CN110956361B - Satellite scheduling method based on task invitation - Google Patents

Satellite scheduling method based on task invitation Download PDF

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CN110956361B
CN110956361B CN201911038391.5A CN201911038391A CN110956361B CN 110956361 B CN110956361 B CN 110956361B CN 201911038391 A CN201911038391 A CN 201911038391A CN 110956361 B CN110956361 B CN 110956361B
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satellite
task
acquiring
capacity
vector
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CN110956361A (en
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靳鹏
张凯
胡笑旋
马华伟
罗贺
王国强
夏维
任送莲
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Hefei University of Technology
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Abstract

The invention provides a satellite scheduling method based on task invitation, and relates to the field of aerospace. The method comprises the following steps: acquiring historical tasks of the satellite; acquiring a historical task demand vector based on a historical task; acquiring a task demand vector to be observed based on the task to be observed; acquiring the similarity of a historical task and a task to be observed based on the two demand vectors; acquiring a target satellite based on the similarity; inviting the target satellite; the target satellite accepts the invitation when meeting the three constraint conditions simultaneously to obtain an invitation satellite; acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value; acquiring a satellite capacity scale value of an invited satellite under the same evaluation factor; acquiring a total satellite capacity vector based on the satellite capacity scale value; and acquiring a value score of the invited satellite based on the weight vector and the total satellite capacity vector. The invention has high efficiency in satellite screening.

Description

Satellite scheduling method based on task invitation
Technical Field
The invention relates to the technical field of aerospace, in particular to a satellite scheduling method based on task invitation.
Background
With the development of aerospace technology, earth observation satellites are increasingly concerned by people. The earth observation satellite acquires relevant information by detecting the earth surface and the lower atmosphere. The earth observation satellite has the unique advantages of wide coverage area, long duration, no limitation of airspace national boundaries and the like, so the earth observation satellite is widely applied to the fields of military reconnaissance, meteorological observation, environmental protection and the like.
For a satellite observation task, how to select a suitable satellite from a plurality of available satellite resources to perform the observation task is a big problem. In the prior art, a method for matching an observation task with an execution satellite generally comprises: and counting all available satellite resources, manually screening the satellites by an operator according to the observation tasks, and pairing the satellites with the observation tasks.
However, the inventor of the present application has found that the method provided by the prior art is actually applied, and the process is complicated and the processing time is long due to the requirement of the operator to perform screening matching on all satellites one by one. Namely, the prior art has the defect of low efficiency in satellite selection.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a satellite scheduling method based on task invitation, and solves the problem of low efficiency of the prior art.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention provides a satellite scheduling method based on task invitation, which solves the technical problem, the scheduling method is executed by a computer and comprises the following steps:
acquiring historical tasks of the satellite;
acquiring a historical task demand vector based on the historical task; acquiring a task demand vector to be observed based on the task to be observed;
acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed;
acquiring a target satellite based on the similarity; inviting the target satellite based on the task to be observed;
judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, if so, accepting the invitation by the target satellite to obtain an invited satellite;
acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value;
acquiring satellite capacity scale values of the invited satellites under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value;
and acquiring the value score of the invited satellite based on the weight vector and the total satellite capacity vector, and selecting the invited satellite with the highest score to execute the task to be observed.
Preferably, the method for acquiring the similarity includes:
Figure GDA0003438196630000031
wherein:
theta represents the similarity of the historical task and the task to be observed;
Figure GDA0003438196630000032
representing a task demand vector to be observed;
Figure GDA0003438196630000033
representing a historical task demand vector.
Preferably, the method for acquiring the target satellite includes:
presetting a similarity threshold;
if the similarity is greater than the similarity threshold, the historical task corresponding to the similarity is a target historical task;
and selecting the satellite which executes the target historical task as a target satellite.
Preferably, the energy constraint is:
Figure GDA0003438196630000034
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure GDA0003438196630000035
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Figure GDA0003438196630000036
representing the energy required by the imaging of the ith satellite in unit time;
Enirepresents the maximum energy of the ith satellite;
the storage capacity constraints are:
Figure GDA0003438196630000041
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure GDA0003438196630000042
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Seis represents the storage amount required by the imaging of the ith satellite in unit time;
Cpirepresenting the maximum storage capacity of the ith satellite;
the task time window constraint is:
Figure GDA0003438196630000043
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure GDA0003438196630000044
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Figure GDA0003438196630000045
representing the camera deflection angle when the ith satellite executes the task j;
kitheta represents a camera deflection angle of the ith satellite for executing a task to be observed;
Seiv denotes the i-th satellite camera angle slew rate.
