Method, device and equipment for obtaining maneuvering parameters for remote rendezvous on low-inclination orbit

Abstract

The present application relates to a method, device and equipment for obtaining maneuvering parameters for long-distance rendezvous on a low-angle orbit. The method comprises: constructing a maneuvering optimization model with only yaw combined maneuvering parameters as design variables through the obtained initial parameters of the rendezvous mission, and dividing the design variables into a first design variable for satisfying the terminal equality constraint, and a second design variable for analytical optimization search, respectively using a maneuvering parameter analytical calculation module and a maneuvering analytical optimization model to solve the first design variable and the second design variable to obtain a corresponding solution, which is a global optimization analytical approximate solution of the maneuvering parameters, and then using the first maneuvering high-precision model to iteratively optimize the global optimization analytical approximate solution until the miss amount converges to a preset convergence standard to obtain high-precision maneuvering parameters. This method can be used to obtain a high-precision solution for only yaw combined maneuvering parameters in a long-distance rendezvous mission on a low-angle orbit.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device and equipment for obtaining maneuvering parameters for long-distance rendezvous in a low-inclination orbit. Background Art

[0002] Low-inclination orbits are those with an orbital plane close to the equator. Most satellites using low-inclination orbits are in geostationary orbits (GEO), which also include low equatorial orbits (ELEO) and medium equatorial orbits (EMEO). GEO orbits, whose orbital period matches the Earth's rotation period, are widely used in communications, navigation, television broadcasting, and missile warning due to their high altitude, wide field of view, and stable sub-satellite point. ELEO orbits offer advantages for space-based situational awareness and rapid revisit observations of areas near the equator. However, due to the high cost of propellant required for orbital plane adjustments in low orbits, they are rarely used for engineering missions. EMEO orbits combine the advantages of both GEO and ELEO orbits and are already being adopted by internet communication satellite constellations serving low-latitude areas where communication is difficult.

[0003] With the development of on-orbit servicing technology, there is an increasing commercial demand for rendezvous services for high-value GEO satellites and other low-inclination orbits. This has also been the focus of new technology trials near GEO orbits in recent years at home and abroad. The design of low-inclination orbits for remote rendezvous and the calculation of maneuvering parameters are key technologies that require breakthroughs. The main difference between low-inclination orbits and commonly used rendezvous orbits in existing manned spaceflight, lunar exploration, and other fields is that their orbital planes are not suitable for characterization using the inclination and right ascension of the ascending node in the classical orbital elements. Accordingly, the calculation method for remote rendezvous maneuver parameters based on the description of the classical orbital element orbital plane is no longer applicable. The maneuvering direction of remote rendezvous in manned spaceflight, lunar exploration, and other fields is restricted. It is generally not along the orbital radial direction, but mainly along the orbital track and normal direction. Some missions consider a combination of track and normal directions (only yaw is allowed, not pitch), which is the so-called yaw-only combined maneuver. Most of the existing GEO orbit rendezvous studies use the Hohmann orbit change model or the Lambert transfer model. The former does not consider the combined maneuver of simultaneous adjustment inside and outside the orbital plane, while the latter requires an orbital radial component (with pitch). The closely related literature "Liu Tao, Hu Haixia, Jie Yongchun, Hu Jinchang. Design of long-distance rendezvous strategy for geostationary satellites. Acta Astronautics, 2020, 41(8):1015-1022" directly adopts the scheme of near-Earth long-distance rendezvous of the Shenzhou spacecraft, does not consider the yaw-only combined maneuver and uses the right ascension of the ascending node, an orbital parameter that is not applicable in the case of small inclination angles. Therefore, it is necessary to study the method of obtaining the parameters of the yaw-only combined maneuver for long-distance rendezvous in low-inclination orbits. Summary of the Invention

[0004] Based on this, it is necessary to provide a method, device and equipment for obtaining maneuvering parameters that can be applied to long-distance rendezvous in low-inclination orbits to address the above technical problems.

