CN107688889B - Satellite-ground time synchronization task planning method for navigation system - Google Patents
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Abstract
The invention discloses a satellite-ground time synchronization task planning method for a navigation system, which comprises the following steps: step 1: uniformly dividing an input planning period into N planning periods; step 2: according to the input time window information V(s,m)The satellite-ground time synchronization task to be planned is regulated according to rulesDividing the periods and decomposing to obtain an element task matrix of each planning period; and step 3: sequentially planning each planning period element task matrix from the first planning period
The meta task in the period is planned until the meta task in the last planning period is planned; and 4, step 4: and splicing the meta tasks of the adjacent planning periods to form the whole planning task and output a planning scheme. The planning method has the advantages of small search space, short calculation time and full utilization of satellite and ground resources.
Description
Technical Field
The invention mainly relates to the technical field of aerospace navigation satellite task planning, in particular to a satellite-ground time synchronization task planning method for a navigation system.
Background
The satellite-ground time synchronization is the core service of the global satellite navigation system, and the accuracy of the time synchronization is a main factor influencing the positioning and time service accuracy of the system. The satellite-to-ground time synchronized task planning problem, as a new type of ground resource scheduling problem, has its own features and complexity due to its specific problem context and planning requirements. The complexity is expressed in that it is a combined Multi-objective optimization problem (CMOP). The satellite-ground time synchronization task requirement of a single satellite has two aspects: firstly, the satellite-ground time synchronization task time of each single satellite needs to be as long as possible, and secondly, the interval between two single-satellite tasks needs to be as short as possible; moreover, as a system manager and a service controller, not only the task requirements of the satellites need to be considered during planning, but also the balance of the system needs to be considered due to the large number of the satellites, so that the difference of the task requirement satisfaction degree of each satellite is as small as possible. Second, this is a Mixed Integer Programming (MIP) problem. The satellite-ground time synchronization task planning needs to plan the number of tasks, the resources needed by each task, the start time and the end time of the task and the like, wherein the number of tasks belongs to an integer variable, and the start time and the end time of the task belong to a continuous variable. Thirdly, this is a Nonlinear Programming (NP) problem. The problem of scheduling ground stations for single targets has proven to be an NP-hard problem, and thus, for multi-target ground station scheduling, is also a nonlinear programming problem. In the prior art, for a Linear Mixed Integer Programming (MILP) problem, ILOG CPLEX or other solver tool can be used to solve, but for a Nonlinear Mixed Integer Programming (MINLP) problem, no solver tool is currently available to solve.
In the method for planning satellite-ground time synchronization in the prior art, a simple heuristic model is adopted by a planning model, and the existing model cannot efficiently utilize satellite-ground visible resources under a global system, so that the time synchronization requirements of all satellites are difficult to meet. The algorithm mainly has two types: rule-based heuristics and evolutionary algorithms. The heuristic Algorithm based on the rules, such as the First-In-First-Served Algorithm (FIFSA), improves the resource utilization rate when the ground resources are In short supply, but the heuristic scheduling Algorithm only obtains a certain feasible solution and does not optimize all optimization targets at the same time. The evolution algorithm carries out evolution search by continuously combining the element tasks in each planning period, and obtains a non-dominated solution by continuous iteration. Although the evolutionary algorithm can be optimized for multiple targets simultaneously, the algorithm has the following two disadvantages: firstly, the search space is large, and if a better solution is to be obtained, the time consumption is large; and secondly, a group of solution sets is obtained, and the user needs to select from the group of solutions, which is not beneficial to the practical application in engineering. Therefore, new planning methods must be studied to solve the complex problem of satellite-to-ground time synchronization mission planning.
With the increase of the satellites on the sky, the ground antenna resources are limited, and the satellite-ground time synchronization task planning problem is a complex problem which needs to be considered by a plurality of decision variables, so that how to reduce the calculation complexity and fully and efficiently utilize the resources of the satellites on the sky and the ground antenna is very important.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides a satellite-ground time synchronization task planning method for a navigation system, which has the advantages of small search space and short calculation time and can fully utilize satellite and ground resources.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a satellite-ground time synchronization task planning method for a navigation system is characterized by comprising the following steps: the method comprises the following steps:
step 1: uniformly dividing an input planning time interval planHorizon into N planning cycles;
step 2: according to the input time window information V(s,m)Decomposing the satellite-ground time synchronization task to be planned according to the planning period to obtainMeta-task matrix to each planning cycle
Wherein i represents the ith planning cycle;
and step 3: sequentially planning each planning period element task matrix from the first planning period
The meta task in the period is planned until the meta task in the last planning period is planned; when the meta-tasks in each planning period are planned, the meta-tasks in each planning period are sequenced firstly, and then the meta-tasks are arranged in sequence according to the sequencing sequence until all the arrangeable meta-tasks are arranged completely;
and 4, step 4: and splicing the meta tasks of the adjacent planning periods to form the whole planning task and output a planning scheme.
