CN107679748B - Star-ground combined operation method for autonomous planning of constellation observation task - Google Patents
Star-ground combined operation method for autonomous planning of constellation observation task Download PDFInfo
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Abstract
The invention relates to a satellite-ground combined operation method, in particular to a satellite-ground combined operation method for autonomous planning of a constellation observation task. The invention aims to solve the problems that the existing star group observation task planning mostly depends on ground centralized star group cooperative task planning, the ground centralized star group cooperative task planning is easy to generate data delay, the response rate is slow in the case of unexpected tasks, and ground measurement and control resources are limited; and the problem of weak computing power of the existing satellite. Firstly, setting a ground cooperative task and annotating a satellite to execute the task; whether unexpected tasks exist or not, if yes, turning to the fifth task, and if not, turning to the third task; judging whether the next task planning time is reached, and turning to the fourth step; if not, turning to the second step; fourthly, starting the ground planning to rotate to the second; fifthly, judging whether to communicate with the ground or not, and turning to six; if not, turning to seven; sixthly, planning and turning the ground again to a second step; seventhly, planning the star group to eight; eighthly, judging whether the communication can be carried out with the ground or not, and turning to six; if not, turning to nine; ninthly, judging whether t is reacheda‑endIf yes, the method changes to seven, and if not, the method changes to eight. The invention is used for the field of constellation observation.
Description
Technical Field
The invention relates to a satellite-ground combined operation method.
Background
The remote sensing satellite is an important way and means for acquiring ground sensitive target information, and is listed as a key research and construction object by each main aerospace mechanism in the world. The planning and scheduling technology of the observation task is one of core technologies supporting effective observation of the remote sensing satellite. At present, the satellite remote sensing technology is gradually developing from single-star observation to multi-star observation, extensive management to fine management. Under the traditional ground control satellite operation mode, the real-time support capability of satellite-ground measurement and control communication is required to be higher and higher.
However, due to the orbital characteristics of the satellite and the limited conditions of the construction of the ground measurement and control station, the real-time ground measurement and control support for the remote sensing satellite is difficult to realize. Particularly, when the satellite is out of the country, the ground measurement and control conditions which can be utilized are very limited. Meanwhile, a plurality of sensitive target observation tasks exist in an overseas non-measurement and control area, and unexpected conditions such as new target appearance, target disappearance, execution failure and incapability of observation are inevitable.
In order to enhance the quick response capability of the remote sensing satellite in the non-measurement and control area to the unexpected situations and improve the utilization efficiency of the satellite remote sensing resources, the remote sensing satellite is required to have the capability of autonomous mission planning, and the cooperative observation of a plurality of satellites can be realized, so that the characteristics and the capabilities of different loads can be fully exerted. With the continuous improvement of the requirements on intellectualization and refinement of satellite operation, the requirement on the autonomous mission planning capability of the remote sensing satellite is increasingly highlighted.
Aiming at the requirements, scholars at home and abroad combine different backgrounds to research[1-2]([1]Leyuqing, wanshinxin, slow-sensitivity, and the like, a type of multi-resource measurement and control scheduling problem research based on improved genetic algorithm [ J]Astronavigation journal, 2012,33(1):85-90.Li Yuqing, Wang Rixin, Xu Minqiang, et alithm for a class of multi-resource range scheduling problem[J].JournalofAstronautics,2012,33(1):85-90.[2]Li Yuqing,Wang Rixin,Liu Yu,et al.Satelliterange scheduling with the priority constraint:An improved genetic algorithmusing a station ID encoding method[J].Chinese Journal of Aeronautics,2015,28(3):789-803.)。
For example, Verfaillie et al propose a dynamic programming algorithm[3]([3]G Verfaillie，EBornschlegl.Designing and Evaluating an On-line On-board Autonomous EarthObservation Satellite Scheduling System[C]The 2nd NASA International works on Planning and Scheduling for space, California, America, March 25-26,2013: 122-126.), can be used for satellite on-orbit autonomous mission Planning; chien et al deeply research the autonomous mission planning problem, design and realize the autonomous planning system of EO-1 satellite[4]([4]Chien S,Cichy B,Davies A,et al.An Autonomous Earth Observing Sensorweb[J]IEEE Intelligent Systems,2005,20(3): 16-24.); tangpattanaakul et al designed a local search heuristic for mission planning of earth remote sensing satellites[5]([5]Tangpattanakul P,Jozefowiez N,Lopez P.A multi-objectivelocal search heuristic for scheduling Earth observations taken by an agilesatellite[J]European Journal of Operational Research 2015,245(2) 542-; chenhao et al have made extensive research on the scheduling algorithm of electromagnetic remote sensing satellite[6,7]([6]Electromagnetic detection satellite multi-star planning method based on dynamic penalty function genetic algorithm [ J]The university of defense science and technology bulletin, 2009,31(2):44-50 CHEN Hao, LI Jun, TANG Yu, et al, an aproach for electronic magnetic detection systems scheduling based on genetic algorithm with dynamic processing function [ J].Jounal of NationalUniversity of Defense Technology,2009,31(2):44-50.[7]Autonomous electromagnetic survey satellite group task planning based on outsourcing contract net [ J]Astronautics,2009,30 (6):2285-2291.CHEN Hao, JING Ning, LI Jun, et al, an aproach for Autonomus electromagnetic detection and reception of satellite communication net [ J].Jouronlof Astronautics,2009,30(6): 2285-; aiming at the observation problem of remote sensing satellites, the Lijun and the like provide a collaborative task planning service model [8 ]]([8]Space and air resource earth observation collaborative task planning service model based on SWE [ J]The university of defense science and technology,2013,35 (3):108-113.LI Jun, LI Jun, ZHONG Zhinong, et al]Journal of National University of failure Technology,2013,35(3): 108-; li Ju Fang and the like research planning and scheduling algorithm for solving satellite observation task by tabu search and intelligent optimization method [9-11]([9]Neighborhood change tabu search algorithm for imaging satellite integrated dispatch of plum blossom, Herenjie, Yaofeng, etc. [ J ]]Systematic engineering theory and practice 2013,33(12):3040-3044.LI Jufang, HE Renjie, YAO Feng, et al].Systems Engineering Theory and Practice,2013,33(12):3040-3044.[10]Evolutionary learning ant colony algorithm for solving multi-star task planning problem [ J]Theory and practice of System engineering, 2013,33(3):791-801.CHEN Yingwu, YAO Feng, LI Jufang, et al].Systems Engineering Theory and Practice,2013,33(3):791-801.[11]Sun K,Li J,Chen Y,et al.Multi-objective mission planning problem of agileEarth observing satellites[J].Aiaa Journal,2012.)。
As can be seen from an analysis of the results of the present study, most of the studies were carried out around solving methods or architectures [12,13] ([12] Li Yuqing, Wang Rixin, Xu Minqining, scheduling and reserving of imaging and satellite based on chemical optimization [ J ]. Journal of computational Information systems.2013.8: 6503. 13] Li Yuqing, Wang Rixin, Xu Minqing.reducing of observing utilization of fusion neural network and chemical optimization [ J ]. Chinen Journal of analytical, 2014,27(3): 687 ] less relates to the design of autonomous operation mechanisms and processes. In fact, for the autonomous cooperative observation problem of the remote sensing satellite constellation, the autonomous operation mechanism and the process serve as a basic technical problem and play an important role and influence on the overall operation effect of the system. Aiming at the defect, an autonomous operation mechanism comprising ground static and dynamic planning and on-satellite autonomous planning is designed for the autonomous task planning problem of the remote sensing satellite constellation, and an operation flow is designed in detail.
