are multiple candidate time windows that meet the time constraints, the best satellite is selected for observation according to the preset optimization objective. The optimization objective is to minimize the difference between the energy required to complete the task and the energy consumed before the task is inserted. If they are the same, the selection continues with minimizing the actual completion time of the task as the objective.

4. A mission-to-remote-sensing satellite bilateral matching system oriented towards service fulfillment, characterized in that, The method for performing task-to-remote-satellite bilateral matching as described in claim 1 includes: The acquisition module is used to acquire remote sensing satellite clusters used to jointly complete the tasks based on the task set and satellite resources, wherein the number of remote sensing satellite clusters corresponds one-to-one with the number of tasks; The construction module is used to build a task-remote sensing satellite matching model based on the task set, satellite resources and remote sensing satellite cluster, with the goal of minimizing overall energy consumption. The solution module is used to complete the task planning of the remote sensing satellite cluster using a distributed collaborative task assignment method based on the task-remote sensing satellite matching model.

5. A storage medium, characterized in that, It stores a computer program for bilateral matching of tasks and remote sensing satellites for service satisfaction, wherein the computer program causes a computer to execute the bilateral matching method of tasks and remote sensing satellites as described in any one of claims 1 to 3.

6. An electronic device, characterized in that, include: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the mission-to-remote-satellite bilateral matching method as described in any one of claims 1 to 3.

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