Giant constellation mission path planning method, device and medium based on space-time grid

Abstract

The embodiment of the present invention discloses a giant constellation task path planning method, device and medium based on time-space grid; the method comprises: dividing the time-space grid based on the topological grouping result of the giant constellation satellite, and numbering the divided grids accordingly; obtaining the dynamic matching relationship between the grid and the satellite topological group in the time domain based on the trajectory path of the satellite sub-satellite point; setting the path weight by using the relationship between the static grid distribution and the constellation deployment characteristics and the task requirements, searching and obtaining the static grid path in the time-space grid based on the shortest path algorithm; and locally dynamically adjusting the static grid path by using the working status of the satellite node that currently receives the task information and the neighborhood topological resources to obtain the next satellite node that forwards the task information.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of giant constellation management and mission planning, and in particular to a giant constellation mission path planning method, device and medium based on a space-time grid. Background Art

[0002] Low-orbit giant constellations have the advantages of wide coverage area, large number of satellites, and low communication latency. By establishing a satellite Internet system and combining it with the deployment of ground gateways, it can provide broader application prospects for global Internet communications.

[0003] The traditional constellation mission planning model usually requires ground stations to manage and issue instructions to satellites performing missions, which makes it difficult to ensure high real-time requirements when facing global multi-user and sudden missions. At the same time, due to the large number of satellites and short transit times in low-orbit giant constellations, it is difficult for limited ground station resources to achieve long-term orbital dynamic evolution of large-scale satellites and carry out mission planning in a short period of time. Therefore, it is necessary to establish a precise constellation management framework to efficiently allocate satellite resources, thereby realizing autonomous constellation mission planning. Summary of the invention

[0004] In view of this, the embodiments of the present invention are intended to provide a giant constellation mission path planning method, device and medium based on a space-time grid; the on-board mission planning process can be simplified, system latency can be reduced, and solutions can be provided for efficient transmission of inter-satellite information and the autonomous operation and mission planning of low-orbit giant constellations.

[0005] The technical solution of the embodiment of the present invention is achieved as follows:

[0006] In a first aspect, an embodiment of the present invention provides a giant constellation mission path planning method based on a space-time grid, the method comprising:

[0007] Divide the space-time grids based on the topological clustering results of the giant constellation satellites, and number the divided grids accordingly;

[0008] Based on the trajectory path of the satellite sub-satellite point, the dynamic matching relationship between the grid and the satellite topology group in the time domain is obtained;

[0009] The path weight is set by using the relationship between the static grid distribution and the constellation deployment characteristics and the task requirements, and the static grid path is obtained by searching in the space-time grid based on the shortest path algorithm;

[0010] The static grid path is locally and dynamically adjusted using the working state of the satellite node that currently receives the task information and the neighborhood topology resources to obtain the next satellite node that forwards the task information.

[0011] In a second aspect, an embodiment of the present invention provides a giant constellation mission path planning device based on a space-time grid, the device comprising: a grid division part, an acquisition part, a search part and a dynamic adjustment part; wherein,

[0012] The grid division part is configured to divide the space-time grid based on the topological grouping result of the giant constellation satellites, and number the divided grids accordingly;

[0013] The acquisition part is configured to acquire a dynamic matching relationship between the grid and the satellite topology group in the time domain based on the trajectory path of the satellite sub-satellite point;

[0014] The search part is configured to set the path weight by using the relationship between the static grid distribution and the constellation deployment characteristics and the task requirements, and to search in the space-time grid to obtain the static grid path based on the shortest path algorithm;

[0015] The dynamic adjustment part is configured to use the working status of the satellite node that currently receives the task information and the neighborhood topology resources to perform local dynamic adjustment on the static grid path to obtain the next satellite node that forwards the task information.

[0016] In a third aspect, an embodiment of the present invention provides a computing device, the computing device comprising: a communication interface, a memory and a processor; each component is coupled together through a bus system; wherein,

[0017] The communication interface is used to receive and send signals during the process of sending and receiving information with other external network elements;

[0018] The memory is used to store a computer program that can be run on the processor;

[0019] The processor is used to execute the steps of giant constellation mission path planning based on space-time grid in the first aspect when running the computer program.

