A multi-satellite collaborative mission planning method and device for multi-observation missions

Abstract

The present invention relates to a multi-satellite collaborative task planning method and device for multiple observation tasks, which belongs to the field of remote sensing satellite technology and solves the problems of high solution complexity and poor interpretability in existing multi-satellite collaborative task planning. The method includes: obtaining observation task information, and synchronously parsing the observation timing, satellite sensor mode, data timeliness and priority in the observation task information; calculating the observation task weight based on the priority of the observation task and matching the observation with the data transmission resource, the observation task weight being the importance of each observation task in the overall observation task; constructing a multi-objective hierarchical task planning model based on maximizing the satisfaction of the observation task and maximizing the reliability of task implementation to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems. By simplifying the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems, the model can be solved quickly and has strong interpretability.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing satellite technology, and in particular to a multi-satellite collaborative mission planning method and device for multiple observation missions. Background Art

[0002] Multi-satellite collaborative mission planning is key to achieving multi-satellite coordinated observation. The quality of the planning scheme directly impacts the performance of multi-satellite observation missions. Most research on multi-satellite collaborative mission planning focuses solely on observation tasks, without comprehensively considering the impact of data transmission resources and full-process reliability on the optimization of multi-satellite collaborative mission planning schemes. Furthermore, multi-satellite collaborative mission planning is often a multi-objective planning problem, resulting in high complexity and limited interpretability.

[0003] As can be seen from this, the existing multi-satellite collaborative mission planning methods for multi-observation missions still have inconveniences and shortcomings, and are in urgent need of further improvement. The goal of creating a multi-satellite collaborative mission planning method and device that can quickly solve, is highly interpretable, and has good mission execution performance for multi-observation missions has become a highly sought-after goal in the industry. Summary of the Invention

[0004] In view of the above analysis, the embodiments of the present invention aim to provide a multi-satellite collaborative mission planning method and device for multiple observation tasks, so as to solve the problems of high solution complexity and poor interpretability in the existing multi-satellite collaborative mission planning.

[0005] On the one hand, an embodiment of the present invention provides a multi-satellite collaborative task planning method for multiple observation tasks, including: obtaining observation task information, and synchronously parsing the observation timing, satellite sensor mode, data timeliness and priority in the observation task information; calculating the observation task weight based on the priority of the observation task and matching the observation with data transmission resources, wherein the observation task weight is the importance of each observation task in the overall observation task; and constructing a multi-objective hierarchical task planning model based on maximizing observation task satisfaction and maximizing task implementation reliability to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems.

[0006] The beneficial effects of the above technical solution are as follows: the goal of task planning is to maximize the satisfaction of observation tasks and the reliability of task implementation; based on the above two goals, a multi-objective hierarchical task planning scheme optimization method is designed to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems. The model can be solved quickly and has strong interpretability.

[0007] Based on a further improvement of the above method, calculating the observation task weight based on the priority of the observation task includes: determining the weight of each observation task according to the priority of the observation task, wherein the smaller the priority value of the observation task, the higher the corresponding priority, and the greater the weight of the observation task:

[0008]

[0009] Among them, Priority i is the priority of the observation task, and i is the i-th observation task.

[0010] Based on a further improvement of the above method, matching observations with data transmission resources includes screening available satellites and data transmission resources based on the observation mission, satellite characteristics and data transmission resource status.

[0011] Based on the further improvement of the above method, the observation task satisfaction includes observation opportunity satisfaction, data timeliness satisfaction, and observation mode satisfaction, wherein,

[0012]

[0013]

[0014] De i =De1 i De2 i ·De3 i ,

[0015] Among them, De is the overall observation task satisfaction, w i For the observation mission Mis i Weight, De i For the observation mission Mis i Observation task satisfaction, Priority i For the observation mission Mis i Priority, De1 i For the observation mission Mis i The observation opportunity satisfaction, De2 i For the observation mission Mis i Data timeliness satisfaction, De3 i For the observation mission Mis i The observation mode satisfaction.