The problems result in that the existing star group observation task planning mostly depends on ground centralized star group cooperative task planning, data delay is easy to occur in the ground centralized star group cooperative task planning, the response rate is slow in the case of unexpected tasks, and ground measurement and control resources are limited; and the computing power of the existing satellite is weak.
Disclosure of Invention
The invention aims to solve the problems that the existing star group observation task planning mostly depends on ground centralized star group cooperative task planning, the ground centralized star group cooperative task planning is easy to generate data delay, the response rate is slow in the case of unexpected tasks, and ground measurement and control resources are limited; and the problem of weak computing power on the existing satellite, and provides a satellite-ground combined operation method for autonomous planning of a constellation observation task.
The specific process of the satellite-ground combined operation method for autonomous planning of the constellation observation task is as follows:
step one, setting the initial time of a ground centralized type constellation static cooperative task initial planning (conventional operation) interval as tstartEnd time tendThe length of the planning interval is Thorizon，Thorizon＝tend-tstartAt tstart-TpreplaStarting initial observation task planning on the ground at the moment, and at tstartSatellite execution is noted in time;
wherein, TpreplaPreparing time for static collaborative task planning of a ground centralized constellation;
step two, judging whether an unexpected observation task exists in the satellite execution process, if so, turning to step five, otherwise, executing step three;
step three, judging whether the satellite reaches the next mission planning time tend-TpreplaIf yes, go to step four(ii) a If not, continuing to execute the step two;
step four, starting the static cooperative task planning of the ground centralized constellation, performing the observation task planning of the next task planning interval and annotating the satellite to execute, and turning to step two;
the planning interval comprises starting time, ending time and planning interval length;
judging whether the satellite is in communication with the ground or not, if so, turning to the sixth step; if not, turning to the seventh step;
step six, setting the starting time of the dynamic collaborative task re-planning interval of the ground centralized constellation as tre-startEnd time tre-endThe length of the planning interval is Tre-horizonAt tre-start-TgetReadyStarting the dynamic cooperative task planning of the ground centralized constellation at a moment, and at tre-startThe front upper note satellite is executed, and the step two is switched;
wherein, TgetReadyPreparation time for ground dynamic mission planning;
step seven, setting the starting time of the constellation autonomous dynamic collaborative task re-planning interval as ta-startEnd time ta-endThe length of the planning interval is Ta-horizonAt ta-startStarting the autonomous dynamic cooperative task planning of the constellation at all times, and turning to the step eight;
step eight, judging whether the satellite can communicate with the ground or not during the period of executing the autonomous dynamic cooperative task planning of the constellation, and if so, turning to step six; otherwise, turning to the ninth step;
step nine, judging whether t is reacheda-endIf yes, turning to the seventh step to carry out autonomous dynamic collaborative task planning of the constellation in the next task planning interval; otherwise, turning to the step eight.
The invention has the beneficial effects that:
aiming at the autonomous operation problem of a remote sensing satellite constellation, the autonomous operation problem is divided into a ground planning part and an on-satellite autonomous planning part, the resource characteristics of the ground and the on-satellite are fully considered, a satellite-ground combined autonomous operation mechanism is provided, an operation flow is designed in detail, and a ground planning and on-satellite planning solving method is respectively provided, the method comprises the steps of 1) a ground re-planning algorithm which can exert the ground calculation advantages, namely a genetic algorithm based on real number coding; 2) an autonomous solving algorithm suitable for the characteristics of on-satellite computing resources, namely an on-satellite autonomous operation task planning solving algorithm based on bidding. The main beneficial effects of the invention are mainly shown in the following aspects:
(1) the invention practically considers the actual current situation of the satellite constellation operation management and task planning in China, and conforms to the development trend that the satellite remote sensing technology gradually observes multi-satellite observation, extensive management to fine management from single satellite observation. Under the traditional ground control satellite operation mode, the real-time support capability of satellite-ground measurement and control communication has higher and higher requirements, and due to the orbital characteristics of the satellite and the limited conditions of the ground measurement and control station construction, the real-time ground measurement and control support of the remote sensing satellite is difficult to realize. Particularly, when the satellite is out of the country, the ground measurement and control conditions which can be utilized are very limited. Meanwhile, a plurality of sensitive target observation tasks exist in an overseas non-measurement and control area, and unexpected conditions such as new target appearance, target disappearance, execution failure and incapability of observation are inevitable. However, autonomous operation of the constellation is not suitable for being completely dependent on-satellite computing, because the on-satellite computing capability limits, a trade-off between computing time and optimizing capability is required, and complete autonomous observation is difficult to embody some specific human intentions. Aiming at the situation, the invention provides a satellite-ground combined operation method for dividing the task planning of the satellite group into a ground planning part and an on-satellite autonomous planning part. The method is an effective operation method which makes use of the advantages and the disadvantages of the autonomous mission planning and the ground planning on the satellite after fully analyzing and comparing the advantages and the disadvantages of the autonomous mission planning and the ground planning on the satellite, so that the whole system can not only exert the advantages of ground computing resources and embody the control intention, but also fully utilize the real-time performance and the flexibility of the on-satellite computing and quickly respond to unexpected missions; the problems that the existing star group observation task planning mostly depends on ground centralized star group cooperative task planning, data delay is easy to occur in the ground centralized star group cooperative task planning, the response rate of unexpected tasks is low, and ground measurement and control resources are limited are solved.
(2) At present, most of research in the same field is carried out around a constellation collaborative observation mission planning solution method or system structure, and the design of an autonomous operation mechanism and a flow is less involved. The invention provides an autonomous mission planning-oriented satellite-ground combined operation method, which comprises an operation mechanism of ground static and dynamic planning and on-satellite autonomous planning, gives complete and detailed independent operation and mission planning flows of a constellation, designs detailed operation flows, respectively gives calculation algorithms of ground planning and on-satellite planning, and carries out simulation experiments, wherein the simulation experiments show that the method can effectively process the quick response problem of unexpected tasks, thereby verifying the reasonability, feasibility and correctness of the method.
