Satellite collision avoidance method, device, and computer-readable storage medium

Abstract

The present application discloses a satellite collision avoidance method, apparatus, and computer-readable storage medium. The method relates to the field of satellite technology. The method comprises: obtaining obstacle information of obstacles within the movable range of a target satellite; calculating the probability that the target satellite will not collide with the obstacle based on the obstacle information and target satellite information of the target satellite; calculating the energy consumed by the target satellite based on the altitude adjusted to avoid collision; constructing a consumption calculation model based on the probability that the target satellite will not collide with the obstacle and the energy consumed by the target satellite; and solving the consumption calculation model using a genetic algorithm with the goal of minimizing consumption to determine the adjusted altitude of the target satellite. This solves the technical problem of excessive fuel consumption when satellites avoid obstacles.

Description

Technical Field

[0001] The present application relates to the field of satellite technology, and in particular to a satellite collision avoidance method, device, and computer-readable storage medium. Background Art

[0002] Currently, the number of low-orbit satellites is increasing, and orbital resources are becoming increasingly scarce. At the same time, there is some space debris in space. For their own safety, low-orbit satellites should be able to cope with the risk of collision.

[0003] Each satellite has its own orbit, and they travel at high speeds, but there's a high probability that some will deviate from their normal orbits. In such cases, satellites operating normally in their orbits will use multi-source data fusion, such as space-based radar and optical sensors, to obtain real-time trajectories of nearby obstacles, such as satellites or space debris, and avoid them promptly. However, these avoidance maneuvers increase propellant consumption, and frequent maneuvers can lead to premature fuel depletion. Satellites running low on fuel face the risk of uncontrolled orbital decay, module shutdown, and even becoming new collision sources.

[0004] The publication number is CN119519812A, and its title is "Method, Device, and Storage Medium for Adjusting Operational Trajectory," which relates to the field of communication satellite technology. It is capable of adjusting the operation trajectory of a communication satellite based on the content of a first signal, thereby avoiding flying objects on the original operation orbit. Human intervention is omitted, and the communication satellite can autonomously avoid flying objects. In the face of an emergency, it can effectively avoid them in the first place. The method includes: receiving a first signal, the first signal including a detection signal emitted by a communication satellite that is reflected back by a flying object and / or detection signals from other communication satellites; wherein the flying object and the communication satellite are on the same operation trajectory; and adjusting the operation trajectory of the communication satellite based on the first signal.

[0005] The publication number is CN111861859A, and its name is "A Space Debris Collision Warning Method", which is applied to space debris positioning systems and warning systems; wherein, the warning system: uses space debris observation information detected by microwave radar on the spacecraft and the spacecraft orbit information to calculate the relative motion trajectory of space debris in the spacecraft orbit coordinate system, and calculates the minimum distance of space debris relative to the spacecraft within the future time T. Through multiple judgments on the minimum distance, it gives warning information and initiates an orbital avoidance program to avoid collision.

[0006] With respect to the technical problem in the prior art mentioned above that the fuel consumption is too high when the satellite avoids obstacles, no effective solution has been proposed so far. Summary of the Invention

[0007] The embodiments of the present application provide a satellite collision avoidance method, apparatus, and computer-readable storage medium to at least solve the technical problem in the prior art of excessive fuel consumption when a satellite avoids obstacles.

[0008] According to one aspect of an embodiment of the present application, a satellite collision avoidance method is provided, comprising: obtaining obstacle information of obstacles within a movable range of a target satellite, wherein the obstacle information includes position information, velocity information, and volume information of the obstacle; calculating a probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes position information, velocity information, and volume information of the target satellite; calculating an energy value consumed by the target satellite based on an altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and solving the consumption calculation model using a genetic algorithm with the goal of minimizing consumption to determine the adjusted altitude of the target satellite.

[0009] According to another aspect of an embodiment of the present application, a satellite collision avoidance device is provided, including: an information acquisition module for acquiring obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; a probability calculation module for calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; an energy value calculation module for calculating the energy value consumed by the target satellite based on the altitude adjusted by the target satellite to avoid collision; a model construction module for constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and an altitude determination module for solving the consumption calculation model through a genetic algorithm with the minimum consumption as the goal, and determining the adjusted altitude of the target satellite.

[0010] According to another aspect of an embodiment of the present application, a satellite collision avoidance device is also provided, including: a processor; and a memory connected to the processor, for providing the processor with instructions for processing the following processing steps: obtaining obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; calculating the energy value consumed by the target satellite based on the altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and solving the consumption calculation model through a genetic algorithm with the minimum consumption as the goal to determine the adjusted altitude of the target satellite.