Preferably, the preset evaluation factors include:
task completion rate, resource utilization, task execution cost, task execution success rate and satellite-borne resources;
the task completion rate comprises: the task completion benefit and the download income; the resource utilization includes: total startup time, number of ground stations and total acceptance time; the task execution cost includes: time requirements and consumption of energy resources; the task execution success rate includes: weather conditions, historical task success number and key equipment reliability; the satellite-borne resources include: the imaging resolution of the satellite sensor, the maximum side-sway angle of the satellite and the maximum storage resource of the satellite.
Preferably, the method for acquiring the factor scale value includes:
inviting experts to score the importance degree of the evaluation factors; deleting the highest score and the lowest score in the scoring result, and calculating the arithmetic mean of the remaining scores, wherein the arithmetic mean is the final score of the importance degree of the evaluation factors;
calculating each two evaluation factors i andratio P of final scores of importance of jij；
Based on the ratio PijAnd acquiring a factor scale value from a preset factor scale interval.
Preferably, the method for obtaining the weight vector includes:
obtaining a weight matrix based on the factor scale value; acquiring a weight vector based on the weight matrix;
wherein obtaining a weight vector based on the weight matrix comprises:
Figure GDA0003438196630000051
wherein:
Via row vector value representing an ith row of the weight matrix;
aija factor scale value representing the ith evaluation factor to the jth evaluation factor;
Figure GDA0003438196630000061
wherein:
Figure GDA0003438196630000062
a relative weight representing the ith evaluation factor;
Figure GDA0003438196630000063
wherein:
w represents a weight vector;
t represents the number of evaluation factors.
Preferably, the method for acquiring the satellite capability scale value includes:
the inviting expert scores the satellite capacity of the inviting satellite under the same evaluation factor; deleting the highest score and the lowest score in the scoring results, and calculating the arithmetic mean of the remaining scores, wherein the arithmetic mean is the final score of the satellite capacity of the invited satellite under the corresponding evaluation factors;
calculating the ratio S of the satellite capability final scores of every two invited satellites i and j under the corresponding evaluation factorsij；
Based on the ratio SijAnd acquiring a satellite capacity scale value under the same evaluation factor with a preset satellite capacity scale interval.
Preferably, the method for acquiring the total satellite capacity vector includes:
acquiring a satellite sub-capacity matrix based on the satellite capacity scale value; acquiring a satellite partial capacity vector based on the satellite partial capacity matrix; acquiring a satellite total capacity vector of an invited satellite based on the satellite sub-capacity vector;
the method for acquiring the satellite sub-capacity vector comprises the following steps:
Figure GDA0003438196630000071
wherein:
Gia row vector value representing the ith row of the satellite sub-capability matrix;
bijindicating satellite Se under the same evaluation factoriTo satellite SejA satellite capability scale value of;
Figure GDA0003438196630000072
wherein:
θirepresenting the relative energy value of the ith satellite under the same evaluation factor;
bt＝(θ1、θ2……θM)T
wherein:
btrepresenting satellite sub-capacity vectors under the tth evaluation factor;
m represents the number of satellites;
the total satellite capacity vector is as follows:
bgeneral assembly＝(b1、b2、...、bt)
Wherein:
t represents the number of evaluation factors.
Preferably, the method for obtaining the value score of the invited satellite includes:
S＝(bgeneral assembly×w)T＝(s1，s2，...，sM)
Wherein:
s represents a score matrix of M invited satellites;
w represents a weight vector;
bgeneral assemblyRepresenting a total satellite capacity vector;
siindicating the score for the ith inviting satellite.
