Multi-granularity multi-pulse observation tracking training method for satellite data-real fusion test

Abstract

The invention discloses a multi-granularity multi-pulse observation tracking training method for a satellite digital-real fusion test, and belongs to the field of spacecraft digitization and computer science. The method comprises the steps of digital twinborn test scene environment building, digital twinborn satellite observation tracking model building, digital twinborn multi-granularity multi-pulse observation tracking training and multi-granularity multi-pulse observation tracking satellite digital-real fusion testing. A multi-granularity multi-pulse observation tracking training method based on satellite number-real fusion is designed and comprises a digital twin tracking satellite multi-granularity multi-pulse observation tracking maneuvering strategy and a digital twin target satellite single-granularity multi-pulse escape maneuvering strategy. And realizing multi-model granularity and multi-pulse orbital transfer satellite tracking training and model number-real fusion correction in an observation task.

Description

Technical Field

[0001] The present invention belongs to the field of spacecraft digitization and computer science, and specifically relates to a multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing. Background Art

[0002] Space power is an important factor related to national security and prosperity. All countries are vigorously developing the construction of space situational awareness and space information reconnaissance systems. Space surveillance has become an important area of ​​concern for all countries in their space activities. With the increasing complexity of the space environment, individuals threatening space assets (including debris, out-of-control satellites, space weapons and small celestial bodies, etc.) have increased dramatically. The motion trajectory of non-cooperative targets is often changeable and difficult to predict. Compared with two-pulse orbit change, small observation satellites use multi-pulse orbit change, and their pulses are dispersed in the orbit change path, which can effectively reduce the accumulated fuel consumption caused by the increase in the number of orbit change rounds. In order to ensure the observation of non-cooperative moving targets while minimizing fuel consumption, it is of great value to carry out multi-pulse observation and tracking training research.

[0003] The current multi-pulse observation and tracking training has the following problems: ① The existing mainstream multi-pulse tracking model often adopts a single fixed model solution, the computational complexity remains unchanged, and the model calculation error will increase with the increase of the observation distance; and in the close-range tracking process, it will be passive because the computational complexity cannot keep up with the changes in the tracking situation. ② For the satellite multi-pulse observation and tracking training model, a fixed simplified modeling method is currently used, which cannot meet the needs of real-time on-board dynamic emergency observation tasks. The accuracy of the model directly affects whether the task can be successfully completed, and there is a lack of model correction processing for the observation model. Summary of the invention

[0004] The technical problems to be solved by the present invention are: ① The existing mainstream multi-pulse tracking model often adopts a single fixed model solution, the computational complexity remains unchanged, and the model calculation error will increase with the increase of the observation distance; and in the close-range tracking process, it will be passive because the computational complexity cannot keep up with the changes in the tracking situation. ② For the satellite multi-pulse observation and tracking training model, a fixed simplified modeling method is currently used, which cannot meet the needs of real-time on-board dynamic emergency observation tasks. The accuracy of the model directly affects whether the task can be successfully completed, and there is a lack of model correction processing for the observation model. In response to the above problems, the present invention introduces a multi-granularity model method and digital-real fusion testing technology, designs a training method, and improves the responsiveness of the observation and tracking task to a certain extent. The present invention solves its technical problems by adopting the following technical solutions: a multi-granularity multi-pulse observation and tracking training method for satellite digital-real fusion testing, and the specific method flow is as follows:

[0005] Step S101: construct a digital twin test scenario environment for satellite digital-real fusion testing, add a digital twin tracking star entity, a digital twin target star entity, and a digital twin property star entity, specifically including:

[0006] ① The digital twin tracking star entity is our training subject, responsible for approaching and observing suspicious target stars in the scene;

[0007] ② The digital twin target star entity is a non-cooperative entity that is responsible for continuously approaching our property star in the scene and avoiding close observation by the tracking star on the way;

