CN114021768A - Method for dynamically matching satellite imaging load based on disaster type - Google Patents
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Abstract
The invention provides a method for dynamically matching satellite imaging loads based on disaster types, which comprises the following steps: s1, modeling satellite resources; s2, primarily screening available satellite resources from the satellite resource set according to the satellite space state and the satellite task state, and determining the satellite resources as the available resources when the satellite space state and the satellite task state are simultaneously available, so as to narrow the candidate resource search range for the subsequent satellite resource matching; s3, using the satellite and the sensor as satellite resource variables, and using sensor type constraint, airspace constraint and frequency domain constraint as satellite resource constraint conditions to implement demand-satellite resource correlation matching; and S4, aiming at the optimization target, sequencing the satellite resource matching schemes meeting the task requirement, and providing the satellite resource matching scheme sequence after optimized sequencing for the client. The method can intelligently match the imaging satellite resources and perform sequencing according to the input disaster type and by combining the satellite resource constraint conditions.
Description
Technical Field
The invention belongs to the technical field of satellite imaging load distribution, and particularly relates to a method for dynamically matching satellite imaging loads based on disaster types.
Background
With the on-orbit stable operation of the domestic remote sensing satellite, different users in different industries put forward a great deal of observation requirements. At the present stage, all users in all industries put forward a great deal of observation requirements on natural disaster observation, and the natural disaster has outburst and unpredictability. Emergency resource planning for disaster events is often difficult to match with actual emergency requirements.
The in-orbit terrestrial observation satellite for the people comprises a resource series, an environment disaster reduction series, a high-resolution series, a space-based series satellite and the like, a satellite load sensor covers from optics to a radar, the spatial resolution is from low to medium and high, and the in-orbit terrestrial observation satellite has all-weather and all-day observation capability at present. China land observation satellite data is widely applied to the fields of natural resources, city planning, environment monitoring, disaster prevention and reduction, agriculture, forestry, water conservancy, meteorology, electronic government affairs, statistics, oceans, surveying and mapping, national major engineering and the like, and makes outstanding contribution to social construction. The common natural disasters are various, and mainly include flood disasters, drought disasters, meteorological disasters such as typhoons, hailstones, snowstorms and sand storms, geological disasters such as volcanoes and earthquake disasters, mountain collapses, landslides and debris flows, marine disasters such as storm tides and tsunamis, forest and grassland fires, major biological disasters and the like. Fig. 4 illustrates a natural disaster task classification table.
The first important task after the disaster happens is to make the integration and planning of emergency resources to meet the actual requirements of emergency response tasks. However, due to the burstiness and complexity of disaster emergency events and certain continuity, the problem of dynamic matching of emergency resources based on multiple tasks needs to be solved, and how to solve the dynamic optimal planning of multiple demands, multiple resources and multiple departments still needs to be researched. In order to fully improve the on-orbit working efficiency of the satellite, realize quick response of emergency disaster relief and provide sufficient decision support for continuous observation of disaster areas, it is necessary to carry out research on a satellite resource overall technology which is intelligently matched with the demands of multi-satellite and multi-load users, and the emergency data acquisition and guarantee capacity is improved by effectively integrating satellite resources.
Disclosure of Invention
In order to overcome the defects in the prior art, the inventor of the invention carries out intensive research, and provides a method for dynamically matching satellite imaging loads based on disaster types, which can intelligently match imaging satellite resources according to input disaster types.
The technical scheme provided by the invention is as follows:
a method for dynamically matching satellite imaging loads based on disaster types comprises the following steps:
s1, modeling satellite resources, and performing standardized description on the satellite resources by two levels of a satellite orbit and a sensor;
s2, primarily screening available satellite resources from the satellite resource set according to a satellite space state and a satellite task state, wherein the satellite space state refers to position state information of a satellite in space, the satellite task state refers to the state whether the satellite can arrange a current task in a specific time period, and when the satellite space state and the satellite task state are available at the same time, the satellite resources are determined to be available resources, and the candidate resource search range is narrowed for the follow-up satellite resource matching;
s3, using the satellite and the sensor as satellite resource variables, and using sensor type constraint, airspace constraint and frequency domain constraint as satellite resource constraint conditions to implement demand-satellite resource correlation matching;
and S4, aiming at the optimization target, sequencing the satellite resource matching schemes meeting the task requirement, and providing the satellite resource matching scheme sequence after optimized sequencing for the client.