(III) advantageous effects
The invention provides a satellite scheduling method based on task invitation. Compared with the prior art, the method has the following beneficial effects:
the invention obtains the historical tasks of the satellite; acquiring a historical task demand vector based on a historical task; acquiring a task demand vector to be observed based on the task to be observed; acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed; acquiring a target satellite based on the similarity; inviting a target satellite based on a task to be observed; judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, and if so, accepting the invitation by the target satellite to obtain an invited satellite; acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value; acquiring a satellite capacity scale value of an invited satellite under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value; and acquiring a value score of the invited satellite based on the weight vector and the total satellite capacity vector, and selecting the invited satellite with the highest score to execute the task to be observed. The method realizes the primary screening of the satellite by comparing the similarity of the task to be observed and the historical task; then, secondary screening is carried out on the satellite by using the three constraints; and finally, considering influence factors when the satellite executes the task, and scoring the satellite by comprehensively considering the relative scale value among the factors and the relative scale value among the satellites under the same factor so as to obtain the most suitable satellite to execute the task.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is an overall flowchart of a satellite scheduling method based on task invitation according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
By providing the satellite scheduling method based on the task invitation, the problem of low efficiency in the prior art is solved, and the satellite selection efficiency is improved.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the embodiment of the invention obtains the historical tasks of the satellite; acquiring a historical task demand vector based on a historical task; acquiring a task demand vector to be observed based on the task to be observed; acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed; acquiring a target satellite based on the similarity; inviting a target satellite based on a task to be observed; judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, and if so, accepting the invitation by the target satellite to obtain an invited satellite; acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value; acquiring a satellite capacity scale value of an invited satellite under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value; and acquiring a value score of the invited satellite based on the weight vector and the total satellite capacity vector, and selecting the invited satellite with the highest score to execute the task to be observed. The embodiment of the invention realizes the primary screening of the satellite by comparing the similarity of the task to be observed and the historical task; then, secondary screening is carried out on the satellite by using the three constraints; and finally, considering influence factors when the satellite executes the task, and scoring the satellite by comprehensively considering the relative scale value among the factors and the relative scale value among the satellites under the same factor so as to obtain the most suitable satellite to execute the task.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
The embodiment of the invention provides a satellite scheduling method based on task invitation, which is executed by a computer and comprises the following steps:
s1, acquiring historical tasks of the satellite;
s2, acquiring a historical task demand vector based on the historical task; acquiring a task demand vector to be observed based on the task to be observed;
s3, acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed;
s4, acquiring a target satellite based on the similarity; inviting the target satellite based on the task to be observed;
s5, judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, if so, accepting the invitation by the target satellite to obtain an invited satellite;
s6, acquiring a factor scale value based on a preset evaluation factor; acquiring a weight vector based on the factor scale value;
s7, acquiring satellite capacity scale values of the invited satellites under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value;
and S8, acquiring the value scores of the invited satellites based on the weight vectors and the total satellite capacity vectors, and selecting the invited satellite with the highest score to execute the task to be observed.
The embodiment of the invention obtains the historical tasks of the satellite; acquiring a historical task demand vector based on a historical task; acquiring a task demand vector to be observed based on the task to be observed; acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed; acquiring a target satellite based on the similarity; inviting a target satellite based on a task to be observed; judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, and if so, accepting the invitation by the target satellite to obtain an invited satellite; acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value; acquiring a satellite capacity scale value of an invited satellite under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value; and acquiring a value score of the invited satellite based on the weight vector and the total satellite capacity vector, and selecting the invited satellite with the highest score to execute the task to be observed. The embodiment of the invention realizes the primary screening of the satellite by comparing the similarity of the task to be observed and the historical task; then, secondary screening is carried out on the satellite by using the three constraints; and finally, considering influence factors when the satellite executes the task, and scoring the satellite by comprehensively considering the relative scale value among the factors and the relative scale value among the satellites under the same factor so as to obtain the most suitable satellite to execute the task.
The following is a detailed analysis of each step.
In step S1, historical assignments of satellites are obtained.
Specifically, the method comprises the following steps of obtaining at a satellite control center: the system comprises tasks to be observed, historical tasks which are completed and satellites corresponding to the completed historical tasks.
And constructing a historical database according to the historical tasks. The historical database is a set of tasks completed in past period of time and is defined as St，St＝(t1、t2、...、tM) Wherein: m is the number of historical tasks, tlIndicating the ith task. In the embodiment of the invention, historical tasks completed by all satellites in the past half-year time period are selected to construct the historical database.
In step S2, a history task demand vector is acquired based on the history task; and acquiring a task demand vector to be observed based on the task to be observed.