[0020] In a fourth aspect, an embodiment of the present invention provides a computer storage medium, wherein the computer storage medium stores a giant constellation task path planning program based on a space-time grid, and when the giant constellation task path planning program based on a space-time grid is executed by at least one processor, the steps of the giant constellation task path planning method based on a space-time grid described in the first aspect are implemented.

[0021] The embodiments of the present invention provide a giant constellation mission path planning method, device and medium based on space-time grid; using multi-scale space-time grid technology, a highly dynamic and complex constellation dynamics evolution model is converted into a grid matching of constellation resources and discrete time and space angles, so as to realize the routing division and satellite resource correspondence of giant constellation long-distance mission planning, thereby realizing efficient interconnection of giant constellations, converting complex orbital long-term evolution and dynamic path planning problems into resource decisions within discrete space-time grids, simplifying the on-board mission planning process, reducing system delays, and providing solutions for efficient transmission of inter-satellite information and realizing autonomous operation and mission planning of low-orbit giant constellations. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of a giant constellation provided by an embodiment of the present invention;

[0023] Figure 2 A schematic flow chart of a giant constellation mission path planning method based on a space-time grid provided by an embodiment of the present invention;

[0024] Figure 3 A schematic diagram of first-level grid division provided by an embodiment of the present invention;

[0025] Figure 4 A schematic diagram of satellite path translation recursion provided by an embodiment of the present invention;

[0026] Figure 5 A schematic diagram of a static grid path provided by an embodiment of the present invention;

[0027] Figure 6 A schematic diagram of a dynamic adjustment process provided by an embodiment of the present invention;

[0028] Figure 7 A schematic diagram of the structure of a giant constellation mission path planning device based on a space-time grid provided by an embodiment of the present invention;

[0029] Figure 8 A schematic diagram of the hardware structure of a computing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0031] See also Figure 1The schematic diagram of a low-orbit giant constellation that can be used in the technical solution of the embodiment of the present invention is shown. Due to the large number of satellites in the low-orbit giant constellation and the short transit time, it is difficult for limited ground station resources to realize the orbital dynamics evolution of long-term large-scale satellites and perform mission planning in a short time. Based on this, the embodiment of the present invention hopes to transform the highly dynamic and complex constellation dynamics evolution model into a grid matching of constellation resources and discrete time and space angles by utilizing multi-scale space-time grid technology, thereby transforming the complex long-term orbital evolution and dynamic planning problems into resource decisions within a discrete space-time grid, simplifying the on-board mission planning process and reducing system latency. Provide a solution for efficient transmission of inter-satellite information and realizing autonomous operation and mission planning of low-orbit giant constellations.

[0032] For the above, see Figure 2 , which shows a giant constellation mission path planning method based on a space-time grid provided by an embodiment of the present invention, the method may include:

[0033] S201: dividing the space-time grids based on the topological grouping results of the giant constellation satellites, and numbering the divided grids accordingly;

[0034] S202: based on the trajectory path of the satellite sub-satellite point, obtain a dynamic matching relationship between the grid and the satellite topology group in the time domain;

[0035] S203: setting path weights by using the relationship between static grid distribution and constellation deployment characteristics and mission requirements, and searching in the space-time grid to obtain a static grid path based on a shortest path algorithm;

[0036] S204: Perform local dynamic adjustment on the static grid path by utilizing the working status of the satellite node that currently receives the task information and the neighborhood topology resources to obtain the next satellite node that forwards the task information.

[0037] pass Figure 2 The technical solution shown uses multi-scale space-time grid technology to transform the highly dynamic and complex constellation dynamics evolution model into a grid matching of constellation resources and discrete time and space angles, realizes the routing division and satellite resource correspondence of long-distance mission planning of giant constellations, thereby realizing efficient interconnection of giant constellations, transforming complex long-term orbital evolution and dynamic path planning problems into resource decisions within discrete space-time grids, simplifying the on-board mission planning process, reducing system latency, and providing solutions for efficient transmission of inter-satellite information and realizing autonomous operation and mission planning of low-orbit giant constellations.