[0016] Based on a further improvement of the above method, the task implementation reliability includes observation reliability, data transmission reliability, and processing reliability. When the observation task is completed collaboratively by multiple observation opportunities, the reliability of the observation task implementation is as follows:

[0017]

[0018]

[0019] in, For the observation mission Mis i The reliability of the jth observation, For observation reliability, is the data transmission reliability, To process reliability.

[0020] Based on the further improvement of the above method, a multi-objective hierarchical task planning model is constructed to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems, further including: when the observation task time is urgent, the observation resources are relatively limited, or the overall reliability of the task implementation is high, first maximize the observation task satisfaction, and then maximize the task implementation reliability; and when the observation task time and the observation resources are relatively abundant, or the overall reliability of the task implementation is low, first maximize the task implementation reliability, and then maximize the observation task satisfaction.

[0021] Based on a further improvement of the above method, calculating the data timeliness satisfaction includes: selecting data transmission resources that meet the timeliness requirements according to the following rules for all observation opportunities corresponding to each observation task in turn, wherein the rules include: calculating the data transmission margin and calculating the usage conflict; and calculating the data timeliness satisfaction based on the allocation of the data transmission resources.

[0022] Based on a further improvement of the above method, calculating the data transmission margin includes: for each observation opportunity, comprehensively considering the availability of data transmission resources and timeliness requirements, calculating the data transmission resources actually available for each observation opportunity, wherein the number of actually available data transmission resources is the data transmission margin of each observation opportunity; selecting the observation opportunity with the smallest data transmission margin to preferentially allocate data transmission resources; and when there are multiple observation plans with the same data transmission margin, allocating data transmission resources to the observation opportunities of high-priority observation tasks.

[0023] Based on a further improvement of the above method, calculating the usage conflict includes: calculating the usage conflict situation for the data transmission resources actually available for each observation opportunity, that is, the number of observation opportunities where no data transmission resources are available; selecting the data transmission resource with the smallest usage conflict to allocate to each observation opportunity; and when the usage conflicts are the same, selecting the data transmission resource with high timeliness.

[0024] On the other hand, an embodiment of the present invention provides a multi-satellite collaborative task planning device for multiple observation tasks, including: an observation task acquisition module for acquiring observation tasks and synchronously analyzing the observation timing, satellite sensor mode, data timeliness and priority in the observation tasks; a weight calculation module for calculating the observation task weight based on the priority of the observation task, wherein the observation task weight is the importance of each observation task in the overall observation task; a matching module for matching observations with data transmission resources; and a model construction module for constructing a multi-objective hierarchical task planning model based on maximizing observation task satisfaction and maximizing task implementation reliability to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems.

[0025] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0026] 1. The goals of mission planning are to maximize observation mission satisfaction and mission implementation reliability. Based on these two goals, a multi-objective hierarchical mission planning optimization method is designed. This method simplifies the multi-objective planning problem for multiple observation missions into multiple serial single-objective planning problems. The model can be solved quickly and has strong interpretability.

[0027] 2. Comprehensively consider the satisfaction of observation mission requirements and the reliability of mission implementation, taking into account the requirements of observation missions in terms of observation timing, observation mode, data transmission requirements, and mission execution reliability;

[0028] 3. Based on the hierarchical planning method, the multi-objective planning problem is simplified into multiple single-objective planning problems, which supports flexible selection of planning objectives based on planning conditions, helps to quickly solve the model, and has strong interpretability and good task execution effect.

[0029] In the present invention, the above-mentioned technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of the present invention will be described in the following description, and some advantages will become apparent from the description or be learned through practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like parts throughout the drawings.

[0031] Figure 1 Flowchart of a multi-satellite collaborative mission planning method for multi-observation missions according to an embodiment of the present invention;

[0032] Figure 2This is a specific flow chart of a multi-satellite collaborative mission planning method for multiple observation missions provided according to an embodiment of the present invention.

[0033] Figure 3 A block diagram of a multi-satellite collaborative mission planning method for multiple observation missions according to an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, and are not used to limit the scope of the present invention.