Specifically, the method for acquiring the historical task demand vector comprises the following steps:
for historical task tlThe embodiment of the invention adopts a seven-dimensional demand vector to quantitatively describe the capacity of task demands, and each dimension demand is respectively a task priority demand, a task coverage area demand, an observation geographical position demand, a task duration observation duration demand, an observation imaging definition demand, a task resource consumption demand and a task observation meteorological condition demand according to the sequence. The demand strength of each dimension is divided into 6 grades, which are respectively represented by numbers 1 to 6, and the larger the number is, the higher the demand grade is, the stronger the demand is.
According to the embodiment of the invention, the historical task is analyzed by inviting experts, so that the strength level corresponding to each dimension requirement of the historical task is determined, a corresponding level value is obtained, and then the qualitative requirement strength is converted into quantitative representation according to the level of each dimension requirement of the historical task to form a historical task requirement vector. Is particularly shown as
Figure GDA0003438196630000121
In the embodiment of the invention, the task to be observed is set to be represented by k, according to the acquisition method of the historical task demand vector, the expert is invited to analyze the observation task, the demand strength grade of each dimension is determined, the corresponding numerical value is obtained, and the qualitative performance is realizedThe strength of the demand is converted into quantitative representation to form a demand vector of the task to be observed, and the demand vector is specifically represented as
Figure GDA0003438196630000131
In step S3, the similarity between the historical task and the task to be observed is obtained based on the historical task demand vector and the task to be observed demand vector.
Specifically, the method for acquiring the similarity between the historical task and the task to be observed is as follows:
Figure GDA0003438196630000132
wherein:
theta represents the similarity of the historical task and the task to be observed;
Figure GDA0003438196630000133
representing a task demand vector to be observed;
Figure GDA0003438196630000134
representing a historical task demand vector.
A greater similarity indicates that the two tasks are more similar.
In step S4, a target satellite is acquired based on the similarity; and inviting the target satellite based on the task to be observed.
Specifically, the method for acquiring the target satellite comprises the following steps:
a similarity threshold is preset. In the embodiment of the present invention, the similarity threshold is 0.7.
And when the similarity is greater than a preset similarity threshold, the historical task corresponding to the similarity is a target historical task.
Screening all historical tasks according to the similarity threshold value to obtain M target historical tasks, and then obtaining M target satellites corresponding to the target historical tasks to form a targetSet of satellites { Se }1,...,SeM}。
Thus, the primary screening of the satellites is completed.
In step S5, it is determined whether the target satellite simultaneously satisfies the energy constraint, the storage capacity constraint, and the task time window constraint, and if all the conditions are satisfied, the target satellite accepts the invitation to obtain an invited satellite.
Specifically, the energy constraint can ensure that the satellite can provide energy meeting the task requirement within the task execution time, and the acquisition method comprises the following steps:
Figure GDA0003438196630000141
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure GDA0003438196630000142
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Figure GDA0003438196630000143
representing the energy required by the imaging of the ith satellite in unit time;
Enirepresenting the maximum energy of the ith satellite.
Specifically, the storage capacity constraint can ensure that the satellite can provide the storage capacity meeting the task requirement within the task execution time, and the acquisition method comprises the following steps:
Figure GDA0003438196630000144
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure GDA0003438196630000145
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Seis represents the storage amount required by the imaging of the ith satellite in unit time;
Cpirepresenting the maximum storage capacity of the ith satellite.
Specifically, the task time window constraint can ensure that the task is not influenced by the adjacent task in the time window, and the obtaining method comprises the following steps:
Figure GDA0003438196630000151
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure GDA0003438196630000152
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Figure GDA0003438196630000153
representing the camera deflection angle when the ith satellite executes the task j;
kitheta represents a camera deflection angle of the ith satellite for executing a task to be observed;
Seiv denotes the i-th satellite camera angle slew rate.
And the target satellite meeting the three constraint conditions can accept the invitation, and the target satellite not meeting any constraint condition refuses the invitation. The target satellite accepting the invitation is used for executing the task to be observed. And designates the target satellite that accepted the invitation as the inviting satellite.
Thus, secondary screening of the satellite is completed.
In step S6, a factor scale value is acquired based on a preset evaluation factor; a weight vector is obtained based on the factor scale value.
Specifically, t evaluation factors may be preset in consideration of task requirements of a task to be executed (i.e., a task to be observed). The examples of the present invention summarize several evaluation factors: task completion rate, resource utilization, task execution cost, task execution success rate and satellite-borne resources.