(3) In order to better exert the advantages of ground computing, the invention adopts a genetic algorithm as a ground re-planning algorithm, when the genetic algorithm is used for satellite task planning, a binary coding mode is usually adopted, each digit of a chromosome represents a time window corresponding to a certain target, the value of the digit is 0 or 1, the time window represents whether an observation task is selected to be arranged or not, and the length of the chromosome is the number of visible time windows of all targets for all satellites. However, when the planning time is long and the target number is large, the binary coding method can cause the chromosomes to be too long and the operation time of the algorithm to be long, thereby reducing the efficiency of the algorithm. Aiming at the problem, the invention adopts a real number coding mode, each digit of the chromosome represents a target, and each digit of the chromosome is represented by a real number, so that the efficiency of the algorithm is increased, and the method is more suitable for the condition of large-scale operation.
(4) The invention fully considers the increasing requirements of the modern aerospace field on the intelligent and refined operation and autonomous mission planning capability of the satellite, designs and realizes an autonomous solving algorithm suitable for the characteristics of on-satellite computing resources, and can enhance the quick response capability of the remote sensing satellite in a non-measurement and control area to the unexpected conditions, thereby effectively improving the utilization efficiency of the satellite remote sensing resources, and realizing the cooperative observation of a plurality of satellites so as to fully exert the characteristics and the capabilities of different loads.
Comparing the response speed of the satellite under the unexpected condition by combining the existence or nonexistence of the on-satellite autonomous dynamic cooperative task planning in the second embodiment;
the first case: autonomous dynamic cooperative task planning capability on satellite
In the unexpected case, the satellite autonomously judges whether the ground communication support can be obtained at the moment for the generated unexpected observation task: (1) if available satellite-ground links exist, the satellite obtains ground communication support, and dynamic cooperative task planning (namely re-planning) of the constellation is carried out on the ground; (2) if no available satellite-ground link exists, the satellite cannot obtain ground communication support, and the satellite performs on-satellite autonomous dynamic cooperative task planning.
The second case: on-satellite-free autonomous dynamic collaborative task planning capability
In the unexpected case, the satellite autonomously judges whether the ground communication support can be obtained at the moment for the generated unexpected observation task: (1) if available satellite-ground links exist, the satellite obtains ground communication support, and dynamic cooperative task planning (namely re-planning) of the constellation is carried out on the ground; (2) if the available satellite-ground link does not exist, the satellite cannot obtain ground communication support, the satellite waits until the available satellite-ground link appears to obtain ground communication support, and then the ground performs dynamic cooperative task planning (i.e. re-planning) of the constellation.
Simulating the two conditions by using software realized in the first embodiment, wherein the software is provided with 100 initial observation targets and an initial planning interval length ThorizonPreparation time T of ground dynamic mission planning (7 days)getReady120min, autonomous mission planning interval Ta-horizon180 min. Unexpected targets and completion deadlines (12hours-48hours) are randomly assigned during the operation process, and different situations such as having a star available link (type I) and not having a star available link (type II) when unexpected observation requests are generated are included.
And (3) operating the first and second conditions for 10 times respectively according to the setting, and counting the operation results:
when the operation times is 1, the generation time of the unexpected task is 520000s, no available satellite-ground link exists at the time, the planning time for the beginning of the unexpected task in the first case is 520000s, the planning time for the beginning of the unexpected task in the second case is 527460s, the response time for the unexpected task in the first case is 40s, and the response time for the unexpected task in the second case is 8060 s; when the operation times are 2 times, the generating time of the unexpected task is 534700s, no available satellite-ground link exists at the time, the planning time for the beginning of the unexpected task in the first case is 534700s, the planning time for the beginning of the unexpected task in the second case is 539750s, the response time for the unexpected task in the first case is 40s, and the response time for the unexpected task in the second case is 5650 s; when the operation times are 9 times, the generating time of the unexpected task is 466000s, no available satellite-ground link exists at the time, the planning time for the beginning of the unexpected task in the first case is 466000s, the planning time for the beginning of the unexpected task in the second case is 466020s, the response time for the unexpected task in the first case is 40s, and the response time for the unexpected task in the second case is 620 s; when the operation times are 10 times, the generating time of the unexpected task is 466000s, an available satellite-ground link exists at the time, the planning time for the beginning of the unexpected task in the first case is 533700s, the planning time for the beginning of the unexpected task in the second case is 533700s, the response time for the unexpected task in the first case is 40s, and the response time for the unexpected task in the second case is 600 s;
through analysis of the simulation operation result, the first kind of situation, namely the support of an on-satellite autonomous task planning solving algorithm based on bidding, has the on-satellite autonomous dynamic cooperative task planning capability, the response speed of a satellite constellation to an unexpected situation is obviously higher, and the planning time operation is stable; in the second kind of situation, namely, when the on-satellite autonomous mission planning solving algorithm based on bidding is not supported and the on-satellite autonomous dynamic cooperative mission planning capability is not provided, the response time of the satellite constellation to the unexpected situation is longer and the fluctuation is larger.
The simulation example can verify that the satellite-ground combined operation mechanism provided by the invention can well process the quick response problem of the unexpected observation request indeed, and can respond to the new task in time under the unexpected condition, thereby effectively improving the utilization efficiency of the satellite remote sensing resource, and realizing the cooperative observation of a plurality of satellites so as to give full play to the characteristics and the capabilities of different loads.
Drawings
FIG. 1 is a schematic diagram of an agile satellite observation;
FIG. 2 is a schematic view of an observation task planning process;
FIG. 3 is a schematic diagram of a decomposition of a constellation observation autonomous mission planning problem;
FIG. 4 is a schematic diagram of a system architecture for multi-satellite cooperative task planning;
FIG. 5 is a schematic diagram of a constellation autonomous operation mechanism and process;
FIG. 6 is a schematic time line diagram of an autonomous mission planning operation flow of a constellation;
FIG. 7 is a schematic diagram of a continuous autonomous planning and ground re-planning coordinated operation timeline;
FIG. 8 is a schematic diagram of a binary encoding scheme of a genetic algorithm;
FIG. 9 is a diagram illustrating a real number encoding scheme of a genetic algorithm;
FIG. 10 is a schematic diagram of a mutation operation of a chromosome of a genetic algorithm;
FIG. 11 is a schematic diagram of a crossover operation of genetic algorithm chromosomes in a single point crossover manner;
FIG. 12 is a flow chart of a genetic algorithm based on real number encoding;
FIG. 13 is a flow chart of an on-board autonomic mission planning solution algorithm based on bidding;
FIG. 14a is a diagram of a distributed simulation demonstration software interface 1;
FIG. 14b is a diagram of a distributed simulation demonstration software interface 2;
FIG. 14c is a diagram of a distributed simulation demonstration software interface 3;
FIG. 15 is a comparison line graph of the response speed of the on-board autonomous dynamic cooperative mission planning to the satellite in an unexpected situation.