As a further improvement of the invention:
when the satellite-ground time synchronization task to be planned is decomposed according to the planning period in the step 2, an element task matrix of each planning period is obtained
As shown in formula (1), and
in the formula (1), the reaction mixture is,
(1≤i≤N，1≤k≤ns×nm) Indicating the kth meta-task of the ith cycle, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in an antenna set, a meta-task matrix
Each row corresponds to a meta-task planned by one satellite, and each column corresponds to a meta-task planned by each ground antennaAnd (5) performing a meta task.
The step 3 of sequencing the meta tasks in each planning period comprises the following steps:
step 3.1: initializing a variable i;
step 3.2: calculating the ith planning period element task matrix
And each attribute value of each meta-task in the meta-task matrix
The meta tasks in the system are sequentially ordered according to preset attribute priority ordering strategies;
step 3.3: pair element task matrix
Checking the sorted meta-tasks according to a constraint principle, if the meta-tasks meet the requirement of the constraint principle, selecting the meta-tasks, otherwise, not selecting the meta-tasks;
step 3.4: if i is less than the planning cycle number N, adding 1 to the variable i, and returning to execute the step 3.2; otherwise, skipping and executing the step 4.
The step 3.2 of ordering according to the preset priority ordering policy comprises the following steps:
step 3.2.1, determining the priority of each attribute for expressing the preference of the user, wherein the attributes are divided into static attributes and dynamic attributes;
step 3.2.2 determining the ith planning cycle element task matrix
And dynamically modifying the attribute value of the dynamic attribute by learning the planned task;
and 3.2.3, performing dictionary sorting on the attribute values of all the static attributes and the attribute values of the dynamic attributes according to the priority of each attribute.
The static attributes in step 3.2.2 include: the task duration TaskLength, the element task number SatTaskNum of the satellite in the period and the element task number AntTaskNum of the antenna in the period;
the expression of the task time TaskLength is shown as the formula (2);
atk end(i)-atk start(i)(2)
the expression of the meta task number SatTaskNum of the satellite in the period is shown as a formula (3);
|{atn i|at(sat)n i＝at(sat)k i,1≤n≤ns×nm}| (3)
the expression of the number of element tasks AntTaskNum of the antenna in the period is shown as a formula (4);
|{atn i|at(ant)n i＝at(ant)k i,1≤n≤ns×nm}| (4)
in the formulae (2) to (4), atk end(i)Representing the end time of the kth meta task in the ith planning cycle; at (a)k start(i)Representing the starting time of the kth meta task in the ith planning cycle; at (a)(sat)n i＝at(sat)k iIndicating that the satellites of the two meta-tasks are the same in the ith planning cycle; at (a)(ant)n i＝at(ant)k iIndicating that the antennas of the two meta-tasks are the same in the ith planning period.
The dynamic properties in step 3.2.2 include: the satellite has no task time length NoTaskLength, and whether the task can be spliced with the IsAdjacent in the previous period or not;
the expression of the satellite task-free time NoTaskLength is shown as a formula (5); the expression of whether the task can be spliced with the IsAdjacent in the previous period is shown as a formula (6);
atk start(i)-timesat(5)
in the formulae (5) and (6),
wherein, timesatRepresenting a satellite-to-ground time synchronization task set in a satellite sat, located in a meta task
Front, and distance meta task
The end time of the latest satellite-ground time synchronization task;
representing the starting time of the kth meta task in the ith planning period, wherein i represents the ith planning period;
representing meta-tasks
The end time of (d);
the mth meta task representing the jth cycle is selected;
the antenna representing both meta-tasks is the same as the satellite;
the satellites representing the two meta-tasks are identical; t is tbeginIndicating the starting time of the planning period planHorizon.
The dictionary ordering in step 3.2.3 refers to sequentially aligning the meta task matrixes according to the determined priority of each attribute
And sorting the attributes of the meta-tasks in the meta-tasks according to the set sorting rule and the size of each attribute value.
The sorting rule according to the setting refers to ascending or descending.