Wherein, the task completion rate comprises: the task completion benefit and the download income. The resource utilization includes: total boot time, number of ground stations, and total acceptance time. The task execution cost comprises: time requirements and consumption of energy resources. The task execution success rate comprises: weather conditions, historical task success count, and critical equipment reliability. The satellite-borne resources include: the imaging resolution of the satellite sensor, the maximum side-sway angle of the satellite and the maximum storage resource of the satellite.
Step S6 specifically includes the following steps:
s601, acquiring a factor scale value.
Specifically, the acquisition method is as follows:
the expert is first invited to score the importance of the evaluation factors. Specifically, in the embodiment of the invention, 10 experts with higher authority and representativeness in the related field are invited to provide satellite data and task data to be executed, the satellite data and the task data to be executed are respectively subjected to comprehensive scoring on the importance of different evaluation factors of the invited satellite according to task requirements, the score is between 1 and 10, and the higher the score is, the stronger the importance is. And respectively counting the scoring results of each evaluation factor, removing the highest score and the lowest score, and solving the arithmetic mean p of the residual scores to obtain the arithmetic mean which is the final score of the importance degree of each evaluation factor.
Then, the ratio P of the final scores of the importance degrees of each two evaluation factors i and j is calculatedij. Based onRatio PijAnd acquiring a factor scale value from a preset factor scale interval. And if the ratio is in a factor scale interval, the factor scale value of the evaluation factor i to the evaluation factor j is the factor scale value corresponding to the factor scale interval.
Specifically, the preset factor scale interval and the corresponding factor scale value are shown in the following table:
TABLE 1
Figure GDA0003438196630000171
In the embodiment of the present invention, the factor scale value aijIndicating the degree of importance of the evaluation factor i to the evaluation factor j.
When the factor scale value is 1, the representative evaluation factor i and the evaluation factor j are equally important. When the factor scale value is greater than 1, the representative evaluation factor i is more important than the evaluation factor j, and a larger factor scale value indicates that the evaluation factor i is more important than the evaluation factor j. When the factor scale value is less than 1, the representative evaluation factor i is less important than the evaluation factor j, and a smaller factor scale value means that the importance of the evaluation factor i is lower than that of the evaluation factor j, i.e., the evaluation factor j is more important than the evaluation factor i.
And S602, acquiring a weight vector. Specifically, the method comprises the following steps:
and S6022, acquiring a weight matrix based on the factor scale value.
Specifically, the weight matrix is constructed as follows:
Figure GDA0003438196630000181
wherein: a isijA factor scale value representing the ith evaluation factor to the jth evaluation factor;
Atthe t-th evaluation factor is shown.
And S6022, acquiring a weight vector based on the weight matrix.
Specifically, the weight vector is calculated by using the constructed weight matrix:
firstly, obtaining a row vector value:
Figure GDA0003438196630000182
wherein:
Virow vector values representing a weight matrix;
aijand the factor scale value of the ith evaluation factor to the jth evaluation factor is shown.
And (3) carrying out normalization treatment:
Figure GDA0003438196630000183
finally, obtaining a weight vector:
Figure GDA0003438196630000191
wherein:
w represents a weight vector;
Figure GDA0003438196630000192
representing the relative weight of the tth evaluation factor.
In step S7, a satellite capability scale value of the invited satellite under the same evaluation factor is obtained; and acquiring the total satellite capacity vector of the invited satellite based on the satellite capacity scale value.
The method specifically comprises the following steps:
and S701, acquiring a satellite capacity scale value.
Specifically, the acquisition method is as follows:
the expert is first invited to score the satellite capabilities of the invited satellites under the same evaluation factor. Specifically, in the embodiment of the invention, 10 experts with higher authority and representativeness in the related field are invited to provide satellite data and data of tasks to be executed, the satellite data and the data of the tasks to be executed are respectively subjected to comprehensive scoring on the satellite capacity of the invited satellite under the same evaluation factor according to task requirements, the score is between 1 and 10, and the higher the score is, the higher the importance is. And respectively counting the scoring result of each satellite capability, removing the highest score and the lowest score, and solving the arithmetic mean S of the residual scores to obtain the arithmetic mean which is the final score of the satellite capability of each invited satellite under the corresponding evaluation factor.