[0011] According to another aspect of an embodiment of the present application, an integrated electronic system is also provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0012] In an embodiment of the present application, information about obstacles within the target satellite's movable range (including their position, velocity, and volume) is used to determine the probability of collision between the target satellite and the obstacle and the energy consumed to avoid the collision. This information is then used to construct a consumption calculation model. Based on this consumption calculation model, the target satellite's movement distance is determined, aiming to minimize energy consumption and maximize the probability of avoiding a collision. The target satellite can then avoid obstacles based on this movement distance, achieving both collision avoidance and reduced energy consumption, thereby extending the satellite's service life and mitigating the risks associated with premature fuel depletion. This solves the prior art issue of excessive fuel consumption when satellites avoid obstacles. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0014] Figure 1 This is a hardware structure block diagram for implementing the satellite according to Example 1 of the present application;

[0015] Figure 2 is a schematic diagram of a satellite constellation according to Example 1 of the present application;

[0016] Figure 3 1 is a flow chart of a satellite collision avoidance method according to the first aspect of Example 1 of the present application;

[0017] Figure 4 is a schematic diagram of the satellite collision avoidance device according to embodiment 2 of the present application; and

[0018] Figure 5 This is a schematic diagram of the satellite anti-collision device according to Example 3 of the present application. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of this application.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0021] Example 1

[0022] According to this embodiment, a method embodiment of a satellite collision avoidance method 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.

[0023] Figure 1 A schematic diagram showing the hardware architecture of the satellite. Figure 1As shown, the satellite includes a satellite computer, 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. The processor can communicate with the onboard peripherals connected to the bus through the bus managed by the bus management module. In addition, the processor is also connected to 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 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0024] It should be noted that Figure 1 The one or more processors and / or other data processing circuits shown in the figure may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be fully or partially integrated into any of the other components of the computing device. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0025] Figure 1 The memory shown in FIG can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the satellite collision avoidance method in the embodiments of the present application. The processor executes the software programs and modules stored in the memory to perform various functional applications and data processing, thereby implementing the satellite collision avoidance method of the aforementioned application. The memory can include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.

[0026] It should be noted that, in some optional embodiments, the above Figure 1 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 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the apparatus described above.

[0027] Figure 2Schematic diagram of a satellite constellation according to this embodiment. Figure 2 As shown, there are multiple obstacles such as multiple satellites or space debris flying in each satellite orbit S 1~ S m , when the target satellite S 0 When flying in its own orbit, it may encounter abandoned satellites or space debris and collide with them, so the target satellite S 0 will periodically monitor whether there are obstacles within the movable range, and if there are obstacles, avoid them with minimal consumption. S 0 can be SAR Satellite (radar satellite).

[0028] Under the above operating environment, according to the first aspect of this embodiment, a satellite collision avoidance method is provided. Figure 1 The star service computer implementation shown in . Figure 3 A schematic diagram showing the process of the method is shown in FIG. Figure 3 As shown, the method includes:

[0029] S 302: Obtain obstacle information of obstacles within the movable range of the target satellite, where the obstacle information includes position information, speed information, and volume information of the obstacles;

[0030] S 304: Calculate a probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, where the target satellite information includes position information, velocity information, and volume information of the target satellite.

[0031] S 306: Calculating the energy consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision;

[0032] S 308: Constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and

[0033] S 310: With the minimum consumption as the goal, the consumption calculation model is solved by genetic algorithm to determine the adjustment height of the target satellite.

[0034] Specifically, the target satellite S 0 can be U ~ L Move within the range of U Indicates the maximum distance the target satellite can escape from its current orbit and move upwards; LIndicates the maximum distance that the target satellite can escape from its current orbit and move downward. S There may be other satellites or space debris within the movable range of 0 that may act as obstacles and block the target satellite. S 0 moves.

[0035] Thus, the target satellite S 0's satellite computer obtains the information about the target satellite from the orbit parameter file and other data that records the information about the satellite or space debris. S Obstacles within the movable range of 0 S 1~ S m Obstacle information, such as the location information, speed information and volume information of the obstacle. S 1~ S m It could be a satellite or space junk.

[0036] Furthermore, the satellite computer determines the target satellite S 0 target satellite information, including the target satellite's position information, speed information and volume information. Then the satellite computer S 0 target satellite information and obstacle information, calculate the target satellite S 0 and various obstacles S 1~ S m The probability of no collision.

[0037] Furthermore, when the target satellite S 0 If there is an obstacle ahead during flight, the flight altitude needs to be adjusted. S 0 is the height (i.e., distance) adjusted to avoid obstacles, and the energy consumed by the target satellite (e.g., fuel mass). S 0 The energy consumed by moving upward and downward is different, and can be set through experience. For example, the energy consumed by moving upward is 0.5 kg / 100 km , the energy consumed by moving downward is 0.3 kg / 100 km .