The method for dynamically matching the satellite imaging load based on the disaster type, provided by the invention, has the following beneficial effects:
the invention provides a method for dynamically matching satellite imaging loads based on disaster types, which is used for modeling satellite resources and carrying out standardized description on the satellite resources by two levels of a satellite operation orbit and a sensor; primarily screening available satellite resources from a satellite resource set according to a satellite space state and a satellite task state, and determining the satellite resources as the available resources when the satellite space state and the satellite task state are simultaneously available, so as to narrow the candidate resource search range for subsequent satellite resource matching; the method comprises the steps of taking a satellite and a sensor as satellite resource variables, taking sensor type constraint, space domain constraint and frequency domain constraint as satellite resource constraint conditions, and implementing requirement-satellite resource correlation matching; and aiming at the optimization target, sequencing the satellite resource matching schemes meeting the task requirements, and providing the satellite resource matching scheme sequences subjected to optimized sequencing for the client. The method can intelligently match and sort the imaging satellite resources according to the input disaster type and by combining the satellite resource constraint conditions, improves the on-orbit working efficiency of the satellite, realizes the quick response of emergency disaster relief and provides sufficient decision support for the continuous observation of disaster areas.
Drawings
FIG. 1 is a flow chart of a method for dynamically matching satellite imaging loads based on disaster type in accordance with the present invention;
FIG. 2 is a flow chart of a satellite task state dynamic solution algorithm;
FIG. 3 is a flow chart of a hierarchical satellite resource matching algorithm;
fig. 4 is a natural disaster task classification.
Detailed Description
The features and advantages of the present invention will become more apparent and appreciated from the following detailed description of the invention.
The invention provides a method for dynamically matching satellite imaging loads based on disaster types, which comprises the following steps as shown in figure 1:
s1, modeling satellite resources, and performing standardized description on the satellite resources by two levels of a satellite orbit and a sensor;
s2, primarily screening available satellite resources from the satellite resource set according to the satellite space state and the satellite task state, and determining the satellite resources as the available resources when the satellite space state and the satellite task state are simultaneously available, so as to narrow the candidate resource search range for the subsequent satellite resource matching;
s3, using the satellite and the sensor as satellite resource variables, and using sensor type constraint, airspace constraint and frequency domain constraint as satellite resource constraint conditions to implement demand-satellite resource correlation matching;
and S4, aiming at the optimization target, sequencing the satellite resource matching schemes meeting the task requirement, and providing the satellite resource matching scheme sequence after optimized sequencing for the client.
Step S1: satellite resource modeling
The main purpose of satellite resource modeling is to standardize the capabilities and features that a satellite and its payload possess in performing a mission. The satellite resource mainly comprises two parts, one is a satellite platform, and the other is a sensor carried on a satellite. The satellite platform is mainly described by a satellite operation orbit, the satellite operation orbit is determined by the orbit number of the satellite, and the orbit number comprises six parameters of an orbit semi-major axis, orbit eccentricity, an orbit inclination angle, a rising point declination, a near-location argument and a mean-near point angle of a designated epoch.
The satellite orbit determines the off-satellite line of the satellite and determines the visible time window of the satellite for the target, and because only the visible time window needs to be concerned in the satellite resource allocation process and how the visible time window is obtained by calculation of the background does not need to be concerned, the satellite orbit is converted into the visible time window for consideration when the satellite capacity is modeled.
The satellite-mounted sensors are described by sensor type, observation parameter values, sensor yaw capability, and other constraints.
For a satellite, its resources may be given the binary O ═ (O)t,Os) To illustrate, O represents a specific satellite, and is constructed as follows:
Ot＝{T1,T2,…,Tnrepresents a set of visible time windows, T, of the satellite to the target within a specified time period1,T2,…,TnIs a visible time window.
Os＝{Sl,Si,Ss,Sa…, representing a set of sensors on board the satellite, SlIs a visible light sensor, SiIs an infrared sensor, SsFor SAR sensors，SaIs an antenna sensor. Then, for each sensor S mounted, the characteristic triplet S is set to (S)t,Sr,Sf) Is described, wherein StIndicates the type of sensor, SrRepresenting the spatial resolution, S, of the sensorfIndicating the sensor operating frequency band.