[0038] against Figure 2 In some implementations of the technical solution shown, the topological grouping result based on the giant constellation satellites is used to divide the space-time grids, and the divided grids are numbered accordingly, including:

[0039] The satellites in the constellation are grouped based on inter-satellite connectivity and relative motion relationships to obtain multiple satellite topological groups; wherein adjacent topological groups are connected by inter-satellite links, and the satellites within the topological group are in a relatively stable operating state;

[0040] According to the coverage of the topological group on the ground, a first-level grid matching the coverage capacity of a single topological group is defined;

[0041] Within each primary grid, a secondary grid is set based on the ground coverage of a single satellite;

[0042] Combined with the orbital inclination characteristics, the grids in adjacent latitude bands are set to be staggered, and the degree of staggering is set for each primary grid to adapt to a variety of inclined orbital distributions;

[0043] Each first-level grid is encoded based on longitude and latitude coordinates.

[0044] For the above implementation, combined with Figure 1 In some examples, the giant constellation shown can be topologically divided according to whether the communication between satellites is connected and whether the relative motion relationship is stable, to obtain multiple satellite topological groups. It should be noted that the inter-satellite links between adjacent topological groups can be realized by using the communication connectivity between the edge satellite nodes in each topological group, and the satellites in each topological group can maintain a relatively stable operation relationship over a long period of time. Based on this, for each topological group, its radius r topo can be constrained by the satellite visibility, i.e. Among them, R E is the radius of the earth, H is the thickness of the atmosphere, l AB is the distance between the center points of adjacent topological groups A and B, and r is the orbital radius of the satellite.

[0045] For the above implementation, in some examples, after obtaining the satellite topology groups, the first-level grids that can match the coverage capability of a single topology group can be divided according to the ground coverage range of each topology group, such as Figure 3 For each first-level grid, the span of a single grid can be measured by the longitude and latitude span of the equatorial region, that is:

[0046] l M'N' =4R E arcsin(r topo / r)

[0047] lat 0 = l M'N' / 111

[0048] lon 0 = l M'N' / 111

[0049] Among them, l M'N' is the width of the boundary of the topological group projected on the ground, lat 0 is the latitude span of the grid, lon 0 is the longitude span of the grid.

[0050] For the above implementation, in some examples, for each primary grid, the range of the secondary grid can be divided according to the constraint of the single satellite coverage range. It is worth noting that the secondary grid should be within the maximum coverage capacity of the satellite, that is, Among them, a is the side length of the secondary grid, h is the satellite orbit height, and θ is the ground elevation angle corresponding to the satellite antenna. It can be understood that the smallest secondary grid unit can be arranged inside the primary grid.

[0051] For the above implementation, in some examples, since the satellites included in the giant constellation are not in the same orbital plane, but are dispersed in orbital planes with different altitudes and orbital inclinations, in order to make the grid as a whole adaptable to a variety of inclined orbital distributions, combined with the orbital inclination characteristics, a grid trial-and-error pseudo-distribution in adjacent latitude bands can be set, and the degree of staggering can be set to lat 0 / 2.

[0052] For the above implementation, in some examples, in order to distinguish the primary grids obtained by the above division, a corresponding identifier for identification and distinction can be set; in the embodiment of the present invention, the longitude and latitude coordinates of the grid vertices can be used for encoding. Specifically, the latitude coordinates of the vertex [lat 1 ,lat 1 +lat 0 ,lat 1 +lat 0 ,lat 1 ], longitude coordinate [lon 1 ,lon 1 ,lon 1 +lon 0 ,lon 1 +lon 0 ] is encoded as AB, such as Figure 3 As shown, the position relationship between the code and the grid is as follows:

[0053] A=[180 / lat 0 -(lat 1 +90) / lat 0 +1]

[0054] B=A+[360 / lon 0 -(lon 1+180) / lon 0 ]-1

[0055] Among them, lat 1 for Figure 3 The latitude value of the lower left vertex of the first-level grid shown in 1 for Figure 3 The longitude value of the lower left vertex of the first-level grid shown in .

[0056] It is worth pointing out that based on the above implementation method and examples, a multi-scale space-time grid system of sky and ground for satellite resource location information can be solved.