[0008] ③ The digital twin asset star entity is an important asset target of ours. It is based on the space station or GEO large relay satellite, runs along a fixed orbit, and has no maneuverability;

[0009] Step S102, constructing a satellite digital twin observation and tracking model for satellite digital-real fusion testing, specifically includes:

[0010] ① Construction of digital twin orbit model, multi-pulse orbit maneuver model of tracking satellite and target satellite;

[0011] ② Construction of a multi-granularity observation computing model library for digital twin tracking stars. Establish a real-time optional multi-granularity computing observation model library on the tracking star, which can be used to select the most appropriate computing granularity according to the tracking situation during the training and testing of the tracking star;

[0012] ③ Construction of a multi-granularity escape calculation model library for the digital twin target star. The target star is defined to have no real-time selectable granularity capability. However, a single calculation model granularity can be configured for the target star before each training. The model granularity is selected from the multi-granularity escape calculation model library and fixed during this training process.

[0013] ④Construct the tracking model of the digital twin tracking star and the target star, and define the tracking star multi-granularity observation calculation model and tracking model as the digital twin observation tracking model;

[0014] Step S103: Performing digital twin multi-granularity multi-pulse observation and tracking training for satellite digital-real fusion testing, and training the digital twin observation and tracking model, specifically including:

[0015] ①Configure the digital twin tracking satellite multi-granularity and multi-pulse observation and tracking maneuvering strategy;

[0016] ② Configure the digital twin target satellite single-granularity multi-pulse escape maneuver strategy;

[0017] ③ Modify the initial orbital parameters of the three, modify the maneuvering constraints of the tracking satellite and the target satellite, and modify the observation constraints, and conduct batch digital twin observation and tracking training to determine the parameter range of the multi-granularity and multi-pulse observation and tracking maneuvering strategy of the tracking satellite for use in digital-physical fusion testing;

[0018] Step S104: Perform satellite digital-real fusion test of multi-granularity multi-pulse observation and tracking, deploy the multi-granularity multi-pulse digital twin observation and tracking model trained in step S103 to the real observation satellite, correct the multi-granularity multi-pulse digital twin observation and tracking model according to the telemetry parameters of the real satellite test, and perform multiple fusion tests to continuously correct the on-board multi-granularity multi-pulse observation and tracking model.

[0019] The advantages of the present invention compared with the prior art are:

[0020] (1) Design a digital-real fusion test process for satellite multi-granularity multi-pulse observation and tracking training. This includes the construction of a digital twin test scenario environment, the construction of a digital twin satellite observation and tracking model, digital twin multi-granularity multi-pulse observation and tracking training, and satellite digital-real fusion testing of multi-granularity multi-pulse observation and tracking. It also provides a solution for satellites to correct the model during observation tasks, which improves the reliability and energy efficiency of onboard observation and tracking training to a certain extent.

[0021] (2) A satellite digital-real fusion multi-granularity multi-pulse observation and tracking training method is designed, including a multi-granularity multi-pulse observation and tracking maneuver strategy for a digital twin tracking satellite, a single-granularity multi-pulse escape maneuver strategy for a digital twin target satellite, and batch digital twin observation and tracking training and digital-real fusion testing. A tracking training process for real-time selection of the observation model granularity on board the satellite is given, which improves the response efficiency and decision-making effectiveness of onboard observation tasks to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of the digital-real fusion test of the multi-granularity multi-pulse observation tracking training of the present invention;

[0023] Figure 2 A maneuvering strategy diagram for multi-granularity and multi-pulse observation and tracking training of the digital twin tracking star of the present invention;

[0024] Figure 3 A maneuvering strategy for single-granularity multi-pulse escape training of a digital twin target satellite of the present invention;

[0025] Figure 4 It is a schematic diagram of the maneuvering method of the target star to avoid the tracking star according to the present invention. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of the present invention.