[0005] A method for obtaining maneuvering parameters for a low-inclination orbit long-distance rendezvous, the method comprising:

[0006] Acquiring initial parameters of the rendezvous mission, the initial parameters including an aiming state vector, a convergence criterion, and a number of maneuvers;

[0007] Constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuver point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, takes minimizing the total velocity increment as the objective function, and takes the terminal miss distance not exceeding the convergence standard as the terminal equality constraint;

[0008] dividing the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0009] Constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint;

[0010] Constructing a maneuver analytical optimization model that uses the second design variable as an optimization variable and introduces an analytical aiming state variable, wherein the maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function;

[0011] Taking the first design variable solution and the second design variable solution as global optimization analytical approximate solutions;

[0012] The global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

[0013] In one embodiment, if the miss distance calculated by using the solution optimized by the first maneuverable high-precision optimization model cannot always be less than the convergence criterion, the optimization fails, and the solution obtained after the current optimization is output as the best high-precision orbit solution of the design variable, and the second maneuverable high-precision optimization model is used to optimize the best high-precision orbit solution of the design variable.

[0014] In one embodiment, the initial parameters also include: initial time, terminal time, initial time tracking and target satellite orbit parameters, initial time tracking and target satellite small inclination non-odd orbit parameters, initial tracking and target satellite total mass, number of maneuvering circles and tracking satellite engine parameters.

[0015] In one embodiment, the first design variable is the tracking and normal components of the first pulse, the tracking component of the second pulse, the tracking component of the N-1th pulse, and the tracking and normal components of the Nth pulse;

[0016] The second design variables are all the remaining design variables except the first design variable among the design variables, and the second design variables are divided into analytical optimization search position variables and analytical optimization search pulse variables;

[0017] Wherein, N represents the number of maneuvers.

[0018] In one embodiment, setting the second design variable to a known value and solving the first design variable using the maneuvering parameter analytical calculation model includes:

[0019] An initial state vector is obtained by calculating the small-angle non-singular orbit parameters of the target satellite according to the initial moment tracking;

[0020] The influence matrix of the pulse track component and normal component of each maneuver is calculated based on the mean right ascension of each maneuver position and the number of maneuver circles;

[0021] Constructing the influence matrix of the first design variable and the analytical optimization search pulse variable according to the influence matrix of the pulse track component and the normal component of each maneuver;

[0022] Constructing a first influence matrix on the terminal state according to the initial state vector;

[0023] Constructing a second influence matrix on the terminal state according to the influence matrix of the analytical optimization search pulse variable and the analytical optimization search pulse variable;

[0024] The first design variable solution that satisfies the terminal equality constraint is calculated based on the first influence matrix, the second influence matrix, the analytical aiming state variable input by the maneuver analytical optimization model, and the influence matrix of the first design variable.

[0025] In one embodiment, the optimizing the global optimization analytical approximate solution using the first maneuverable high-precision optimization model iteratively until the miss distance calculated by the optimized solution is less than the convergence criterion includes:

[0026] A high-precision orbit integration model is used to perform simulation based on the initial parameters, the mean right ascension of each maneuvering point, and the maneuvering pulse in the global optimization analytical approximate solution to obtain a terminal state vector;

[0027] A miss distance is calculated based on the terminal state vector and the aiming state vector, and whether the miss distance is less than a convergence criterion is determined based on the terminal equality constraint. If the miss distance is less than the convergence criterion, the global optimization analytical approximate solution obtained at this time is the high-precision trajectory optimal solution.

[0028] If the miss distance is not less than the convergence criterion, it is determined whether the number of iterations has reached a preset upper limit. If so, the global optimization analytical approximate solution obtained at this time is used as the best solution for the high-precision trajectory.

[0029] If the preset upper limit is not reached, updating the analytical aiming state variables in the maneuver analytical optimization model according to the miss amount;

[0030] Then, the second design variable and the first design variable are re-solved using the maneuver analytical optimization model and the maneuver parameter analytical calculation model, and the solution is used as the current global optimization analytical approximate solution;

[0031] The next round of optimization iteration is performed based on the current global optimal analytical approximate solution.

[0032] In one embodiment, in the second maneuver high-precision optimization model, a sequential quadratic programming algorithm is used based on the initial parameters and the best high-precision orbit solution to optimize and solve the high-precision orbit optimal solution that meets the high-precision orbit terminal constraints.

