A low-orbit mega-constellation networking orbit control strategy method

Abstract

The present application relates to a kind of low-orbit giant constellation networking orbit control strategy methods, comprising the following steps: S1: according to last group of orbit control ignition timing, GNSS telemetry and ground measured orbit data, constellation key parameter calibration and forecast are carried out;S2: according to the calibration result calculated in step S1 and nominal constellation configuration parameter, constellation networking stage is independently judged, and orbit control strategy is generated;S3: according to the control strategy generated in step S2, the constellation configuration evolution of a period of time in the future is calculated, and the control strategy is verified.The advantage is that it is suitable for the low-orbit giant constellation networking task configured with electric propulsion, and meets the existing giant constellation orbit control task demand.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of low-orbit mega-constellation, in particular to a low-orbit mega-constellation networking orbit control strategy method. BACKGROUND

[0002] With the application of spacecraft technology, more and more low-orbit mega-constellations composed of thousands of satellites or even tens of thousands of satellites have emerged. Such constellations often adopt the launch mode of one rocket carrying multiple satellites, and after the separation of the satellite and the rocket, the satellites still need to use the carried electric propulsion to autonomously form a network, and have the characteristics of batch launch density and multiple satellite orbit control task concentration.

[0003] The traditional single-satellite autonomous orbit insertion strategy cannot meet the existing mega-constellation orbit control task requirements.

[0004] The foregoing description is to provide general background information and does not necessarily constitute prior art. SUMMARY

[0005] The application aims to provide a low-orbit mega-constellation networking orbit control strategy method, which is suitable for low-orbit mega-constellation networking tasks with electric propulsion and meets the existing mega-constellation orbit control task requirements.

[0006] The application provides a low-orbit mega-constellation networking orbit control strategy method, which comprises the following steps:

[0007] S1: according to the last group of orbit control firing time sequence, GNSS telemetry and ground determined orbit data, key parameters of the constellation are calibrated and predicted;

[0008] S2: according to the calibration results calculated in step S1 and the nominal constellation configuration parameters, the constellation networking stage is autonomously judged, and an orbit control strategy is generated;

[0009] S3: according to the orbit control strategy generated in step S2, the post-control constellation configuration evolution in a future period of time is calculated, and the control strategy is verified.

[0010] Further, the step S1 comprises:

[0011] S11: GNSS telemetry and ground determined orbit results are obtained to determine the orbit elements before and after orbit control, including semi-major axis a, eccentricity e, orbit inclination i, perigee argument w, ascending node right ascension Omega and true anomaly M;

[0012] S12: according to the orbit control firing time sequence and the change of the orbit elements before and after orbit control, the electric propulsion thrust is calibrated; the orbit calibration method is used to calculate the velocity increment of the satellite according to the orbit change parameters; and the propulsion system thrust is calculated according to the satellite velocity increment and the electric propulsion working time;

[0013] S13: According to the determination of the orbit result, the constellation configuration evolution is calculated.

[0014] Further, the formula for calculating the propulsion system thrust in step S12 is:

[0015]

[0016] TΔt=mΔV (2)

[0017]

[0018] In formula (1), Δa is the change of the satellite orbit altitude, Δv is the satellite speed increment, r is the satellite orbit radius, μ is a constant, and 3.986×10 14 m 3 / s 2 ;

[0019] In formula (2), T is the thrust, Δt is the working time of the electric propulsion system, m is the satellite mass, and ΔV is the satellite speed increment. According to formula (1) and formula (2), formula (3) can be obtained. The orbit position parameters within a period of time before and after the orbit control are obtained, the difference between the orbit semi-major axes before and after the orbit control is obtained after the post-precise orbit determination, and the actual thrust of the electric propulsion system is calculated.

[0020] Further, the step S2 comprises:

[0021] S21: Calculate the average orbit parameters of the constellation configuration and the configuration target root difference Δa, Δu, Δi and its standard deviation σ a 、σ Δu 、σ i ; the calculation formula is:

[0022]

[0023]

[0024] In the formula, a i , u i , i i are the plane root value of the orbit semi-major axis, the plane latitude angle and the plane inclination angle of the i-th satellite in the constellation, which are provided by the current orbit parameters of the constellation satellite, N is the number of satellites in the same batch of constellation, Δu i is the phase difference value between the i-th satellite in the constellation and the satellite on the back side.