[0035] A specific embodiment of the present invention discloses a multi-satellite collaborative mission planning method for multiple observation missions. Figure 1 The multi-satellite collaborative task planning method for multiple observation tasks includes: in step S102, obtaining observation task information and synchronously analyzing the observation timing, satellite sensor mode, data timeliness and priority in the observation task information; in step S104, calculating the observation task weight based on the priority of the observation task and matching the observation with data transmission resources, wherein the observation task weight is the importance of each observation task in the overall observation task; and in step S106, constructing a multi-objective hierarchical task planning model based on maximizing observation task satisfaction and maximizing task implementation reliability to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems.

[0036] Compared with the existing technology, the multi-satellite collaborative mission planning method for multiple observation tasks provided in this embodiment has the goals of maximizing the satisfaction of observation tasks and maximizing the reliability of task implementation; based on the above two goals, a multi-objective hierarchical task planning scheme optimization method is designed, which simplifies the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems. The model can be solved quickly and has strong interpretability.

[0037] In the following, reference will be made to Figure 1 and Figure 2 , each step of the multi-satellite collaborative mission planning method for multi-observation missions according to an embodiment of the present invention is described in detail.

[0038] In step S102, observation mission information is obtained and analyzed simultaneously for observation timing, satellite sensor mode, data timeliness, and priority. Observation timing refers to the time period during which a remote sensing satellite observes a target. Data timeliness requires that the remote sensing satellite transmit observed data within a specified time period, thus meeting the timeliness requirement.

[0039] In step S104, the observation task weight is calculated based on the priority of the observation task and the observation is matched with the data transmission resource, wherein the observation task weight is the importance of each observation task in the overall observation task. Specifically, the calculation of the observation task weight based on the priority of the observation task includes: determining the weight of each observation task according to the priority of the observation task, wherein the smaller the priority value of the observation task, the higher the corresponding priority, and the greater the observation task weight:

[0040]

[0041] Among them, Priority i is the priority of the observation task, and i is the i-th observation task.

[0042] Matching observations with data transmission resources involves screening available satellites and data transmission resources based on the observation mission, satellite characteristics, and data transmission resource status.

[0043] In step S106, a multi-objective hierarchical task planning model is constructed based on maximizing the overall observation task satisfaction and maximizing the overall task implementation reliability to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems.

[0044] Specifically, the observation task satisfaction includes observation opportunity satisfaction, data timeliness satisfaction, and observation mode satisfaction (i.e., the satisfaction of the sensor mode required for observation).

[0045]

[0046]

[0047] De i =De1 i De2 i ·De3 i ,

[0048] Among them, De is the overall observation task satisfaction, w i For the observation mission Mis i Weight, De i For the observation mission Mis i Observation task satisfaction, Priority i For the observation mission Mis i Priority, De1 i For the observation mission Mis i The observation opportunity satisfaction, De2 i For the observation mission Mis i Data timeliness satisfaction, De3 i For the observation mission Mis iThe observation mode satisfaction degree (i.e., the satisfaction degree of the sensor mode required for observation).

[0049] Calculating data timeliness satisfaction includes: selecting data transmission resources that meet timeliness requirements for all observation opportunities corresponding to each observation task in accordance with the following rules, wherein the rules include: calculating data transmission margin and calculating usage conflicts; and calculating data timeliness satisfaction based on data transmission resource allocation. Specifically, calculating data transmission margin includes: for each observation opportunity, comprehensively considering data transmission resource availability and timeliness requirements, calculating the data transmission resources actually available for each observation opportunity, wherein the number of actually available data transmission resources is the data transmission margin for each observation opportunity; selecting the observation opportunity with the smallest data transmission margin to prioritize data transmission resources allocation; and when there are multiple observation plans with the same data transmission margin, allocating data transmission resources to the observation opportunities of the high-priority observation task. Calculating usage conflicts includes: calculating usage conflicts for the actually available data transmission resources for each observation opportunity, i.e., the number of observation opportunities resulting in no available data transmission resources; selecting the data transmission resources with the smallest usage conflicts to allocate to each observation opportunity; and when usage conflicts are the same, selecting data transmission resources with high timeliness.