[0057] against Figure 2 In some implementations of the technical solution shown, the acquisition of a dynamic matching relationship between a grid and a satellite topology group in the time domain based on the trajectory path of a sub-satellite point includes:

[0058] Based on the latitude band distribution of the first-level grid, the longitude span generated by the sub-satellite point trajectory of a single satellite in different latitude bands is counted;

[0059] The satellite's sub-satellite point trajectory is represented by intersections with the latitude band boundaries, thereby representing the satellite path as discrete path endpoints entering and exiting different latitude bands;

[0060] Combined with the periodic drift generated by the satellite orbit, the endpoints of the initial periodic path are used as a template to perform translation recursion on the endpoints of the multi-periodic path;

[0061] The grid points are matched with the translated path endpoints to obtain the grid path spanned by the satellite sub-satellite point trajectory and the duration of spanning a single grid.

[0062] For the above implementation, combined with Figure 4 As shown, the latitude band can be composed of 7 latitude values ​​lat c The result is obtained by dividing, where {lat c |lat c =lat 0 k, -3≤k≤3}, k represents the latitude value sequence number; therefore, the total number of latitude bands is 6. In some examples, after the longitude spans of the sub-satellite point trajectory in different latitude bands are counted, the sub-satellite point trajectory of the satellite can be represented by the intersection with the latitude band boundary. In some examples, the periodic drift of the satellite orbit due to the rotation of the earth in, T N represents the satellite's node period, ω e is the angular velocity of the Earth's rotation, It represents the average angular velocity of the satellite orbit plane drifting along the equator, J 2is the main part of the non-spherical perturbation of the earth, a, e, i are the semi-major axis, eccentricity, and orbital inclination of the satellite, respectively, and n is the angular velocity of the satellite. Combining the above drift, taking the initial period path of the satellite as a model, it can be deduced that the path point of the mth period is translated in the longitude direction with a span of Δβ·m, thus completing the translation recursion of the endpoints of the multi-period path, such as Figure 4 In some examples, the primary grids crossed by the satellite sub-satellite point trajectory are matched according to the multi-period path endpoints obtained by recursion, so that the primary grid paths passed by the satellite and the topological group represented by the satellite can be obtained (such as Figure 4 It is worth noting that this implementation and example discretize the long-term motion of satellites in the constellation in terms of time and space, so as to predict the topological resources that can correspond to each grid at different times, and then provide a dynamic matching relationship between the first-level grid and the on-board topological group, so as to continuously provide the satellite with neighborhood resource information.

[0063] against Figure 2 The technical solution shown, in some implementations, uses the relationship between static grid distribution and constellation deployment characteristics and mission requirements to set path weights, and searches in the space-time grid based on the shortest path algorithm to obtain a static grid path, including:

[0064] Obtain configuration parameters of orbital inclination and intersatellite links in giant constellations;

[0065] Based on the orbital inclination and configuration parameters of the intersatellite link, different weights are assigned to the grid paths according to a set priority strategy;

[0066] Based on the shortest path algorithm, the grid is statically searched to obtain the grid set G corresponding to the shortest path. 1 ,…g i …g n} as the static mesh path.

[0067] For the above implementation, it should be noted that the set priority strategies include same-orbit priority, non-cross-polar region priority, and longitude span less than 180° priority, which can ensure the stability of inter-satellite interconnection; according to the configuration parameters of the constellation about the orbital inclination and the inter-satellite link, it is possible to assign weights to the paths connected by the grids, and then obtain the grid set G corresponding to the shortest path through the shortest path search algorithm according to the weights. 1 ,…g i …g n};like Figure 5As shown in the figure, taking the 7 grids from the starting point to the end point as an example, this set can be considered as the preliminary static grid path planning for long-distance information jumps between satellites. When actually performing information jumps or task forwarding, local dynamic adjustments are made based on the preliminary grid path planning to obtain the actual grid path forwarded from the current satellite to the next satellite.

[0068] Based on this, for Figure 2 In some implementations of the technical solution shown, the local dynamic adjustment of the static grid path using the working state of the satellite node that currently receives the task information and the neighborhood topology resources to obtain the next satellite node that forwards the task information includes:

[0069] The grid set G corresponding to the shortest path corresponding to the satellite node that currently receives the mission information is G={g 1 ,…g i …g n The i-th grid g in} i Perform the following steps until all grids have completed the execution and obtain the next satellite node to forward the task information:

[0070] Get the i-th grid g i Satellite neighborhood resource information;

[0071] Filtering a set of candidate satellites for the next node from the neighborhood resources according to the satellite position and the matching relationship with the grid;