[0025] Further, the step S2 further comprises:

[0026] S22: According to the average semi-major axis difference Δa and the average phase difference calculated in step S21, the constellation networking task phase is judged.

[0027] If the average semi-major axis difference Δa > Δa1 or the average phase difference Δu < Δu1, the constellation networking task is in the phase separation stage;

[0028] If the average semi-major axis difference Δa2 < Δa ≤ Δa1, the constellation networking task is in the configuration coarse capture stage;

[0029] If the average semi-major axis difference Δa ≤ Δa2, the constellation networking task is in the number fine tuning stage;

[0030] Wherein, Δa1, Δa2, Δu1, need to be selected in combination with the networking task; Δa1 is selected as 5% of the semi-major axis change amount, Δa2 is selected as 95% of the semi-major axis change amount, and Δu1 is selected as 10% of the nominal phase difference of the constellation configuration.

[0031] Further, the step S2 further comprises:

[0032] S23: According to the constellation task stage judged in step S22, further distinguishing the working normal satellite from the working abnormal satellite;

[0033] According to the task requirements in different stages, the judgment conditions are as follows:

[0034] Phase separation stage working normal judgment: the phase difference |Δu i -Δu|<3σ Δu of the i th star is less than 3σ, mark the star as normal, otherwise mark the star as abnormal;

[0035] Configuration coarse capture stage working normal judgment: the semi-major axis |Δa i -Δa|<3σ a of the i th star is less than 3σ, && the phase difference Δu i -Δu|<3σ Δu is less than 3σ, && the inclination difference |Δi i -Δi|<3σ i is less than 3σ, mark the star as normal, otherwise mark the star as abnormal;

[0036] Number fine tuning stage working normal judgment: the semi-major axis |Δa i -Δa|<3σ a of the i th star is less than 3σ, && the phase difference Δu i -Δu|<3σ Δu is less than 3σ, && the inclination difference |Δi i -Δi|<3σ i is less than 3σ, mark the star as normal, otherwise mark the star as abnormal.

[0037] Further, the step S2 further comprises:

[0038] S24: According to the networking task stage and the orbit control task normal flag determined in steps S22 and S23, generating an orbit control strategy:

[0039] Orbit control strategy during normal satellite phase separation phase;

[0040] Orbit control strategy during the coarse acquisition phase of normal star configuration;

[0041] Calculate the element increments required for satellite orbit control

[0042] Δa=a m -a i ; Δi = i m -i i ;

[0043] For coarse-grained capture missions involving constellation configurations, which typically involve changing the half-field axis and tilt angle, a control strategy based on latitude argument can be established. This strategy utilizes thrust with components only in the tangential and normal directions, and none in the radial direction. The relationship between the angle β between the thrust direction and the orbital coordinate system and the latitude depression angle is as follows:

[0044] β=cos(w+M)β max ;

[0045] Where w+M is the latitudinal argument, β max This is the maximum swing angle of the track control.

[0046] The maximum swing angle of the track control is calculated using the following iterative method:

[0047]

[0048] ;

[0049] Among them, F r F n F t Let F be the radial, normal, and tangential components of the thrust, F be the thrust modulus of the propulsion system, and n be the orbital angular velocity for that orbit.

[0050]

[0051]

[0052] The maximum swing angle β was calculated through simulation iteration. max The satellite autonomously performs orbit control tasks based on its maximum swing angle.

[0053] Orbit control strategy during normal satellite element fine-tuning phase;

[0054] Abnormal satellite orbit control strategy: Considering the feasibility of orbit control, when an abnormality in the propulsion system or other failures of the entire satellite cause a delay in the orbit control mission of a certain satellite, in order to prevent the difference in the number of orbital elements from continuing to widen due to inconsistency, the right ascension of the ascending node is avoided by offsetting the orbital inclination angle.

[0055] Further, step S3 includes:

[0056] The constellation orbit control evaluation module uses MATLAB-STK co-simulation to evaluate the constellation orbit control process, the evolution of the elements, and to verify the correctness of the orbit control strategy.