Detailed Description
The first embodiment is as follows: the specific process of the star-ground combined operation method for autonomous planning of the constellation observation task in the embodiment is as follows: as shown in fig. 1-5;
flow introduction of satellite-ground combined operation mechanism
In the initial stage, an initial task plan is generated for each satellite through unified ground centralized planning, after the initial task of each satellite is started to be executed, under the normal condition, each satellite executes an expected observation task according to the set initial task plan, and an area is observed (a satellite observation target, such as a satellite observation area); when an unexpected observation task exists, the satellite autonomously judges whether the ground communication support can be obtained:
if available satellite-ground links exist, the satellite obtains ground communication support, and dynamic cooperative task planning (namely re-planning) of the constellation is carried out on the ground;
if the available satellite-ground link does not exist, the satellite cannot obtain ground communication support, and the satellite performs autonomous dynamic cooperative task planning;
the unexpected observation task comprises finding unexpected targets in an observation area, disappearance of the targets or failure and occlusion of the satellite;
the ground centralized planning is obtained by evolutionary computation (genetic algorithm);
the specific operation flow of the satellite-ground combined operation mechanism is as follows:
step one, setting the initial time of a ground centralized type constellation static cooperative task initial planning (conventional operation) interval as tstartEnd time tendThe length of the planning interval is Thorizon，Thorizon＝tend-tstartAt tstart-Tprepla(tstartDecreasing Tprepla) Starting initial observation task planning on the ground at the moment, and at tstartSatellite execution is noted in time;
the planning interval refers to a time interval included in planning calculation, namely in the formed task instruction, the starting time of a first task to the ending time of a last task are all in the time interval;
wherein, TpreplaPreparing time for planning a static cooperative task of a ground centralized constellation, wherein the preparation time comprises processes of negotiation, calculation, instruction injection and the like;
step two, judging whether an unexpected observation task exists in the satellite execution process, if so, turning to step five, otherwise, executing step three;
step three, judging whether the satellite reaches the next mission planning time tend-Tprepla(time t)endDecreasing TpreplaDetermining the next task, wherein the next task is preset, and the planning time of the next task is within the interval of the first step); if not, continuing to execute the step two;
step four, starting the static cooperative task planning of the ground centralized constellation, carrying out the observation task planning of the planning interval of the next task (the next task in the step three) and annotating the satellite to execute, and turning to the step two;
the planning interval comprises starting time, ending time and planning interval length;
judging whether the satellite is in communication with the ground or not, if so, turning to the sixth step; if not, turning to the seventh step;
step six, setting the starting time of the dynamic collaborative task re-planning interval of the ground centralized constellation as tre-startEnd time tre-endThe length of the planning interval is Tre-horizonAt tre-start-TgetReadyTime (t)re-startDecreasing TgetReadyTime) starting the ground centralized type constellation dynamic cooperative task planning and at tre-startThe front upper note satellite is executed, and the step two is switched;
wherein, TgetReadyPreparation time for ground dynamic mission planning;
step seven, setting the starting time of the constellation autonomous dynamic collaborative task re-planning interval as ta-startEnd time ta-endThe length of the planning interval is Ta-horizonAt ta-startStarting the autonomous dynamic cooperative task planning of the constellation at all times, considering that the autonomous dynamic cooperative task re-planning method of the constellation can quickly complete and update each star task, neglecting the calculation and task update time, and turning to the step eight;
wherein, Ta-horizonThe value of (A) is determined according to the orbit characteristics of the constellation and the distribution situation of the ground measurement and control resources, communication with the ground can be carried out in the interval, and the ground hasEnough time is generated to generate new task planning upper notes;
step eight, judging whether the satellite can communicate with the ground or not during the period of executing the autonomous dynamic cooperative task planning of the constellation, and if so, turning to step six; otherwise, turning to the ninth step;
step nine, judging whether t is reacheda-endIf yes, turning to the seventh step to carry out autonomous dynamic collaborative task planning of the constellation in the next task planning interval; otherwise, turning to the step eight;
if under extreme conditions, Ta-horizonIn time:
1. failure to communicate with the ground;
2. the ground does not finish the new planning and upper pouring;
3. the new planning execution time is not reached;
in the above case, the end time t of the execution of the autonomous plan is seta-endAnd execution start time t of ground re-planningre-startThere will be a period of no-file in between, as shown in case (c) in fig. 6. For such cases, as seen from step seven to step nine, the constellation will start a new round of autonomous mission planning and execute until a new ground plan is obtained and the new ground plan starts to execute, as shown in fig. 7.
The second embodiment is as follows: the present embodiment will be described with reference to fig. 12, and the present embodiment is different from the first embodiment in that: in the sixth step, the dynamic collaborative task re-planning of the ground centralized constellation adopts a genetic algorithm based on real number coding, and the specific process is as follows:
when a genetic algorithm is used for satellite mission planning, a binary coding mode is often adopted. That is, each digit of the chromosome represents a time window corresponding to a certain target, and its value is 0 or 1, which represents whether the time window is selected to schedule an observation task, and the length of the chromosome is the number of visible time windows of all targets to all satellites. However, in practical applications, when the planning interval is long, the number of visible time windows of the target is large, the chromosomes generated by adopting a binary coding mode is too long, and each digit of the chromosomes needs to be subjected to constraint conflict check, which results in too long operation time and reduced algorithm efficiency.
As shown in fig. 8, fig. 8 shows a binary coding method conventionally used when a satellite mission is planned by using a genetic algorithm, where each bit of a chromosome represents a time window corresponding to a certain target, and its value is 0 or 1, which represents whether the time window is selected to be scheduled with an observation mission, and the length of the chromosome is the number of visible time windows of all targets for all satellites.
Therefore, the invention adopts a real number coding mode in the genetic algorithm, namely a real number coding mode
Sixthly, encoding the tasks initially planned by each ground centralized star group static collaborative task in the step one according to a real number encoding mode to generate an initial population (the number of the initial population is equal to the number of chromosomes) (the population consists of individuals);
the real number encoding mode specifically includes:
FIG. 9 shows a real number coding scheme adopted in the present invention for satellite mission planning using a genetic algorithm, where each digit of a chromosome represents an observation target, and for the ith digit of a chromosome corresponding to any observation target I in the entire observation target set I, the observation target I has a total of n for all satellitesiA visible time window, each time window is numbered as 1-niThen the value w at the ith position of the chromosomeiTo this niOne of a natural number, wiSelection of w-th observation task representing observation target iiA time window to complete; w is not less than 1i≤niI is more than or equal to 1 and less than or equal to I, wherein I is the number of observation targets and is a positive integer;
this establishes a mapping between the chromosomes and the points of the search space of the problem.
