Optimization method, device and storage medium for antenna array for communication with satellite

Abstract

The present application discloses an optimization method, device and storage medium for antenna arrays communicating with satellites, including: determining multiple antenna arrays corresponding to a target car and multiple satellites covering the antenna arrays; determining a first satellite connection vector corresponding to each antenna array based on multiple antenna arrays and multiple satellites; randomly generating an initialization population containing multiple second satellite connection vectors according to the first satellite connection vector, wherein the second satellite connection vector is a randomly generated initialization satellite connection vector; generating a corresponding satellite connection optimization function based on the initialization population, and determining the optimal solution of the target optimization function corresponding to the multiple satellite connection optimization functions using a genetic algorithm; and determining the satellites connected to each antenna array when the optimal solution to the target optimization function is determined. Thus, the technical effect of reducing communication loss and improving communication efficiency is achieved.

Description

Technical Field

[0001] The present application relates to the field of satellite communication technology, and in particular to an optimization method, device and storage medium for an antenna array for communicating with a satellite. Background Art

[0002] With the continuous development of automobile communication technology and satellite communication technology, automobiles can receive communication signals sent by satellites by installing phased arrays. For example, when a car is driving in places where mobile communication networks cannot cover, such as deserts and grasslands, it can communicate with satellites through phased arrays to determine the location of the car. For another example, new cars often come with voice call and text message communication functions, so that reliable two-way voice calls and text message communications can be achieved through satellite communications in places where mobile communication networks cannot cover. Therefore, it can be seen from the above that the communication connection between the vehicle-mounted antenna array and the satellite has a huge impact on some functions of the car.

[0003] In addition, since the beam scanning range of a single antenna array is limited, multiple antenna arrays are often installed in cars. Through certain installation methods, the antenna array can cover a larger angle range, thereby increasing the number of satellites that can communicate. Figure 1 This is a schematic diagram of an existing vehicle-mounted antenna array. Figure 1 As shown, a certain car is equipped with 4 antenna arrays, and the installation angles of the antenna arrays 1 to 4 are different. Therefore, by setting the coverage range of the 180° angle area, the technical effect of achieving the maximum beam coverage range can be achieved.

[0004] It is worth noting that due to the large number of satellites, there may be a situation where multiple satellites cover the car at the same time (that is, cover the above multiple antenna arrays at the same time). Therefore, for any antenna array among the multiple antenna arrays, selecting a suitable satellite for communication connection can not only reduce communication loss, but also improve communication efficiency.

[0005] With respect to the technical problem existing in the above-mentioned prior art of how to select a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array, thereby reducing communication loss and improving communication efficiency, no effective solution has been proposed yet. Summary of the invention

[0006] The embodiments of the present disclosure provide a method, device and storage medium for optimizing an antenna array for communicating with a satellite, so as to at least solve the technical problem existing in the prior art of how to select a suitable satellite for communication connection when multiple satellites simultaneously cover a vehicle-mounted antenna array, thereby reducing communication losses and improving communication efficiency.

[0007] According to one aspect of an embodiment of the present disclosure, there is provided an optimization method for an antenna array for satellite communication, including: determining multiple antenna arrays corresponding to a target vehicle and multiple satellites covering the antenna arrays; determining multiple first satellite connection vectors corresponding to each antenna array respectively based on the multiple antenna arrays and the multiple satellites, wherein the first satellite connection vectors are used to represent the satellites connected to each antenna array; randomly generating an initialization population including multiple second satellite connection vectors based on the multiple first satellite connection vectors, wherein the second satellite connection vectors are randomly generated initialization satellite connection vectors; generating a corresponding satellite connection optimization function based on the initialization population, and determining an optimal solution of a target optimization function corresponding to the multiple satellite connection optimization functions using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of each antenna array connected to each satellite, and the target optimization function is used to indicate the maximum fitness of each antenna array connected to each satellite; and determining the satellites connected to each antenna array when the optimal solution to the target optimization function is determined.

[0008] According to another aspect of an embodiment of the present disclosure, a storage medium is further provided, the storage medium including a stored program, wherein when the program is running, a processor executes any one of the methods described above.

[0009] According to another aspect of an embodiment of the present disclosure, there is also provided an optimization device for an antenna array for communicating with a satellite, comprising: a first determination module, for determining a plurality of antenna arrays corresponding to a target vehicle and a plurality of satellites covering the antenna arrays; a second determination module, for determining a plurality of first satellite connection vectors corresponding to each antenna array respectively based on the plurality of antenna arrays and the plurality of satellites, wherein the first satellite connection vector is used to represent the satellite connected to each antenna array; an initialization module, for randomly generating an initialization population including a plurality of second satellite connection vectors based on the plurality of first satellite connection vectors, wherein the second satellite connection vector is a randomly generated initialization satellite connection vector; an optimal solution determination module, for generating a corresponding satellite connection optimization function based on the initialization population, and determining an optimal solution of a target optimization function corresponding to the plurality of satellite connection optimization functions by using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of each antenna array connected to each satellite, and the target optimization function is used to indicate the maximum fitness of each antenna array connected to each satellite; and a satellite determination module, for determining the satellite connected to each antenna array when the optimal solution to the target optimization function is determined.

[0010] According to another aspect of an embodiment of the present disclosure, there is also provided an optimization device for an antenna array for communicating with a satellite, comprising: a processor; and a memory connected to the processor, for providing the processor with instructions for processing the following processing steps: determining multiple antenna arrays corresponding to a target vehicle and multiple satellites covering the antenna arrays; determining multiple first satellite connection vectors corresponding to each antenna array respectively based on the multiple antenna arrays and the multiple satellites, wherein the first satellite connection vectors are used to represent the satellites connected to each antenna array; randomly generating an initialization population including multiple second satellite connection vectors based on the multiple first satellite connection vectors, wherein the second satellite connection vectors are randomly generated initialization satellite connection vectors; generating a corresponding satellite connection optimization function based on the initialization population, and determining an optimal solution of a target optimization function corresponding to the multiple satellite connection optimization functions using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of each antenna array connected to each satellite, and the target optimization function is used to indicate the maximum fitness of each antenna array connected to each satellite; and determining the satellites connected to each antenna array when the optimal solution to the target optimization function is determined.