[0033] A device for acquiring maneuvering parameters for a low-inclination orbit long-distance rendezvous, the device comprising:

[0034] An initial parameter acquisition module is used to obtain initial parameters of the rendezvous mission, wherein the initial parameters include an aiming state vector, a convergence criterion, and a number of maneuvers;

[0035] a maneuver optimization model construction module, configured to construct a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuvering point of each maneuver, the track direction and normal component of the maneuvering pulse in the LVLH coordinate system as design variables, minimizes the total velocity increment as an objective function, and uses the terminal miss distance not exceeding the convergence standard as a terminal equality constraint;

[0036] a design variable partitioning module for partitioning the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0037] a first design variable solving module, configured to construct a maneuvering parameter analytical calculation model, set the second design variable as a known quantity, and solve the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint;

[0038] a second design variable solving module, configured to construct a maneuvering analytical optimization model using the second design variable as an optimization variable and introducing an analytical aiming state variable, wherein the maneuvering analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function;

[0039] A global optimization analytical approximate solution obtaining module, configured to use the first design variable solution and the second design variable solution as a global optimization analytical approximate solution;

[0040] The maneuvering parameter acquisition module is used to iteratively optimize the global optimization analytical approximate solution using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence standard, and then output it as the high-precision orbit optimal solution of the design variable to obtain the maneuvering parameters.

[0041] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0042] Acquiring initial parameters of the rendezvous mission, wherein the initial parameters include an aiming state vector, a convergence criterion, and a number of maneuvers;

[0043] Constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuver point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, takes minimizing the total velocity increment as the objective function, and takes the terminal miss distance not exceeding the convergence standard as the terminal equality constraint;

[0044] dividing the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0045] Constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint;

[0046] Constructing a maneuver analytical optimization model that uses the second design variable as an optimization variable and introduces an analytical aiming state variable, wherein the maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function;

[0047] The first design variable solution and the second design variable solution are used as global optimization analytical approximate solutions;

[0048] The global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

[0049] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0050] Acquiring initial parameters of the rendezvous mission, the initial parameters including an aiming state vector, a convergence criterion, and a number of maneuvers;

[0051] Constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuver point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, takes minimizing the total velocity increment as the objective function, and takes the terminal miss distance not exceeding the convergence standard as the terminal equality constraint;

[0052] dividing the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0053] Constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint;

[0054] Constructing a maneuver analytical optimization model that uses the second design variable as an optimization variable and introduces an analytical aiming state variable, wherein the maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function;

[0055] Taking the first design variable solution and the second design variable solution as global optimization analytical approximate solutions;

[0056] The global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

[0057] The above-mentioned method, device and equipment for obtaining maneuvering parameters for long-distance rendezvous in a low-inclination orbit respectively construct a maneuvering optimization model, a maneuvering parameter analytical calculation module, a maneuvering analytical optimization model and a first maneuvering high-precision optimization model through the initial parameters of the rendezvous mission obtained. In the maneuvering optimization model, the mean right ascension of the maneuvering point of each maneuver, the track direction and normal component of the maneuvering pulse in the LVLH coordinate system are used as design variables. The design variable is only the yaw combined maneuvering parameter that needs to be solved in this method, and it is necessary to simultaneously satisfy the minimum total speed as the objective function and the terminal equality constraint. In this method, the design variables are divided into The first design variable constrained by the terminal equality constraint and the second design variable used for analytical optimization search are used. The first design variable is solved using the maneuver parameter analytical calculation module to obtain a solution that satisfies the terminal equality constraint. The second design variable is then solved using the maneuver analytical optimization model to obtain a solution that satisfies the objective function. This results in a global optimal analytical approximate solution for the maneuver parameters. The first maneuver high-precision model is then used to iteratively optimize the global optimal analytical approximate solution as the initial solution until the miss distance converges to the preset convergence criterion. The solution corresponding to the current moment is then output as the high-precision orbit optimal solution to obtain the high-precision maneuver parameters. This method is suitable for solving the yaw-only combined maneuver parameters for long-range rendezvous on low-inclination orbits. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a diagram illustrating an application environment of a method for obtaining maneuvering parameters for a remote rendezvous in a low-inclination orbit according to an embodiment;

[0059] Figure 2 1. A schematic flow chart of a method for obtaining maneuvering parameters for a remote rendezvous in a low-inclination orbit according to an embodiment;

[0060] Figure 3 A schematic diagram of a low-inclination orbit long-range rendezvous-only yaw combined maneuver mission in one embodiment;

[0061] Figure 4 A schematic diagram of a calculation process in a maneuver parameter analysis calculation model in one embodiment;

[0062] Figure 5 A schematic diagram of a calculation flow in a first maneuver high-precision optimization model in one embodiment;