Each digit of the chromosome represents an object.
Sixthly, performing constraint check on each chromosome, namely the observation task of each observation target (for example, the battery discharge depth in the energy is less than or equal to 20%, and the energy in a single circle is balanced), and abandoning the execution of the task which does not pass the constraint check, namely enabling the chromosome to be on the positionValue wiIs 0; the task of checking by constraint then executes step sixty-three, at which time the value w of this bit of the chromosomeiIs 1. ltoreq. wi≤ni；
Sixthly, calculating the adaptive value of each individual (one chromosome is an individual); obtaining the best individual with the maximum adaptive value, and executing the step six or four;
step six, the end condition of the algorithm is that a certain number of evolutionary times is determined through some simulation experiments, so that the population adaptation value is not obviously improved at the later stage of evolution, the algorithm is stopped after the population completes the iterations, and the number of iterations is usually related to the population scale: when the population scale is large, the iteration times are correspondingly large; when the population scale is small, the iteration times are correspondingly small.
Setting the maximum value of the iteration times, and if the maximum value of the iteration times is met, turning to the sixth step and the seventh step; otherwise, turning to the step sixty-five;
sixthly, putting the individuals with the calculated adaptive values in the step six and three into a mating pool according to a selection mechanism, wherein the number of the individuals entering the mating pool is equal to the number of the initial population, and executing the step six;
the selection mechanism is an elite retention strategy, namely, the individual with the highest adaptive value in the population is directly selected to enter a mating pool, and the remaining individuals are selected according to a roulette selection mechanism, so that the probability that the individual with the high adaptive value enters the mating pool is higher, the probability that the individual with the low adaptive value enters the mating pool is lower, and the process similar to the natural biological evolution, win or loss is completed.
Sixthly, performing variation on all individuals entering the mating pool, performing cross operation after the variation is finished to generate new individuals, updating the population to obtain a next generation population, and returning to the sixth step;
and sixthly, obtaining the optimal individual with the maximum adaptive value and outputting a task planning result (the optimal individual with the maximum adaptive value).
Other steps and parameters are the same as those in the first embodiment.
The third concrete implementation mode: the present embodiment differs from the first or second embodiment in that: calculating the adaptive value of each individual in the sixth step and the third step by optimizing an objective function;
wherein the optimization objective is Q1、Q2Or Q3；
ViThe profit value of the satellite observation target (the profit value of the satellite observation target is related to the importance and priority of the target, the importance and priority of the target are high, and the profit value is large), xiIf the observation target is selected to be observed, xiIf not, x is observedi＝0，Q1Optimizing an objective function for a first type;
eicost of observation target (battery energy consumed by observation target), Q2Optimizing the objective function for a second type;
Other steps and parameters are the same as those in the first or second embodiment.
The fourth concrete implementation mode: the difference between this embodiment mode and one of the first to third embodiment modes is: and in the sixth step, all individuals entering the mating pool are mutated, and the specific process is as follows:
the variation adopts a variation strategy, which is as follows: setting a mutation probability threshold, and carrying out mutation operation on each individual entering a mating pool when the chromosome mutation probability (set according to the situation) is greater than or equal to the mutation probability threshold, and randomly reassigning a certain chromosome to complete the mutation operation;
FIG. 10 shows a mutation operation of a chromosome in a genetic algorithm. When the chromosome is mutated, a certain position in the chromosome is randomly selected, and the genetic position is randomly assigned again, so that the mutation operation is completed.
When the chromosome mutation probability is smaller than the mutation probability threshold, the individual does not carry out mutation operation;
one individual is a chromosome.
Other steps and parameters are the same as those in one of the first to third embodiments.
The fifth concrete implementation mode: the difference between this embodiment and one of the first to fourth embodiments is: after the variation in the sixth step is finished, performing cross operation to generate a new individual; the specific process is as follows:
crossover operations mimic the reproductive phenomena of biological evolution, and produce new individuals by swapping gene segments of two chromosomes. The cross operation adopts a cross strategy which is as follows: randomly selecting two individuals in a mating pool as parents to carry out chromosome crossing, and generating new individuals as offspring in a single-point crossing mode (fig. 11 shows a process that the genetic algorithm chromosomes carry out crossing operation in the single-point crossing mode, the single-point crossing mode is that only one crossing point is randomly selected, the original chromosome is divided into two sections by taking the crossing point as a boundary, one of the two chromosomes is exchanged, the crossing operation is completed, and the new individuals are generated);
the number of new individuals is the same as the population number.
Other steps and parameters are the same as in one of the first to fourth embodiments.
The sixth specific implementation mode: the difference between this embodiment and one of the first to fifth embodiments is: the method for obtaining the next generation of population by updating the population in the sixth step comprises the following specific steps:
when the adaptability of the child generation is higher than that of the parent generation, replacing the original parent generation with the child generation to form a new population, and executing the step six and the step two; otherwise, the child does not replace the parent and executes the step six and two.
Other steps and parameters are the same as those in one of the first to fifth embodiments.
The seventh embodiment: the present embodiment is described with reference to fig. 13, and differs from one of the first to sixth embodiments in that: in the seventh step, the autonomous dynamic collaborative task re-planning of the constellation adopts an on-board autonomous task planning solving algorithm based on bidding, and the specific process is as follows:
when dynamic task requirements under the influence of accidental targets or various uncertain factors occur, the problem of the star group observation task planning can be respectively regarded as a game process selected from a star pair observation target and an observation window. A complete mission plan is formed from three aspects of bid inviting, bidding and bid evaluation by utilizing a bid inviting and bidding case extended from the game theory idea, so that a solving algorithm for solving the autonomous mission plan mathematical model is obtained.
For each satellite in the satellite constellation having equal status in the original observation task, in the one-time unexpected cooperative task planning process, the satellite sending the unexpected task request is the master satellite, and the other satellites are the slave satellites. It should be noted that the roles of the satellites are not fixed, but change with the change of the tasks and the environment, so that the responses and the planning of the dynamic tasks can be better adapted.