[0072] The satellites in the candidate satellite set S are sorted according to their availability, and the sorted candidate satellite set S = {s 1 ,…s j …s max} to obtain the satellite s with the best matching degree j as potential subjects for evaluation;

[0073] The best matching satellites j Determine whether the task information can be accepted. If so, for the i+1th grid g i+1 Follow the above steps;

[0074] Otherwise, the sorted candidate satellite set S = {s 1 ,…s j …s max Satellites in j+1 As a potential evaluation subject, determine whether the task information can be accepted;

[0075] Until the sorted candidate satellite set S = {s 1 ,…s j …s max} cannot receive the mission information, then the i-1th grid g i-1 Perform network path planning for the starting point, obtain a new static grid path G', and perform local dynamic adjustment based on the new static grid path G'.

[0076] For the above implementation, it should be noted that domain resource information can be continuously provided to the satellite by utilizing the dynamic matching relationship between the primary grid and the onboard topological group. Availability can be determined by including the visual connectivity between the previous node satellite to which the mission information is transmitted and the matching degree with the grid position, so as to obtain the satellite with the best matching degree. In addition, whether the mission information can be accepted can be judged based on whether the satellite is currently in working condition and the priority of the task currently executed by the satellite. For example, if the satellite is not currently in working condition, it can be considered that the mission information can be accepted; and even if it is currently in working condition, but the priority of the task currently executed by the satellite is lower than the task to be forwarded, then it can also be considered that the mission information can be accepted; based on this, the specific implementation process of the above implementation is as follows: Figure 6 As shown, including:

[0077] S601: Get the static grid path G = {g 1 ,…g i …g n};

[0078] S602: Get the i-th grid g i Satellite neighborhood resource information;

[0079] S603: Based on the domain resource information, select the candidate satellite set S of the next node according to the satellite position and the grid matching relationship;

[0080] S604: Sort the candidate satellite set S according to availability. The sorted set S = {s 1 ,…s j …s max};

[0081] S605: Towards satellite j Establish a link and transmit task description information;

[0082] S606: Satellites j Determine whether it is currently in working state:

[0083] If yes, go to S607;

[0084] If not, go to S609: confirm that the match is successful, and return to S602 to obtain the i+1th grid g i Satellite neighborhood resource information;

[0085] S607: Satellitesj Determine whether the priority of the currently executed task is higher than the task to be forwarded:

[0086] If yes, then execute S608: determine satellite s j Unable to accept the task, j = j + 1; and re-match the candidate satellite from the candidate satellite set S and return to execute S605; if all satellites in the candidate satellite set S cannot accept the task information, then the i-1th grid g i-1 Perform network path planning for the starting point, obtain a new static grid path G' and return to execute S601;

[0087] If not, go to S609: confirm that the match is successful, and return to S602 to obtain the i+1th grid g i Satellite neighborhood resource information; until all grids g i Complete the above process.

[0088] Based on the same inventive concept as the above technical solution, see Figure 7 , which shows a giant constellation task path planning device 70 based on time-space grid provided by an embodiment of the present invention, the device 70 includes: a grid division part 701, an acquisition part 702, a search part 703 and a dynamic adjustment part 704; wherein,

[0089] The grid division part 701 is configured to divide the space-time grids based on the topological grouping result of the giant constellation satellites, and number the divided grids accordingly;

[0090] The acquisition part 702 is configured to acquire a dynamic matching relationship between a grid and a satellite topology group in a time domain based on a trajectory path of a sub-satellite point;

[0091] The search part 703 is configured to set path weights by using the relationship between static grid distribution and constellation deployment characteristics and mission requirements, and to search for a static grid path in the space-time grid based on a shortest path algorithm;

[0092] The dynamic adjustment part 704 is configured to dynamically adjust the static grid path locally by utilizing the working status of the satellite node that currently receives the task information and the neighborhood topology resources to obtain the next satellite node that forwards the task information.