Then calculating the ratio S of the final scores of the satellite abilities of every two invited satellites i and j under the corresponding evaluation factorsij. Based on the ratio SijAnd acquiring a satellite capacity scale value in a preset satellite capacity scale interval. If the ratio is in a satellite capacity scale interval, the satellite capacity scale value of the inviting satellite i to the inviting satellite j is the satellite capacity scale value corresponding to the satellite capacity scale interval.
Specifically, the preset satellite capability scale interval and the corresponding satellite capability scale value are shown in the following table:
TABLE 2
Figure GDA0003438196630000201
In the embodiment of the invention, the satellite capability scale value bijIndicating the strength of the ability of the inviting satellite i to the inviting satellite j under the same evaluation factor.
When the satellite capability scale value is 1, the representative evaluation factor i and the evaluation factor j are equally important. When the satellite capacity scale value is larger than 1, the satellite i has stronger capacity than the satellite j under the current evaluation factor, and the larger the satellite capacity scale value is, the stronger the satellite i has more capacity than the satellite j is. When the satellite capacity scale value is less than 1, the satellite i has weaker capability than the satellite j under the current evaluation factor, and the smaller the satellite capacity scale value is, the weaker the capability of the satellite i is than the capability of the satellite j is, namely, the stronger the capability of the satellite j is than the capability of the satellite i.
S702, acquiring a total satellite capacity vector. Specifically, the method comprises the following steps:
s7021, acquiring a satellite sub-capacity matrix under each evaluation factor based on the satellite capacity scale value.
Specifically, each evaluation factor corresponds to one satellite sub-capability matrix, so that t satellite sub-capability matrices are constructed in the embodiment of the invention.
And constructing a satellite sub-capacity matrix according to the satellite capacity scale value, wherein for the ith evaluation factor, the corresponding satellite capacity matrix is as follows:
Figure GDA0003438196630000211
wherein:
bijindicating satellite Se under the ith evaluation factoriTo satellite SejThe satellite capability scale value of (a).
S7022, acquiring satellite sub-capacity vectors based on the satellite sub-capacity matrix.
Specifically, a satellite partial capacity vector is obtained based on a satellite partial capacity matrix under each evaluation factor, and the satellite partial capacity vector obtaining method comprises the following steps:
first, the average of the row vectors is found:
Figure GDA0003438196630000212
wherein:
Gia row vector value representing the ith row of the satellite sub-capacity matrix;
bijindicating satellite Se under the same evaluation factoriTo satellite SejThe satellite capability scale value of (a).
Figure GDA0003438196630000221
Wherein:
θirepresenting the relative energy value of the ith satellite under the same evaluation factor.
bt＝(θ1、θ2……θM)T
Wherein:
btrepresenting satellite sub-capacity vectors under the tth evaluation factor;
m represents the number of satellites.
S7023, acquiring a total satellite capacity vector of the invited satellite based on the satellite sub-capacity vectors.
Counting the satellite sub-capacity vectors under all the evaluation factors, and acquiring the total satellite capacity vector of the invited satellite according to all the satellite sub-capacity vectors, wherein the acquisition method of the total satellite capacity vector comprises the following steps:
bgeneral assembly＝(b1、b2、...、bt)
Wherein:
birepresenting satellite sub-capacity vectors under the ith evaluation factor;
t represents the number of evaluation factors.
In step S8, a value score of the invited satellite is obtained based on the weight vector and the total satellite capability vector, and the invited satellite with the highest score is selected to perform the task to be observed.
The calculation method of the value score of the inviting satellite comprises the following steps:
S＝(bgeneral assembly×w)T＝(s1，s2，...，sM)
Wherein:
s represents a score matrix of M invited satellites;
w represents a weight vector;
bgeneral assemblyRepresenting a total satellite capacity vector;
siindicating the score for the ith inviting satellite.
In the embodiment of the invention, the number N of the satellites for executing the task can be preset according to the requirement of a user, the value scores of all the satellites are counted, and the first N satellites with the highest value scores are selected for executing the task.