[0057] This invention provides a method for orbit control strategy for low-Earth orbit (LEO) mega-constellation networking. Aiming at autonomous networking of mega-constellations, it designs an automatic constellation networking strategy generation algorithm encompassing constellation parameter calibration, constellation orbit control strategy, and constellation orbit control strategy evaluation modules. First, high-precision calibration of constellation parameters is achieved using thruster nominal parameters, GNSS and ground-based external measurement data, basic orbital perturbation parameters, satellite surface mass ratio, and the previous set of orbit control strategies. Then, using the nominal constellation configuration and orbit determination results, the algorithm autonomously determines the networking mission stage of the constellation and, considering the different orbit control progress of each satellite, classifies them into two categories: abnormal satellites and normal satellites, formulating different orbit control strategies for each. Finally, through joint simulation with MATLAB-STK, the correctness of the strategy is verified, and the remaining fuel, networking duration, and constellation configuration evolution are evaluated. This method is applicable to LEO mega-constellation networking missions with electric propulsion and meets the requirements of existing mega-constellation orbit control missions. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of the module flow of the orbit control strategy method for low-Earth orbit mega-constellation networking provided in an embodiment of the present invention.

[0059] Figure 2 This is a flowchart illustrating step S2 of the low-Earth orbit mega-constellation networking orbit control strategy method provided in an embodiment of the present invention. Detailed Implementation

[0060] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0061] The terms "first," "second," "third," "fourth," etc., used in the specification and claims of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0062] Example 1

[0063] Figure 1 This is a schematic diagram of the module flow of the orbit control strategy method for low-Earth orbit mega-constellation networking provided in an embodiment of the present invention. Please refer to... Figure 1 The orbit control strategy method for low-Earth orbit mega-constellation networking provided in this embodiment of the invention includes the following steps:

[0064] S1: Based on the previous set of orbit control ignition timing, GNSS telemetry and ground orbit measurement data, perform constellation key parameter calibration and prediction;

[0065] S2: Based on the calibration results and nominal constellation configuration parameters calculated in step S1, perform autonomous judgment during the constellation networking stage and generate orbit control strategies;

[0066] S3: Calculate the evolution of the post-control constellation configuration over a future period based on the orbit control strategy generated in step S2, and verify the control strategy.

[0067] It should be noted that the low-Earth orbit (LEO) mega-constellation networking orbit control strategy method provided by this invention aims at autonomous networking of mega-constellations. It designs an automatic constellation networking strategy generation algorithm encompassing constellation parameter calibration, constellation orbit control strategy, and constellation orbit control strategy evaluation modules. First, high-precision calibration of constellation parameters is achieved using thruster nominal parameters, GNSS and ground-based external measurement data, basic orbital perturbation parameters, satellite surface mass ratio, and the previous set of orbit control strategies. Then, using the nominal constellation configuration and orbit determination results, the algorithm autonomously determines the networking mission stage of the constellation and, considering the different orbit control progress of each satellite, classifies them into two categories: abnormal satellites and normal satellites, formulating different orbit control strategies for each. Finally, through joint simulation with MATLAB-STK, the correctness of the strategy is verified, and the remaining fuel, networking duration, and constellation configuration evolution are evaluated. This method is applicable to LEO mega-constellation networking missions with electric propulsion and meets the existing mega-constellation orbit control mission requirements.

[0068] Further, step S1 includes:

[0069] S11: GNSS telemetry and ground-based orbit determination results, determining the number of orbital elements before and after orbit control, semi-major axis a, eccentricity e, orbital inclination i, argument of perigee w, right ascension of ascending node Ω, and true anomaly M;

[0070] S12: The electric propulsion thrust is calibrated based on the orbit control ignition sequence and the change in the number of orbital elements before and after orbit control; the orbit calibration method calculates the satellite's velocity increment based on the orbital change parameters; the propulsion system thrust is calculated based on the satellite's velocity increment and the electric propulsion working time.

[0071] S13: Based on the determined orbit results, calculate the evolution of the constellation configuration.