Step S2: dynamic pre-processing of satellite resources
The dynamic preprocessing of the satellite resources based on the state information aims to preliminarily screen available satellite resources from a satellite set according to the satellite task state and the satellite space state and narrow the candidate resource searching range for the follow-up satellite resource matching.
The satellite state information includes a satellite mission state and a satellite space state, which determine whether the satellite is available for an observation mission within a certain time period. For alternative satellite resources, its state space S may be set S ═ S1,S2,…,SnDescription of S, wherein SiRepresenting the state information of satellite i over a specified period of time. For satellite i, its state information consists of the spatial state and the mission state, i.e. Si＝Si,space∩Si,taskIn which S isi,spaceRepresenting the spatial state, S, of satellite ii,taskIndicating the mission status of satellite i. The space state and the task state are in a parallel relationship, that is, for the satellite i, the space state and the task state can be used as an available resource only when the space state and the task state are simultaneously available.
In the dynamic preprocessing process of the satellite resources, the reduction of the search range of the satellite resources can be realized through the following two steps: and judging the satellite space state and the satellite task state.
The satellite space state, namely the position state information of the satellite in the space, directly influences the visible time window of the observation target, so that the satellite space state can be equivalently regarded as the distribution state of the target visible time window for judging the satellite transit condition.
The satellite mission state refers to a state whether the satellite can schedule a current mission within a specific time period. Representation of satellite mission state by Boolean valueState, i.e. Si,taskE.g., { true, false }, if Si,taskAnd true, the satellite task state is available, and the satellite task state is not available.
For satellite mission state Si,taskThe determinants include the following three aspects:
set of visible time windows Ot，Ot＝{T1,T2,…,TnRepresents a set of visible time windows, T, of the satellite to the target within a specified time period1,T2,…,TnIs a visible time window;
set of satellite executable task states U (O)t): the satellite executable task state refers to the state that whether the satellite can execute a task in a certain visible time window or not, and is mainly determined by constraint conditions such as satellite fixed storage capacity, electric quantity, action interval time and the like;
set of scheduled tasks for satellite M: m ═ M1,M2,…,MnAnd indicating the set of observation tasks scheduled by the satellite within the specified observation time range. Wherein M isi∈{M1,M2,…,MnRepresents a certain scheduled observation task for the satellite. For scheduled observation tasks MiIn other words, it can be described by a binary set, i.e. MiT denotes that an observation task M has been schedulediP denotes the observation task MiThe priority of (2).
Considering the above three influencing factors, as shown in fig. 2, a dynamic solution method for satellite task state is proposed to determine the satellite task state Si,taskThe method comprises the following steps:
inputting: set of visible time windows OtSet of executable task states for satellite U (O)t) The satellite has scheduled a set of tasks M.
And (3) outputting: satellite mission State Si,task。
(1) Sequentially combining the visible time window sets O according to the time sequencetOrdering with the satellite scheduled task set M, satellite task state Si,taskAssigning the initial value as true;
(2) in the order of succession from OtIn which a visible time window T is takeniJudgment of TiThe executable task state of the satellite in the visible time window is displayed, and if the state is executable, the Step3 is turned; otherwise, if i<n, n is the number of visible time windows, i equals i +1, and Step2 is executed continuously, if i equals n, Si,taskAssigning false, ending the method and quitting the calculation;
(3) searching whether there is a time period and T from the set MiIf the arranged observation tasks are crossed, the method is ended and the calculation is quitted; if yes, turning to Step 4;
(4) comparing the priority levels of the current task with the scheduled task, if the priority level of the current task is higher than that of the scheduled task, ending the method, and quitting the calculation; otherwise, turning to Step 5;
(5) if i is n, then Si,taskAssigning false, ending the method and quitting the calculation; if i<And n, if i is equal to i +1, turning to Step2 for circulation.
Step S3: intelligent matching of satellite resources
The dynamic preprocessing of the satellite resources is to primarily screen the satellite resources in time and space to obtain available satellite resources, and then to find satellite resources meeting task requirements from the available resources, namely to intelligently match the requirements and the satellite resources. The satellite resource matching Problem is actually a Constraint Satisfaction Problem (CSP for short), and the process of searching for matching resources is a process of performing Constraint check to find a feasible solution that satisfies all Constraint conditions.