[0038] Furthermore, the satellite computer constructs a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite, wherein the consumption calculation model is used to indicate the ratio between the probability that the target satellite does not collide with the obstacle and the energy value consumed when the altitude is adjusted. The satellite computer constructs the consumption calculation model according to the following formula :

[0039] ,

[0040] in represents the altitude (i.e., distance) that the target satellite adjusts to avoid collision, Ps ( ) represents the probability that the target satellite does not collide after adjusting its altitude, E ( ) represents the energy consumed by the target satellite to adjust its altitude. K Indicates the error value.

[0041] Therefore, the star service computer uses the consumption calculation model to maximize the probability of no collision and minimize the energy consumption (i.e., maximum), determines the altitude (i.e., distance) to which the target satellite should be adjusted.

[0042] Furthermore, the star service computer uses genetic algorithms to solve the consumption calculation model with the goal of minimum consumption, so that The maximum value is obtained, thereby determining the adjustment height (i.e., distance) of the target satellite. The genetic algorithm is as follows:

[0043] First, the star service computer initializes the initial population of the genetic algorithm, where the initial population includes the initial individuals 、 ,..., The initial individual is used to indicate the adjustment height (i.e., distance) of the target satellite. The constraint condition for adjusting the height is greater than or equal to the maximum distance of upward movement. U , and is less than or equal to the maximum distance of downward movement L .

[0044] After that, the star service computer will consume the calculation model As the initial individual for evaluation 、 ,..., The fitness model of . Thus, the star service computer will 、 ,..., Substitute into the consumption calculation model respectively , k =1~ y .

[0045] The consumption calculation model is thus:

[0046] .

[0047] Then the star service computer determines the fitness Calculate the selection probability of each initial individual based on its fitness. Then, select the first number of initial individuals with the highest selection probability as the first individual, thereby generating the first population. Individuals with higher fitness have a greater probability of being selected. The method for calculating the selection probability can be, for example, a roulette wheel selection method.

[0048] The star service computer then determines a second number of individuals from the first population based on a preset crossover rate, performs a crossover operation on the individuals, generates new individuals (ie, second individuals), and thus forms the second population with the second individuals.

[0049] The star service computer then determines a third number of individuals from the second population based on a preset mutation rate, performs mutation operations on the individuals, generates new individuals (ie, the third individual), and thus forms the third population with the third individual.

[0050] At this point, the first round of iteration of the genetic algorithm is completed.

[0051] In the second iteration, the Star Service Computer inputs the third individual from the third population into the consumption calculation model to determine the fitness of each third individual. The Star Service Computer then performs selection, crossover, and mutation on the third individuals according to the steps in the first iteration, generating a new population. This completes the second iteration of the genetic algorithm.

[0052] The star service computer then performs multiple rounds of iterative calculations according to the above steps until the preset number of iterations is reached.

[0053] For example, the number of iterations is preset to three, so the star service computer uses the individual with the highest fitness determined in the third round of iteration as the adjustment height.

[0054] As mentioned in the background, the number of low-orbit satellites is increasing, while orbital resources are becoming increasingly scarce. Furthermore, there is space debris in space. For their own safety, low-orbit satellites must be able to mitigate collision risks. Each satellite has its own orbit and operates at a relatively high speed, but it is very likely that some satellites will deviate from their normal orbits. In such cases, satellites operating normally in their orbits will use multi-source data fusion, such as space-based radar and optical sensors, to obtain real-time trajectories of nearby obstacles, such as satellites or space debris, and avoid them promptly. However, satellites evading obstacles consume more propellant, and frequent maneuvers can lead to premature fuel depletion. Satellites running low on fuel face the risk of uncontrolled orbital decay, functional module shutdown, and even becoming new collision sources.

[0055] To address the above-mentioned technical issues, the technical solutions of the embodiments of the present application utilize information about obstacles within the target satellite's movable range (including their position, velocity, and volume) to determine the probability of collision between the target satellite and the obstacle and the energy consumed to avoid the collision. This information is then used to construct a consumption calculation model. Based on this consumption calculation model, the target satellite's movement distance is determined, aiming to minimize energy consumption and maximize the probability of avoiding a collision. The target satellite can then avoid obstacles based on this movement distance, achieving both collision avoidance and reduced energy consumption, thereby extending the satellite's service life and avoiding the various risks associated with premature fuel depletion. This resolves the prior art issue of excessive fuel consumption when satellites avoid obstacles.

[0056] Optionally, the operation of calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

[0057] Specifically, the satellite computer determines that at the next moment, the target satellite S 0's location information ( x 0, y 0, z 0), and all obstacles S j Location information ( x j , y j , z j ). Among them, at the next moment, the target satellite S 0's location information ( x 0, y 0, z 0) can be the target satellite S 0 after adjusting the flight altitude. Then the satellite computer will calculate the position information based on the position information ( x 0, y 0, z 0) and obstacles S j Location information ( x j , y j , z j ), calculate the target satellite S 0 On the flight trajectory after adjusting the flight altitude, S jMinimum approach distance d j :

[0058] .