[0011] The present application provides an optimization method for an antenna array that communicates with a satellite. First, a processor determines multiple antenna arrays corresponding to a target vehicle and multiple satellites covering the antenna arrays. Then, based on the multiple antenna arrays and the multiple satellites, the processor determines multiple first satellite connection vectors corresponding to each antenna array. Further, the processor randomly generates an initialization population containing multiple second satellite connection vectors based on the multiple first satellite connection vectors. Thereafter, the processor generates a corresponding satellite connection optimization function based on the initialization population, and uses a genetic algorithm to determine the optimal solution of a target optimization function corresponding to the multiple satellite connection optimization functions. Finally, when the optimal solution to the target optimization function is determined, the satellites connected to each antenna array are determined.

[0012] Since the present application generates a corresponding satellite connection optimization function based on multiple first satellite connection vectors corresponding to each antenna array, and the satellite connection optimization function is used to indicate the degree of adaptability of each antenna array to each satellite connection, when the degree of adaptability is the largest, it indicates that the satellite connected to the antenna array for communication is optimal. That is, before selecting any one of the multiple satellites for communication connection, the antenna array in the present application predetermines the most suitable satellite corresponding to each antenna array, and connects the antenna array to the most suitable satellite for communication, thereby further reducing communication loss and improving communication efficiency.

[0013] The publication number is CN118523833A, and the name is intelligent antenna control method and related equipment for satellite communication terminal. The method includes: obtaining the initial parameters and environmental data of the system through system initialization and environmental parameter perception, preprocessing the received signal, and adjusting the beam direction and shape of the antenna array unit according to the preprocessed signal to obtain a directional beam signal. According to the directional beam signal, multi-mode switching and resource allocation processing are performed on the communication requirements and network conditions to obtain allocation data. According to the allocation data, interference detection and classification processing are performed on the signal quality and interference situation of the received signal to obtain an interference suppression strategy. According to the interference suppression strategy, the shape and direction of the antenna array unit are dynamically adjusted and self-optimized to obtain antenna parameters and control strategies.

[0014] The publication number is CN118714633A, and the name is a method for intelligent energy consumption control for satellite IoT communication in remote areas. The method specifically includes: determining the estimated energy consumption and delay of IoT communication between user equipment, each edge server and each satellite in different types of remote areas according to the location coordinate information and the calculation load information; determining the predicted movement trajectory of the user equipment, minimizing the estimated energy consumption and the estimated delay as the optimization goal, combining the predicted movement trajectory of the user equipment, and using a multi-objective particle swarm optimization algorithm to dynamically select the optimal edge server and the optimal satellite for the user equipment; based on the predicted movement trajectory of the user equipment, dynamically adjusting the beam pointing parameters, transmission power parameters and beamforming weight parameters of the optimal satellite.

[0015] Thus, when multiple satellites simultaneously cover the vehicle-mounted antenna array, a suitable satellite is selected for communication connection, and the communication loss is further reduced and the communication efficiency is improved. This solves the technical problem in the prior art of how to select a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array, thereby reducing the communication loss and improving the communication efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present application. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings:

[0017] Figure 1 is a schematic diagram of an existing vehicle-mounted antenna array;

[0018] Figure 2 is a schematic diagram of a communication connection between multiple satellites and a target vehicle according to Example 1 of the present application;

[0019] Figure 3A is a schematic diagram of the hardware architecture of satellites 101-10n according to Embodiment 1 of the present application;

[0020] Figure 3B is a schematic diagram of the hardware architecture of the on-board processor of the target vehicle 20 according to Embodiment 1 of the present application;

[0021] Figure 4 is a flow chart of an optimization method for an antenna array for communicating with a satellite according to Embodiment 1 of the present application;

[0022] Figure 5 is a modular schematic diagram of an optimization device for an antenna array for communicating with a satellite according to Embodiment 2 of the present application;

[0023] Figure 6 This is a modular schematic diagram of an optimization device for an antenna array for communicating with a satellite according to Example 3 of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0026] Example 1

[0027] According to this embodiment, an embodiment of an optimization method for an antenna array for communicating with a satellite is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0028] Figure 2 A schematic diagram of the communication connection between multiple satellites and a target car according to the present embodiment is shown. The system includes: multiple satellites 101~10n and a target car 20. The target car 20 is equipped with multiple antenna arrays, and the antenna arrays of the target car 20 are within the communication coverage of the multiple satellites 101~10n, so that the target car 20 can be connected to the multiple satellites 101~10n through the antenna array. In addition, the installation angles of the antenna arrays of the target car 20 are different, and by setting the angle area of ​​each antenna array, the coverage of the antenna array can be maximized, so that the target car 20 can receive data information sent by multiple satellites 101~10n through the antenna array.

[0029] Figure 3A It further shows Figure 1 Schematic diagram of the hardware architecture of satellites 101~10n. Figure 3A As shown, satellites 101~10n include an integrated electronic system, which includes: a processor, a memory, a bus management module and a communication interface. The memory is connected to the processor, so that the processor can access the memory, read the program instructions stored in the memory, read data from the memory or write data to the memory. The bus management module is connected to the processor and is also connected to a bus such as a CAN bus. Therefore, the processor can communicate with the satellite-borne peripherals connected to the bus through the bus managed by the bus management module. In addition, the processor is also connected to communication devices such as cameras, star sensors, measurement and control transponders, and data transmission equipment via the communication interface. It can be understood by those skilled in the art that Figure 3A The structure shown is for illustration only and does not limit the structure of the above electronic device. Figure 3A More or fewer components as shown, or with Figure 3A Different configurations are shown.

[0030] Figure 3B It further shows Figure 2 Schematic diagram of the hardware architecture of the onboard processor of the target car 20. Figure 3B As shown, the onboard processor of the target car 20 may include one or more processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory for storing data, a transmission device for communication functions, and an input / output interface. The memory, the transmission device, and the input / output interface are connected to the processor via a bus. In addition, it may also include: a display, a keyboard, and a cursor control device connected to the input / output interface. A person skilled in the art can understand that Figure 3BThe structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 3B More or fewer components as shown, or with Figure 3B Different configurations are shown.

[0031] It should be noted that Figure 3A and Figure 3B The one or more processors and / or other data processing circuits shown in the figure may generally be referred to as "data processing circuitry" herein. The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other elements in the computing device. As involved in the embodiments of the present disclosure, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0032] Figure 3A and Figure 3B The memory shown in the figure can be used to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the optimization method for antenna arrays for satellite communication in the embodiment of the present disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the optimization method for antenna arrays for satellite communication of the above-mentioned application program is realized. The memory may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.