[0093] In some examples, the grid division part 701 is configured as follows:

[0094] The satellites in the constellation are grouped based on inter-satellite connectivity and relative motion relationships to obtain multiple satellite topological groups; wherein adjacent topological groups are connected by inter-satellite links, and the satellites within the topological group are in a relatively stable operating state;

[0095] According to the coverage of the topological group on the ground, a first-level grid matching the coverage capacity of a single topological group is defined;

[0096] Within each primary grid, a secondary grid is set based on the ground coverage of a single satellite;

[0097] Combined with the orbital inclination characteristics, the grids in adjacent latitude bands are set to be staggered, and the degree of staggering is set for each primary grid to adapt to a variety of inclined orbital distributions;

[0098] Each first-level grid is encoded based on longitude and latitude coordinates.

[0099] In some examples, the obtaining portion 702 is configured to:

[0100] Based on the latitude band distribution of the first-level grid, the longitude span generated by the sub-satellite point trajectory of a single satellite in different latitude bands is counted;

[0101] The satellite's sub-satellite point trajectory is represented by intersections with the latitude band boundaries, thereby representing the satellite path as discrete path endpoints entering and exiting different latitude bands;

[0102] Combined with the periodic drift generated by the satellite orbit, the endpoints of the initial periodic path are used as a template to perform translation recursion on the endpoints of the multi-periodic path;

[0103] The grid points are matched with the translated path endpoints to obtain the grid path spanned by the satellite sub-satellite point trajectory and the duration of spanning a single grid.

[0104] In some examples, the search portion 703 is configured to:

[0105] Obtain configuration parameters of orbital inclination and intersatellite links in giant constellations;

[0106] Based on the orbital inclination and configuration parameters of the intersatellite link, different weights are assigned to the grid paths according to a set priority strategy;

[0107] Based on the shortest path algorithm, the grid is statically searched to obtain the grid set G corresponding to the shortest path. 1 ,…g i …g n} as the static mesh path.

[0108] In some examples, the dynamic adjustment portion 704 is configured to:

[0109] The grid set G corresponding to the shortest path corresponding to the satellite node that currently receives the mission information is G={g 1 ,…g i …g n The i-th grid g in}i Perform the following steps until all grids have completed the execution and obtain the next satellite node to forward the task information:

[0110] Get the i-th grid g i Satellite neighborhood resource information;

[0111] Filtering a set of candidate satellites for the next node from the neighborhood resources according to the satellite position and the matching relationship with the grid;

[0112] The satellites in the candidate satellite set S are sorted according to their availability, and the sorted candidate satellite set S = {s 1 ,…s j …s max} to obtain the satellite s with the best matching degree j as potential subjects for evaluation;

[0113] The best matching satellites j Determine whether the task information can be accepted. If so, for the i+1th grid g i+1 Follow the above steps;

[0114] Otherwise, the sorted candidate satellite set S = {s 1 ,…s j …s max Satellites in j+1 As a potential evaluation subject, determine whether the task information can be accepted;

[0115] Until the sorted candidate satellite set S = {s 1 ,…s j …s max} cannot receive the mission information, then the i-1th grid g i-1 Perform network path planning for the starting point, obtain a new static grid path G', and perform local dynamic adjustment based on the new static grid path G'.

[0116] It can be understood that in this embodiment, "part" can be part of a circuit, part of a processor, part of a program or software, etc., and of course it can also be a unit, a module, or a non-modular one.

[0117] In addition, each component in this embodiment 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 integrated unit may be implemented in the form of hardware or in the form of software function modules.

[0118] If the integrated unit is implemented in the form of a software function module and is not 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 this embodiment is essentially or the part that contributes to the prior art or the whole 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.) or a processor to perform all or part of the steps of the method described in this embodiment. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0119] Therefore, this embodiment provides a computer storage medium, which stores a giant constellation task path planning program based on a space-time grid. When the giant constellation task path planning program based on a space-time grid is executed by at least one processor, the steps of the giant constellation task path planning method based on a space-time grid in the above technical solution are implemented.

[0120] According to the above-mentioned giant constellation mission path planning device 70 based on space-time grid and computer storage medium, see Figure 8 , which shows the specific hardware structure of a computing device 80 provided by an embodiment of the present invention that can implement the above-mentioned giant constellation mission path planning device 70 based on the space-time grid. The computing device 80 can be a wireless device, a mobile or cellular phone (including a so-called smart phone), a personal digital assistant (PDA), a video game console (including a video display, a mobile video game device, a mobile video conferencing unit), a laptop computer, a desktop computer, a TV set-top box, a tablet computing device, an e-book reader, a fixed or mobile media player, etc. The computing device 80 includes: a communication interface 801, a memory 802 and a processor 803; the various components are coupled together through a bus system 804. It can be understood that the bus system 804 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 804 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, in Figure 8 In the figure, various buses are labeled as bus system 804. Among them,

[0121] The communication interface 801 is used to receive and send signals during the process of sending and receiving information with other external network elements;

[0122] The memory 802 is used to store a computer program that can be run on the processor 803;

[0123] The processor 803 is used to execute the steps of the giant constellation mission path planning method based on space-time grid in the above technical solution when running the computer program.