[0050] The reliability of task implementation includes observation reliability, data transmission reliability, and processing reliability. When the observation task is completed by multiple observation opportunities, the reliability of observation task implementation is as follows:

[0051]

[0052]

[0053] in, For the observation mission Mis i The reliability of the jth observation, For observation reliability, is the data transmission reliability, To process reliability.

[0054] Constructing a multi-objective hierarchical task planning model to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems further includes: when the observation task time is urgent, the observation resources are relatively limited, or the overall task implementation reliability is high, first maximize the observation task satisfaction, and then maximize the task implementation reliability; and when the observation task time and observation resources are relatively abundant, or the overall task implementation reliability is low, first maximize the task implementation reliability, and then maximize the observation task satisfaction.

[0055] Another specific embodiment of the present invention discloses a multi-satellite collaborative task planning device for multiple observation tasks, including: an observation task acquisition module 302, used to acquire observation tasks and synchronously analyze the observation timing, satellite sensor mode, data timeliness and priority in the observation tasks; a weight calculation module 304, used to calculate the observation task weight based on the priority of the observation task, wherein the observation task weight is the importance of each observation task in the overall observation task; a matching module 306, used to match observations with data transmission resources; and a model construction module 308, used to construct a multi-objective hierarchical task planning model based on maximizing observation task satisfaction and maximizing task implementation reliability to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems.

[0056] In the following, reference will be made to Figure 2 , a multi-satellite collaborative mission planning method for multi-observation missions according to an embodiment of the present invention is described in detail by way of specific examples.

[0057] This embodiment provides a multi-satellite collaborative mission planning method for multiple observation missions. Figure 2 This process primarily involves analyzing observation task acceptance, calculating observation task weights, matching observation and data transmission resources, and constructing and solving planning models. Observation task acceptance analysis accepts observation tasks, extracts demand-related factors, and calculates task priorities through observation task weights, determining the importance of each task within the task set. Observation and data transmission resources are then allocated based on demand factors and priorities through matching observation and data transmission resources.

[0058] S1. Observation mission acceptance analysis:

[0059] Observation mission acceptance and analysis: Accept observation missions and simultaneously analyze factors such as observation timing, satellite sensor mode, data timeliness and priority in the observation missions.

[0060] Each observation task is described by a four-tuple consisting of observation time, satellite sensor mode, data timeliness, and priority:

[0061] ScoutDem={ScotTDem,SensDem,TimeLDem,Priority},

[0062] ScotTDem can be expressed as a time interval, observation frequency, and interval. The observation time interval can be expressed as [s_STD, e_STD]; the observation frequency can be expressed as FSTD; and the observation time interval can be expressed as ISTD.

[0063] The satellite sensor mode (SensDem) covers the observation mission's requirements for payload type, observation mode, and resolution. Each observation mission provides a satellite sensor mode sequence when determining its satellite sensor mode requirements. The order of the sequence indicates the priority of the satellite sensor mode requirements.

[0064] Data timeliness TimeLDem expresses the time delay between the completion of observation task data processing and the observation.

[0065] Priority describes the priority sequence of a certain observation task among many observation tasks. The smaller the value, the higher the priority.

[0066] S2. Calculation of observation task weights and matching of observation and data transmission resources:

[0067] The observation task weight calculation is based on the observation task priority. The importance of each observation task in the overall observation task is calculated to lay the foundation for the optimization of planning schemes.

[0068] The matching of observation and data transmission resources is based on the observation mission, satellite characteristics and data transmission resource status. Available satellites and data transmission resources are screened, and satellite visibility analysis of observation missions and station forecast calculations are carried out.

[0069] S3. Planning model construction and solution:

[0070] The objectives of the task planning are to maximize the satisfaction of the observation task and the reliability of the task implementation. Based on the above two objectives, a multi-objective hierarchical task planning scheme optimization method is designed to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems.

[0071] Planning model construction and solution Conduct multi-satellite collaborative mission planning objectives and constraints analysis, carry out planning objective calculation method design and planning constraint formal description, build planning model; solve the planning model based on a certain algorithm.

[0072] The optimization of multi-observation mission planning schemes primarily considers two aspects: mission satisfaction and mission implementation reliability. Mission satisfaction is a comprehensive balance of observation opportunity satisfaction, data timeliness satisfaction, and observation mode satisfaction. Mission implementation reliability is a comprehensive balance of observation reliability, data transmission reliability, and processing reliability.