[0059] Thus, according to the above formula, the satellite computer traverses the target satellite S 0 All time points of flying on the flight track after adjusting the flight altitude t , find the obstacles S j The corresponding minimum distance is used as the target satellite S 0 and obstacles S j Minimum approach distance d j .

[0060] Furthermore, the satellite computer calculates the minimum approach distance d j As well as the speed and volume information of the target satellite and the obstacle, the probability of no collision between the target satellite and the obstacle is calculated.

[0061] Therefore, this technical solution can accurately assess the probability of no collision by calculating the minimum approach distance between the target satellite and the obstacle and combining the speed information and volume information of both parties, making the calculation of the collision probability more comprehensive and accurate.

[0062] Optionally, the operation of calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: calculating the probability that the target satellite and the obstacle do not collide based on the following formula: Ps :

[0063] (1)

[0064] (2)

[0065] (3)

[0066] (4)

[0067] (5)

[0068] in P j Indicates the target satellite and the j The probability of collision with an obstacle, m Indicates the number of obstacles, j =1~ m , T0 indicates the volume information of the target satellite. T j Indicates the j The volume information of each obstacle, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and j The equivalent collision radius of obstacles, Indicates the target satellite and j The effective time window for the relative interaction of obstacles, d j Indicates the minimum approach distance, represents the speed error, Indicates position error.

[0069] Specifically, the satellite computer acquires the target satellite S Volume of 0 T 0 and various obstacles S j Volume T j , then use formula (5) according to the target satellite S Volume of 0 T 0 and various obstacles S j Volume T j , calculate the target satellites respectively S 0 equivalent radius r 0 and obstacles S j The equivalent radius r j , then calculate the target satellite S 0 equivalent radius r 0 and obstacles S j The equivalent radius r j The target satellite is obtained by summing S 0 and obstacles S j The equivalent collision radius R j .

[0070] Furthermore, the satellite computer obtains the speed of the target satellite and each obstacle, and then calculates the target satellite according to the speed of the target satellite and each obstacle.S 0 and each obstacle S j Relative speed V j Then the star service computer uses formula (4) according to the equivalent collision radius R j and relative speed V j , calculate the effective time window The effective time window Used to indicate the higher the relative speed, the target satellite S 0 and obstacles S j The shorter the rendezvous time, the smaller the chance of collision.

[0071] Furthermore, the satellite computer obtains the speed error determined based on the empirical value , using formula (3) according to the speed error and the effective time window Determining position error .

[0072] Furthermore, the satellite computer uses formula (2) according to the effective time window , position error , equivalent collision radius R j , relative speed V j and minimum approach distance d j , calculate the target satellite S 0 and obstacles S j Probability of collision P j .in It represents the product of relative velocity and equivalent collision radius, reflecting the volume of collision area swept per unit time. Medium, minimum approach distance d j The smaller it is, the weaker the exponential decay is and the higher the collision probability is; It indicates the cumulative effect of speed error within the time window. The higher the speed or the longer the time window, the more obvious the error accumulation.

[0073] Furthermore, the satellite computer uses formula (1) according to the target satellite S 0 and obstacles S j Probability of collision P j , calculate the target satellite S 0 and obstacles Sj Probability of no collision Ps .

[0074] Therefore, this technical solution makes the assessment of collision probability more comprehensive and accurate through the minimum approach distance, dynamic parameters such as the speed and volume of the target satellite and obstacle, as well as the influence of speed error and position error.

[0075] Optionally, the operation of constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite includes:

[0076] Construct a consumption calculation model based on the following formula :

[0077] ,

[0078] in Indicates the altitude that the target satellite adjusts to avoid collision. Ps ( ) represents the probability that the target satellite does not collide after adjusting its altitude, E ( ) represents the energy consumed by the target satellite to adjust its altitude. K The error value is represented by . Thus, the star service computer can use the consumption calculation model to maximize the probability of no collision and minimize the energy consumption (i.e., The maximum altitude is used to determine the target satellite's adjusted altitude. This technical solution uses a consumption calculation model based on the probability of collision avoidance and the amount of energy consumed to determine the target satellite's moving distance. This ensures a trade-off between safety and energy consumption at different adjustment altitudes, ensuring flight safety while reducing unnecessary energy waste.

[0079] Optionally, with minimum consumption as the goal, a consumption calculation model is solved by a genetic algorithm to determine the operation of adjusting the height of the target satellite, including: determining the number of binary bits of an initial population composed of multiple chromosomes of the genetic algorithm based on the movable range and movement accuracy of the target satellite, wherein the movement accuracy is used to indicate the unit length of the target satellite's movement; generating a binary-based initial population based on the binary bit number, wherein the initial population is the initial adjustment height of the target satellite; and solving the consumption calculation model based on the initial population to determine the adjustment height of the target satellite.