[0033] It should be noted that, in some optional embodiments, the above Figure 3A and Figure 3B The devices shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. Figure 3A and Figure 3B This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the above described apparatus.

[0034] In the above operating environment, according to a first aspect of this embodiment, a method for optimizing an antenna array for communicating with a satellite is provided. The method comprises: Figure 3B The on-board processor implementation shown in . Figure 4 A schematic diagram showing the process of the method is shown in FIG. Figure 4 As shown, the method includes:

[0035] S402: Determine multiple antenna arrays corresponding to the target car and multiple satellites covering the antenna arrays;

[0036] S404: Based on the multiple antenna arrays and the multiple satellites, determine multiple first satellite connection vectors corresponding to the respective antenna arrays, wherein the first satellite connection vectors are used to represent the satellites connected to the respective antenna arrays;

[0037] S406: randomly generating an initialization population including a plurality of second satellite connection vectors according to the plurality of first satellite connection vectors, wherein the second satellite connection vector is a randomly generated initialization satellite connection vector;

[0038] S408: generating a corresponding satellite connection optimization function based on the initialized population, and determining an optimal solution of a target optimization function corresponding to the plurality of satellite connection optimization functions using a genetic algorithm, wherein the satellite connection optimization function is used to indicate a degree of fitness of each antenna array connected to each satellite, and the target optimization function is used to indicate a maximum degree of fitness of each antenna array connected to each satellite; and

[0039] S410: When an optimal solution to the target optimization function is determined, satellites connected to each antenna array are determined.

[0040] Specifically, first, the onboard processor of the target car 20 determines multiple antenna arrays corresponding to the target car 20 and multiple satellites covering the multiple antenna arrays (S402). For example, the onboard processor of the target car 20 can determine the driving route of the target car 20 based on the navigation information pre-input by the user. And the onboard processor of the target car 20 can determine multiple satellites based on the pre-stored ephemeris information. j In addition, the onboard processor of the target vehicle 20 stores the information related to the multiple antenna arrays. i Related parameter information, such as multiple antenna arrays i The number and installation angle of the target vehicle 20 can be determined to determine the multiple antenna arrays installed on the target vehicle 20. i That is, the onboard processor of the target vehicle 20 can determine the multiple antenna arrays corresponding to the target vehicle 20 i And covering multiple antenna arrays i Multiple satellites j .

[0041] refer to Figure 2 As shown, in this embodiment, the target vehicle 20 is provided with a plurality of antenna arrays, for example i (in, i =1~I), and each antenna array i The angle regions are set differently so that the target vehicle 20 can pass through multiple antenna arrays. iCommunicate with satellites. In addition, due to the high mobility of satellites, there are multiple satellites. j Antenna array covering 20 target cars at the same time i In this case, multiple antenna arrays i Any antenna array in the j However, in order to save communication resources, in this embodiment of the present application, each antenna array can only communicate with a single satellite within the communication coverage area.

[0042] For example, the target vehicle 20 is provided with multiple antenna arrays i (in, i =1~I), and the antenna array i Ability to communicate with multiple satellites j Thus, the antenna array 1 may be connected to the satellite 1, may be connected to the satellite 2, and may also be connected to the satellite 3, which will not be described in detail here.

[0043] Further, the onboard processor of the target vehicle 20 determines a first satellite connection vector corresponding to each antenna array based on the multiple antenna arrays and the multiple satellites (S404). The first satellite connection vector is used to represent the first satellite connection vector corresponding to each antenna array. i Connected satellites. Specifically, referring to the above-mentioned contents, it can be known that, for example, antenna array 1 can be connected to satellite 1, antenna array 1 can be connected to satellite 2, ..., antenna array 1 can be connected to satellite J. Antenna array 2 can be connected to satellite 1, antenna array 2 can be connected to satellite 2, ..., antenna array 2 can be connected to satellite J. And so on. Antenna array I can be connected to satellite 1, antenna array I can be connected to satellite 2, ..., antenna array I can be connected to satellite J. No further details will be given here.

[0044] Therefore, in this embodiment, the antenna arrays are determined i The corresponding first satellite connection vector .in, , . And among them, Indicates satellites 1~J connected to antenna array 1, Indicates satellites 1~J connected to antenna array 2, Represents satellites 1~J connected to antenna array I.

[0045] Further, the onboard processor of the target vehicle 20 randomly generates an initialization population including a plurality of second satellite connection vectors according to the first satellite connection vector (S406). The second satellite connection vector is a randomly generated initialization satellite connection vector. Specifically, the onboard processor of the target vehicle 20 determines the initialization population of the plurality of second satellite connection vectors according to the first satellite connection vector. i The corresponding first satellite connection vector Afterwards, the onboard processor of the target car 20 randomly generates an initialization population .in, . And wherein, the second satellite connection vector in the initialization population , the second satellite connection vector , ..., the second satellite connection vector .

[0046] Then, the onboard processor of the target vehicle 20 generates a corresponding satellite connection optimization function based on the initialization population, and uses a genetic algorithm to determine the optimal solution of the target optimization function corresponding to the multiple satellite connection optimization functions (S408). The satellite connection optimization function is used to indicate the optimal solution of each antenna array. i With each satellite j The adaptability of the communication connection, the target optimization function is used to indicate the suitability of each antenna array i With each satellite j Specifically, when the onboard processor of the target vehicle 20 determines an initialization population including a plurality of second satellite connection vectors, the onboard processor of the target vehicle 20 generates a corresponding satellite connection optimization function based on the initialization population. .in, . And among them, The connection vector with the second satellite The corresponding satellite connection optimization function, The connection vector with the second satellite The corresponding satellite connection optimization function, ..., The connection vector with the second satellite Corresponding satellite connection optimization function.

[0047] The onboard processor of the target vehicle 20 then uses a genetic algorithm to determine the optimal function for connecting with multiple satellites. The corresponding objective optimization function F. Among them, . And wherein the target optimization function is used to indicate the maximum fitness of each antenna array and each satellite communication connection. Finally, the on-board processor of the target car 20 uses a genetic algorithm to determine the optimal solution corresponding to the target optimization function F. That is, the on-board processor of the target car 20 determines the fitness of each antenna array with each satellite communication connection. i The most suitable satellite. For example, if in the multiple satellite connection optimization function, The adaptation degree is the largest, which means that the satellite connection optimization function The corresponding second satellite connection vector The adaptability of each antenna array and satellite connection is the largest. If in multiple satellite connection optimization functions, The adaptation degree is the largest, which means that the satellite connection optimization function The corresponding second satellite connection vector The adaptability of each antenna array and satellite connection is the largest. And so on. If in multiple satellite connection optimization functions, The adaptation degree is the largest, which means that the satellite connection optimization function The corresponding second satellite connection vector The adaptability of each antenna array to the satellite connection is the greatest.