CSP is an important problem in the Artificial Intelligence (AI) research field and has wide application in the resource planning and scheduling problem. The CSP contains a set of variables and a set of constraints, which can be abstracted as CSP { V, C }, where V ═ C }1,V2,…,VmDenotes a set of variables, C ═ C1,C 2,…,CnAnd represents a constraint set, and solving the CSP is to find one or more assignments of all variables so that all constraint conditions can be met.
The analysis solving process based on the CSP comprises the steps of firstly defining the constitution of satellite resource variables aiming at satellite resources; secondly, a series of constraint conditions for satellite resources in the requirements are arranged; and finally, performing association matching on the demand and the satellite resources.
In the satellite resource correlation matching problem, user requirements are certain, and satellite resources are optional, that is, for a specific user requirement, a satellite platform and a sensor required for completing a task can be selected, so that satellite resource variables are regarded as a variable set in the CSP.
The satellite resource variables consist of two parts: satellite: a selected satellite platform; a sensor: which sensors in the satellite platform are selected.
Therefore, the satellite resource variable is a two-dimensional variable, that is, V ═ { Sat, Sensor }, where Sat denotes a satellite, a value range is defined in a candidate satellite set, Sensor denotes a Sensor, and a value range is defined in a Sensor set carried by a specified satellite Sat.
The above description makes explicit which variables are in the satellite resource association matching problem, and the specific description of the variables refers to the satellite resource description model.
The satellite resource constraint can be regarded as requirements of the satellite resource on certain parameter indexes extracted from requirements (such as observation of various disaster types). And mapping the requirements on the sensors in the requirements into constraint conditions one by one according to the constituent elements of the requirements to form a satellite resource constraint set. Satellite resource constraints include: sensor type constraints, spatial domain constraints, frequency domain constraints. The sensor type constraint is the requirement on the sensor type, and comprises visible light, infrared, SAR and antenna sensors; spatial constraints, i.e. sensor spatial resolution requirements; the frequency domain constraint is the requirement of the working frequency band of the sensor.
Demand-satellite resource association matching requires searching of satellite resource variable solution space on the sensor type constraint, spatial constraint, and frequency domain constraint. Wherein the sensor type constraint is a set of satellite-borne sensors Os＝{Sl,Si,Ss,Sa…}，SlIs a visible light sensor, SiIs an infrared sensor, SsBeing SAR sensors, SaIs an antenna sensor; spatial constraints, i.e. sensor spatial resolution requirements; the frequency domain constraint is the requirement of the working frequency band of the sensor.
All satellite candidate resources form a satellite resource space, and the satellite resource space is a small-scale space because the number and the scale of the satellite group are limited at present and the satellite resource space is compressed in the dynamic preprocessing of the satellite resources.
The variable space is gradually searched in a hierarchical searching mode:
one round of screening: and screening the satellite resources based on the sensor type constraint.
And (4) two-round screening: and screening satellite resources based on airspace constraints.
Three rounds of screening: and screening the satellite resources based on the frequency domain constraint.
While searching the variable space based on the constraint condition, a dynamic solution space is constructed, and new solutions can be added into the solution space or existing solutions in the solution space can be removed.
For the problem of matching the demand-satellite resource association, as shown in fig. 3, the specific implementation is as follows:
inputting: demand, candidate satellite resource.
And (3) outputting: and (5) a satellite resource matching scheme.
(1) Inputting candidate satellite resources, initializing solution space as
(2) Performing one-round screening from candidate satellite resources according to the type constraint of the sensor, if the satellite carries the sensor with the type required in the constraint, adding the satellite into a solution space, otherwise, not adding the satellite;
(3) carrying out two rounds of screening on the satellite in the solution space according to the spatial constraint, if the sensor carried by the satellite meets the spatial constraint requirement, keeping the satellite in the solution space, and if not, moving the satellite out of the solution space;
(4) carrying out three-wheel screening on the carried sensor of the satellite in the solution space according to frequency domain constraint, if the sensor carried by the satellite meets the requirement of the frequency domain constraint, keeping the satellite in the solution space, and if not, moving the satellite out of the solution space;
(5) and outputting the solution space to obtain a satellite resource matching scheme which can meet the requirement and complete the task.
