Synchronous communication satellite resource allocation method based on ship leg beam coverage
By dividing the sections of the ship's route and judging beam coverage using linear interpolation method, and optimizing resource allocation with genetic algorithms, the optimal problem of satellite resource allocation during ship navigation is solved, and the balanced allocation of resources and the minimization of beam switching is achieved.
Patent Information
- Application Number
- CN202411838443.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-13
- Publication Date
- 2025-03-07
AI Technical Summary
In ship navigation missions, the coverage of communication satellite beams varies with the change of ship position, making it difficult for existing resource allocation algorithms to achieve the optimal resource allocation scheme.
By dividing the sections of the ship's route, the spatial and temporal information within the section is obtained using linear interpolation method, and whether the beam can cover the ship, combined with genetic algorithms, a comprehensive fitness function is constructed to optimize resource allocation.
The optimal solution for the position monitoring of ships during navigation and satellite resource allocation is realized, ensuring the balanced allocation of resources and the minimization of beam switching.
Smart Images
Figure CN119582928A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of satellite communication technology, and in particular to a synchronous communication satellite resource allocation method based on ship segment beam coverage. Background Art
[0002] In the ocean-going missions of ships, geosynchronous communication satellites are usually used to provide them with uninterrupted satellite communication guarantee. Therefore, it is necessary to implement a reasonable and efficient communication satellite resource allocation algorithm. The communication satellite resource allocation problem is a task planning problem, that is, for the given input as the ship's navigation mission and the constraint condition as the communication satellite resources, find a feasible solution, that is, the resource allocation result, which makes it optimal under certain evaluation indicators.
[0003] In conventional resource allocation problems, only the constraints of the two dimensions of resource quantity and resource occupancy time need to be considered. However, in the communication satellite resource allocation problem of ship navigation missions, the position of the ship will change according to the route, resulting in changes in the coverage of the communication satellite beam on the ship. Therefore, in the resource allocation process, it is necessary to add a third dimension, namely the spatial dimension. Constraints, making it difficult to directly use conventional resource optimization algorithm models to implement it, and it is necessary to design a new resource optimization algorithm model for this. Therefore, we propose a synchronous communication satellite resource allocation method based on the coverage of the ship's flight segment beam. Summary of the invention
[0004] The purpose of the present invention is to solve the problem of communication satellite resource allocation when a ship is sailing. If the problem is simply based on the constraints of the two dimensions of resource quantity and resource occupation time, the satellite beam cannot fully cover the ship after the position of the ship changes according to the route, and thus the optimal resource allocation plan cannot be obtained. By adding the constraints of the third dimension, namely the spatial dimension, a new resource optimization algorithm model is designed.
[0005] To achieve the above object, the present invention provides a method for allocating resources of synchronous communication satellites based on the coverage of ship segment beams, comprising the following steps: S1. Divide the flight segments according to the starting and ending point information of the ship route and the coverage range of the satellite beam, use the linear interpolation method to obtain the spatial and temporal information within the flight segment, and determine whether the beam can cover the ship within a certain time and a certain flight segment; S2. Taking the number of valid flight segments as the queue length, the satellite beam resource allocation problem is transformed into a digital queue optimization problem. According to the principles of beam coverage and resource availability, a feasible satellite beam resource allocation scheme is determined. S3. Using genetic algorithms, with the goal of maximizing the comprehensive fitness function, optimize the feasible satellite beam resource allocation schemes and select the best scheme.
[0006] As a further improvement of the technical solution, the S1 divides the flight segments and determines whether the beam can cover the ship at this time. The method steps are as follows: S1.1.1. The flight segments are divided based on the intersection of the satellite beam and the flight path; S1.1.2. Use the linear interpolation method to calculate the time when the ship arrives at any position in the route segment, and calculate the position of the ship at any point in time; S1.1.3. Calculate the distance from the ship position to the center of the beam, compare the distance with the radius of the beam, and determine whether the beam can cover the ship at this time.
[0007] As a further improvement of the technical solution, the linear interpolation method used in S1.1.2 is as follows:
[0008] in, is the starting point, The starting time, is the end point position, The time for the end, is any position between the starting point and the end point. It is the time corresponding to any position between the starting point and the end point.