[0027] According to one embodiment of the present invention, a multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing of the present invention is: Figure 1 This is a flow chart of the digital-real fusion test of the multi-granularity multi-pulse observation tracking training of the present invention. Figure 2 This is the maneuver strategy diagram for the multi-granularity and multi-pulse observation and tracking training of the digital twin tracking star of the present invention. Figure 3 The maneuver strategy for the single-granularity multi-pulse escape training of the digital twin target satellite of the present invention is Figure 4 FIG. 1 is a schematic diagram of the maneuvering method of the target star avoiding the tracking star of the present invention, and is introduced by taking a typical three-star scene as an example. Figure 1 As shown, specifically including:

[0028] Step S101: construct a digital twin test scenario environment for satellite digital-real fusion testing, add a digital twin tracking star entity, a digital twin target star entity, and a digital twin property star entity, specifically including:

[0029] ① The digital twin tracking star entity is our training subject, responsible for approaching and observing suspicious target stars in the scene;

[0030] ② The digital twin target star entity is a non-cooperative entity that is responsible for continuously approaching our property star in the scene and avoiding close observation by the tracking star on the way;

[0031] ③ The digital twin property satellite entity is our property target, which is based on the GEO large relay satellite and runs along a fixed orbit without maneuverability;

[0032] Step S102, constructing a satellite digital twin observation and tracking model for satellite digital-real fusion testing, specifically includes:

[0033] ① Construction of digital twin orbit model, multi-pulse orbit maneuver model of tracking satellite and target satellite;

[0034] ② Construction of a multi-granularity observation computing model library for digital twin tracking stars. Establish a real-time optional multi-granularity computing observation model library on the tracking star, so that the tracking star can select the most appropriate computing granularity according to the tracking situation during training and testing;

[0035] ③ Construction of a multi-granularity escape computing model library for the digital twin target satellite. Define that the target satellite has no real-time selectable granularity capability. Configure a single computing model granularity for the target satellite before each training. Select from the multi-granularity escape computing model library and fix this model granularity during this training process.

[0036] ④Construct the tracking model of the digital twin tracking star and the target star, and define the tracking star multi-granularity observation calculation model and tracking model as the digital twin observation tracking model;

[0037] Step S103: Performing digital twin multi-granularity multi-pulse observation and tracking training for satellite digital-real fusion testing, and training the digital twin observation and tracking model, specifically including:

[0038] ①Configure the digital twin tracking satellite multi-granularity and multi-pulse observation and tracking maneuvering strategy;

[0039] ② Configure the digital twin target satellite single-granularity multi-pulse escape maneuver strategy;

[0040] ③ Modify the initial orbital parameters of the tracking satellite, target satellite and property satellite, modify the maneuvering constraints of the tracking satellite and target satellite, and modify the observation constraints, and conduct batch digital twin observation and tracking training to determine the parameter range of the multi-granularity and multi-pulse observation and tracking maneuvering strategy of the tracking satellite for use in digital-physical fusion testing;

[0041] Step S104: Perform satellite digital-real fusion test of multi-granularity multi-pulse observation and tracking, deploy the multi-granularity multi-pulse digital twin observation and tracking model trained in step S103 to the real observation satellite, correct the multi-granularity multi-pulse digital twin observation and tracking model according to the telemetry parameters of the real satellite test, and perform multiple fusion tests to continuously correct the on-board multi-granularity multi-pulse observation and tracking model.

[0042] The tracking model in step S102 (4) is specifically implemented as follows:

[0043] Define the safe approach area geometrically, and note that the position of the sun in the Earth's equatorial inertial system is , in the calculation, according to the ephemeris, the position of the target star in the Earth's equatorial inertial system is , then the position vector pointing from the target star to the sun at time t is: ;