Step S4: satellite resource matching scheme ordering
Satellite resource sets meeting task requirements are screened out through satellite resource association matching, all satellite resources in the sets can meet user requirements, and users can finally select the satellite resources. When various choices are made, in order to provide a more optimized resource matching scheme, different optimization targets are considered to be introduced to sequence the satellite resources, and a scheme sequence after optimized sequencing is shown to a user so as to meet different preferences of the user.
The satellite resource matching scheme selection problem can be solved by using a binary group { R }iS, where R represents a particular application requirement and S ═ S1,S2,…,SnIndicates the satellite resource matching scheme for the application requirement, and there are n selectable matching schemes. Each matching scheme in turn consists of satellites and sensors, i.e. Si＝{Sati,Sensori}. In combination with the actual situation, this section will sort the n selectable resource matching schemes with three optimization objectives of frequency-first, time-first, and coverage-first, respectively.
(1) Frequency priority criterion
Satellite resource association matching is a process for associating requirements with satellite resources, when a user selects matching every time, a selection scheme forms a record, and after the system runs for a long time, a plurality of pieces of record data are generated in a background database.
For a certain application requirement, based on empirical knowledge and specific performance parameters of the satellite, the user's preference for selecting different satellites to use is different among the same type of satellites that meet the requirement. The preference is not a random choice among different users, but is often verified to be effective through long-term practical application.
Therefore, the past user selection scheme record in the satellite resource matching has a certain reference value. Based on the frequency data, the frequency of each satellite platform and the sensor carried by the satellite platform can be counted and finally selected by a user according to a certain application requirement, and the frequency data is supported by the archived data in the background database.
The frequency first means that each matching scheme is sorted according to the user selection frequency, and the scheme with the highest selection frequency is considered preferentially.
The selection frequency calculation formula is as follows:
in the formula, f (S)i) Represents a matching scheme SiOf (2) a selection frequency, N (S)i) Represents a matching scheme SiThe frequency of the selection of (a) is,
representing the total selection frequency of all matching schemes.
(2) Time priority criterion
The time in time priority refers to the earliest starting time to execute the task. Due to the difference of the satellite orbits, the visible time windows of different satellites to the same target are different, and have a precedence relationship in time. For user requirements, some requirements are urgent, the requirement on timeliness is high, and the earlier task execution is expected to be better; some requirements are not very sensitive in time, and only the task needs to be completed within a specified time period, and whether the time is ahead or behind is not important, so that the user experience is not influenced.
For user requirements with requirements on timeliness, a time priority criterion is provided, the earliest executable time of the target under different satellite resource matching schemes is calculated respectively, and then the selectable matching schemes are sequenced according to the time sequence relation.
Aiming at the same target, the existing n satellite resource matching schemes { S }1,S2,…,SnFor matching scheme SiIn other words, it designates the satellite SatiAnd a Sensori. In the dynamic pretreatment process of satellite resources, the satellite Sat is obtainediSet of executable task visible time windows for a target Ti1,Ti2,…,TinGet the matching scheme SiEarliest start time T capable of executing task on targetimin。
Timin＝min(Ti1,Ti2,…,Tin) Wherein T isinIs the nth time window of visibility of the ith satellite.
Each alternative satellite resource solution may find its earliest starting time for performing a task on the target, and then rank the alternative matching solutions according to that time.
(3) Coverage priority criteria
The coverage rate is mainly for observation satellites, namely the imaging coverage rate of regional targets, and is mainly for the regional targets, and for point targets, the imaging coverage rate problem is not considered because one imaging strip can completely cover the regional targets. The area target imaging coverage rate Cov is determined by the satellite imaging strip and the area target, and the specific relation is as follows:
in the formula, SimageRepresenting the area of overlap of the imaged swath with the regional target, SareaRepresenting the area of the area target. Wherein SimageDetermined by a number of factors, including the width of the imaged swath, the relative position of the imaged swath and the regional target, etc.; and SareaIt is a fixed value.
Due to the difference of satellite orbits and the difference of the angle of view and the roll angle of the mounted sensor, the coverage rate of the same area target for one-time imaging of different satellites is different. The regional target imaging coverage rate is taken as a key index of the satellite in the aspect of dynamic capability evaluation, and users often prefer the regional target imaging coverage rate to the satellite, and hope that the target can be shot by the satellite as much as possible. Based on the preference of the user to the coverage rate of the regional targets, the coverage rate of the satellite to the targets in each optional matching scheme can be preliminarily calculated through a background, and then the satellite resource matching schemes are sequenced according to the coverage rate by using the feedback calculation result.