[0063] Figure 6 A schematic flow chart of a method for acquiring maneuvering parameters for a remote rendezvous in a low-inclination orbit according to another embodiment;

[0064] Figure 7 A schematic diagram of the relative state changes between the tracking satellite and the target satellite obtained by simulating a low-inclination orbit long-distance rendezvous mission according to the maneuvering parameters obtained by the method in one embodiment;

[0065] Figure 8 This is a structural block diagram of a device for acquiring maneuvering parameters for remote rendezvous in a low-inclination orbit according to one embodiment;

[0066] Figure 9 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0068] The method for obtaining maneuvering parameters for remote rendezvous on a low-inclination orbit provided in this application can be applied to Figure 1 In the application environment shown, tracking satellite 102 communicates with server 104 via a network. Tracking satellite 102 can be, but is not limited to, a propellant supply satellite, an on-orbit maintenance satellite, an orbit life extension satellite, etc. Server 104 can be, but is not limited to, an independent server or a server cluster consisting of multiple servers.

[0069] In one embodiment, Figure 2 As shown in the figure, a method for obtaining maneuvering parameters for remote rendezvous in a low-inclination orbit is provided. Figure 1 Taking the server 104 in the example as an example, the following steps are included:

[0070] Step S200, obtaining initial parameters of the rendezvous mission, the initial parameters including the aiming state vector, convergence criterion, and number of maneuvers;

[0071] Step S210, constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuvering point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, minimizes the total velocity increment as the objective function, and uses the terminal miss distance not exceeding the convergence standard as the terminal equality constraint;

[0072] Step S220 , dividing the design variables into first design variables for satisfying the terminal equality constraint and second design variables for analytical optimization search;

[0073] Step S230: constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies the terminal equality constraint;

[0074] Step S240: constructing a maneuver analytical optimization model that uses the second design variable as the optimization variable and introduces the analytical aiming state variable. The maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function.

[0075] Step S250, taking the first design variable solution and the second design variable solution as the global optimization analytical approximate solution;

[0076] In step S260, the global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

[0077] The maneuver parameter acquisition method provided in this application is specifically applied in the long-distance rendezvous scenario on a low-inclination orbit, such as Figure 3 As shown, both the tracking satellite and the target satellite are operating in low-inclination orbits. The tracking satellite achieves a remote rendezvous with the target satellite through N maneuvers that include both track and normal components. This method is used to obtain high-precision values for the track and normal components of the maneuver pulse, specifically the combined yaw-only maneuver parameters.

[0078] In step S200, at the beginning of the method, the initial parameters of a rendezvous mission are obtained. The initial parameters include the aiming state vector X Aim , convergence criterion ε X As well as the number of maneuvers N, it also includes: initial time t0, terminal time t F , Initial tracking satellite orbit parameters E C0 (a C0 ,e C0 ,i C0 ,Ω C0 ,ω C0,M C0 ), orbital parameters of target satellite at initial moment E T0 (a T0 ,e T0 ,i T0 ,Ω T0 ,ω T0 ,M T0 ), the low-inclination non-singular orbit parameter NE of the tracking satellite at the initial moment C0 (a C0 ,λ C0 ,e xC0 ,e yC0 ,i xC0 ,i yC0 ), the low-inclination non-singular orbit parameter NE of the target satellite at the initial moment T0 (a T0 ,λ T0 ,e xT0 ,e yT0 ,i xT0 ,i yT0 ), the total mass of the initial tracking and target satellites are mass C0 with mass T0 、Number of maneuvering circles is C j (j=1,2,..,N) and tracking satellite engine parameter thrust T max and specific impulse I sp Where a, e, i, Ω, ω and M represent the semi-major axis, eccentricity, inclination, right ascension of the ascending node, angular distance of periapsis and mean anomaly of the satellite orbit respectively, and λ is the mean right ascension. The corresponding relationship between the small-angle non-singular orbit elements and the classical orbit elements is: λ=Ω+ω+M, e x =ecos(Ω+ω),e y =esin(Ω+ω), i x =icosΩ and i y =isinΩ.

[0079] In this paper, all parameters with subscript “0” represent the initial point, subscript “C” represents the orbit of the tracking satellite, subscript “T” represents the orbit of the target satellite, and subscript “Aim” represents the aiming parameter.