In summary, compared with the prior art, the method has the following beneficial effects:
the embodiment of the invention obtains the historical tasks of the satellite; acquiring a historical task demand vector based on a historical task; acquiring a task demand vector to be observed based on the task to be observed; acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed; acquiring a target satellite based on the similarity; inviting a target satellite based on a task to be observed; judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, and if so, accepting the invitation by the target satellite to obtain an invited satellite; acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value; acquiring a satellite capacity scale value of an invited satellite under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value; and acquiring a value score of the invited satellite based on the weight vector and the total satellite capacity vector, and selecting the invited satellite with the highest score to execute the task to be observed. The embodiment of the invention realizes the primary screening of the satellite by comparing the similarity of the task to be observed and the historical task; then, secondary screening is carried out on the satellite by using the three constraints; and finally, considering influence factors when the satellite executes the task, and scoring the satellite by comprehensively considering the relative scale value among the factors and the relative scale value among the satellites under the same factor so as to obtain the most suitable satellite to execute the task.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for scheduling a satellite based on task invitations, wherein the scheduling method is executed by a computer and comprises the following steps:
acquiring historical tasks of the satellite;
acquiring a historical task demand vector based on the historical task; acquiring a task demand vector to be observed based on the task to be observed;
acquiring the similarity of the historical task and the task to be observed based on the historical task demand vector and the task to be observed;
acquiring a target satellite based on the similarity; inviting the target satellite based on the task to be observed;
judging whether the target satellite simultaneously meets energy constraint, storage capacity constraint and task time window constraint, if so, accepting the invitation by the target satellite to obtain an invited satellite;
acquiring a factor scale value based on a preset evaluation factor; obtaining a weight vector based on the factor scale value;
acquiring satellite capacity scale values of the invited satellites under the same evaluation factor; acquiring a total satellite capacity vector of the invited satellite based on the satellite capacity scale value;
and acquiring the value score of the invited satellite based on the weight vector and the total satellite capacity vector, and selecting the invited satellite with the highest score to execute the task to be observed.
2. The scheduling method of claim 1, wherein the method for obtaining the similarity comprises:
Figure FDA0003438196620000021
wherein:
theta represents the similarity of the historical task and the task to be observed;
Figure FDA0003438196620000022
representing a task demand vector to be observed;
Figure FDA0003438196620000023
representing a historical task demand vector.
3. The scheduling method of claim 1 wherein the target satellite acquisition method comprises:
presetting a similarity threshold;
if the similarity is greater than the similarity threshold, the historical task corresponding to the similarity is a target historical task;
and selecting the satellite which executes the target historical task as a target satellite.
4. The scheduling method of claim 1, wherein the energy constraint is:
Figure FDA0003438196620000024
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure FDA0003438196620000025
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Figure FDA0003438196620000026
representing the energy required by the imaging of the ith satellite in unit time;
Enirepresents the maximum energy of the ith satellite;
the storage capacity constraints are:
Figure FDA0003438196620000031
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure FDA0003438196620000032
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Seis represents the storage amount required by the imaging of the ith satellite in unit time;
Cpirepresenting the maximum storage capacity of the ith satellite;
the task time window constraint is:
Figure FDA0003438196620000033
wherein:
m represents the number of satellites, and N represents the number of historical tasks on the ith satellite;
Figure FDA0003438196620000034
representing a planned task j on the ith satellite;
start represents a Start time, End represents an End time;
k represents a task to be observed;
Figure FDA0003438196620000035
representing the camera deflection angle when the ith satellite executes the task j;
kitheta represents a camera deflection angle of the ith satellite for executing a task to be observed;
Seiv denotes the i-th satellite camera angle slew rate.
5. The scheduling method of claim 1, wherein the preset evaluation factor comprises:
task completion rate, resource utilization, task execution cost, task execution success rate and satellite-borne resources;
the task completion rate comprises: the task completion benefit and the download income; the resource utilization includes: total startup time, number of ground stations and total acceptance time; the task execution cost includes: time requirements and consumption of energy resources; the task execution success rate includes: weather conditions, historical task success number and key equipment reliability; the satellite-borne resources include: the imaging resolution of the satellite sensor, the maximum side-sway angle of the satellite and the maximum storage resource of the satellite.
6. The scheduling method of claim 1, wherein the factor scale value obtaining method comprises:
inviting experts to score the importance degree of the evaluation factors; deleting the highest score and the lowest score in the scoring result, and calculating the arithmetic mean of the remaining scores, wherein the arithmetic mean is the final score of the importance degree of the evaluation factors;
calculating the ratio of the final scores of the importance degrees of each of the two evaluation factors i and jValue Pij；
Based on the ratio PijAnd acquiring a factor scale value from a preset factor scale interval.