[0080] Specifically, when determining the target satellite's adjustment altitude using a genetic algorithm, the satellite computer first generates an initial population, where each chromosome corresponding to the initial individual in the initial population is a binary string. The satellite computer then determines the number of binary bits in the chromosome binary string based on the target satellite's movable range and movement accuracy. The movement accuracy indicates the unit length of the target satellite's movement, for example, 100 km. The satellite computer then determines the number of binary bits in the initial population using the following formula: n :

[0081] ,

[0082] in U Indicates the maximum distance the target satellite is adjusted upwards. L Indicates the maximum distance that the target satellite is adjusted downward, where L is a negative number, SA Indicates the movement accuracy of the preset target satellite.

[0083] Furthermore, the star service computer will 、 ,..., (i.e. decimal numbers) are substituted into the consumption calculation model , k =1~ y .

[0084] The consumption calculation model is thus:

[0085] .

[0086] Then the star service computer determines the fitness Calculate the selection probability of each initial individual based on its fitness. Then, select the first number of initial individuals with the highest selection probability as the first individual, thereby generating the first population. Individuals with higher fitness have a greater probability of being selected. The method for calculating the selection probability can be, for example, a roulette wheel selection method.

[0087] Furthermore, the satellite service computer generates the distance (decimal number) adjusted by the first individual in the first group, that is, the target satellite. n The star service computer then determines a second number of individuals from the first population based on a predetermined crossover rate, performs a crossover operation on the chromosome binary strings corresponding to the plurality of individuals, and generates chromosome binary strings for new individuals (i.e., the second individual), thereby forming the second population with the second individual.

[0088] The Star Service Computer then determines a third number of individuals from the second population based on a pre-set mutation rate, performs a mutation operation on the chromosome binary strings corresponding to these individuals, and generates chromosome binary strings for a new individual (i.e., the third individual). The Star Service Computer then decodes each chromosome binary string using the following formula to determine the third individual (i.e., the adjusted height):

[0089] ,

[0090] ,

[0091] in Indicates the accuracy parameter, which is a transition value; Represents the chromosome binary string i number of digits; n The number of bits representing the chromosome binary string.

[0092] Thus, the Star Service Computer formed the third individual into the third group.

[0093] At this point, the first round of iteration of the genetic algorithm is completed.

[0094] In the second iteration, the Star Service Computer inputs the third individual from the third population into the consumption calculation model to determine the fitness of each third individual. Then, following the steps from the first iteration, the Star Service Computer sequentially performs selection, crossover, and mutation operations on the chromosome binary strings of the third individual to generate a new population. This completes the second iteration of the genetic algorithm.

[0095] The star service computer then performs multiple rounds of iterative calculations according to the above steps until the preset number of iterations is reached.

[0096] For example, the number of iterations is preset to three, so the star service computer uses the individual with the highest fitness determined in the third round of iteration as the adjustment height.

[0097] Therefore, this technical solution avoids invalid solutions due to insufficient precision by ensuring that the step size of the height adjustment meets the preset accuracy requirements, and ensures the accuracy of the solution and avoids invalid iterations by converting the binary string into the actual adjustment height.

[0098] Optionally, the operation of determining the number of binary bits of an initial population composed of a plurality of chromosomes of a genetic algorithm according to the movable range and the moving accuracy of the target satellite includes:

[0099] The number of binary digits of the initial population is determined according to the following formula n :

[0100] ,

[0101] in U Indicates the maximum distance the target satellite is adjusted upwards. L Indicates the maximum distance to which the target satellite is adjusted downwards. SA Indicates the moving accuracy of the target satellite.

[0102] This technical solution, through the calculated binary bit number, ensures that the adjustment height of each chromosome binary string has sufficient accuracy within the target satellite's movable range. This not only avoids the solution being too coarse due to overly coarse coding, but also prevents the waste of computing resources caused by overly detailed coding.

[0103] Optionally, the operation of determining the adjustment altitude of the target satellite includes: determining a chromosome binary string corresponding to the adjustment altitude according to the consumption calculation model; and decoding the chromosome binary string using the following formula to determine the adjustment altitude:

[0104] ,

[0105] ,

[0106] in represents the precision parameter, Represents the chromosome binary string i digits, n The number of bits representing the chromosome binary string.

[0107] Therefore, this technical solution is based on parameter restrictions such as the movement accuracy of the target satellite and the number of bits of the chromosome binary string, so that on the basis of satisfying these constraints, the decoding strategy can be flexibly adjusted so that the final adjusted height meets the actual needs.

[0108] In addition, according to a second aspect of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0109] Therefore, according to this embodiment, obstacle information (including position, velocity, and volume) within the target satellite's movable range is used to determine the collision probability between the target satellite and the obstacle and the energy consumed to avoid the collision. This information is then used to construct a consumption calculation model. Based on this consumption calculation model, the target satellite's movement distance is determined to minimize energy consumption and maximize the probability of avoiding a collision. The target satellite can then avoid obstacles based on this movement distance, achieving both collision avoidance and reduced energy consumption, thereby extending the satellite's service life and mitigating the risks associated with premature fuel depletion. This solves the existing technical problem of excessive fuel consumption when satellites avoid obstacles.