[0044] The tracking star optimizes its strategy to fly into the safe approach zone of the target star, and the target star also continuously optimizes its strategy to avoid the tracking star from flying into its own safe approach zone, thus constructing a two-star zero-sum model: , where x p , x e Indicates the status of the two people chasing and fleeing, x p Indicates tracking star, x e represents the target star, u is a pair of strategies, and the initial state constitutes the initial boundary condition of the game: ;Terminal time constraints In order for the tracking star to enter the safe approach area of ​​the target star at the terminal time, the terminal position constraint is: , that is, the terminal always tracks the star to the target star The distance is less than the safe approach area radius At the terminal moment, the angle between the target star and the sun is tracked with the target star as the vertex Smaller than the safe approach area angle ; The target satellite maneuvers in orbit so that the terminal always tracks the satellite outside its own safety zone ; At the same time, the total fuel constraint is expressed by the speed increment , To track the pulse vector of the star change orbit, The pulse vector for the target star’s orbit change, both of which must be smaller than the upper pulse limit of the fuel constraint;

[0045] definition is the strategy return, if the following inequalities all satisfy u p and all u e , This is called a saddle point equilibrium, or a saddle point strategy:

[0046] .

[0047] In step S103, the maneuver strategy of ① the multi-granularity multi-pulse observation and tracking training of the digital twin tracking star is as follows Figure 2 As shown, the specific implementation includes:

[0048] Step S301: whether the target star calculates the minimum distance identifier Set to 1, and select a suitable orbit determination granularity model. First, perform model consistency verification. If the model fails the verification, perform model correction. If the model passes the verification, orbit determination for the target satellite is performed, and execute step S302;

[0049] Step S302: Calculate the minimum distance between the target star and the property star based on the orbit determination result in step S301 , and the time to reach the minimum distance , execute step S303;

[0050] Step S303: Determine the minimum distance between the target star and the property star Is it smaller than the threat distance of the property star? ,judge:

[0051] ① If the minimum distance between the target satellite and the property satellite is less than the threat distance of the property satellite, the tracking satellite selects an appropriate orbit change granularity model, first performs model consistency verification, and corrects the model if it fails the verification. After passing the verification, the orbit change pulse is calculated to approach the target satellite, and the orbit determination parameters, the time of reaching the minimum distance, the pulse maneuver time and the pulse maneuver component are stored, and step S304 is executed;

[0052] ② If the minimum distance between the target star and the property star is greater than the threat distance of the property star, return to step S301 to re-orbit the target star;

[0053] Step S304: judging whether the maneuvering time has been reached according to the stored pulse maneuvering time.

[0054] ① If the recorded time is reached, the pulse maneuver at the corresponding time is executed;

[0055] ② If the pulse maneuvering time has not been reached, the identifier Set to 0, then execute step S305;

[0056] Step S305: Continue to select the appropriate granularity to determine the orbit of the target satellite and The last orbit determination result stored All are recursively extended to the stored minimum distance arrival time , and compare the recursive results of the two orbit determinations:

[0057] ① If the difference is less than the set maneuver judgment threshold, it is considered that the target satellite has not made an evasive maneuver, and the process returns to step S305 to re-determine the orbit of the target satellite;

[0058] ② If the difference is greater than the set maneuver judgment threshold, it is considered that the target satellite has made an evasive maneuver, and step S306 is executed;

[0059] Step S306: further determine whether the recursive result of this orbit determination is less than the threat distance of the property star :

[0060] ① If the recursive result of this orbit determination is less than the threat distance of the property satellite, it is considered that the target satellite has made a maneuver and has not changed its threat intention. The stored minimum distance, minimum distance time, maneuver time and maneuver pulse are cleared, and the identifier is Set to 1, return to step S301, re-orbit the target satellite, and recalculate the minimum distance and the time to reach the minimum distance;

[0061] ② If the recursive result of this orbit determination is greater than the threat distance of the property star , it is considered that the target star has made a maneuver, but the terminal position does not threaten the property star. There are two possibilities. One is that the target star has given up the task of threatening the property star. The other is that the target star is performing the first few pulses of the multi-pulse orbit change and is in the transfer orbit and cannot be judged as a threat. No matter which possibility is it, the target star has the intention of threatening the property star before. Therefore, the tracking star adopts the strategy of approaching the property star for both possibilities, and at the same time selects the appropriate orbital maneuver granularity to solve and store the maneuver time and pulse maneuver component, and executes step S304.