[0048] Referring to the above contents, it can be known that in this embodiment, since each antenna array i It can only communicate with one satellite, so when there are multiple satellites j In the case of i With each satellite j There are many different communication connection methods. Furthermore, since each antenna array i With each satellite j The adaptability when communicating between them is different, so for each antenna array i For example, choosing the most suitable satellite for communication connection can help reduce communication loss and improve communication efficiency.

[0049] Thus, when the onboard processor of the target vehicle 20 uses the genetic algorithm to determine the optimal solution of the target optimization function corresponding to the plurality of satellite connection optimization functions (i.e., when determining the satellite connection optimization function with the greatest fitness), the most suitable satellite for communication connection for each antenna array can be determined. The above content will be described in detail later, so it will not be repeated here.

[0050] Finally, the onboard processor of the target vehicle 20 further determines the satellites connected to each antenna array when the optimal solution of the target optimization function is determined (S410). The adaptation degree is the largest, which means that the satellite connection optimization function The corresponding second satellite connection vector The adaptability of each antenna array connected to the satellite is the largest. Therefore, the onboard processor of the target vehicle 20 can further determine the satellites connected to each antenna array based on the determined optimal solution.

[0051] As described in the background technology, due to the large number of satellites, there may be a situation where multiple satellites cover the car at the same time (that is, cover the above multiple antenna arrays at the same time). Therefore, for any antenna array among the multiple antenna arrays, selecting a suitable satellite for communication connection can not only reduce communication loss, but also improve communication efficiency.

[0052] In view of this, the present application provides an optimization method for an antenna array communicating with a satellite. And because the present application generates a corresponding satellite connection optimization function based on multiple first satellite connection vectors corresponding to each antenna array, and the satellite connection optimization function is used to indicate the degree of fitness of each antenna array connected to each satellite, when the degree of fitness is maximum, it indicates that the satellite connected to the antenna array for communication is optimal. That is, before selecting any one of the multiple satellites for communication connection, the antenna array in the present application predetermines the most suitable satellite corresponding to each antenna array, and connects the antenna array to the most suitable satellite for communication, thereby further reducing communication losses and improving communication efficiency.

[0053] Thus, when multiple satellites simultaneously cover the vehicle-mounted antenna array, a suitable satellite is selected for communication connection, and the communication loss is further reduced and the communication efficiency is improved. This solves the technical problem in the prior art of how to select a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array, thereby reducing the communication loss and improving the communication efficiency.

[0054] Optionally, the operation of determining the optimal solution of the target optimization function corresponding to the multiple satellite connection optimization functions using the genetic algorithm includes: determining multiple third satellite connection vectors based on the multiple second satellite connection vectors, wherein the third satellite connection vectors are sub-generation satellite connection vectors of the second satellite connection vectors; cross-copying each of the third satellite connection vectors to generate multiple fourth satellite connection vectors; performing mutation operations on each of the fourth satellite connection vectors to generate multiple fifth satellite connection vectors; and repeating iterations until a termination condition is met, and outputting the optimal solution corresponding to the target optimization function, wherein the termination condition is used to indicate a preset number of iterations.

[0055] Specifically, referring to the above contents, the onboard processor of the target vehicle 20 randomly generates an initialization population including a plurality of second satellite connection vectors when determining the first satellite connection vector, wherein the plurality of second satellite connection vectors are "chromosomes".

[0056] Afterwards, the on-board processor of the target vehicle 20 randomly generates an initialization population including multiple second satellite connection vectors, and determines the corresponding multiple satellite connection optimization functions, and further determines the satellite connection optimization function corresponding to each second satellite connection vector as the fitness function.

[0057] Further, the on-board processor of the target vehicle 20 determines a plurality of third satellite connection vectors based on the plurality of second satellite connection vectors. The plurality of second satellite connection vectors are initialized satellite connection vectors, and the plurality of third satellite connection vectors are sub-generation satellite connection vectors of the plurality of second satellite connection vectors. For example, when the fitness function corresponding to each second satellite connection vector is determined, the on-board processor of the target vehicle 20 may select some second satellite connection vectors as the first generation according to the fitness corresponding to each second satellite connection vector, and use them to generate the sub-generation (i.e., the plurality of third satellite connection vectors). That is, the second satellite connection vector with a higher fitness has a higher probability of being selected to generate the sub-generation.

[0058] Then, the onboard processor of the target vehicle 20 performs a cross-copy operation on each third satellite connection vector and generates a plurality of fourth satellite connection vectors. The onboard processor of the target vehicle 20 performs a cross-copy operation on each third satellite connection vector, which helps to explore different areas of the solution space.

[0059] Then, the onboard processor of the target vehicle 20 performs a mutation operation on each fourth satellite connection vector and generates a corresponding fifth satellite connection vector. The onboard processor of the target vehicle 20 performs a mutation operation on each fifth satellite connection vector, which helps to increase diversity and prevent the algorithm from converging to a local optimal solution too early.

[0060] Therefore, after the onboard processor of the target vehicle 20 cross-copies and mutates each third satellite connection vector, a plurality of fifth satellite connection vectors (i.e., a new generation population) can be generated. And because the plurality of third satellite connection vectors (i.e., a sub-generation population) are generated based on the plurality of second satellite connection vectors with higher fitness, the fitness of the plurality of fifth satellite connection vectors finally generated is higher.

[0061] Finally, the above steps are repeated until the termination condition is met. The termination condition may be, for example, reaching a preset number of iterations, or the average fitness no longer significantly improving. When the termination condition is met, the onboard processor of the target vehicle 20 outputs the optimal solution corresponding to the target optimization function. The optimal solution corresponding to the target optimization function is used to indicate the maximum fitness of each antenna array connected to each satellite.

[0062] Thus, by utilizing a genetic algorithm to determine the optimal solution of a target optimization function corresponding to a plurality of satellite connection optimization functions, a technical effect of further improving communication efficiency is achieved.