[0110] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0111] Through the above description of the embodiments, 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, or by means of hardware, but in many cases the former is a better implementation method. Based on this 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), including several instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0112] Example 2

[0113] Figure 4 FIG4 shows a satellite collision avoidance device 400 according to this embodiment, which corresponds to the method according to the first aspect of embodiment 1. Figure 4 As shown, the device 400 includes: an information acquisition module 410, used to obtain obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; a probability calculation module 420, used to calculate the probability that the target satellite and the obstacle do not collide based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; an energy value calculation module 430, used to calculate the energy value consumed by the target satellite based on the altitude adjusted by the target satellite to avoid collision; a model construction module 440, used to construct a consumption calculation model based on the probability that the target satellite and the obstacle do not collide and the energy value consumed by the target satellite; and an altitude determination module 450, used to solve the consumption calculation model through a genetic algorithm with the minimum consumption as the goal, and determine the adjusted altitude of the target satellite.

[0114] Optionally, the probability calculation module 420 includes: a first calculation submodule, used to calculate the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and a second calculation submodule, used to calculate the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

[0115] Optionally, the energy value calculation module 430 includes a third calculation submodule for calculating the probability of no collision between the target satellite and the obstacle according to the following formula: Ps :

[0116] (1)

[0117] (2)

[0118] (3)

[0119] (4)

[0120] (5)

[0121] in P j Indicates the target satellite and the j The probability of collision with an obstacle, m Indicates the number of obstacles, j =1~ m , T 0 indicates the volume information of the target satellite. T j Indicates the j The volume information of each obstacle, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and j The equivalent collision radius of obstacles, Indicates the target satellite and j The effective time window for the relative interaction of obstacles, d j Indicates the minimum approach distance, represents the speed error, Indicates position error.

[0122] Optionally, the model building module 440 includes: a fourth calculation submodule for building a consumption calculation model according to the following formula :

[0123] ,

[0124] in Indicates the altitude that the target satellite adjusts to avoid collision. Ps ( ) represents the probability that the target satellite does not collide after adjusting its altitude, E ( ) represents the energy consumed by the target satellite to adjust its altitude. K Indicates the error value.

[0125] Optionally, the altitude determination module 450 includes: a first determination submodule, used to determine the number of binary bits of an initial population composed of multiple chromosomes of the genetic algorithm based on the movable range and movement accuracy of the target satellite, wherein the movement accuracy is used to indicate the unit length of the target satellite's movement; a second determination submodule, used to generate a binary-based initial population based on the number of binary bits, wherein the initial population is the initial adjustment altitude of the target satellite; and a third determination submodule, used to solve the consumption calculation model based on the initial population to determine the adjustment altitude of the target satellite.

[0126] Optionally, the first determining submodule includes: a first determining unit for determining the number of binary digits of the initial population according to the following formula: n :

[0127] ,

[0128] in U Indicates the maximum distance the target satellite is adjusted upwards. L Indicates the maximum distance to which the target satellite is adjusted downwards. SA Indicates the movement accuracy of the target satellite.

[0129] Optionally, the third determination submodule includes: a second determination unit, configured to determine a chromosome binary string corresponding to the adjustment height according to the consumption calculation model; and a third determination unit, configured to decode the chromosome binary string using the following formula to determine the adjustment height:

[0130] ,

[0131] ,

[0132] in represents the precision parameter, Represents the chromosome binary string i digits,n The number of bits representing the chromosome binary string.

[0133] Therefore, according to this embodiment, obstacle information (including position, velocity, and volume) within the target satellite's movable range is used to determine the collision probability between the target satellite and the obstacle and the energy consumed to avoid the collision. This information is then used to construct a consumption calculation model. Based on this consumption calculation model, the target satellite's movement distance is determined to minimize energy consumption and maximize the probability of avoiding a collision. The target satellite can then avoid obstacles based on this movement distance, achieving both collision avoidance and reduced energy consumption, thereby extending the satellite's service life and mitigating the risks associated with premature fuel depletion. This solves the existing technical problem of excessive fuel consumption when satellites avoid obstacles.

[0134] Example 3

[0135] Figure 5 FIG2 shows a satellite collision avoidance device 500 according to this embodiment, which corresponds to the method according to the first aspect of embodiment 1. Figure 5 As shown, the device 500 includes: a processor 510; and a memory 520, connected to the processor 510, for providing the processor 510 with instructions for processing the following processing steps: obtaining obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes the position information, speed information and volume information of the obstacle; calculating the probability that the target satellite and the obstacle do not collide based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes the position information, speed information and volume information of the target satellite; calculating the energy consumed by the target satellite based on the altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model based on the probability that the target satellite and the obstacle do not collide and the energy consumed by the target satellite; and solving the consumption calculation model using a genetic algorithm with the minimum consumption as the goal to determine the adjusted altitude of the target satellite.