[0062] The maneuver strategy of the single-granularity multi-pulse escape training of the digital twin target satellite in step S103 is as follows: Figure 3 As shown, the specific implementation includes:

[0063] Step S401, firstly, the model consistency verification is performed, and if the verification fails, the model is corrected, and after the verification passes, the target star is determined as the property star, and the multi-pulse orbit change is solved to approach the property star;

[0064] Step S402: The target star is a tracking star, and the orbit is determined. Step S403 is executed;

[0065] Step S403: Calculate the minimum distance between the tracking star and the target star based on the orbit determination result in step S402 , and the time to reach the minimum distance , execute step S404;

[0066] Step S404: Determine the minimum distance between the tracking star and the target star Is it smaller than the threat distance of the target star? ,judge:

[0067] ① If the minimum distance between the tracking star and the target star Less than the target star's threat distance The target star uses a fixed orbit change granularity to calculate the orbit change pulse to avoid the tracking star, and stores the orbit determination parameters, the time of reaching the minimum distance, the pulse maneuvering time and the pulse maneuvering component, and executes step S405;

[0068] ② If the minimum distance between the tracking star and the target star Greater than the target star's threat distance , return to step S401 to re-orbit the tracking star;

[0069] Step S405: Determine whether the maneuvering time has been reached according to the stored pulse maneuvering time:

[0070] ① If the recorded time is reached, the pulse maneuver at the corresponding time is executed;

[0071] ② If the pulse maneuvering time has not been reached, execute step S402.

[0072] In step S404, ① the maneuvering method of the target star to avoid the tracking star is as follows: Figure 4 As shown, the specific implementation includes: tracking the star with the minimum distance When flying over the target star, the target star will be the center of the circle. The circle with a radius of is divided into a semicircle containing the minimum distance and a semicircle area not containing the minimum distance. The target star moves one target star threat distance toward the semicircle area not containing the minimum distance. , and the target star must be within the threat distance of the property star Within the range of , short-distance pulse maneuvers are performed under this scheme.

[0073] In summary, the present invention discloses a multi-granularity multi-pulse observation and tracking training method for satellite digital-real fusion testing, including designing a digital-real fusion test process for observation and tracking training, and designing a multi-granularity multi-pulse observation and tracking training method, which can solve the problems existing in the current satellite observation and tracking training to a certain extent, and improve the response efficiency and decision-making effectiveness in on-board observation tasks.

[0074] The contents not described in detail in the specification of the present invention belong to the prior art known to the professional and technical personnel in this field.