[0073] As a further improvement of the present invention, in said S3: designing a multi-objective hierarchical task planning scheme optimization method, simplifying the multi-objective planning problem for multi-observation tasks into multiple serial single-objective planning problems includes:

[0074] When the observation task is urgent, the observation resources are relatively limited, or the overall reliability of the task implementation is high, the first consideration is to maximize the satisfaction of the observation task, and then consider the reliability of the task implementation. Consider the following planning methods:

[0075]

[0076] (P2)max Re(x)

[0077]

[0078] Where De(x) is the observed task satisfaction, Re(x) is the task implementation reliability, x is the set of planning schemes, and x1 is the subset of x.

[0079] When the time and resources for observation tasks are relatively abundant or the reliability of task implementation is generally low, the reliability of task implementation should be considered first, and then the maximization of observation task satisfaction should be considered. The following planning methods can be considered:

[0080]

[0081] (P2)max De(x)

[0082]

[0083] Where De(x) is the observed task satisfaction, Re(x) is the task implementation reliability, x is the set of planning schemes, and x1 is the subset of x.

[0084] 1. Calculation of observation task weights

[0085] The two main indicators of the planning scheme are observation task satisfaction and task implementation reliability. The overall indicator of the planning scheme needs to be integrated based on the individual indicators of each observation task. The overall indicator value of the planning scheme can be calculated based on the weighted indicators of observation task satisfaction and task implementation reliability of each observation task.

[0086] The weighted value of each observation task is based on the observation task priority i OK, the smaller the priority value, the higher the corresponding priority and the greater the weighted value:

[0087]

[0088] 2. Observation mission satisfaction calculation

[0089] Assume that the observation tasks Mis1, Mis2, ..., Mis NumM , the corresponding observation task satisfactions are De1, De2, ..., De NumM , the observation task satisfaction is comprehensively expressed by the observation opportunity satisfaction, data timeliness satisfaction, and observation mode satisfaction:

[0090] De i =De1 i De2 i ·De3 i ,

[0091] The overall observation task satisfaction of the planning scheme can be expressed as:

[0092]

[0093] (1) Observation timing satisfaction De1 i

[0094] For the observation opportunity expressed in time intervals, the observation opportunity satisfaction can be expressed as:

[0095]

[0096] Among them, [s_sco i ,e_sco i ] is the observation mission Mis i Actual observation window, [s_STD i ,e_STD i ] is the observation mission Mis i The observation task window is 0<x<1 and becomes smaller as the distance between observation time and observation opportunity increases.

[0097] For observation opportunities expressed in terms of observation frequency and time interval, the satisfaction of observation opportunities is expressed as:

[0098]

[0099] Where, FS i is the actual observation frequency, FSTD i is the required observation frequency, 0<δ≤1 and becomes smaller as the time interval between two adjacent observations deviates from the interval requirement.

[0100] (2) Data timeliness satisfaction

[0101] Some observation missions require multiple observation opportunities to complete the observation mission, and there is often a one-to-many relationship between observation missions and observation opportunities. In a specific planning scheme, the data transmission resources that meet the timeliness requirements are selected for all observation opportunities corresponding to each observation mission in turn. The rules are as follows:

[0102] Step 1: Calculate the data transmission margin. For each observation opportunity, consider the available data transmission resources and timeliness requirements. The actual number of available data transmission resources is the data transmission margin for that observation opportunity. Prioritize the observation opportunity with the smallest data transmission margin for data transmission resource allocation. If multiple observation plans have the same data transmission margin, data transmission resources are allocated first to the observation opportunity with the highest priority.

[0103] Step 2: Calculate usage conflicts. For each observation opportunity, calculate the usage conflicts for the available data transmission resources. This is the number of observation opportunities where the data transmission resources would be unavailable if they were allocated to that observation opportunity. The data transmission resource with the lowest usage conflict is assigned to that observation opportunity. If the usage conflicts are the same, the data transmission resource with the highest timeliness is prioritized.