[0072] Furthermore, the formula for calculating the thrust of the propulsion system in step S12 is:

[0073]

[0074] TΔt=mΔV (2)

[0075]

[0076] In formula (1), Δa is the change in satellite orbital altitude, Δv is the satellite velocity increment, r is the satellite orbital radius, and μ is a constant of 3.986 × 10⁻⁶. 14 m 3 / s 2 ;

[0077] In formula (2), T is the thrust, Δt is the working time of the electric propulsion system, m is the satellite mass, and ΔV is the satellite velocity increment. Formula (3) can be obtained from formula (1) and formula (2). The orbital position parameters within a certain period before and after orbit control are obtained. After precise orbit determination, the difference between the semi-major axis of the orbit before and after orbit control is obtained. The actual thrust of the electric propulsion system can be calculated.

[0078] Further, step S2 includes:

[0079] S21: Calculate the differences between the average orbital parameters and the target root numbers of the constellation configuration, Δa, Δu, Δi, and their standard deviation σ. a σ Δu σ i The calculation formula is:

[0080]

[0081]

[0082] In the formula, a i u i i i The root mean square value of the semi-major axis, mean latitude, depression angle, and mean inclination angle of the i-th satellite in the constellation are provided by the current orbital parameters of the constellation satellites, where N is the number of satellites in the same batch of constellations, and Δu i It represents the phase difference between the i-th satellite in the constellation and the satellite behind it.

[0083] Figure 2 This is a flowchart illustrating step S2 of the low-Earth orbit mega-constellation network orbit control strategy method provided in an embodiment of the present invention. Please refer to... Figure 1 The step S2 provided in this embodiment of the invention further includes:

[0084] S22: Determine the constellation networking task stage based on the average half-major axis difference Δa and average phase difference calculated in step S21.

[0085] If the average half-major axis difference Δa > Δa1 or the average phase difference Δu < Δu1, then the constellation networking task is in the phase separation stage.

[0086] If the average half-major axis difference Δa2 < Δa ≤ Δa1, then the constellation networking task is in the configuration coarse capture stage;

[0087] If the average semi-major axis difference Δa ≤ Δa2, then the constellation networking task is in the root number fine-tuning stage;

[0088] Among them, Δa1, Δa2, and Δu1 need to be selected based on the specific networking task; Δa1 is selected as 5% of the amount that needs to be changed in the semi-major axis, Δa2 is selected as 95% of the amount that needs to be changed in the semi-major axis, and Δu1 is selected as 10% of the nominal phase difference of the constellation configuration.

[0089] Furthermore, step S2 also includes:

[0090] S23: Based on the constellation mission phase determined in step S22, further distinguish between satellites that are functioning normally and satellites that are not functioning normally;

[0091] Based on the task requirements at different stages, the judgment conditions are as follows:

[0092] Normal operation during phase separation phase: Phase difference of the i-th star |Δu i -Δu|<3σ Δu Mark normal as a star, otherwise mark abnormal as a star;

[0093] Normal operation judgment during the configuration coarse capture stage: semi-major axis of the i-th star | Δa i -Δa|<3σ a &&Phase difference Δu i -Δu|<3σ Δu && Inclination difference|Δi i -Δi|<3σ i Mark normal as a star, otherwise mark abnormal as a star;

[0094] Judgment of normal operation during the element fine-tuning stage: semi-major axis of the i-th star | Δa i -Δa|<3σ a &&Phase difference Δu i -Δu|<3σ Δu && Inclination difference|Δi i -Δi|<3σ i Mark normal stars; otherwise, mark abnormal stars.

[0095] Furthermore, step S2 also includes:

[0096] S24: Generate track control strategy based on the network setup task stage and track control task normal indicators specified in steps S22 and S23:

[0097] Orbit control strategy during normal satellite phase separation phase;

[0098] Orbit control strategy during the coarse acquisition phase of normal star configuration;

[0099] Calculate the element increments required for satellite orbit control

[0100] Δa=am -a i ; Δi = i m -i i ;

[0101] For coarse-grained capture missions involving constellation configurations, which typically involve changing the half-field axis and tilt angle, a control strategy based on latitude argument can be established. This strategy utilizes thrust with components only in the tangential and normal directions, and none in the radial direction. The relationship between the angle β between the thrust direction and the orbital coordinate system and the latitude depression angle is as follows:

[0102] β=cos(w+M)β max ;

[0103] Where w+M is the latitudinal argument, β max This is the maximum swing angle of the track control.