The constraint principle in step 3.3 means that:
constraint 1:
in the formula (7), the reaction mixture is,
denotes the ith ((j-1). times.n) of the i-th cyclem+ k) decision variables for whether or not a metatask is selected, j represents the satellite number of the metatask, k represents the antenna number of the metatask, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in the antenna set;
constraint 2:
in the formula (8), the reaction mixture is,
denotes the ith ((k-1) × n) in the ith cyclem+ j) decision variables for whether or not the meta task is selected, j represents the antenna serial number of the meta task, k represents the satellite serial number of the meta task, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in the antenna set.
The splicing principle in step 4 refers to that for the element tasks with the same antenna and the same satellite in the adjacent planning periods, if the ending time of the element task in the previous planning period is equal to the starting time of the element task in the next planning period, the two element tasks are spliced.
Compared with the prior art, the invention has the advantages that:
the navigation system satellite-ground time synchronization task planning method of the invention divides the planning time interval into N planning periods uniformly, and decomposes the satellite-ground time synchronization task according to the planning periods according to the input time window information to obtain the meta task matrix of each planning period
By aligning the task matrix
Each element task in the element task list is planned and arranged, so that the complex multi-objective optimization problem is simplified to form element task matrixes in each planning period in pairs
The selected element tasks in the adjacent period are spliced according to a certain splicing rule, so that the problems that the time length of each satellite-ground time synchronization task of a single satellite is as long as possible and the interval between two tasks of the single satellite is as short as possible are maximally ensured, therefore, the method has the advantages of small search space, short calculation time and full utilization of satellite and ground resources.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a schematic diagram of the present invention for planning and arranging meta-tasks in each planning period.
Detailed Description
The invention is further described below with reference to the drawings and specific preferred embodiments of the description, without thereby limiting the scope of protection of the invention.
FIG. 1 is a flow chart of a satellite-ground time synchronization task planning method of the navigation system of the present invention, which comprises the following steps:
step 1: uniformly dividing an input planning time interval planHorizon into N planning cycles; step 2: according to the input time window information V(s,m)Decomposing the satellite-ground time synchronization task to be planned according to the planning period to obtain the meta-task matrix of each planning period
Wherein i represents the ith planning cycle; and step 3: starting from the first planning cycle, in turnPlanning each planning period element task matrix
The meta task in the period is planned until the meta task in the last planning period is planned; when the meta-tasks in each planning period are planned, the meta-tasks in each planning period are sequenced firstly, and then the meta-tasks are arranged in sequence according to the sequencing sequence until all the arrangeable meta-tasks are arranged completely; and 4, step 4: and splicing the meta tasks of the adjacent planning periods to form the whole planning task and output a planning scheme. The planning time interval is uniformly divided into N planning periods, and the satellite-ground time synchronization task is decomposed according to the planning periods according to the input time window information to obtain the element task matrix of each planning period
By aligning the task matrix
Each element task in the element task list is planned and arranged, so that the complex multi-objective optimization problem is simplified to form element task matrixes in each planning period in pairs
The selected element tasks in the adjacent period are spliced according to a certain splicing rule, so that the problems that the time length of each satellite-ground time synchronization task of a single satellite is as long as possible and the interval between two tasks of the single satellite is as short as possible are maximally ensured, therefore, the method has the advantages of small search space, short calculation time and full utilization of satellite and ground resources.
In this embodiment, when the satellite-ground time synchronization task to be planned is decomposed according to the planning period in step 2, the meta-task matrix of each planning period is obtained
As shown in formula (1)And is and
in the formula (1), the reaction mixture is,
(1≤i≤N，1≤k≤ns×nm) Indicating the kth meta-task of the ith cycle, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in the antenna set. Meta task matrix
Each row corresponds to a meta task planned by one satellite, each column corresponds to a meta task planned by each ground antenna, and a satellite-ground time synchronization task in a planning period is decomposed into ns×nmAnd (4) performing a meta task.