The invention has been described in detail with reference to specific embodiments and illustrative examples, but the description is not intended to be construed in a limiting sense. Those skilled in the art will appreciate that various equivalent substitutions, modifications or improvements may be made to the technical solution of the present invention and its embodiments without departing from the spirit and scope of the present invention, which fall within the scope of the present invention. The scope of the invention is defined by the appended claims.
Those skilled in the art will appreciate that those matters not described in detail in the present specification are well known in the art.
Claims (10)
1. A method for dynamically matching satellite imaging loads based on disaster types is characterized by comprising the following steps:
s1, modeling satellite resources, and performing standardized description on the satellite resources by two levels of a satellite orbit and a sensor;
s2, primarily screening available satellite resources from the satellite resource set according to a satellite space state and a satellite task state, wherein the satellite space state refers to position state information of a satellite in space, the satellite task state refers to the state whether the satellite can arrange a current task in a specific time period, and when the satellite space state and the satellite task state are available at the same time, the satellite resources are determined to be available resources, and the candidate resource search range is narrowed for the follow-up satellite resource matching;
s3, using the satellite and the sensor as satellite resource variables, and using sensor type constraint, airspace constraint and frequency domain constraint as satellite resource constraint conditions to implement demand-satellite resource correlation matching;
and S4, aiming at the optimization target, sequencing the satellite resource matching schemes meeting the task requirement, and providing the satellite resource matching scheme sequence after optimized sequencing for the client.
2. The method for dynamically matching satellite imaging payloads according to disaster types as claimed in claim 1, wherein in step S1, the satellite resource is binary O ═ (O) in terms of resourcet,Os) To illustrate, O represents a specific satellite, and is constructed as follows:
Ot＝{T1,T2,…,Tnrepresents a set of visible time windows, T, of the satellite to the target within a specified time period1,T2,…,TnIs a visible time window.
Os＝{Sl,Si,Ss,Sa…, representing a set of sensors on board the satellite, SlIs a visible light sensor, SiIs an infrared sensor, SsBeing SAR sensors, SaIs an antenna sensor; for each sensor S mounted, the characteristic triplet S (S) is usedt,Sr,Sf) Is described, wherein StIndicates the type of sensor, SrRepresenting the spatial resolution, S, of the sensorfIndicating the sensor operating frequency band.
3. The method for dynamically matching satellite imaging payloads according to disaster types as claimed in claim 1, wherein the step of determining satellite resources as available resources in step S2 comprises the following two sub-steps: judging the satellite space state and the satellite task state;
and (3) judging the satellite space state: equivalently considering the satellite space state as a target visible time window distribution state, and determining the target visible time window distribution state by determining the position of the satellite in the space, wherein the target visible time window distribution state is used for judging the satellite transit condition;
and (3) judging the satellite task state: by visible time window set OtSet of executable task states for satellite U (O)t) And a set of scheduled tasks M for the satellite as a determinantAnd judging whether the satellite can schedule the current task in a specific time period.
4. The method for dynamically matching satellite imaging payloads based on disaster type as recited in claim 3, wherein the scheduled observation tasks are described by a binary group, MiT denotes that an observation task M has been schedulediP denotes a scheduled observation task MiThe priority of (2).
5. The method for dynamically matching satellite imaging loads based on disaster type as claimed in claim 4, wherein the determination of the satellite mission state is determined by:
(1) sequentially combining the visible time window sets O according to the time sequencetOrdering with the satellite scheduled task set M, satellite task state Si,taskAssigning the initial value as true;
(2) in the order of succession from OtIn which a visible time window T is takeniJudgment of TiThe executable task state of the satellite in the visible time window is displayed, and if the state is executable, the Step3 is turned; otherwise, if i<n, n is the number of visible time windows, i equals i +1, and Step2 is executed continuously, if i equals n, Si,taskAssigning false, ending the method and quitting the calculation;
(3) searching from the set M whether there is a time period and a visible time window TiIf the arranged observation tasks are crossed, the method is ended and the calculation is quitted; if yes, turning to Step 4;
(4) comparing the priority levels of the current task with the scheduled task, if the priority level of the current task is higher than that of the scheduled task, ending the method, and quitting the calculation; otherwise, turning to Step 5;
(5) if i is n, then Si,taskAssigning false, ending the method and quitting the calculation; if i<And n, if i is equal to i +1, turning to Step2 for circulation.