Dividing one complete independent dynamic collaborative task re-planning of the star group into bidding processes, bidding processes and bid evaluation processes by utilizing a bidding case extended from the game theory idea;
seventhly, when an unexpected task occurs, a main satellite in the satellite constellation sends out an unexpected task request, and the unexpected task is decomposed into a plurality of subtasks to form an unexpected subtask set; namely, the total observation task represents a set of observation subtasks;
wherein the primary satellite is a satellite which sends an unexpected task request;
seventhly, determining the execution sequence of the unexpected subtasks by adopting a maximum priority strategy for the unexpected subtask set;
seventhly, the main satellite selects the unexpected subtasks with the most front ordering from the unexpected subtask set, and sends out bidding information to each auxiliary satellite through the inter-satellite link aiming at the selected unexpected subtasks;
the secondary star is a satellite except the main star in the constellation;
seventhly, a bidding process is carried out;
seventhly, after receiving the bid inviting information, the slave stars perform unexpected subtask constraint check (for example, the battery discharge depth in the energy is less than or equal to 20%, the energy in the energy is balanced in a single circle, and whether unexpected tasks can be inserted into the initial task set without conflict);
seventhly, sending out bid information from the slave star to the master star, wherein the subtask bid information which does not pass the constraint check is an empty set; the unexpected subtask bid information checked by the constraint is represented by an octave array;
seventy-four steps-seventy-five steps are bidding;
seventhly, the main star obtains bidding information sent by the auxiliary star to the main star in the seventeenth step, the main star calculates and compares net earnings of tasks completed by all bidding auxiliary stars, the net earnings are the difference between earnings and cost, sub-task distribution is carried out according to the principle that the net earnings of the tasks are the maximum, the bidding auxiliary star with the maximum net earnings wins the bid, and the main star completes the bid evaluation process to obtain bid evaluation results;
seventhly, evaluating the bid;
seventhly, returning the bid evaluation result to the winning satellite, obtaining the unexpected subtask planning scheme (the bidding information given by the winning satellite, namely the eight-element number group in the seventeenth step, can determine the execution time of the subtask, the corresponding execution satellite and the like, and then the planning scheme of the subtask), executing the subtask planning scheme by the winning satellite, and removing the unexpected subtask from the unexpected subtask set;
seventhly, the main satellite judges whether the task planning arrangement of all the unexpected subtasks in the step seven is finished, if so, the program is ended, and the task planning schemes of all the unexpected subtasks are output; otherwise, continuing to arrange the next subtask, and turning to the seventh step.
Other steps and parameters are the same as those in one of the first to sixth embodiments.
The specific implementation mode is eight: the present embodiment differs from one of the first to seventh embodiments in that: in the seventh step, the execution sequence of the unexpected subtasks is determined by adopting a maximum priority strategy for the unexpected subtask set, and the process is as follows:
the unexpected subtasks have different priorities, the main star sorts the unexpected subtasks according to the sequence of the task priorities from high to low, selects the unexpected subtasks in sequence according to the sorting, and preferentially selects the unexpected subtasks closest to the task specified completion time if more than one task with the maximum priority is available.
Other steps and parameters are the same as those in one of the first to seventh embodiments.
The specific implementation method nine: the present embodiment differs from the first to eighth embodiments in that: in the seventh step, the main satellite selects the unexpected subtasks with the most front ordering from the unexpected subtask set, and sends out bidding information to each auxiliary satellite through the inter-satellite link aiming at the selected unexpected subtasks, wherein the bidding information is expressed by a seven-element array as follows:
[j,Latitudej,Longitudej,TaskLETj,TaskDurationj,PRj,TaskTypej]
wherein j is an unexpected subtask number; latitudejObserving the target latitude; longituudejIs the observation target longitude; TaskLETjRequiring a latest start time for the unexpected subtask; TaskDurationjAn unexpected subtask duration; PRjAn unexpected subtask priority; TaskTypejFor unexpected subtask type, when unexpected subtask type TaskTypejFor general survey, TaskTypejWhen the unexpected subtask type TaskType is 0jFor detailed investigation, TaskTypej＝1；
The general survey refers to the process of roughly observing a target region in a large range by utilizing a satellite with higher orbit height and lower resolution, and some important targets or suspicious targets can be found or roughly identified through the general survey;
the detailed survey refers to that a satellite with lower orbit height and higher resolution is used for finishing accurate observation of a target, and an important target or a suspicious target can be locked through the detailed survey to obtain more accurate target information.
Other steps and parameters are the same as those in one to eight of the embodiments.
The detailed implementation mode is ten: the present embodiment differs from one of the first to ninth embodiments in that: sending bidding information from the slave star to the master star in the step seven, wherein the subtask bidding information which does not pass the constraint check is an empty set; the unexpected subtask bid information checked by the constraint is represented by an octave array; the octave number group is:
[k,j,TaskTypej,TaskSTjk,TaskETjk,TaskDurationjk,Costjk,Profitjk]
k is a satellite number; j is an unexpected subtask number; TaskTypejIs an unexpected subtask type; TaskSTjkAs a satellite SkPerforming a subtask tjThe start time of (c); TaskETjkAs a satellite SkPerforming a subtask tjThe end time of (d); TaskDurationjkAs a satellite SkPerforming a subtask tjThe duration of (d); costjkAs a satellite SkCompletes the subtask tjThe cost of (a); profitjkAs a satellite SkCompletes the subtask tjThe gain of (1).
Other steps and parameters are the same as those in one of the first to ninth embodiments.
The following examples were used to demonstrate the beneficial effects of the present invention:
the first embodiment is as follows:
software implementation of satellite-ground combined operation method for autonomous planning of constellation observation task
The invention develops HLA-based distributed simulation demonstration software by applying pRTi1516+ VC6.0+ STK, and performs demonstration verification on the operation mechanism and the process, wherein the software comprises 3 main interfaces of operation control, information display and STK demonstration, as shown in figures 14a, 14b and 14 c. The software applies a genetic algorithm based on real number coding to carry out ground dynamic task planning, and applies a solving algorithm based on bidding to carry out on-satellite autonomous task planning.
The software sets 100 initial observation targets and the length T of an initial planning intervalhorizonPreparation time T of ground dynamic mission planning (7 days)getReady120min, autonomous mission planning interval Ta-horizon180 min. During the operation, unexpected targets and completion deadlines (12hours-48hours) are randomly designated, and different conditions including that a link available for a satellite (type I) and a link not available for a satellite (type II) exist when unexpected observation requests are generated are included, the operation is performed for 10 times, and the operation result statistics are as follows:
TABLE 1 simulation run results statistics
The result analysis of the simulation operation shows that the satellite-ground joint operation mechanism provided by the invention can well process the quick response problem of the unexpected observation request, can respond to the unexpected new task in time under the condition of ensuring the normal execution of the original task, and verifies the effectiveness of the joint operation mechanism.