[0075] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing, characterized in that: The specific process of the method is as follows: Step S101: construct a digital twin test scenario environment for satellite digital-real fusion testing, add a digital twin tracking star entity, a digital twin target star entity, and a digital twin property star entity, specifically including: ① The digital twin tracking star entity is our training subject, responsible for approaching and observing suspicious target stars in the scene; ② The digital twin target star entity is a non-cooperative entity that is responsible for continuously approaching our property star in the scene and avoiding close observation by the tracking star on the way; ③ The digital twin property star entity is our property target, which is based on the space station or GEO large relay satellite and runs along a fixed orbit without maneuverability; Step S102, constructing a satellite digital twin observation and tracking model for satellite digital-real fusion testing, specifically includes: ① Construction of digital twin orbit model, multi-pulse orbit maneuver model of tracking satellite and target satellite; ② Construction of a multi-granularity observation computing model library for digital twin tracking stars. Establish a real-time optional multi-granularity observation computing model library on the tracking star, so that the tracking star can select the most appropriate computing granularity according to the tracking situation during training and testing; ③ Construction of a multi-granularity escape computing model library for the digital twin target satellite. Define that the target satellite has no real-time selectable granularity capability. Configure a single computing model granularity for the target satellite before each training. Select from the multi-granularity escape computing model library and fix this model granularity during this training process. ④Construct the tracking model of the digital twin tracking star and the target star, and define the tracking star multi-granularity observation calculation model and tracking model as the digital twin observation tracking model; Step S103: Performing digital twin multi-granularity multi-pulse observation and tracking training for satellite digital-real fusion testing, and training the digital twin observation and tracking model, specifically including: ①Configure the digital twin tracking satellite multi-granularity and multi-pulse observation and tracking maneuvering strategy; ② Configure the digital twin target satellite single-granularity multi-pulse escape maneuver strategy; ③ Modify the initial orbital parameters of the tracking satellite, target satellite and property satellite, modify the maneuvering constraints of the tracking satellite and target satellite, and modify the observation constraints, and conduct batch digital twin observation and tracking training to determine the parameter range of the multi-granularity and multi-pulse observation and tracking maneuvering strategy of the tracking satellite for use in digital-physical fusion testing; Step S104: Perform satellite digital-real fusion test of multi-granularity multi-pulse observation and tracking, deploy the multi-granularity multi-pulse digital twin observation and tracking model trained in step S103 to the real observation satellite, correct the multi-granularity multi-pulse digital twin observation and tracking model according to the telemetry parameters of the real satellite test, and perform multiple fusion tests to continuously correct the on-board multi-granularity multi-pulse observation and tracking model.

2. The multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing according to claim 1 is characterized in that: The tracking model in step S102 specifically includes: Define the safe approach area geometrically, and note that the position of the sun in the Earth's equatorial inertial system is , in the calculation, according to the ephemeris, the position of the target star in the Earth's equatorial inertial system is , then the position vector pointing from the target star to the sun at time t is: ; The tracking star optimizes its strategy to fly into the safe approach zone of the target star, and the target star also continuously optimizes its strategy to avoid the tracking star from flying into its own safe approach zone, thus constructing a two-star zero-sum model: , where x p , x e Indicates the status of the two people chasing and fleeing, x p Indicates tracking star, x e represents the target star, u is a pair of strategies, and the initial state constitutes the initial boundary condition of the game: ;Terminal time constraints In order for the tracking star to enter the safe approach area of ​​the target star at the terminal time, the terminal position constraint is: , that is, the terminal always tracks the star to the target star The distance is less than the safe approach area radius At the terminal moment, the angle between the target star and the sun is tracked with the target star as the vertex Smaller than the safe approach area angle ; The target satellite maneuvers in orbit so that the terminal always tracks the satellite outside its own safety zone ; At the same time, the total fuel constraint is expressed by the speed increment , To track the pulse vector of the star's orbit change, The pulse vector for the target star’s orbit change, both of which must be smaller than the upper pulse limit of the fuel constraint; definition is the strategy return, if the following inequalities all satisfy u p and all u e , This is called a saddle point equilibrium, or a saddle point strategy: 。 3. The multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing according to claim 1 is characterized in that: The maneuvering strategy of the multi-granularity multi-pulse observation and tracking training of the digital twin tracking star in step S103 specifically includes: Step S301, select a suitable orbit determination granularity model, first perform model consistency verification, if the model fails the verification, perform model correction, if it passes the verification, orbit determination for the target satellite is performed, and execute step S302; Step S302: Calculate the minimum distance between the target star and the property star based on the orbit determination result in step S301 , and the time to reach the minimum distance , execute step S303; Step S303: Determine the minimum distance between the target star and the property star Is it smaller than the threat distance of the property star? ,judge: ① If the minimum distance between the target satellite and the property satellite is less than the threat distance of the property satellite, the tracking satellite selects an appropriate orbit change granularity model, first performs model consistency verification, and corrects the model if it fails the verification. After passing the verification, the orbit change pulse is calculated to approach the target satellite, and the orbit determination parameters, the time of reaching the minimum distance, the pulse maneuver time and the pulse maneuver component are stored, and step S304 is executed; ② If the minimum distance between the target star and the property star is greater than the threat distance of the property star, return to step S301 to re-orbit the target star; Step S304: Determine whether the maneuvering time has been reached according to the stored pulse maneuvering time: ① If the recorded time is reached, the pulse maneuver at the corresponding time is executed; ② If the pulse maneuvering time has not been reached, execute step S305; Step S305: Continue to select the appropriate granularity to determine the orbit of the target star and The last orbit determination result stored All are recursively extended to the stored minimum distance arrival time , and compare the recursive results of the two orbit determinations: ① If the difference is less than the set maneuver judgment threshold, it is considered that the target satellite has not made an evasive maneuver, and the process returns to step S305 to re-determine the orbit of the target satellite; ② If the difference is greater than the set maneuver judgment threshold, it is considered that the target satellite has made an evasive maneuver, and step S306 is executed; Step S306: further determine whether the recursive result of this orbit determination is less than the threat distance of the property star : ① If the recursive result of this orbit determination is less than the threat distance of the property satellite, it is considered that the target satellite has made a maneuver and has not changed its threat intention. The stored minimum distance, minimum distance time, maneuver time and maneuver pulse are cleared, and the process returns to step S301. The orbit of the target satellite is re-determined, and the minimum distance and the time of reaching the minimum distance are recalculated. ② If the recursive result of this orbit determination is greater than the threat distance of the property star , it is considered that the target star has made a maneuver, but the terminal position does not threaten the property star. There are two situations. One is that the target star has given up the task of threatening the property star, and the other is that the target star is executing the first few pulses of the multi-pulse orbit change and is in the transfer orbit and no threat can be determined. Both situations indicate that the target star has the intention of threatening the property star before. Therefore, the tracking star adopts the strategy of approaching the property star for both situations, and at the same time selects the appropriate orbital maneuver granularity to solve and store the maneuver time and pulse maneuver component, and executes step S304.