[0063] Optionally, based on the initialized population, the operation of generating a corresponding satellite connection optimization function includes: determining multiple influencing factors corresponding to each second satellite connection vector in the initialized population, wherein the influencing factors include the maximum elevation angle of the satellite, the satellite coverage time and load balancing; determining a weight coefficient corresponding to each influencing factor; and generating multiple satellite connection optimization functions corresponding to each second satellite connection vector based on the multiple influencing factors and the weight coefficients corresponding to each influencing factor.

[0064] Specifically, first, when the on-board processor of the target car 20 determines multiple satellite connection optimization functions, the on-board processor of the target car 20 can determine multiple influencing factors corresponding to each second satellite connection vector in the initialization population. Among them, since there are many factors that affect the adaptability between each antenna array and each satellite, the three factors of the maximum elevation angle of the satellite, the longest coverage time and load balancing are the most important, the three influencing factors of the maximum elevation angle of the satellite, the satellite coverage time and the load balancing are selected in this embodiment. Among them, the maximum elevation angle of the satellite tends to select a high elevation angle satellite, and its corresponding satellite-to-ground link is the shortest and the signal attenuation is the weakest. The longest coverage time can greatly reduce the switching frequency. Load balancing tends to select the satellite with the largest number of idle channels.

[0065] Then, the onboard processor of the target vehicle 20 determines the weight coefficients corresponding to the various influencing factors. The weight coefficient corresponding to the maximum elevation angle of the satellite is set to , and set the weight coefficient corresponding to the longest coverage time to , set the weight coefficient corresponding to load balancing to .

[0066] Finally, the on-board processor of the target vehicle 20 generates a plurality of satellite connection optimization functions corresponding to each second satellite connection vector based on the plurality of influencing factors and the weight coefficients corresponding to each influencing factor. .in, ,and Thus, the multiple satellite connection optimization functions corresponding to each second satellite connection vector are It can be expressed by the following formula:

[0067] (Formula 1)

[0068] (Formula 2)

[0069] (Formula 3)

[0070] in, i is the antenna array tag, i =1~I. j is the satellite tag, j =1~J. Represents an antenna array i By satellite j The duration covered. Represents an antenna array i By satellite j The maximum duration covered. Represents an antenna array i To Satellite j The signal-to-noise ratio of the link, Representation and antenna array i The maximum signal-to-noise ratio among all satellite links within the communication elevation range. Representation and antenna array i Satellite for communication links j The number of remaining channels. Representation and antenna array i The maximum number of remaining channels among all satellites in communication. represents the weight coefficient corresponding to the maximum elevation angle of the satellite, represents the weight coefficient corresponding to the longest coverage time, Indicates the weight coefficient corresponding to load balancing. is a binary variable representing the antenna array i Whether with satellite j Formula 2 indicates that a single antenna array can only communicate with a single satellite to save satellite resources.

[0071] For example, the vector connected with the second satellite The corresponding satellite connection optimization function is . And among them, .in, . And among them, .

[0072] Connect vector with second satellite The corresponding satellite connection optimization function is . And among them, .in, . And among them, .

[0073] And so on.

[0074] Connect vector with second satellite The corresponding satellite connection optimization function is . And among them, .in, . And among them, .

[0075] Thus, through the above-mentioned operation of generating multiple satellite connection optimization functions corresponding to each second satellite connection vector based on multiple influencing factors and weight coefficients corresponding to each influencing factor, the technical effect of determining the adaptability of each antenna array to communicate with each satellite is achieved.

[0076] Optionally, the operation of determining the weight coefficient corresponding to each influencing factor includes: determining a historical period, and based on the driving route of the target vehicle and the ephemeris information of each satellite, collecting multiple first samples, wherein the first sample is used to indicate the duration of time that each antenna array is covered by multiple satellites and the maximum duration of time that each antenna array is covered by any one of the multiple satellites; based on the multiple satellites corresponding to each antenna array, collecting multiple second samples, wherein the second samples are used to indicate the signal-to-noise ratio from each antenna array to the multiple satellites and the maximum signal-to-noise ratio from each antenna array to any one of the multiple satellites; based on the multiple satellites corresponding to each antenna array, collecting multiple third samples, wherein the third sample is used to indicate the number of remaining channels of the multiple satellites communicating with each antenna array and the maximum number of remaining channels of any one of the majority of multiple satellites communicating with each antenna array; and determining the weight coefficient corresponding to each influencing factor based on the multiple first samples, the multiple second samples and the multiple third samples. Further optionally, the operation of determining the weight coefficient corresponding to each influencing factor based on multiple first samples, multiple second samples and multiple third samples includes: determining the corresponding first variance contribution rate based on the multiple first samples, and using the first variance contribution rate as the first weight coefficient, wherein the first weight coefficient corresponds to the multiple first samples; determining the corresponding second variance contribution rate based on the multiple second samples, and using the second variance contribution rate as the second weight coefficient, wherein the second weight coefficient corresponds to the multiple second samples; and determining the corresponding third variance contribution rate based on the multiple third samples, and using the third variance contribution rate as the third weight coefficient, wherein the third weight coefficient corresponds to the multiple third samples.

[0077] Specifically, referring to the above content, it can be known that if the weight coefficient corresponding to the maximum satellite elevation angle, the weight coefficient corresponding to the coverage duration, and the weight coefficient corresponding to the load balancing are to be predetermined, it is necessary to predetermine the historical period, and determine the driving route of the target vehicle 20 and the ephemeris information of multiple satellites in the corresponding historical period. The driving route of the target vehicle 20 can be input in advance by the driver, and the ephemeris information of multiple satellites can be pre-stored in the on-board processor of the target vehicle 20, for example.

[0078] Thus, when the driving route of the target vehicle 20 and the ephemeris information of multiple satellites are determined, the on-board processor of the target vehicle 20 can determine the time information of the on-board processor of the target vehicle 20 communicating with each satellite and the time information of the on-board processor of the target vehicle 20 disconnecting the communication connection with each satellite based on the driving speed and the driving route, and when the on-board processor of the target vehicle 20 communicates with each satellite and the time of disconnecting the communication connection with each satellite is determined, the time when the on-board processor of the target vehicle 20 communicates with each satellite can be further determined. That is, when it is determined that the on-board processor of the target vehicle 20 communicates with each satellite, the duration of the antenna array of the target vehicle 20 being covered by each satellite can be determined. And when the duration of the antenna array of the target vehicle 20 being covered by each satellite is determined, the maximum duration (i.e., the first sample) of each antenna array being covered by any one of the multiple satellites can be determined.