[0124] It can be understood that the memory 802 in the embodiment of the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 802 of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0125] The processor 803 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 803. The above processor 803 may be a general processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor are combined to be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 802, and the processor 803 reads the information in the memory 802 and completes the steps of the above method in combination with its hardware.

[0126] It is understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0127] For software implementation, the techniques described herein can be implemented by modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0128] Specifically, the processor 803 is further configured to execute the steps of the giant constellation mission path planning method based on the space-time grid in the aforementioned technical solution when running the computer program, which will not be repeated here.

[0129] It can be understood that the exemplary technical solutions of the giant constellation task path planning device 70 and the computing device 80 based on the space-time grid belong to the same concept as the technical solution of the giant constellation task path planning method based on the space-time grid. Therefore, the details not described in detail in the technical solutions of the giant constellation task path planning device 70 and the computing device 80 based on the space-time grid can be referred to the description of the technical solution of the giant constellation task path planning method based on the space-time grid. The embodiment of the present invention will not be described in detail.

[0130] It should be noted that the technical solutions described in the embodiments of the present invention can be combined arbitrarily without conflict.

[0131] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A giant constellation mission path planning method based on space-time grid, It is characterized in that The method comprises: Divide the space-time grids based on the topological clustering results of the giant constellation satellites, and number the divided grids accordingly; Based on the trajectory path of the satellite sub-satellite point, the dynamic matching relationship between the grid and the satellite topology group in the time domain is obtained; The path weight is set by using the relationship between the static grid distribution and the constellation deployment characteristics and the task requirements, and the static grid path is obtained by searching in the space-time grid based on the shortest path algorithm; Using the working state of the satellite node that currently receives the task information and the neighborhood topology resources, the static grid path is locally and dynamically adjusted to obtain the next satellite node that forwards the task information; The step of obtaining a dynamic matching relationship between a grid and a satellite topology group in the time domain based on the trajectory path of the satellite sub-satellite point includes: Based on the latitude band distribution of the first-level grid, the longitude span generated by the sub-satellite point trajectory of a single satellite in different latitude bands is counted; The satellite's sub-satellite point trajectory is represented by intersections with the latitude band boundaries, thereby representing the satellite path as discrete path endpoints entering and exiting different latitude bands; Combined with the periodic drift generated by the satellite orbit, the endpoints of the initial periodic path are used as a template to perform translation recursion on the endpoints of the multi-periodic path; The grid points are matched with the translated path endpoints to obtain the grid path spanned by the satellite sub-satellite point trajectory and the duration of spanning a single grid.

2. The method according to claim 1, It is characterized in that The method of dividing the space-time grid based on the topological clustering result of the giant constellation satellites and numbering the divided grids accordingly includes: The satellites in the constellation are grouped based on inter-satellite connectivity and relative motion relationships to obtain multiple satellite topological groups; wherein adjacent topological groups are connected by inter-satellite links, and the satellites within the topological group are in a relatively stable operating state; According to the coverage of the topological group on the ground, a first-level grid matching the coverage capacity of a single topological group is defined; Within each primary grid, a secondary grid is set based on the ground coverage of a single satellite; Combined with the orbital inclination characteristics, the grids in adjacent latitude bands are set to be staggered, and the degree of staggering is set for each primary grid to adapt to a variety of inclined orbital distributions; Each first-level grid is encoded based on longitude and latitude coordinates.

3. The method according to claim 1, It is characterized in that The method of setting the path weight by using the relationship between the static grid distribution and the constellation deployment characteristics and the task requirements, and searching for the static grid path in the space-time grid based on the shortest path algorithm, includes: Obtain configuration parameters of orbital inclination and intersatellite links in giant constellations; Based on the orbital inclination and configuration parameters of the intersatellite link, different weights are assigned to the grid paths according to a set priority strategy; Based on the shortest path algorithm, the grid is statically searched to obtain the grid set corresponding to the shortest path. G= { g 1 ,… g i … g n } as the static mesh path.