[0104] The maximum swing angle of the track control is calculated using the following iterative method:

[0105]

[0106] ;

[0107] Among them, F r F n F t Let F be the radial, normal, and tangential components of the thrust, F be the thrust modulus of the propulsion system, and n be the orbital angular velocity for that orbit.

[0108]

[0109]

[0110] The maximum swing angle β was calculated through simulation iteration. max The satellite autonomously performs orbit control tasks based on its maximum swing angle.

[0111] Orbit control strategy during normal satellite element fine-tuning phase;

[0112] Abnormal satellite orbit control strategy: Considering the feasibility of orbit control, when an abnormality in the propulsion system or other failures of the entire satellite cause a delay in the orbit control mission of a certain satellite, in order to prevent the difference in the number of orbital elements from continuing to widen due to inconsistency, the right ascension of the ascending node is avoided by offsetting the orbital inclination angle.

[0113] Further, step S3 includes:

[0114] The constellation orbit control evaluation module uses MATLAB-STK co-simulation to evaluate the constellation orbit control process, the evolution of the elements, and to verify the correctness of the orbit control strategy.

[0115] As can be seen from the above description, the advantages of this invention are:

[0116] This invention provides a method for orbit control strategy for low-Earth orbit (LEO) mega-constellation networking. Aiming at autonomous networking of mega-constellations, it designs an automatic constellation networking strategy generation algorithm encompassing constellation parameter calibration, constellation orbit control strategy, and constellation orbit control strategy evaluation modules. First, high-precision calibration of constellation parameters is achieved using thruster nominal parameters, GNSS and ground-based external measurement data, basic orbital perturbation parameters, satellite surface mass ratio, and the previous set of orbit control strategies. Then, using the nominal constellation configuration and orbit determination results, the algorithm autonomously determines the networking mission stage of the constellation and, considering the different orbit control progress of each satellite, classifies them into two categories: abnormal satellites and normal satellites, formulating different orbit control strategies for each. Finally, through joint simulation with MATLAB-STK, the correctness of the strategy is verified, and the remaining fuel, networking duration, and constellation configuration evolution are evaluated. This method is applicable to LEO mega-constellation networking missions with electric propulsion and meets the requirements of existing mega-constellation orbit control missions.