[0136] Optionally, the operation of calculating the probability that the target satellite does not collide with the obstacle based on the obstacle information and the target satellite information of the target satellite includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle.

[0137] Optionally, the operation of calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: calculating the probability that the target satellite and the obstacle do not collide based on the following formula: Ps :

[0138] (1)

[0139] (2)

[0140] (3)

[0141] (4)

[0142] (5)

[0143] in P j Indicates the target satellite and the j The probability of collision with an obstacle, m Indicates the number of obstacles, j =1~ m , T 0 indicates the volume information of the target satellite. T j Indicates the j The volume information of each obstacle, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and j The equivalent collision radius of obstacles, Indicates the target satellite and j The effective time window for the relative interaction of obstacles, d j Indicates the minimum approach distance, represents the speed error, Indicates position error.

[0144] Optionally, the operation of constructing a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite includes: constructing the consumption calculation model according to the following formula :

[0145] ,

[0146] in Indicates the altitude that the target satellite adjusts to avoid collision. Ps ( ) represents the probability that the target satellite does not collide after adjusting its altitude, E ( ) represents the energy consumed by the target satellite to adjust its altitude. K Indicates the error value.

[0147] Optionally, with minimum consumption as the goal, a consumption calculation model is solved by a genetic algorithm to determine the operation of adjusting the height of the target satellite, including: determining the number of binary bits of an initial population composed of multiple chromosomes of the genetic algorithm based on the movable range and movement accuracy of the target satellite, wherein the movement accuracy is used to indicate the unit length of the target satellite's movement; generating a binary-based initial population based on the binary bit number, wherein the initial population is the initial adjustment height of the target satellite; and solving the consumption calculation model based on the initial population to determine the adjustment height of the target satellite.

[0148] Optionally, the operation of determining the number of binary digits of the initial population composed of multiple chromosomes of the genetic algorithm according to the movable range and the moving accuracy of the target satellite includes: determining the number of binary digits of the initial population according to the following formula n :

[0149] ,

[0150] in U Indicates the maximum distance the target satellite is adjusted upwards. L Indicates the maximum distance to which the target satellite is adjusted downwards. SA Indicates the moving accuracy of the target satellite.

[0151] Optionally, the operation of determining the adjustment altitude of the target satellite includes: determining a chromosome binary string corresponding to the adjustment altitude according to the consumption calculation model; and decoding the chromosome binary string using the following formula to determine the adjustment altitude:

[0152] ,

[0153] ,

[0154] in represents the precision parameter, Represents the chromosome binary string i digits, n The number of bits representing the chromosome binary string.

[0155] Therefore, according to this embodiment, obstacle information (including position, velocity, and volume) within the target satellite's movable range is used to determine the collision probability between the target satellite and the obstacle and the energy consumed to avoid the collision. This information is then used to construct a consumption calculation model. Based on this consumption calculation model, the target satellite's movement distance is determined to minimize energy consumption and maximize the probability of avoiding a collision. The target satellite can then avoid obstacles based on this movement distance, achieving both collision avoidance and reduced energy consumption, thereby extending the satellite's service life and mitigating the risks associated with premature fuel depletion. This solves the existing technical problem of excessive fuel consumption when satellites avoid obstacles.

[0156] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0157] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0158] 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. In actual implementation, there may be other division methods, such as 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.

[0159] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0160] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0161] If the integrated unit is implemented as 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, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), a mobile hard drive, a magnetic disk, or an optical disk.

[0162] 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 principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A satellite collision avoidance method, characterized in that: include: Obtaining obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes position information, velocity information, and volume information of the obstacles; Calculating a probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes position information, velocity information, and volume information of the target satellite; Calculating the energy consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and With the minimum consumption as the goal, the consumption calculation model is solved by a genetic algorithm to determine the adjustment height of the target satellite, wherein: The operation of calculating the probability that the target satellite and the obstacle do not collide based on the obstacle information and the target satellite information of the target satellite includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle, and wherein The operation of calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: The probability that the target satellite and the obstacle do not collide is calculated according to the following formula: Ps : （1） （2） （3） （4） （5） in P j Indicates that the target satellite is j The probability of collision with an obstacle, m represents the number of obstacles, j =1~ m , T 0 represents the volume information of the target satellite, T j Indicates the j The volume information of each obstacle, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates that the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and the j The equivalent collision radius of obstacles, Indicates the target satellite and the j The effective time window for the relative interaction of obstacles, d j represents the minimum approach distance, represents the speed error, Indicates position error.