[0104] Based on the allocation of data transmission resources, calculate the data timeliness satisfaction De2 i as follows:

[0105]

[0106] Among them, NumDem i For the observation mission Mis i The number of data transmission resources required, NumTD i is the actual assignment to the observation task Mis i The number of data transmission resources.

[0107] Since the above-mentioned data transmission resource allocation method is a deterministic algorithm, therefore, for the same planning scheme, as long as the input conditions are the same, the corresponding data transmission resource allocation results must be the same.

[0108] (3) Observation mode satisfaction

[0109] The demand of observation tasks for observation modes reflects the demand of observation opportunities for observation modes. Each observation opportunity has a list of observation modes. When planning, try to choose the observation mode with a priority of 1, and then the observation mode with a relatively lower priority. It can be expressed as:

[0110]

[0111] in, For the observation mission Mis i The satisfaction degree of the observation mode of the jth observation, if the observation mode in the planning scheme is the observation mode with the observation task priority order of 1, then Take the value 1. If the observation mode in the planning scheme is no longer in the observation task, then The value is 0. And it becomes smaller as the priority increases. When an observation task has multiple observation opportunities, the observation mode satisfaction of the corresponding observation task can be expressed as:

[0112]

[0113] 3. Calculation of mission implementation reliability

[0114] The reliability of task implementation mainly includes observation reliability, data transmission reliability, and processing reliability. When the observation task is completed by multiple observation opportunities, the reliability of the observation task implementation in the planning scheme can be expressed as:

[0115]

[0116]

[0117] Where, For the observation mission Mis i The reliability of the jth observation, For observation reliability, is the data transmission reliability, To ensure the reliability of the process, the values are obtained through long-term accumulation of data statistics.

[0118] The reliability Re of the overall task implementation of the planning scheme is expressed as:

[0119]

[0120] This embodiment also provides a multi-satellite collaborative mission planning device for multiple observation missions, comprising: one or more processors; and a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-satellite collaborative mission planning method for multiple observation missions described above. Because the hardware in the above device is conventional hardware in the prior art, its detailed description is omitted here.

[0121] In summary, in the planning of multi-satellite collaborative missions, the present invention sets the goals of mission planning as maximizing the satisfaction of observation missions and maximizing the reliability of mission implementation; based on the above two goals, a multi-objective hierarchical mission planning scheme optimization method is designed, and the multi-objective planning problem for multiple observation tasks is simplified into multiple serial single-objective planning problems. The model can be solved quickly and has strong interpretability; in addition, the observation mission satisfaction comprehensively considers the satisfaction of observation opportunity, data timeliness and observation mode; the mission implementation reliability comprehensively considers the observation reliability, data transmission reliability and processing reliability; it takes into account and balances the multi-directional requirements of the observation mission, which is conducive to mission execution and has a good task execution effect.

[0122] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0123] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. A multi-satellite collaborative mission planning method for multiple observation missions, characterized in that: include: Obtain observation mission information and simultaneously analyze the observation timing, satellite sensor mode, data timeliness and priority in the observation mission information; Calculating observation task weights based on the priorities of the observation tasks and matching observations with data transmission resources, wherein the observation task weights represent the importance of each observation task in the overall observation task; and Based on the maximization of observation task satisfaction and task implementation reliability, a multi-objective hierarchical task planning model is constructed to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems. The observation task satisfaction includes observation opportunity satisfaction, data timeliness satisfaction, and observation mode satisfaction. From i =From1 i ·From2 i ·De3 i , Among them, De is the overall observation task satisfaction, w i For the observation mission Mis i Weight, De i For the observation mission Mis i Observation task satisfaction, Priority i For the observation mission Mis i Priority, De1 i For the observation mission Mis i The observation opportunity satisfaction, De2 i For the observation mission Mis i Data timeliness satisfaction, De3 i For the observation mission Mis i Observation mode satisfaction; The task implementation reliability includes observation reliability, data transmission reliability, and processing reliability. When the observation task is completed collaboratively by multiple observation opportunities, the reliability of the observation task implementation is as follows: in, For the observation mission Mis i The reliability of the jth observation, For observation reliability, is the data transmission reliability, To process reliability.