In this embodiment, the step of sorting according to the preset priority sorting policy in step 3 includes: step 3.1: initializing a variable i; step 3.2: calculating the ith planning period element task matrix
And each attribute value of each meta-task in the meta-task matrix
The meta tasks in the system are sorted according to a preset attribute priority sorting strategy; step 3.3: pair element task matrix
Sequentially checking the sorted meta-tasks according to a constraint principle, if the meta-tasks meet the requirement of the constraint principle, selecting the meta-task, otherwise, not selecting the meta-task; step 3.4: if i is less than the planning cycle number N, adding 1 to the variable i, and returning to execute the step 3.2; otherwise, skipping and executing the step 4. The decomposed satellite-ground time synchronization task planning problem evolves into a multicycle 0-1 planning problem which is mutually independent,namely, the problem of whether each element task in each planning period element task matrix is selected or not is solved, the complex multi-objective optimization problem is simplified into a 0-1 planning problem, the complex problem is simplified, the search space is reduced, and the calculation time is shortened. The meta-task matrix after planning using the 0-1 planning problem evolves into the following equation:
wherein, variable
As meta-tasks
A decision variable whether selected;
the representation is selected;
indicating no selection.
In this embodiment, the step of sorting according to the preset priority sorting policy in step 3.2 includes: step 3.2.1, determining the priority of each attribute for expressing the preference of the user, wherein the attributes are divided into static attributes and dynamic attributes; step 3.2.2 calculating the ith planning period element task matrix
And dynamically modifying the attribute value of the dynamic attribute by learning the planned task; and 3.2.3, performing dictionary sorting on the attribute values of all the static attributes and the attribute values of the dynamic attributes according to the priority of each attribute. The attribute priority for expressing the preference of the user is set according to the degree of importance of the user to each attribute, and after the static attribute value and the dynamic attribute value of each meta task are determined, the attributes are sequentially sorted according to the size of the attribute value according to the dictionary sorting idea.
The static attributes in step 3.2.2 include: the task duration TaskLength, the element task number SatTaskNum of the satellite in the period and the element task number AntTaskNum of the antenna in the period;
the expression of the task time TaskLength is shown as the formula (2);
atk end(i)-atk start(i)(2)
the expression of the meta task number SatTaskNum of the satellite in the period is shown as a formula (3);
|{atn i|at(sat)n i＝at(sat)k i,1≤n≤ns×nm}| (3)
the expression of the number of element tasks AntTaskNum of the antenna in the period is shown as a formula (4);
|{atn i|at(ant)n i＝at(ant)k i,1≤n≤ns×nm}| (4)
in the formulae (2) to (4), atk end(i)Representing the end time of the kth meta task in the ith planning cycle; at (a)k start(i)Representing the starting time of the kth meta task in the ith planning cycle; at (a)(sat)n i＝at(sat)k iIndicating that the satellites of the two meta-tasks are the same in the ith planning cycle; at (a)(ant)n i＝at(ant)k iThe antennas of the two meta tasks in the ith planning period are the same; the element task number SatTaskNum of the satellite in the period refers to the task number of the satellite in all element tasks of the planning period; the number of element tasks AntTaskNum of the antenna in the planning period refers to the number of tasks belonging to the antenna in all the element tasks of the planning period.
The dynamic properties in step 3.2.2 include: the satellite has no task time length NoTaskLength, and whether the task can be spliced with the IsAdjacent in the previous period or not;
the expression of the satellite task-free time NoTaskLength is shown as a formula (5); the expression of whether the task can be spliced with the IsAdjacent in the previous period is shown as a formula (6);
atk start(i)-timesat(5)
in the formulae (5) and (6),
wherein, timesatRepresenting a satellite-to-ground time synchronization task set in a satellite sat, located in a meta task
Front, and distance meta task
The end time of the latest satellite-ground time synchronization task;
representing the starting time of the kth meta task in the ith planning period, wherein i represents the ith planning period;
representing meta-tasks
The end time of (d);
the mth meta task representing the jth cycle is selected;
the antenna representing both meta-tasks is the same as the satellite;
the satellites representing the two meta-tasks are identical; t is tbeginRepresenting the starting time of the planning period planHorizon; dynamic attribute satellite mission-free time length NoTaThe attribute values of the skLength and the boolean variable IsAdjacent need to be dynamically modified by continually learning the previously planned tasks. Fig. 2 shows a schematic diagram of a method for planning each meta task in step 3 in this embodiment. In this embodiment, because the resource utilization rate of the satellite antenna is considered by the user first, the first two attributes of the satellite no-task duration and whether the task can be spliced with the previous period are ranked according to the preference of the user, and after the priority of each attribute is determined, as shown in the leftmost column in table 1, the element task matrix is aligned to
Each meta task in (2) is ordered according to the magnitude of each attribute value by referring to the idea of dictionary ordering. The idea of dictionary ordering is to prioritize each attribute according to the attributes that have been determined and then apply the meta-task matrix
And each meta task in the meta task is sorted according to the size of each attribute value and a set sorting rule. The sorting rule means that the attribute values of the meta-tasks are sorted in an ascending or descending order. As shown in Table 1, desc indicates descending order, and asc indicates ascending order. Of course, the attribute priorities may be set in the order shown in the third column of table one according to user preference.