[0009] As a further improvement of the technical solution, S2 transforms the satellite beam resource allocation problem into a digital queue optimization problem, and the method steps are as follows: S2.1.1. Collect flight segments and beam information: Define the total number of flight segments obtained in S1 as M, and number all valid flight segments from 1 to M. Similarly, number the number of satellite beam resources from 1 to R, analyze the coverage capability of each beam for each flight segment, and construct the beam coverage matrix. ,in Representation beam Can it cover Valid flight segments, if covered If it cannot be covered, ; S2.1.2. Initialize the resource allocation queue: create a digital queue Q with a length of M. At the same time, create a marking array V with a length of M to mark whether the flight segment has been effectively allocated resources. Initially, all elements are set to 0, indicating that they are not allocated; S2.1.3, iterate resource allocation: allocate satellite beams to valid segments without allocated resources, and update relevant parameters after the allocation is completed; S2.1.4. Verify the validity of the resource allocation scheme: traverse the digital queue to verify it.
[0010] As a further improvement of the technical solution, when allocating satellite beams in S2.1.3, for the valid flight segments of the unallocated resources found , traverse all beams , check the beam Whether the following two conditions are met: A. Beam Can cover Valid flight segments; B. Beam The remaining resources are greater than the flight segment The number of tasks required.
[0011] As a further improvement of the technical solution, in S2.1.3, the allocated beam , update its allocated resource quantity , and update the remaining resource quantity , and from the available beam set corresponding to the beam Remove flight segment ; in, is the number of resources currently allocated to each beam, is the amount of resources required, is the amount of remaining resources, is the total number of resources, is the set of available beams.
[0012] As a further improvement of the technical solution, S3 uses a genetic algorithm to select the optimal solution, and the method steps are as follows: S3.1.1. Set population parameters: Set the population size , and the mutation probability to be used in the genetic algorithm later and the maximum number of genetic generations , and generate the initial population ; S3.1.2. Establish a comprehensive fitness function: Construct a comprehensive fitness function F by taking into account the degree of satisfying the flight segment resource requirements, the balanced allocation of resources and the number of beam switching; S3.1.3, Generate a new generation of population through crossover and mutation operations; S3.1.4. Establish the genetic termination condition: If the current genetic generation exceeds the preset maximum genetic generation , then terminate the genetic algorithm. If the maximum number of genetic generations has not been reached , then the Generation population Return to the previous step as the current population and continue the genetic operation.
[0013] As a further improvement of this technical solution, S3.1.2 takes the average value of resource satisfaction rate of all flight segments , is the resource satisfaction index of all flight segments, and the variance of the number of flight segments allocated to each beam is It is an indicator of the degree of balance of beam allocation, with the minimum number of beam switching. is the beam switching indicator.
[0014] As a further improvement of the technical solution, the formula of the comprehensive fitness function F of S3.1.2 is:
[0015] in, is the weight of resource satisfaction, The weight of the equalization degree assigned to the beam, is the beam switching weight.
[0016] As a further improvement of the present technical solution, S3.1.2 compares the fitness value of the new individual with the fitness value of the current optimal individual. If the fitness value of the new individual is greater than the fitness value of the current optimal individual, the fitness value is updated to the fitness value of the new individual.
[0017] Compared with the prior art, the present invention has the following beneficial effects: The synchronous communication satellite resource allocation method based on the coverage of the ship's flight segment beam divides the flight segment according to the starting and ending point information of the ship's route and the coverage range of the satellite beam, obtains the space and time information in the flight segment by using the linear interpolation method, and judges whether the beam can cover the ship in a certain time and a certain flight segment, so as to realize the position monitoring of the ship during navigation, and obtains the satellite resource allocation plan of the ship during navigation with the spatial position of the ship as the constraint condition; the number of effective flight segments is used as the queue length, and the satellite beam resource allocation problem is converted into a digital queue optimization problem, so that the advantages and disadvantages of the satellite beam resource allocation plan can be intuitively judged, and it is convenient to realize mutation operation when the genetic algorithm is used for optimization in the subsequent optimization; the genetic algorithm is used to take into account the degree of meeting the flight segment resource demand, the balanced resource allocation and the number of beam switching, and a comprehensive fitness function is constructed. With the maximum comprehensive fitness function as the goal, the feasible satellite beam resource allocation plan is optimized, the best plan is selected, and the optimal allocation of satellite beam resources is realized. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1 It is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a schematic diagram of the S1 process of the present invention; Figure 3 This is a schematic diagram of the S2 process of the present invention; Figure 4 It is a schematic diagram of the S3 process of the present invention. DETAILED DESCRIPTION
[0019] The following will be combined with the accompanying drawings in the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0020] At present, in conventional resource allocation problems, only the constraints of the two dimensions of resource quantity and resource occupancy time need to be considered. However, in the communication satellite resource allocation problem of ship navigation missions, since the position of the ship will change according to the route, the coverage of the communication satellite beam to the ship will change. Therefore, in the resource allocation process, it is necessary to add a third dimension, namely the spatial dimension. Constraints, therefore, are difficult to implement directly using conventional resource optimization algorithm models, and a new resource optimization algorithm model needs to be designed for this purpose.