[0117] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A low-Earth orbit mega-constellation networking orbit control strategy method, characterized in that, Includes the following steps: S1: Based on the previous set of orbit control ignition timing, GNSS telemetry and ground orbit measurement data, perform constellation key parameter calibration and prediction; S2: Based on the calibration results and nominal constellation configuration parameters calculated in step S1, perform autonomous judgment during the constellation networking stage and generate orbit control strategies; Step S2 includes: S21: Calculate the differences between the average orbital parameters and the target root numbers of the constellation configuration, Δa, Δu, Δi, and their standard deviation σ. a σ Δu σ i The calculation formula is: In the formula, a i u i i i The root mean square value of the semi-major axis, mean latitude, depression angle, and mean inclination angle of the i-th satellite in the constellation are provided by the current orbital parameters of the constellation satellites, where N is the number of satellites in the same batch of constellations, and Δu i This represents the phase difference between the i-th satellite in the constellation and the satellite behind it. S22: Determine the constellation networking task stage based on the average half-major axis difference Δa and average phase difference calculated in step S21. If the average half-major axis difference Δa > Δa1 or the average phase difference Δu < Δu1, then the constellation networking task is in the phase separation stage. If the average half-major axis difference Δa2 < Δa ≤ Δa1, then the constellation networking task is in the configuration coarse capture stage; If the average semi-major axis difference Δa ≤ Δa2, then the constellation networking task is in the root number fine-tuning stage; Among them, Δa1, Δa2, and Δu1 need to be selected based on the specific networking task; Δa1 is selected as 5% of the amount that needs to be changed in the semi-major axis, Δa2 is selected as 95% of the amount that needs to be changed in the semi-major axis, and Δu1 is selected as 10% of the nominal phase difference of the constellation configuration. S23: Based on the constellation mission phase determined in step S22, further distinguish between satellites that are functioning normally and satellites that are not functioning normally; Based on the task requirements at different stages, the judgment conditions are as follows: Normal operation during phase separation phase: Phase difference of the i-th star |Δu i -Δu|<3σ Δu Mark normal as a star, otherwise mark abnormal as a star; Normal operation judgment during the configuration coarse capture stage: semi-major axis of the i-th star | Δa i -Δa|<3σ a &&Phase difference Δu i -Δu|<3σ Δu && Inclination difference|Δi i -Δi|<3σ i Mark normal as a star, otherwise mark abnormal as a star; Judgment of normal operation during the element fine-tuning stage: semi-major axis of the i-th star | Δa i -Δa|<3σ a &&Phase difference Δu i -Δu|<3σ Δu && Inclination difference|Δi i -Δi|<3σ i Mark normal as a star, otherwise mark abnormal as a star; S24: Generate track control strategy based on the network setup task stage and track control task normal indicators specified in steps S22 and S23: Orbit control strategy during normal satellite phase separation phase; Orbit control strategy during the coarse acquisition phase of normal star configuration; Calculate the element increments required for satellite orbit control Δa=a m -a i ;Δi=i m -i i ; For constellation configuration coarse capture missions, in order to change the half-field axis and tilt angle, a control strategy based on latitude argument is established, where the thrust direction has components only in the tangential and normal directions, but no component in the radial direction. The relationship between the thrust direction and the orbital coordinate system angle β and the latitude depression angle is as follows: β = cos(w + M)βmax; Where w+M is the latitude argument and βmax is the maximum sway angle of the orbit control; The maximum swing angle of the track control is calculated using the following iterative method: Among them, F r F n F t Let F be the radial, normal, and tangential components of the thrust, F be the thrust modulus of the propulsion system, and n be the orbital angular velocity for that orbit. Through simulation iteration, the maximum swing angle βmax is calculated, and the on-board autonomous system performs orbit control tasks based on the maximum swing angle. Orbit control strategy during normal satellite element fine-tuning phase; Abnormal satellite orbit control strategy: Considering the feasibility of orbit control, when an abnormality in the propulsion system or other failures of the entire satellite cause a delay in the orbit control mission of a certain satellite, in order to prevent the difference in the number of orbital elements from continuing to widen due to inconsistency, the right ascension of the ascending node is avoided by offsetting the orbital inclination angle. S3: Calculate the evolution of the post-control constellation configuration over a future period based on the orbit control strategy generated in step S2, and verify the control strategy.

2. The orbit control strategy method for low-Earth orbit mega-constellation networking according to claim 1, characterized in that, Step S1 includes: S11: GNSS telemetry and ground-based orbit determination results, determining the number of orbital elements before and after orbit control, semi-major axis a, eccentricity e, orbital inclination i, argument of perigee w, right ascension of ascending node Ω, and true anomaly M; S12: The electric propulsion thrust is calibrated based on the orbit control ignition sequence and the change in the number of orbital elements before and after orbit control; the orbit calibration method calculates the satellite's velocity increment based on the orbital change parameters; the propulsion system thrust is calculated based on the satellite's velocity increment and the electric propulsion working time. S13: Based on the determined orbit results, calculate the evolution of the constellation configuration.

3. The orbit control strategy method for low-Earth orbit mega-constellation networking according to claim 2, characterized in that, The formula for calculating the thrust of the propulsion system in step S12 is: （2） In formula (1), Δa is the change in satellite orbital altitude, Δv is the satellite velocity increment, r is the satellite orbital radius, and μ is a constant of 3.986 × 10⁻⁶. 14 m 3 / s 2 ; In formula (2), T is the thrust, Δt is the working time of the electric propulsion system, m is the satellite mass, and ΔV is the satellite velocity increment. Formula (3) can be obtained from formula (1) and formula (2). The orbital position parameters within a certain period before and after orbit control are obtained. After precise orbit determination, the difference between the semi-major axis of the orbit before and after orbit control is obtained. The actual thrust of the electric propulsion system can be calculated.

4. The orbit control strategy method for low-Earth orbit mega-constellation networking according to claim 1, characterized in that, Step S3 includes: The constellation orbit control evaluation module uses MATLAB-STK co-simulation to evaluate the constellation orbit control process, the evolution of the elements, and to verify the correctness of the orbit control strategy.

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