TABLE 1
| Attribute priority | Value ordering | Attribute priority | Value ordering |
| NoTaskLength | desc | TaskLength | desc |
| IsAdjacent | desc | IsAdjacent | desc |
| TaskLength | desc | NoTaskLength | desc |
| AntTaskNum | desc | AntTaskNum | desc |
| SatTaskNum | asc | SatTaskNum | asc |
In this embodiment, the constraint rule in step 3.3 refers to:
constraint 1:
in the formula (7), the reaction mixture is,
denotes the ith ((j-1). times.n) of the i-th cyclem+ k) decision variables for whether or not a metatask is selected, j represents the satellite number of the metatask, k represents the antenna number of the metatask, nsRepresenting the total number of satellites in the set, nmIndicating a day in which the antennas are concentratedTotal number of lines;
constraint 2:
in the formula (8), the reaction mixture is,
denotes the ith ((k-1) × n) in the ith cyclem+ j) decision variables for whether or not the meta task is selected, j represents the antenna serial number of the meta task, k represents the satellite serial number of the meta task, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in the antenna set.
Formula (7) shows that in each planning period, one satellite can only execute one task at most; equation (8) indicates that one antenna can only perform one task at most in each planning period. For each element task sequenced in each planning period, checking the selected element task according to the constraint principle
Non-selected meta-tasks
In this embodiment, the splicing rule in step 4 refers to that, for the meta tasks having the same antenna and the same satellite in the adjacent planning periods, if the ending time of the meta task in the previous planning period is equal to the starting time of the meta task in the next planning period, the two meta tasks are spliced. Let t1 and t2 denote meta-tasks of adjacent planning periods, respectively, the condition for executing the splicing operation is as shown in equation (9):
(t1s＝t2s)∩(t1m＝t2m)∩(t1end＝t2start) (9)
after splicing, t1 and t2 are integrated into a new task, and the element values of the new task are as follows:
<antenna, satellite, start time, end time>＝<t1m,t1s,t1start,t2end>。
The foregoing is considered as illustrative of the preferred embodiments of the invention and is not to be construed as limiting the invention in any way. Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical spirit of the present invention should fall within the protection scope of the technical scheme of the present invention, unless the technical spirit of the present invention departs from the content of the technical scheme of the present invention.
Claims (9)
1. A satellite-ground time synchronization task planning method for a navigation system is characterized by comprising the following steps: the method comprises the following steps:
step 1: uniformly dividing an input planning time interval planHorizon into N planning cycles;
step 2: according to the input time window information V(s,m)Decomposing the satellite-ground time synchronization task to be planned according to the planning period to obtain the meta-task matrix of each planning period
As shown in formula (1), wherein i represents the ith programming cycle;
in the formula (1), the reaction mixture is,
a kth meta task representing an ith cycle; n issRepresenting the total number of satellites in the set of satellites; n ismRepresents the total number of antennas in the antenna set, wherein i is more than or equal to 1 and less than or equal to N, k is more than or equal to 1 and less than or equal to Ns×nm；
And step 3: sequentially planning each planning period element task matrix from the first planning period
Meta-task in the planning cycle until the last meta-task in the planning cycleFinishing scribing; when the meta-tasks in each planning period are planned, the meta-tasks in each planning period are sequenced firstly, and then the meta-tasks are arranged in sequence according to the sequencing sequence until all the arrangeable meta-tasks are arranged completely;
and 4, step 4: and splicing the meta tasks of the adjacent planning periods to form the whole planning task and output a planning scheme.
2. The navigation system satellite-ground time synchronization mission planning method according to claim 1, characterized in that: the step 3 of sequencing the meta-tasks in each planning period comprises the following steps:
step 3.1: initializing a variable i;
step 3.2: calculating the ith planning period element task matrix
And each attribute value of each meta-task in the meta-task matrix
The meta tasks in the system are sorted according to a preset attribute priority sorting strategy;
step 3.3: pair element task matrix
Sequentially checking the sorted meta-tasks according to a constraint principle, if the meta-tasks meet the requirement of the constraint principle, selecting the meta-task, otherwise, not selecting the meta-task;
step 3.4: if i is less than the planning cycle number N, adding 1 to the variable i, and returning to execute the step 3.2; otherwise, skipping and executing the step 4.