[0079] Then, the onboard processor of the target vehicle 20 determines the signal-to-noise ratio between each antenna array and each satellite based on the communication connection signal with each satellite. And when the signal-to-noise ratio between each antenna array and each satellite is determined, the maximum signal-to-noise ratio (i.e., the second sample) of any one of the multiple satellites can be determined.

[0080] Further, the on-board processor of the target vehicle 20 determines the number of remaining channels of the multiple satellites connected to the respective antenna arrays based on the signals connected to the respective satellites for communication, and determines the maximum number of remaining channels of any one of the multiple satellites connected to the respective antenna arrays for communication (i.e., the third sample).

[0081] After that, when the onboard processor of the target vehicle 20 determines the first sample, the second sample, and the third sample, the weight coefficients corresponding to the various influencing factors can be further determined. For example, the onboard processor of the target vehicle 20 can determine the first variance contribution rate based on the first sample, and use the first variance contribution rate as the first weight coefficient. The onboard processor of the target vehicle 20 can determine the second variance contribution rate based on the second sample, and use the second variance contribution rate as the second weight coefficient. The onboard processor of the target vehicle 20 can determine the third variance contribution rate based on the third sample, and use the third variance contribution rate as the third weight coefficient.

[0082] The first variance contribution rate may be, for example, a ratio of the variance corresponding to the first sample to the total variance. The second variance contribution rate may be, for example, a ratio of the variance corresponding to the second sample to the total variance. The third variance contribution rate may be, for example, a ratio of the variance corresponding to the third sample to the total variance. The total variance may be, for example, the sum of the variance corresponding to the first sample, the variance corresponding to the second sample, and the variance corresponding to the third sample.

[0083] Thus, the operation of determining the first variance contribution rate, the second variance contribution rate and the third variance contribution rate based on the first sample, the second sample and the third sample achieves the technical effect of being able to accurately determine the satellites connected to the communication with each antenna array by determining the weight coefficients corresponding to each influencing factor.

[0084] Therefore, according to the first aspect of this embodiment, the technical effect of selecting a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array is achieved, further reducing communication losses and improving communication efficiency.

[0085] In addition, reference Figure 1 As shown, according to the second aspect of this embodiment, a storage medium is provided, wherein the storage medium includes a stored program, wherein when the program is run, a processor executes any one of the above methods.

[0086] Therefore, according to this embodiment, the technical effect of selecting a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array is achieved, and further reducing communication losses and improving communication efficiency is achieved.

[0087] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0088] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0089] Example 2

[0090] Figure 5 The optimization device for the antenna array for communicating with a satellite according to this embodiment is shown, and the device corresponds to the method according to the first aspect of embodiment 1. Figure 5 As shown, the device includes: a first determination module 510, used to determine multiple antenna arrays corresponding to the target car and multiple satellites covering the antenna arrays; a second determination module 520, used to determine multiple first satellite connection vectors corresponding to each antenna array respectively based on the multiple antenna arrays and the multiple satellites, wherein the first satellite connection vector is used to represent the satellite connected to each antenna array; an initialization module 530, used to randomly generate an initialization population including multiple second satellite connection vectors according to the multiple first satellite connection vectors, wherein the second satellite connection vector is a randomly generated initialization satellite connection vector; an optimal solution determination module 540, used to generate a corresponding satellite connection optimization function based on the initialization population, and determine the optimal solution of the target optimization function corresponding to the multiple satellite connection optimization functions by using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of each antenna array connected to each satellite, and the target optimization function is used to indicate the maximum fitness of each antenna array connected to each satellite; and a satellite determination module 550, used to determine the satellite connected to each antenna array when the optimal solution of the target optimization function is determined.

[0091] Optionally, the optimal solution determining module 540 includes: a third determining module, used to determine a plurality of third satellite connection vectors based on the plurality of second satellite connection vectors, wherein the third satellite connection vector is a sub-generation satellite connection vector of the second satellite connection vector; a cross-copying module, used to cross-copy each third satellite connection vector and generate a plurality of fourth satellite connection vectors; a mutation module, used to perform a mutation operation on each fourth satellite connection vector and generate a plurality of fifth satellite connection vectors; and a repeated iteration module, used to repeat the iteration until a termination condition is satisfied, and output an optimal solution corresponding to the target optimization function, wherein the termination condition is used to indicate a preset number of iterations.

[0092] Optionally, the optimal solution determination module 540 also includes: a fourth determination module, used to determine multiple influencing factors corresponding to each second satellite connection vector in the initialized population, where the influencing factors include satellite maximum elevation angle, satellite coverage time and load balancing; a fifth determination module, used to determine the weight coefficient corresponding to each influencing factor; and an optimization function generation module, used to generate multiple satellite connection optimization functions corresponding to each second satellite connection vector based on multiple influencing factors and the weight coefficients corresponding to each influencing factor.

[0093] Optionally, the fifth operation module includes: a first sample acquisition module, which is used to determine the historical period and collect multiple first samples based on the driving route of the target car and the ephemeris information of each satellite, wherein the first sample is used to indicate the duration of each antenna array being covered by multiple satellites and the maximum duration of each antenna array being covered by any one of the multiple satellites; a second sample acquisition module, which is used to collect multiple second samples based on multiple satellites corresponding to each antenna array, wherein the second samples are used to indicate the signal-to-noise ratio from each antenna array to multiple satellites and the maximum signal-to-noise ratio from each antenna array to any one of the multiple satellites; a third sample acquisition module, which is used to collect multiple third samples based on multiple satellites corresponding to each antenna array, wherein the third sample is used to indicate the number of remaining channels of multiple satellites communicating with each antenna array and the maximum number of remaining channels of any one of the majority of multiple satellites communicating with each antenna array; and a weight coefficient determination module, which is used to determine the weight coefficient corresponding to each influencing factor based on the multiple first samples, the multiple second samples and the multiple third samples.

[0094] Optionally, the weight coefficient determination module includes: a first variance contribution rate determination module, used to determine the corresponding first variance contribution rate based on multiple first samples, and use the first variance contribution rate as a first weight coefficient, wherein the first weight coefficient corresponds to the multiple first samples; a second variance contribution rate determination module, used to determine the corresponding second variance contribution rate based on multiple second samples, and use the second variance contribution rate as a second weight coefficient, wherein the second weight coefficient corresponds to the multiple second samples; and a third variance contribution rate determination module, used to determine the corresponding third variance contribution rate based on multiple third samples, and use the third variance contribution rate as a third weight coefficient, wherein the third weight coefficient corresponds to the multiple third samples.