4. The method according to claim 1, It is characterized in that The locally dynamically adjusting the static grid path by using the working state of the satellite node currently receiving the task information and the neighborhood topology resources to obtain the next satellite node forwarding the task information includes: The grid set corresponding to the shortest path corresponding to the satellite node that currently receives the mission information G= { g 1 ,… g i … g n } i Grid g i Perform the following steps until all grids have completed the execution and obtain the next satellite node to forward the task information: Get the i Grid g i Satellite neighborhood resource information; Filtering a set of candidate satellites for the next node from the neighborhood resources according to the satellite position and the matching relationship with the grid; The candidate satellites are assembled S The satellites in the array are sorted by availability, and the sorted candidate satellites are selected from the set S= { s 1 ,… s j … s max } to obtain the satellite with the best match s j as potential subjects for evaluation; The best matching satellite s j Determine whether the task information can be accepted. If so, i +1 grid g i+1 Follow the above steps; Otherwise, the sorted candidate satellite set S= { s 1 ,… s j … s max Satellites in s j+1 As a potential evaluation subject, determine whether the task information can be accepted; Until the sorted set of candidate satellites S= { s 1 ,… s j … s max } cannot receive the mission information, then i -1 grid g i-1 Perform network path planning for the starting point to obtain a new static grid path G ', and according to the new static mesh path G 'Perform local dynamic adjustments.

5. A giant constellation mission path planning device based on space-time grid, It is characterized in that The device comprises: a grid division part, an acquisition part, a search part and a dynamic adjustment part; wherein, The grid division part is configured to divide the space-time grid based on the topological grouping result of the giant constellation satellites, and number the divided grids accordingly; The acquisition part is configured to acquire a dynamic matching relationship between the grid and the satellite topology group in the time domain based on the trajectory path of the satellite sub-satellite point; The search part is configured to set the path weight by using the relationship between the static grid distribution and the constellation deployment characteristics and the task requirements, and to search in the space-time grid to obtain the static grid path based on the shortest path algorithm; The dynamic adjustment part is configured to use the working state of the satellite node that currently receives the task information and the neighborhood topology resources to perform local dynamic adjustment on the static grid path to obtain the next satellite node that forwards the task information; The acquisition part is further configured as follows: Based on the latitude band distribution of the first-level grid, the longitude span generated by the sub-satellite point trajectory of a single satellite in different latitude bands is counted; The satellite's sub-satellite point trajectory is represented by intersections with the latitude band boundaries, thereby representing the satellite path as discrete path endpoints entering and exiting different latitude bands; Combined with the periodic drift generated by the satellite orbit, the endpoints of the initial periodic path are used as a template to perform translation recursion on the endpoints of the multi-periodic path; The grid points are matched with the translated path endpoints to obtain the grid path spanned by the satellite sub-satellite point trajectory and the duration of spanning a single grid.

6. The device according to claim 5, It is characterized in that The search part is configured as follows: Obtain configuration parameters of orbital inclination and intersatellite links in giant constellations; Based on the orbital inclination and configuration parameters of the intersatellite link, different weights are assigned to the grid paths according to a set priority strategy; Perform a static search on the grid based on the shortest path algorithm to obtain the grid set corresponding to the shortest path G= { g 1 ,… g i … g n} as the static grid path 7. A computing device, It is characterized in that The computing device includes: a communication interface, a memory and a processor; each component is coupled together through a bus system; wherein, The communication interface is used to receive and send signals during the process of sending and receiving information with other external network elements; The memory is used to store a computer program that can be run on the processor; The processor is used to execute the steps of the giant constellation mission path planning method based on space-time grid according to any one of claims 1 to 4 when running the computer program.

8. A computer storage medium, It is characterized in that The computer storage medium stores a giant constellation mission path planning program based on a space-time grid. When the giant constellation mission path planning program based on a space-time grid is executed by at least one processor, the steps of the giant constellation mission path planning method based on a space-time grid according to any one of claims 1 to 4 are implemented.

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