[0021] Therefore, the present invention proposes to divide the flight segments according to the starting and ending point information of the ship route and the coverage of the satellite beam, and use the number of valid flight segments as the queue length to transform the satellite beam resource allocation problem into a digital queue optimization problem. According to the principles of beam coverage and resource availability, feasible satellite beam resource allocation schemes are determined, and a genetic algorithm is used to optimize the feasible satellite beam resource allocation schemes with the goal of maximizing the comprehensive fitness function to select the best scheme.
[0022] The details are as follows: See also Figure 1 As shown, the present invention provides a synchronous communication satellite resource allocation method based on ship segment beam coverage, comprising the following steps: S1. Divide the flight segments according to the starting and ending point information of the ship route and the coverage range of the satellite beam, use the linear interpolation method to obtain the spatial and temporal information within the flight segment, and determine whether the beam can cover the ship within a certain time and a certain flight segment; S2. Taking the number of valid flight segments as the queue length, the satellite beam resource allocation problem is transformed into a digital queue optimization problem. According to the principles of beam coverage and resource availability, a feasible satellite beam resource allocation scheme is determined. S3. Using genetic algorithms, with the goal of maximizing the comprehensive fitness function, optimize the feasible satellite beam resource allocation schemes and select the best scheme.
[0023] like Figure 2As shown, S1 divides the flight segment and determines whether the beam can cover the ship at this time. The method steps are as follows: S1.1.1. The flight segments are divided based on the intersection of the satellite beam and the flight path; S1.1.2. Use the linear interpolation method to calculate the time when the ship arrives at any position in the route segment, and calculate the position of the ship at any point in time; S1.1.3. Calculate the distance from the ship position to the beam center, compare the distance with the beam radius, and determine whether the beam can cover the ship at this time; Among them, linear interpolation is a simple method for numerical estimation between two known data points, and its formula is:
[0024] in, is the starting point, The starting time, is the location of the end point, The time for the end, is any position between the starting point and the end point. It is the time corresponding to any position between the starting point and the end point.
[0025] For example, the ship is located at a position coordinate of 10 nautical miles at 9 am and at a position coordinate of 30 nautical miles at 11 am. If we want to know the position of the ship at 10:30 am , then substitute the data into the formula, namely:
[0026] That is, at 10:30 a.m. the ship was at 25 nautical miles.
[0027] Among them, the distance from the ship position to the beam center is calculated , the beam center position is , the ship's position is , according to the distance formula between two points:
[0028] If the distance from the ship position to the beam center is greater than the radius of the beam, the ship is within the coverage of the beam; otherwise, it is not within the coverage.