6. The method for dynamically matching satellite imaging loads based on disaster types according to claim 1, wherein in step S3, the demand-satellite resource association matching is implemented by hierarchically screening satellite resource variables, and a round of screening: screening satellite resources based on sensor type constraints; and (4) two-round screening: satellite resource screening is carried out based on airspace constraints; three rounds of screening: and screening the satellite resources based on the frequency domain constraint.
7. The method for dynamically matching satellite imaging loads based on disaster types according to claim 6, wherein in the step of implementing demand-satellite resource association matching by hierarchically screening satellite resource variables, specific implementation manners are as follows:
(1) inputting candidate satellite resources, initializing solution space as
(2) Performing one-round screening from candidate satellite resources according to the type constraint of the sensor, if the satellite carries the sensor with the type required in the constraint, adding the satellite into a solution space, otherwise, not adding the satellite;
(3) carrying out two rounds of screening on the satellite in the solution space according to the spatial constraint, if the sensor carried by the satellite meets the spatial constraint requirement, keeping the satellite in the solution space, and if not, moving the satellite out of the solution space;
(4) carrying out three-wheel screening on the carried sensor of the satellite in the solution space according to frequency domain constraint, if the sensor carried by the satellite meets the requirement of the frequency domain constraint, keeping the satellite in the solution space, and if not, moving the satellite out of the solution space;
(5) and outputting the solution space to obtain a satellite resource matching scheme which can meet the requirement and complete the task.
8. The method for dynamically matching satellite imaging loads based on disaster types according to claim 1, wherein in step S4, the frequency priority criterion is used as an optimization target, the satellite resource matching schemes are sorted according to the user selection frequency, and the scheme with the highest selection frequency is prioritized;
the selection frequency calculation formula is as follows:
in the formula, f (S)i) Represents a matching scheme SiOf (2) a selection frequency, N (S)i) Represents a matching scheme SiThe frequency of the selection of (a) is,
representing the total selection frequency of all matching schemes.
9. The method for dynamically matching satellite imaging loads based on disaster types as claimed in claim 1, wherein in step S4, the earliest starting time T for each satellite resource matching scheme to perform tasks on the target is obtained with time priority criteria as an optimization targetiminThen, the matching schemes are sorted according to the time; wherein, Timin＝min(Ti1,Ti2,…,Tin)，TinIs the nth time window of visibility of the ith satellite.
10. The method according to claim 1, wherein in step S4, with a coverage priority criterion as an optimization objective, the coverage of satellites to the objective in each satellite resource matching scheme is determined, and the satellite resource matching schemes are sorted according to the coverage, wherein the area target imaging coverage Cov is determined by the satellite imaging strip and the area objective, and the specific relationship is as follows:
in the formula, SimageRepresenting the area of overlap of the imaged swath with the regional target, SareaRepresenting the area of the area target.
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| CN115361055A (en) * | 2022-08-16 | 2022-11-18 | 中国科学院上海微系统与信息技术研究所 | Satellite communication system inter-satellite switching method based on user group |
| CN115580342A (en) * | 2022-11-17 | 2023-01-06 | 成都国恒空间技术工程股份有限公司 | Aerospace intelligence information acquisition method and system based on intelligent networking |
| CN116155367A (en) * | 2023-04-17 | 2023-05-23 | 北京国电高科科技有限公司 | Data transmission method, device, system, electronic equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115361055A (en) * | 2022-08-16 | 2022-11-18 | 中国科学院上海微系统与信息技术研究所 | Satellite communication system inter-satellite switching method based on user group |
| CN115361055B (en) * | 2022-08-16 | 2023-07-21 | 中国科学院上海微系统与信息技术研究所 | Inter-satellite switching method of satellite communication system based on user group |
| CN115580342A (en) * | 2022-11-17 | 2023-01-06 | 成都国恒空间技术工程股份有限公司 | Aerospace intelligence information acquisition method and system based on intelligent networking |
| CN116155367A (en) * | 2023-04-17 | 2023-05-23 | 北京国电高科科技有限公司 | Data transmission method, device, system, electronic equipment and medium |
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