2. The method according to claim 1, characterized in that The operation of constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite includes: The consumption calculation model is constructed according to the following formula : ， in represents the altitude adjusted by the target satellite to avoid collision, represents the probability that the target satellite does not collide after adjusting its altitude, represents the energy value consumed by the target satellite to adjust its altitude, K Indicates the error value.

3. The method according to claim 1, characterized in that With minimum consumption as the goal, solving the consumption calculation model by a genetic algorithm to determine an operation for adjusting the altitude of the target satellite includes: Determining the number of binary bits of an initial population composed of a plurality of chromosomes of the genetic algorithm according to the movable range and the moving precision of the target satellite, wherein the moving precision is used to indicate a unit length of movement of the target satellite; generating a binary-based initial population according to the binary digit number, wherein the initial population is an initial adjusted altitude of the target satellite; and The consumption calculation model is solved according to the initial population to determine the adjustment altitude of the target satellite.

4. The method according to claim 3, characterized in that The operation of determining the number of binary bits of an initial population composed of a plurality of chromosomes of the genetic algorithm according to the movable range and the moving accuracy of the target satellite comprises: The number of binary digits n of the initial population is determined according to the following formula: ， Wherein, U represents the maximum distance of the target satellite adjusted upward, L represents the maximum distance of the target satellite adjusted downward, and SA represents the moving accuracy of the target satellite.

5. The method according to claim 3, characterized in that The operation of determining the adjusted altitude of the target satellite includes: determining a chromosome binary string corresponding to the adjustment height according to the consumption calculation model; and The chromosome binary string is decoded by the following formula to determine the adjustment height: ， ， in represents the precision parameter, represents the i-th digit of the chromosome binary string, and n represents the number of bits of the chromosome binary string.

6. A satellite collision avoidance device, characterized in that: include: an information acquisition module, configured to acquire obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes position information, speed information, and volume information of the obstacles; a probability calculation module, configured to calculate a probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes position information, velocity information, and volume information of the target satellite; an energy value calculation module, configured to calculate the energy value consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; A model construction model is used to construct a consumption calculation model based on the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; as well as The altitude determination module is used to solve the consumption calculation model by genetic algorithm with the minimum consumption as the goal, and determine the adjustment altitude of the target satellite, wherein: The probability calculation module includes: a first calculation submodule, configured to calculate the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and a second calculation submodule, configured to calculate the probability that the target satellite and the obstacle will not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle, and wherein, The energy value calculation module includes a third calculation submodule, which is used to calculate the probability Ps that the target satellite and the obstacle do not collide according to the following formula: （1） （2） （3） （4） （5） in P j Indicates that the target satellite is j The probability of collision with an obstacle, m represents the number of obstacles, j =1~ m , T 0 represents the volume information of the target satellite, T j Indicates the j The volume information of each obstacle, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates that the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and the j The equivalent collision radius of obstacles, Indicates the target satellite and the j The effective time window for the relative interaction of obstacles, d j represents the minimum approach distance, represents the speed error, Indicates position error.

7. A satellite collision avoidance device, 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: Obtaining obstacle information of obstacles within the movable range of the target satellite, wherein the obstacle information includes position information, velocity information, and volume information of the obstacles; Calculating a probability that the target satellite does not collide with the obstacle based on the obstacle information and target satellite information of the target satellite, wherein the target satellite information includes position information, velocity information, and volume information of the target satellite; Calculating the energy consumed by the target satellite according to the altitude adjusted by the target satellite to avoid collision; constructing a consumption calculation model according to the probability that the target satellite does not collide with the obstacle and the energy value consumed by the target satellite; and With the minimum consumption as the goal, the consumption calculation model is solved by a genetic algorithm to determine the adjustment height of the target satellite, wherein: The operation of calculating the probability that the target satellite and the obstacle do not collide based on the obstacle information and the target satellite information of the target satellite includes: calculating the minimum approach distance between the target satellite and the obstacle based on the position information of the target satellite and the position information of the obstacle; and calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle, and wherein The operation of calculating the probability that the target satellite and the obstacle do not collide based on the minimum approach distance and the speed information and volume information of the target satellite and the obstacle includes: The probability Ps that the target satellite and the obstacle do not collide is calculated according to the following formula: （1） （2） （3） （4） （5） in P j Indicates that the target satellite is j The probability of collision with an obstacle, m represents the number of obstacles, j =1~ m , T 0 represents the volume information of the target satellite, T j Indicates the j The volume information of each obstacle, r 0 represents the equivalent radius of the target satellite, r j Indicates the j The equivalent radius of an obstacle, V j Indicates that the target satellite and the j The relative speed of the obstacle, R j Indicates the target satellite and the j The equivalent collision radius of obstacles, Indicates the target satellite and the j The effective time window for the relative interaction of obstacles, d j represents the minimum approach distance, represents the speed error, Indicates position error.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

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