[0029] like Figure 3 As shown, S2 transforms the satellite beam resource allocation problem into a digital queue optimization problem, and the method steps are as follows: S2.1.1. Collect flight segments and beam information: Define the total number of flight segments obtained in S1 as M, and number all valid flight segments from 1 to M. Similarly, number the number of satellite beam resources from 1 to R, analyze the coverage capability of each beam for each flight segment, and construct the beam coverage matrix. ,in Representation beam Can it cover Valid flight segments, if covered If it cannot be covered, ; S2.1.2. Initialize the resource allocation queue: create a digital queue Q with a length of M. At the same time, create a marking array V with a length of M to mark whether the flight segment has been effectively allocated resources. Initially, all elements are set to 0, indicating that they are not allocated; S2.1.3, iterate resource allocation: allocate satellite beams to valid segments without allocated resources, and update relevant parameters after the allocation is completed; S2.1.4. Verify the validity of the resource allocation scheme: traverse the digital queue to verify it; The satellite's beam resources are numbered from 1 to R, and each beam (numbered ), denoted as At the same time, the number of resources currently allocated to each beam is counted in real time, recorded as , then the remaining resources of the beam are , analyze the coverage capability of each beam for each flight segment and build a beam coverage matrix ,in Representation beam Can it cover Valid flight segments, if covered If it cannot be covered, ; Suppose there is a satellite with 5 beam resources, numbered 1, 2, 3, 4, and 5. At the same time, the route of a ship is divided into 8 valid segments.
[0030] The total resources and allocated resources for each beam are as follows: Beam Total resources Allocated resources Remaining resources 1 20 8 12 2 15 5 10 3 18 10 8 4 25 12 13 5 22 15 7 Analyze the coverage capability of each beam for each flight segment and build a beam coverage matrix Beam Segment 1 Segment 2 Segment 3 Segment 4 Segment 5 Segment 6 Segment 7 Segment 8 1 1 0 1 0 1 0 0 1 2 0 1 0 1 0 1 0 0 3 1 1 0 0 0 0 1 0 4 0 0 1 1 0 0 0 1 5 0 0 0 0 1 1 1 1 Assume that the number of resources required to perform the mission in each segment is: 5, 8, 6, 9, 7, 6, 5, 4 Assume there is such a digital queue of length 8, Verify that it is a valid resource allocation scheme: For Location ,number , Condition A verification, check the beam coverage matrix , , indicating that beam 1 can cover segment 1, satisfying condition A; Condition B verifies that the remaining resources of beam 1 are 12, and the mission required resources of segment 1 are 5, which meets condition B.
[0031] And so on, verify each position, after checking the digital queue The verification of all positions in the digital queue satisfies the above two conditions, so It represents an effective resource allocation scheme, that is, according to this scheme, satellite beam resources can be reasonably allocated to each flight segment to ensure the ship's demand for satellite communication and other resources when performing tasks in the corresponding flight segment.
[0032] In order to more accurately verify the effectiveness of the solution, when allocating satellite beams in S2.1.3, the valid segments of the unallocated resources found , traverse all beams , check the beam Whether the following two conditions are met: A. Beam Can cover Valid flight segments; B. Beam The remaining resources are greater than the flight segment The number of tasks required; When all beams When these two conditions are met, an effective resource allocation scheme is obtained.
[0033] In order to improve the allocation efficiency of beam resources, S2.1.3 , update its allocated resource quantity , and update the remaining resource quantity , and from the available beam set corresponding to the beam Remove flight segment ; in, is the number of resources currently allocated to each beam, is the amount of resources required, is the amount of remaining resources, is the total amount of resources, is the set of available beams; Considering that its resources have been allocated to this segment, the availability of this beam may have changed for other unallocated segments, so the segment is removed from the set of available beams corresponding to this beam. , and then High beam resource allocation efficiency.
[0034] like Figure 4 As shown, S3 uses a genetic algorithm to select the optimal solution, and the method steps are as follows: S3.1.1. Set population parameters: Set the population size , and the mutation probability to be used in the genetic algorithm later and the maximum number of genetic generations , and generate the initial population ; S3.1.2. Establish a comprehensive fitness function: Construct a comprehensive fitness function F by taking into account the degree of satisfying the flight segment resource requirements, the balanced allocation of resources and the number of beam switching; S3.1.3, Generate a new generation of population through crossover and mutation operations; S3.1.4. Establish the genetic termination condition: If the current genetic generation exceeds the preset maximum genetic generation , then terminate the genetic algorithm. If the maximum number of genetic generations has not been reached , then the Generation population Return to the previous step as the current population and continue the genetic operation; Crossover: Randomly select two individuals from the current population and randomly select a position, and cut the two individuals into two parts from this position; then, combine the first half of individual A and the second half of individual B to form a new individual. Mutation: For the generated new individuals, the number at each position is changed with a certain probability p (called mutation probability), and the changed value is still within the legal range.