2. The multi-satellite collaborative mission planning method for multi-observation missions according to claim 1, characterized in that: Calculating the observation task weight based on the priority of the observation task includes: The weight of each observation task is determined according to the priority of the observation task, wherein the smaller the priority value of the observation task, the higher the corresponding priority, and the greater the weight of the observation task: Among them, Priority i is the priority of the observation task, and i is the i-th observation task.

3. The multi-satellite collaborative mission planning method for multi-observation missions according to claim 1, characterized in that: Matching observations with data transmission resources includes screening available satellites and data transmission resources based on the observation mission, satellite characteristics, and data transmission resource status.

4. The multi-satellite collaborative mission planning method for multi-observation missions according to claim 1, characterized in that: Constructing a multi-objective hierarchical task planning model to simplify the multi-objective planning problem for multi-observation tasks into multiple serial single-objective planning problems further includes: When the observation task is urgent, observation resources are limited, or the overall reliability of the task implementation is high, first maximize the satisfaction of the observation task, and then maximize the reliability of the task implementation; and When the observation task time and the observation resources are sufficient, or the overall reliability of the task implementation is low, the task implementation reliability is maximized first, and then the observation task satisfaction is maximized.

5. The multi-satellite collaborative mission planning method for multi-observation missions according to claim 2, characterized in that: Calculating the data timeliness satisfaction includes: Selecting data transmission resources that meet timeliness requirements according to the following rules for all observation opportunities corresponding to each observation task, wherein the rules include: calculating data transmission margin and calculating usage conflicts; and Based on the data transmission resource allocation, the data timeliness satisfaction is calculated.

6. The multi-satellite collaborative mission planning method for multi-observation missions according to claim 5, characterized in that: Calculating data transmission margin includes: For each observation opportunity, the data transmission resources actually available for each observation opportunity are calculated based on the availability of data transmission resources and timeliness requirements, where the number of actually available data transmission resources is the data transmission margin for each observation opportunity; Select the observation opportunity with the smallest data transmission margin to prioritize the allocation of data transmission resources; and When there are multiple observation plans with the same data transmission margin, data transmission resources are allocated to the observation opportunities of the high-priority observation tasks.

7. The multi-satellite collaborative mission planning method for multi-observation missions according to claim 5, characterized in that: Computational use conflicts include: For each observation opportunity, calculate the actual available data transmission resources, and the number of observation opportunities resulting in the use of conflicting data transmission resources. Selecting the data transmission resource with the least usage conflict to allocate to each observation opportunity; and When the usage conflicts are the same, a data transmission resource with high timeliness is selected.

8. A multi-satellite collaborative mission planning device for multiple observation missions, characterized in that: include: An observation task acquisition module is used to obtain observation task information and simultaneously analyze the observation timing, satellite sensor mode, data timeliness and priority in the observation task information; A weight calculation module, configured to calculate the observation task weight based on the priority of the observation task, wherein the observation task weight is the importance of each observation task in the overall observation task; A matching module for matching observations with data transmission resources; and A model building module is used to construct a multi-objective hierarchical task planning model based on maximizing the satisfaction of observation tasks and maximizing the reliability of task implementation, so as to simplify the multi-objective planning problem for multiple observation tasks into multiple serial single-objective planning problems; The observation task satisfaction includes observation opportunity satisfaction, data timeliness satisfaction, and observation mode satisfaction. From i =From1 i ·From2 i ·De3 i , Among them, De is the overall observation task satisfaction, w i For the observation mission Mis i Weight, De i For the observation mission Mis i Observation task satisfaction, Priority i For the observation mission Mis i Priority, De1 i For the observation mission Mis i The observation opportunity satisfaction, De2 i For the observation mission Mis i Data timeliness satisfaction, De3 i For the observation mission Mis i Observation mode satisfaction; The task implementation reliability includes observation reliability, data transmission reliability, and processing reliability. When the observation task is completed collaboratively by multiple observation opportunities, the reliability of the observation task implementation is as follows: in, For the observation mission Mis i The reliability of the jth observation, For observation reliability, is the data transmission reliability, To process reliability.

Images