4. The multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing according to claim 1 is characterized in that: The maneuvering strategy of the single-granularity multi-pulse escape training of the digital twin target satellite in step S103 specifically includes: Step S401, firstly, the model consistency verification is performed, and if the verification fails, the model is corrected, and after the verification passes, the target star is determined as the property star, and the multi-pulse orbit change is solved to approach the property star; Step S402: The target star is a tracking star, and the orbit is determined. Step S403 is executed; Step S403: Calculate the minimum distance between the tracking star and the target star based on the orbit determination result in step S402 , and the time to reach the minimum distance , execute step S404; Step S404: Determine the minimum distance between the tracking star and the target star Is it smaller than the threat distance of the target star? ,judge: ① If the minimum distance between the tracking star and the target star Less than the threat distance of the target star The target star uses a fixed orbit change granularity to calculate the orbit change pulse to avoid the tracking star, and stores the orbit determination parameters, the time of reaching the minimum distance, the pulse maneuvering time and the pulse maneuvering component, and executes step S405; ② If the minimum distance between the tracking star and the target star Greater than the target star's threat distance , return to step S401 to re-orbit the tracking star; Step S405: Determine whether the maneuvering time has been reached according to the stored pulse maneuvering time: ① If the recorded time is reached, the pulse maneuver at the corresponding time is executed; ② If the pulse maneuvering time has not been reached, execute step S402.

5. The multi-granularity multi-pulse observation tracking training method for satellite digital-real fusion testing according to claim 4 is characterized in that: The maneuvering method of the target star to avoid the tracking star in step S404 specifically includes: When flying over the target star, the target star will be the center of the circle. The circle with a radius of is divided into a semicircle containing the minimum distance and a semicircle area not containing the minimum distance. The target star moves a target star threat distance toward the semicircle area not containing the minimum distance. , and the target star must be within the threat distance of the property star Within the range of , short-distance pulse maneuvers are performed under this scheme.

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