[0035] In order to more accurately set the degree of segment resource demand, resource balance allocation and beam switching times, S3.1.2 takes the average value of all segment resource satisfaction rates. , is the resource satisfaction index of all flight segments, and the variance of the number of flight segments allocated to each beam is It is an indicator of the degree of balance of beam allocation, with the minimum number of beam switching. is the beam switching index; Among them, the indicator formulas for the degree of flight segment resource demand, resource balance allocation and beam switching times are as follows:
[0036] in, is the total number of valid flight segments, The current flight segment.
[0037]
[0038] in, is the total number of beams, is the number of flight segments allocated in the resource allocation plan. is the mean number of flight segments.
[0039]
[0040] in, is the number of beam switching times.
[0041] Among them, the formula of the comprehensive fitness function F of S3.1.2 is:
[0042] in, is the weight of resource satisfaction, The weight of the equalization degree assigned to the beam, is the beam switching weight.
[0043] If more attention is paid to meeting the resource requirements of the flight segment, If you want a more balanced distribution of resources, you can increase If the number of beam switching is the most critical factor, you can increase These weight coefficients need to be determined according to the specific application scenario and optimization goal. They can usually be preliminarily set through experiments or prior knowledge, and then adjusted according to the actual effect during the optimization process.
[0044] In order to obtain the global optimal individual, S3.1.2 compares the fitness value of the new individual with the fitness value of the current optimal individual. If the fitness value of the new individual is greater than the fitness value of the current optimal individual, the fitness value is updated to the fitness value of the new individual. In the above satellite beam resource allocation problem, each possible resource allocation scheme (represented by a digital queue) is regarded as an individual, and the quality of the individual is measured by the fitness function. The higher the fitness value, the better the resource allocation scheme corresponding to the individual. The operation of "comparing the fitness value of the new individuals with the fitness value of the current best individual" is to calculate the fitness values of these new individuals after each new individual is generated through genetic operations (such as crossover, mutation, etc.), and then compare them with the fitness value of the currently recorded best individual (the individual with the highest fitness value found so far in the entire optimization process); If the fitness value of the new individual is greater than the fitness value of the current optimal individual, the fitness value is updated to the fitness value of the new individual. This means that if the fitness value of a new individual is found to be higher than the fitness value of the previously recorded optimal individual, it means that the resource allocation plan represented by this new individual is better. Therefore, the current optimal individual is replaced by this new individual, and the recorded optimal fitness value is updated to the fitness value of this new individual, so that this new optimal standard can be used to measure and select better individuals in the future.
[0045] In summary, the working principle of this solution is as follows: The synchronous communication satellite resource allocation method based on the coverage of the ship's flight segment beam divides the flight segment according to the starting and ending point information of the ship's route and the coverage range of the satellite beam, obtains the space and time information in the flight segment by using the linear interpolation method, and judges whether the beam can cover the ship in a certain time and a certain flight segment, so as to realize the position monitoring of the ship during navigation, and obtains the satellite resource allocation scheme of the ship during navigation with the spatial position of the ship as the constraint condition, and converts the satellite beam resource allocation problem into a digital queue optimization problem with the number of effective flight segments as the queue length, so as to intuitively judge the advantages and disadvantages of the satellite beam resource allocation scheme, and facilitate the subsequent use of genetic algorithm optimization, and easy to realize mutation operation, and use genetic algorithm to take into account the degree of meeting the flight segment resource demand, resource balance allocation and beam switching times, to construct a comprehensive fitness function, and take the maximum comprehensive fitness function as the goal, optimize the feasible satellite beam resource allocation scheme, select the best scheme, and realize the optimal allocation of satellite beam resources.
[0046] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.
Claims
1. A synchronous communication satellite resource allocation method based on ship segment beam coverage, characterized in that: The following steps are involved: S1. Divide the flight segments according to the starting and ending point information of the ship route and the coverage range of the satellite beam, use the linear interpolation method to obtain the spatial and temporal information within the flight segment, and determine whether the beam can cover the ship within a certain time and a certain flight segment; S2. Taking the number of valid flight segments as the queue length, the satellite beam resource allocation problem is transformed into a digital queue optimization problem. According to the principles of beam coverage and resource availability, a feasible satellite beam resource allocation scheme is determined. S3. Using genetic algorithms, with the goal of maximizing the comprehensive fitness function, optimize the feasible satellite beam resource allocation schemes and select the best scheme.
2. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 1 is characterized in that: The S1 divides the flight segments and determines whether the beam can cover the ship at this time. The method steps are as follows: S1.1.
1. The flight segments are divided based on the intersection of the satellite beam and the flight path; S1.1.
2. Use the linear interpolation method to calculate the time when the ship arrives at any position in the route segment, and calculate the position of the ship at any point in time; S1.1.
3. Calculate the distance from the ship position to the center of the beam, compare the distance with the radius of the beam, and determine whether the beam can cover the ship at this time.
3. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 2 is characterized in that: The linear interpolation method used in S1.1.2 is as follows: in, is the starting point, The starting time, is the location of the end point, The time for the end, is any position between the starting point and the end point. It is the time corresponding to any position between the starting point and the end point.
4. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 1 is characterized in that: S2 transforms the satellite beam resource allocation problem into a digital queue optimization problem, and the method steps are as follows: S2.1.
1. Collect flight segments and beam information: Define the total number of flight segments obtained in S1 as M, and number all valid flight segments from 1 to M. Similarly, number the number of satellite beam resources from 1 to R, analyze the coverage capability of each beam for each flight segment, and construct the beam coverage matrix. ,in Representation beam Can it cover Valid flight segments, if covered If it cannot be covered, ; S2.1.
2. Initialize the resource allocation queue: create a digital queue Q with a length of M. At the same time, create a marking array V with a length of M to mark whether the flight segment has been effectively allocated resources. Initially, all elements are set to 0, indicating that they are not allocated; S2.1.3, iterate resource allocation: allocate satellite beams to valid segments without allocated resources, and update relevant parameters after the allocation is completed; S2.1.
4. Verify the validity of the resource allocation scheme: traverse the digital queue to verify it.
5. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 4 is characterized in that: When allocating satellite beams in S2.1.3, for valid segments of unallocated resources found , traverse all beams , check the beam Whether the following two conditions are met: A. Beam Can cover Valid flight segments; B. Beam The remaining resources are greater than the flight segment The number of tasks required.
6. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 4 is characterized in that: S2.1.3 is used to allocate the beam , update its allocated resource quantity , and update the remaining resource quantity , and from the available beam set corresponding to the beam Remove flight segment ; in, is the number of resources currently allocated to each beam, is the amount of resources required, is the amount of remaining resources, is the total number of resources, is the set of available beams.
7. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 1 is characterized in that: S3 uses a genetic algorithm to select the optimal solution, and the method steps are as follows: S3.1.
1. Set population parameters: Set the population size , and the mutation probability to be used in the genetic algorithm later and the maximum number of genetic generations , and generate the initial population ; S3.1.
2. Establish a comprehensive fitness function: Construct a comprehensive fitness function F by taking into account the degree of satisfying the flight segment resource requirements, the balanced allocation of resources and the number of beam switching; S3.1.3, Generate a new generation of population through crossover and mutation operations; S3.1.
4. Establish the genetic termination condition: If the current genetic generation exceeds the preset maximum genetic generation , then terminate the genetic algorithm. If the maximum number of genetic generations has not been reached , then the Generation population Return to the previous step as the current population and continue the genetic operation.
8. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 7 is characterized in that: S3.1.2 is based on the average resource satisfaction rate of all flight segments. , is the resource satisfaction index of all flight segments, and the variance of the number of flight segments allocated to each beam is It is an indicator of the degree of balance of beam allocation, with the minimum number of beam switching. is the beam switching indicator.
9. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 8 is characterized in that: The formula of the comprehensive fitness function F of S3.1.2 is: in, is the weight of resource satisfaction, The weight of the equalization degree assigned to the beam, is the beam switching weight.
10. The synchronous communication satellite resource allocation method based on ship segment beam coverage according to claim 7 is characterized in that: The S3.1.2 compares the fitness value of the new individual with the fitness value of the current optimal individual. If the fitness value of the new individual is greater than the fitness value of the current optimal individual, the fitness value is updated to the fitness value of the new individual.