[0095] Therefore, according to this embodiment, the technical effect of selecting a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array is achieved, and further reducing communication losses and improving communication efficiency is achieved.

[0096] Example 3

[0097] Figure 6 The optimization device for the antenna array for communicating with a satellite according to this embodiment is shown, and the device corresponds to the method according to embodiment 1. Figure 6 As shown, the device includes: a processor 610; and a memory 620, connected to the processor 610, for providing the processor 610 with instructions for processing the following processing steps: determining multiple antenna arrays corresponding to the target vehicle and multiple satellites covering the antenna arrays; determining multiple first satellite connection vectors corresponding to each antenna array respectively based on the multiple antenna arrays and the multiple satellites, wherein the first satellite connection vectors are used to represent the satellites connected to each antenna array; randomly generating an initialization population including multiple second satellite connection vectors according to the multiple first satellite connection vectors, wherein the second satellite connection vectors are randomly generated initialization satellite connection vectors; generating a corresponding satellite connection optimization function based on the initialization population, and determining the optimal solution of the target optimization function corresponding to the multiple satellite connection optimization functions by using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of each antenna array connected to each satellite, and the target optimization function is used to indicate the maximum fitness of each antenna array connected to each satellite; and determining the satellites connected to each antenna array when the optimal solution to the target optimization function is determined.

[0098] Optionally, the operation of determining the optimal solution of the target optimization function corresponding to the multiple satellite connection optimization functions using the genetic algorithm includes: determining multiple third satellite connection vectors based on the multiple second satellite connection vectors, wherein the third satellite connection vectors are sub-generation satellite connection vectors of the second satellite connection vectors; cross-copying each of the third satellite connection vectors to generate multiple fourth satellite connection vectors; performing mutation operations on each of the fourth satellite connection vectors to generate multiple fifth satellite connection vectors; and repeating iterations until a termination condition is met, and outputting the optimal solution corresponding to the target optimization function, wherein the termination condition is used to indicate a preset number of iterations.

[0099] Optionally, based on the initialized population, the operation of generating a corresponding satellite connection optimization function includes: determining multiple influencing factors corresponding to each second satellite connection vector in the initialized population, wherein the influencing factors include satellite maximum elevation angle, satellite coverage time and load balancing; determining a weight coefficient corresponding to each influencing factor; and generating multiple satellite connection optimization functions corresponding to each second satellite connection vector based on the multiple influencing factors and the weight coefficients corresponding to each influencing factor.

[0100] Optionally, the operation of determining the weight coefficient corresponding to each influencing factor includes: determining a historical period, and based on the driving route of the target vehicle and the ephemeris information of each satellite, collecting multiple first samples, wherein the first sample is used to indicate the duration of time that each antenna array is covered by multiple satellites and the maximum duration of time that each antenna array is covered by any one of the multiple satellites; based on the multiple satellites corresponding to each antenna array, collecting multiple second samples, wherein the second samples are used to indicate the signal-to-noise ratio from each antenna array to the multiple satellites and the maximum signal-to-noise ratio from each antenna array to any one of the multiple satellites; based on the multiple satellites corresponding to each antenna array, collecting multiple third samples, wherein the third sample is used to indicate the number of remaining channels of the multiple satellites communicating with each antenna array and the maximum number of remaining channels of any one of the majority of multiple satellites communicating with each antenna array; and determining the weight coefficient corresponding to each influencing factor based on the multiple first samples, the multiple second samples and the multiple third samples.

[0101] Optionally, the operation of determining the weight coefficient corresponding to each influencing factor based on multiple first samples, multiple second samples and multiple third samples includes: determining the corresponding first variance contribution rate based on the multiple first samples, and using the first variance contribution rate as the first weight coefficient, wherein the first weight coefficient corresponds to the multiple first samples; determining the corresponding second variance contribution rate based on the multiple second samples, and using the second variance contribution rate as the second weight coefficient, wherein the second weight coefficient corresponds to the multiple second samples; and determining the corresponding third variance contribution rate based on the multiple third samples, and using the third variance contribution rate as the third weight coefficient, wherein the third weight coefficient corresponds to the multiple third samples.

[0102] Therefore, according to this embodiment, the technical effect of selecting a suitable satellite for communication connection when multiple satellites simultaneously cover the vehicle-mounted antenna array is achieved, and further reducing communication losses and improving communication efficiency is achieved.

[0103] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0104] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0105] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0106] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0108] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc., which can store program code.

[0109] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for optimizing an antenna array for communicating with a satellite, characterized in that: include: Determining a plurality of antenna arrays corresponding to a target vehicle and a plurality of satellites covering the antenna arrays; Based on the multiple antenna arrays and the multiple satellites, determine a first satellite connection vector corresponding to each antenna array, wherein the first satellite connection vector is used to represent a satellite connected to each antenna array; Randomly generate an initialization population including a plurality of second satellite connection vectors according to the first satellite connection vector, wherein the second satellite connection vector is a randomly generated initialization satellite connection vector; Based on the initialization population, a corresponding satellite connection optimization function is generated, and an optimal solution of a target optimization function corresponding to the plurality of satellite connection optimization functions is determined by using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of the connection between each antenna array and each satellite, and the target optimization function is used to indicate the maximum fitness of the connection between each antenna array and each satellite; as well as When the optimal solution of the objective optimization function is determined, the satellites connected to the respective antenna arrays are determined, wherein The operation of determining the optimal solution of the target optimization function corresponding to the plurality of satellite connection optimization functions by using a genetic algorithm comprises: Determine a plurality of third satellite connection vectors based on the plurality of second satellite connection vectors, wherein the third satellite connection vectors are child satellite connection vectors of the second satellite connection vectors; Cross-copying each third satellite connection vector and generating a plurality of fourth satellite connection vectors; performing a mutation operation on each fourth satellite connection vector and generating a plurality of fifth satellite connection vectors; as well as The iteration is repeated until a termination condition is met, and an optimal solution corresponding to the target optimization function is output, wherein the termination condition is used to indicate a preset number of iterations.