Example two:
comparison of response speed of on-satellite autonomous dynamic cooperative mission planning to satellite under unexpected condition
The first case: autonomous dynamic cooperative task planning capability on satellite
In the unexpected case, the satellite autonomously judges whether the ground communication support can be obtained at the moment for the generated unexpected observation task: (1) if available satellite-ground links exist, the satellite obtains ground communication support, and dynamic cooperative task planning (namely re-planning) of the constellation is carried out on the ground; (2) if no available satellite-ground link exists, the satellite cannot obtain ground communication support, and the satellite performs on-satellite autonomous dynamic cooperative task planning.
The second case: on-satellite-free autonomous dynamic collaborative task planning capability
In the unexpected case, the satellite autonomously judges whether the ground communication support can be obtained at the moment for the generated unexpected observation task: (1) if available satellite-ground links exist, the satellite obtains ground communication support, and dynamic cooperative task planning (namely re-planning) of the constellation is carried out on the ground; (2) if the available satellite-ground link does not exist, the satellite cannot obtain ground communication support, the satellite waits until the available satellite-ground link appears to obtain ground communication support, and then the ground performs dynamic cooperative task planning (i.e. re-planning) of the constellation.
Simulating the two conditions by using software realized in the first embodiment, wherein the software is provided with 100 initial observation targets and an initial planning interval length ThorizonPreparation time T of ground dynamic mission planning (7 days)getReady120min, autonomous mission planning interval Ta-horizon180 min. Unexpected targets and completion deadlines (12hours-48hours) are randomly assigned during the operation process, and different situations such as having a star available link (type I) and not having a star available link (type II) when unexpected observation requests are generated are included.
Simulating the first kind of situation to ensure that the capacity of ground centralized type constellation dynamic cooperative task planning and on-satellite autonomous dynamic cooperative task planning is simultaneously realized, namely ensuring that a genetic algorithm based on real number coding and an on-satellite autonomous task planning solving algorithm based on bidding are both available; and simulating the second kind of situation, namely, only running a genetic algorithm based on real number coding to perform ground centralized star group dynamic cooperative task planning, and closing an on-satellite autonomous task planning solving algorithm based on bidding.
According to the setting, the operation is carried out for 10 times in the first and second conditions, and the operation result statistics is as follows:
TABLE 2 simulation run results statistics
Fig. 15 is a line graph comparing response speeds of on-satellite autonomous dynamic cooperative mission planning to satellites in unexpected situations;
through analysis of the simulation operation result, the first kind of situation, namely the support of an on-satellite autonomous task planning solving algorithm based on bidding, has the on-satellite autonomous dynamic cooperative task planning capability, the response speed of a satellite constellation to an unexpected situation is obviously higher, and the planning time operation is stable; in the second kind of situation, namely, when the on-satellite autonomous mission planning solving algorithm based on bidding is not supported and the on-satellite autonomous dynamic cooperative mission planning capability is not provided, the response time of the satellite constellation to the unexpected situation is longer and the fluctuation is larger.
The simulation example can verify that the satellite-ground combined operation mechanism provided by the invention can well process the quick response problem of the unexpected observation request indeed, and can respond to the new task in time under the unexpected condition, thereby effectively improving the utilization efficiency of the satellite remote sensing resource, and realizing the cooperative observation of a plurality of satellites so as to give full play to the characteristics and the capabilities of different loads.
The present invention is capable of other embodiments and its several details are capable of modifications in various obvious respects, all without departing from the spirit and scope of the present invention.
Claims (10)
1. The star-ground combined operation method for autonomous planning of the constellation observation task is characterized by comprising the following steps: the method comprises the following specific processes:
step one, setting the initial time of the initial planning interval of the static cooperative task of the ground centralized constellation as tstartEnd time tendThe length of the planning interval is Thorizon，Thorizon＝tend-tstartAt tstart-TpreplaStarting initial observation task planning on the ground at the moment, and at tstartSatellite execution is noted in time;
wherein, TpreplaPreparing time for static collaborative task planning of a ground centralized constellation;
step two, judging whether an unexpected observation task exists in the satellite execution process, if so, turning to step five, otherwise, executing step three;
step three, judging whether the satellite reaches the next mission planning time tend-TpreplaIf yes, turning to the fourth step; if not, continuing to execute the step two;
step four, starting the static cooperative task planning of the ground centralized constellation, performing the observation task planning of the next task planning interval and annotating the satellite to execute, and turning to step two;
the planning interval comprises starting time, ending time and planning interval length;
judging whether the satellite is in communication with the ground or not, if so, turning to the sixth step; if not, turning to the seventh step;
step six, setting the starting time of the dynamic collaborative task re-planning interval of the ground centralized constellation as tre-startEnd time tre-endThe length of the planning interval is Tre-horizonAt tre-start-TgetReadyStarting the dynamic cooperative task planning of the ground centralized constellation at a moment, and at tre-startThe front upper note satellite is executed, and the step two is switched;
wherein, TgetReadyPreparation time for ground dynamic mission planning;
step seven, setting the starting time of the constellation autonomous dynamic collaborative task re-planning interval as ta-startEnd time ta-endThe length of the planning interval is Ta-horizonAt ta-startStarting the autonomous dynamic cooperative task planning of the constellation at all times, and turning to the step eight;
step eight, judging whether the satellite can communicate with the ground or not during the period of executing the autonomous dynamic cooperative task planning of the constellation, and if so, turning to step six; otherwise, turning to the ninth step;
step nine, judging whether t is reacheda-endIf yes, turning to the seventh step to carry out autonomous dynamic collaborative task planning of the constellation in the next task planning interval; otherwise, turning to the step eight.
2. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 1, characterized in that: in the sixth step, the dynamic collaborative task re-planning of the ground centralized constellation adopts a genetic algorithm based on real number coding, and the specific process is as follows:
sixthly, encoding the tasks initially planned by each ground centralized star group static cooperative task in the step one according to a real number encoding mode to generate an initial population;
the real number encoding mode specifically includes:
each position of the chromosome represents an observation target, and for any observation target I in the whole observation target set I, the observation target I corresponds to the ith position of the chromosome, and n is shared by all satellitesiA visible time window, each time window is numbered as 1-niThen the value w at the ith position of the chromosomeiTo this niOne of a natural number, wiSelection of w-th observation task representing observation target iiA time window to complete; w is not less than 1i≤niI is more than or equal to 1 and less than or equal to I, wherein I is the number of observation targets and is a positive integer;
sixthly, carrying out constraint check on each position of the chromosome, namely the observation task of each observation target, and abandoning the execution of the task which does not pass the constraint check, namely enabling the value w of the position of the chromosomeiIs 0; the task of checking by constraint then executes step sixty-three, at which time the value w of this bit of the chromosomeiIs 1. ltoreq. wi≤ni；
Sixthly, calculating the adaptive value of each individual; obtaining the best individual with the maximum adaptive value, and executing the step six or four;
step six four, setting the maximum value of the iteration times, and if the maximum value of the iteration times is met, turning to step six seven; otherwise, turning to the step sixty-five;
sixthly, putting the individuals with the calculated adaptive values in the step six and three into a mating pool according to a selection mechanism, wherein the number of the individuals entering the mating pool is equal to the number of the initial population, and executing the step six;
sixthly, performing variation on all individuals entering the mating pool, performing cross operation after the variation is finished to generate new individuals, updating the population to obtain a next generation population, and returning to the sixth step;
and sixthly, obtaining the optimal individual with the maximum adaptive value and outputting a task planning result.
3. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 2, characterized in that: calculating an adaptive value of each individual in the sixth step and the third step; obtaining the optimal individual with the maximum adaptive value, calculating the adaptive value of each individual and obtaining the adaptive value by optimizing the objective function;
the optimization objective is Q1、Q2Or Q3；
Wherein ViValue of return, x, for the satellite observation targetiIf the observation target is selected to be observed, xiIf not, x is observedi＝0，Q1Optimizing an objective function for a first type;
wherein eiTo observe the cost of the target, Q2Optimizing the objective function for a second type;
wherein y isiWhether the observation arrangement for observing the target is the same as the original task or not is the same as the original taskiTake 1, different from yiTaking beta, beta epsilon (0, 1); z is a radical ofiTo observe whether the target is an unintended target, unintended target ziTaken 1, not ziTaking 0; q3The objective function is optimized for the third kind.
4. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 2, characterized in that: and in the sixth step, all individuals entering the mating pool are mutated, and the specific process is as follows:
the variation adopts a variation strategy, which is as follows: setting a mutation probability threshold, and carrying out mutation operation on each individual entering a mating pool when the chromosome mutation probability is greater than or equal to the mutation probability threshold, and randomly re-assigning a value to a certain chromosome to complete the mutation operation;
when the chromosome mutation probability is smaller than the mutation probability threshold, the individual does not carry out mutation operation;
one individual is a chromosome.
5. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 2, characterized in that: after the variation in the sixth step is finished, performing cross operation to generate a new individual; the specific process is as follows:
the cross operation adopts a cross strategy which is as follows: randomly selecting two individuals in a mating pool as parents to carry out chromosome crossing, and generating new individuals as offspring in a single-point crossing mode.
6. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 2, characterized in that: the method for obtaining the next generation of population by updating the population in the sixth step comprises the following specific steps:
when the adaptability of the child generation is higher than that of the parent generation, replacing the original parent generation with the child generation to form a new population, and executing the step six and the step two; otherwise, the child does not replace the parent and executes the step six and two.
7. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 1, characterized in that: in the seventh step, the autonomous dynamic collaborative task re-planning of the constellation adopts an on-board autonomous task planning solving algorithm based on bidding, and the specific process is as follows:
seventhly, when an unexpected task occurs, a main satellite in the satellite constellation sends out an unexpected task request, and the unexpected task is decomposed into a plurality of subtasks to form an unexpected subtask set;
wherein the primary satellite is a satellite which sends an unexpected task request;
seventhly, determining the execution sequence of the unexpected subtasks by adopting a maximum priority strategy for the unexpected subtask set;
seventhly, the main satellite selects the unexpected subtasks with the most front ordering from the unexpected subtask set, and sends out bidding information to each auxiliary satellite through the inter-satellite link aiming at the selected unexpected subtasks;
the secondary star is a satellite except the main star in the constellation;
seventhly, after receiving the bid inviting information by each slave star, carrying out unexpected subtask constraint check on the slave star;
seventhly, sending out bid information from the slave star to the master star, wherein the subtask bid information which does not pass the constraint check is an empty set; the unexpected subtask bid information checked by the constraint is represented by an octave array;
seventhly, the main star obtains bidding information sent by the auxiliary star to the main star in the seventeenth step, the main star calculates and compares net earnings of tasks completed by all the auxiliary stars, the net earnings are the difference between earnings and cost, the auxiliary star with the largest net earnings wins the bid, and the main star completes the bid evaluation process to obtain a bid evaluation result;
seventhly, returning the bid evaluation result to the winning satellite to obtain the unexpected subtask planning scheme, executing the subtask planning scheme by the winning satellite, and removing the unexpected subtask from the unexpected subtask set;
seventhly, the main satellite judges whether the task planning arrangement of all the unexpected subtasks in the step seven is finished, if so, the program is ended, and the task planning schemes of all the unexpected subtasks are output; otherwise, go to step seven two.
8. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 7, wherein: in the seventh step, the execution sequence of the unexpected subtasks is determined by adopting a maximum priority strategy for the unexpected subtask set, and the process is as follows:
the unexpected subtasks have different priorities, the main star sorts the unexpected subtasks according to the sequence of the task priorities from high to low, selects the unexpected subtasks in sequence according to the sorting, and preferentially selects the unexpected subtasks closest to the task specified completion time if more than one task with the maximum priority is available.
9. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 7, wherein: in the seventh step, the main satellite selects the unexpected subtasks with the most front ordering from the unexpected subtask set, and sends out bidding information to each auxiliary satellite through the inter-satellite link aiming at the selected unexpected subtasks, wherein the bidding information is expressed by a seven-element array as follows:
[j,Latitudej,Longitudej,TaskLETj,TaskDurationj,PRj,TaskTypej]
wherein j is an unexpected subtask number; latitudejObserving the target latitude; longituudejIs the observation target longitude; TaskLETjRequiring a latest start time for the unexpected subtask; TaskDurationjAn unexpected subtask duration; PRjAn unexpected subtask priority; TaskTypejFor unexpected subtask type, when unexpected subtask type TaskTypejFor general survey, TaskTypejWhen the unexpected subtask type TaskType is 0jFor detailed investigation, TaskTypej＝1。
10. The star-ground combined operation method for autonomous planning of the constellation observation task according to claim 7, wherein: sending bidding information from the slave star to the master star in the step seven, wherein the subtask bidding information which does not pass the constraint check is an empty set; the unexpected subtask bid information checked by the constraint is represented by an octave array; the octave number group is:
[k,j,TaskTypej,TaskSTjk,TaskETjk,TaskDurationjk,Costjk,Profitjk]
wherein k is a satellite number; j is an unexpected subtask number; TaskTypejIs an unexpected subtask type; TaskSTjkAs a satellite SkPerforming a subtask tjThe start time of (c); TaskETjkAs a satellite SkPerforming a subtask tjThe end time of (d); TaskDurationjkAs a satellite SkPerforming a subtask tjThe duration of (d); costjkAs a satellite SkCompletes the subtask tjThe cost of (a); profitjkAs a satellite SkCompletes the subtask tjThe gain of (1).
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