7. The scheduling method of claim 6 wherein the obtaining of the weight vector comprises:
obtaining a weight matrix based on the factor scale value; acquiring a weight vector based on the weight matrix;
wherein obtaining a weight vector based on the weight matrix comprises:
Figure FDA0003438196620000041
wherein:
Via row vector value representing an ith row of the weight matrix;
aija factor scale value representing the ith evaluation factor to the jth evaluation factor;
Figure FDA0003438196620000051
wherein:
Figure FDA0003438196620000052
a relative weight representing the ith evaluation factor;
Figure FDA0003438196620000053
wherein:
w represents a weight vector;
t represents the number of evaluation factors.
8. The scheduling method of claim 1 wherein the method for obtaining the satellite capability scale value comprises:
the inviting expert scores the satellite capacity of the inviting satellite under the same evaluation factor; deleting the highest score and the lowest score in the scoring results, and calculating the arithmetic mean of the remaining scores, wherein the arithmetic mean is the final score of the satellite capacity of the invited satellite under the corresponding evaluation factors;
calculating the ratio S of the satellite capability final scores of every two invited satellites i and j under the corresponding evaluation factorsij；
Based on the ratio SijAnd acquiring a satellite capacity scale value under the same evaluation factor with a preset satellite capacity scale interval.
9. The scheduling method of claim 8 wherein the method for obtaining the total satellite capacity vector comprises:
acquiring a satellite sub-capacity matrix based on the satellite capacity scale value; acquiring a satellite partial capacity vector based on the satellite partial capacity matrix; acquiring a satellite total capacity vector of an invited satellite based on the satellite sub-capacity vector;
the method for acquiring the satellite sub-capacity vector comprises the following steps:
Figure FDA0003438196620000061
wherein:
Gia row vector value representing the ith row of the satellite sub-capability matrix;
bijindicating satellite Se under the same evaluation factoriTo satellite SejA satellite capability scale value of;
Figure FDA0003438196620000062
wherein:
θirepresenting the relative energy value of the ith satellite under the same evaluation factor;
bt＝(θ1、θ2……θM)T
wherein:
btrepresenting satellite sub-capacity vectors under the tth evaluation factor;
m represents the number of satellites;
the total satellite capacity vector is as follows:
bgeneral assembly＝(b1、b2、...、bt)
Wherein:
t represents the number of evaluation factors.
10. The scheduling method of claim 9 wherein the method of obtaining the value score of the inviting satellite comprises:
S＝(bgeneral assembly×w)T＝(s1，s2，...，sM)
Wherein:
s represents a score matrix of M invited satellites;
w represents a weight vector;
bgeneral assemblyRepresenting a total satellite capacity vector;
siindicating the score for the ith inviting satellite.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106648852A (en) * 2016-11-18 2017-05-10 合肥工业大学 Multi-satellite mission scheduling method and device based on double ant colonies
CN109657930A (en) * 2018-11-29 2019-04-19 合肥工业大学 Resource Alliance's construction method of cotasking based on dummy constellation
WO2019079796A1 (en) * 2017-10-20 2019-04-25 HawkEye 360, Inc. Scheduling system of a plurality of hierarchical tasks for a satellite system.
CN109872060A (en) * 2019-02-01 2019-06-11 中国地质大学（武汉） A method of for more satellite sensor joint observation Scheme Choices

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106648852A (en) * 2016-11-18 2017-05-10 合肥工业大学 Multi-satellite mission scheduling method and device based on double ant colonies
WO2019079796A1 (en) * 2017-10-20 2019-04-25 HawkEye 360, Inc. Scheduling system of a plurality of hierarchical tasks for a satellite system.
CN109657930A (en) * 2018-11-29 2019-04-19 合肥工业大学 Resource Alliance's construction method of cotasking based on dummy constellation
CN109872060A (en) * 2019-02-01 2019-06-11 中国地质大学（武汉） A method of for more satellite sensor joint observation Scheme Choices

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
基于遗传算法的多星调度方法;章密等;《合肥工业大学学报（自然科学版）》;20170731;第40卷(第7期);全文 *
多维动态规划在对地观测卫星调度中的应用;张利宁;《计算机仿真》;20070531;全文 *

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