2. The method according to claim 1, characterized in that Based on the initialization population, the operation of generating a corresponding satellite connection optimization function includes: Determine a plurality of influencing factors corresponding to each second satellite connection vector in the initialization population, wherein the influencing factors include a maximum elevation angle of the satellite, a satellite coverage time, and load balancing; Determining weight coefficients corresponding to the respective influencing factors; and Based on the multiple influencing factors and the weight coefficients corresponding to the respective influencing factors, multiple satellite connection optimization functions corresponding to the respective second satellite connection vectors are generated.

3. The method according to claim 2, characterized in that The operation of determining the weight coefficient corresponding to each of the influencing factors includes: Determine a historical period, and based on the driving route of the target vehicle and the ephemeris information of each satellite, collect a plurality of first samples, wherein the first samples are used to indicate the duration of each antenna array being covered by the plurality of satellites and the maximum duration of each antenna array being covered by any one of the plurality of satellites; Based on a plurality of satellites corresponding to the respective antenna arrays, a plurality of second samples are collected, wherein the second samples are used to indicate a signal-to-noise ratio from the respective antenna arrays to the plurality of satellites and a maximum signal-to-noise ratio from the respective antenna arrays to any one of the plurality of satellites; Based on a plurality of satellites corresponding to the respective antenna arrays, a plurality of third samples are collected, wherein the third samples are used to indicate the number of remaining channels of the plurality of satellites communicating with the respective antenna arrays and the maximum number of remaining channels of any one of the plurality of satellites communicating with the respective antenna arrays; and Based on the plurality of first samples, the plurality of second samples, and the plurality of third samples, weight coefficients corresponding to the respective influencing factors are determined.

4. The method according to claim 3, characterized in that The operation of determining the weight coefficients corresponding to the respective influencing factors based on the plurality of first samples, the plurality of second samples, and the plurality of third samples includes: Based on the multiple first samples, determine a corresponding first variance contribution rate, and use the first variance contribution rate as a first weight coefficient, wherein the first weight coefficient corresponds to the multiple first samples; Based on the plurality of second samples, determining a corresponding second variance contribution rate, and using the second variance contribution rate as a second weight coefficient, wherein the second weight coefficient corresponds to the plurality of second samples; and Based on the plurality of third samples, a corresponding third difference contribution rate is determined, and the third difference contribution rate is used as a third weight coefficient, wherein the third weight coefficient corresponds to the plurality of third samples.

5. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is run, the processor executes the method according to any one of claims 1 to 4.

6. An optimization device for an antenna array for communicating with a satellite, characterized in that: include: A first determination module is used to determine a plurality of antenna arrays corresponding to a target vehicle and a plurality of satellites covering the antenna arrays; A second determining module is configured to determine a plurality of first satellite connection vectors corresponding to each antenna array respectively based on the plurality of antenna arrays and the plurality of satellites, wherein the first satellite connection vectors are used to represent satellites connected to each antenna array; an initialization module, configured to randomly generate an initialization population including a plurality of second satellite connection vectors according to the plurality of first satellite connection vectors, wherein the second satellite connection vectors are randomly generated initialization satellite connection vectors; an optimal solution determination module, configured to generate a corresponding satellite connection optimization function based on the initialization population, and to determine an optimal solution of a target optimization function corresponding to the plurality of satellite connection optimization functions by using a genetic algorithm, wherein the satellite connection optimization function is used to indicate a degree of fitness of the connection between each antenna array and each satellite, and the target optimization function is used to indicate a maximum degree of fitness of the connection between each antenna array and each satellite; as well as A satellite determination module is used to determine the satellites connected to each antenna array when the optimal solution to the target optimization function is determined, wherein The optimal solution determination module comprises: A third determining module is configured to determine a plurality of third satellite connection vectors based on the plurality of second satellite connection vectors, wherein the third satellite connection vectors are child-generation satellite connection vectors of the second satellite connection vectors; A cross-copy module, used for cross-copying each third satellite connection vector and generating a plurality of fourth satellite connection vectors; a mutation module, configured to perform a mutation operation on each fourth satellite connection vector and generate a plurality of fifth satellite connection vectors; and The iterative module is used to iterate repeatedly until a termination condition is met and output an optimal solution corresponding to the target optimization function, wherein the termination condition is used to indicate a preset number of iterations.

7. The device according to claim 6, characterized in that The optimal solution determination module further includes: a fourth determination module, configured to determine a plurality of influencing factors corresponding to each second satellite connection vector in the initialization population, wherein the influencing factors include a maximum elevation angle of the satellite, a satellite coverage time, and load balancing; A fifth determining module, configured to determine a weight coefficient corresponding to each of the influencing factors; and The optimization function generating module is used to generate a plurality of satellite connection optimization functions corresponding to the respective second satellite connection vectors based on the plurality of influencing factors and the weight coefficients corresponding to the respective influencing factors.

8. An optimization device for an antenna array for communicating with a satellite, characterized in that: include: processor; as well as A memory, connected to the processor, configured to provide the processor with instructions for processing the following processing steps: Determining a plurality of antenna arrays corresponding to a target vehicle and a plurality of satellites covering the antenna arrays; Based on the multiple antenna arrays and the multiple satellites, determine a plurality of first satellite connection vectors corresponding to the respective antenna arrays, wherein the first satellite connection vectors are used to represent satellites connected to the respective antenna arrays; Randomly generate an initialization population including a plurality of second satellite connection vectors according to the plurality of first satellite connection vectors, wherein the second satellite connection vectors are randomly generated initialization satellite connection vectors; Based on the initialization population, a corresponding satellite connection optimization function is generated, and an optimal solution of a target optimization function corresponding to the plurality of satellite connection optimization functions is determined by using a genetic algorithm, wherein the satellite connection optimization function is used to indicate the fitness of the connection between each antenna array and each satellite, and the target optimization function is used to indicate the maximum fitness of the connection between each antenna array and each satellite; as well as When the optimal solution to the objective optimization function is determined, the satellites connected to the respective antenna arrays are determined, wherein The operation of determining the optimal solution of the target optimization function corresponding to the plurality of satellite connection optimization functions by using a genetic algorithm comprises: Determine a plurality of third satellite connection vectors based on the plurality of second satellite connection vectors, wherein the third satellite connection vectors are child satellite connection vectors of the second satellite connection vectors; Cross-copying each third satellite connection vector and generating a plurality of fourth satellite connection vectors; performing a mutation operation on each fourth satellite connection vector and generating a plurality of fifth satellite connection vectors; as well as The iteration is repeated until a termination condition is met, and an optimal solution corresponding to the target optimization function is output, wherein the termination condition is used to indicate a preset number of iterations.

Images