3. The navigation system satellite-ground time synchronization mission planning method according to claim 2, characterized in that: the step 3.2 of ordering according to the preset attribute priority ordering strategy comprises the following steps:
step 3.2.1, determining the priority of each attribute for expressing the preference of the user, wherein the attributes are divided into static attributes and dynamic attributes;
step 3.2.2 calculating the ith planning period element task matrix
And dynamically modifying the attribute value of the dynamic attribute by learning the planned task;
and 3.2.3, performing dictionary sorting on the attribute values of all the static attributes and the attribute values of the dynamic attributes according to the priority of each attribute.
4. The navigation system satellite-ground time synchronization mission planning method according to claim 3, characterized in that: the static attributes in step 3.2.2 include: the task duration TaskLength, the element task number SatTaskNum of the satellite in the period and the element task number AntTaskNum of the antenna in the period;
the expression of the task time TaskLength is shown as the formula (2);
atk end(i)-atk start(i)(2)
the expression of the meta task number SatTaskNum of the satellite in the period is shown as a formula (3);
|{atn i|at(sat)n i＝at(sat)k i,1≤n≤ns×nm}| (3)
the expression of the number of element tasks AntTaskNum of the antenna in the period is shown as a formula (4);
|{atn i|at(ant)n i＝at(ant)k i,1≤n≤ns×nm}| (4)
in the formulae (2) to (4), atk end(i)Representing the end time of the kth meta task in the ith planning cycle; at (a)k start(i)Representing the starting time of the kth meta task in the ith planning cycle; at (a)(sat)n i＝at(sat)k iIs shown in the ith planThe satellites of the two meta-tasks in the period are the same; at (a)(ant)n i＝at(ant)k iIndicating that the antennas of the two meta-tasks are the same in the ith planning period.
5. The navigation system satellite-ground time synchronization mission planning method according to claim 3, characterized in that: the dynamic properties in step 3.2.2 include: the satellite has no task time length NoTaskLength, and whether the task can be spliced with the IsAdjacent in the previous period or not;
the expression of the satellite task-free time NoTaskLength is shown as a formula (5); the expression of whether the task can be spliced with the IsAdjacent in the previous period is shown as a formula (6);
atk start(i)-timesat(5)
in the formulae (5) and (6),
wherein, timesatShowing that in the satellite sat's satellite-ground time synchronization task set, is located at the meta-task atk iBefore, and distance element task atk iThe end time of the latest satellite-ground time synchronization task;
representing the starting time of the kth meta task in the ith planning period, wherein i represents the ith planning period;
representing meta-tasks
The end time of (d);
the mth meta task representing the jth cycle is selected;
the antenna representing both meta-tasks is the same as the satellite;
the satellites representing the two meta-tasks are identical; t is tbeginIndicating the starting time of the planning period planHorizon.
6. The navigation system satellite-ground time synchronization mission planning method according to claim 3, characterized in that: the dictionary ordering in step 3.2.3 refers to sequentially aligning the meta task matrixes according to the determined priority of each attribute
And sorting the attributes of the meta-tasks in the meta-tasks according to the set sorting rule and the size of each attribute value.
7. The navigation system satellite-ground time synchronization mission planning method of claim 6, wherein: the sorting rule according to the setting refers to ascending or descending.
8. The navigation system satellite-ground time synchronization mission planning method according to claim 2, characterized in that: the constraint principle in step 3.3 means that:
constraint 1:
in the formula (7), the reaction mixture is,
denotes the ith ((j-1). times.n) of the i-th cyclem+ k) decision variables for whether or not a metatask is selected, j represents the satellite number of the metatask, k represents the antenna number of the metatask, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in the antenna set;
constraint 2:
in the formula (8), the reaction mixture is,
denotes the ith ((k-1) × n) in the ith cyclem+ j) decision variables for whether or not the meta task is selected, j represents the antenna serial number of the meta task, k represents the satellite serial number of the meta task, nsRepresenting the total number of satellites in the set, nmRepresenting the total number of antennas in the antenna set.
9. The navigation system satellite-ground time synchronization mission planning method according to any one of claims 1 to 8, characterized by: the splicing in step 4 refers to that for the meta tasks with the same antenna and the same satellite in the adjacent planning periods, if the ending time of the meta task in the previous planning period is equal to the starting time of the meta task in the next planning period, the two meta tasks are spliced.
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