[0080] In step S210 , in this method, a maneuver optimization model is first constructed based on initial parameters. The model includes design variables, objective functions, and terminal equality constraints.

[0081] Specifically, the design variables, i.e., the final maneuver parameters, include the mean right ascension of the maneuvering point for each maneuver, and the track and normal components of the maneuvering pulse in the LVLH coordinate system. The design variables are expressed as:

[0082] x=(λ1,...,λN ,Δv y1 ,...,Δv yN ,Δv z1 ,..,Δv zN )(j=1,2,...,N)

[0083] Among them, the origin of the LVLH coordinate system is at the center of mass of the spacecraft, that is, the satellite, the x-axis points along the center of the earth to the direction of the spacecraft (also called the orbital radial direction), the z-axis is along the normal to the orbital plane (also called the orbital normal direction), and the y-axis forms a right-handed coordinate system (also called the orbital track direction) along the direction of orbital motion with the x-axis and z-axis.

[0084] Specifically, the objective function is to minimize the total speed increment:

[0085]

[0086] Specifically, the terminal equality constraint, that is, the terminal miss distance does not exceed the preset convergence standard, is expressed as:

[0087] |X q (t F )-X Aim,q |≤ε X,q (q=1,2,...,6) (2)

[0088] In formula (2), X q (t F ) and X Aim,q Respectively represent the terminal state quantity X(t F ) and the aiming state vector X aim The qth component of , the subscript F represents the parameter of the remote rendezvous terminal time, ε X,q They represent the convergence criteria ε X The qth component of .

[0089] In step S220, the design variables are divided into two parts. In fact, the content of this step should be the content of the maneuvering parameter analytical calculation model. It is written separately just to reflect this part of the content. Next, it will be explained together with the content of the maneuvering parameter analytical calculation model in step S230.

[0090] Specifically, the maneuvering parameter analytical calculation model is a maneuvering parameter calculation model that satisfies the analytical orbit terminal equality constraint based on the optimization variables, the tracking and non-singular orbit parameters of the target satellite at the initial moment, and the aiming parameters.

[0091] In the maneuver parameter analytical calculation model, the design variables to be solved are divided into two parts: x = (x F T ,x GA T) T , where x F is the first design variable used to satisfy the terminal equality constraint, x GA For the remaining design variables except the first design variable, set them as analytical optimization search variables.

[0092] Furthermore, the first design variable is the tracking and normal components of the first pulse, the tracking component of the second pulse, the tracking component of the N-1th pulse, and the tracking and normal components of the Nth pulse, which are expressed as: x F =(Δv y1 ,Δv y2 ,Δv y(N-1) ,Δv yN ,Δv z1 ,Δv zN ) T .

[0093] Furthermore, the second design variable is divided into analytical optimization search position variable and analytical optimization search pulse variable: x GA =(x GA,λ T ,x GA,Δv T ) T , where x GA,λ =(λ1,...,λ N ) T Search position variables for parsing optimization, x GA,Δv =(Δv y3 ,...,Δv y(N-2) ,Δv z2 ,..,Δv z(N-1) ) T Search for pulse variables for analytical optimization.

[0094] The process of solving the first design variable according to the maneuvering parameter analytical calculation model includes:

[0095] The initial state vector X(t0) is obtained by calculating the small-angle non-singular orbit parameters of the target satellite according to the initial tracking time:

[0096]

[0097] In formula (3), a R =(a C0 +a T0 ) / 2 is the reference semi-major axis.

[0098] Then, the influence matrices of the pulse track component and normal component of each maneuver are calculated based on the mean ascension of each maneuver position and the number of maneuver circles, which are expressed as follows:

[0099]

[0100]

[0101] In formula (4) and formula (5), and They represent the influence matrix of the pulse track component and the influence matrix of the normal component of each maneuver respectively. Where μ is the Earth's gravitational constant, R e is the average radius of the Earth's equator, J2 is the J2 coefficient of the Earth's non-spherical perturbation, is the average angular velocity of the reference orbit, is the average velocity of the reference orbit, i R =(i C0 +i T0 ) / 2, ΔT=t F -t0,

[0102] Next, the influence matrix of the first design variable and the influence matrix of the pulse variable for analytical optimization search are constructed based on the influence matrix of the pulse track component and the normal component of each maneuver, and are expressed as:

[0103]

[0104]

[0105] In formula (6) and formula (7), Φ xF and Φ xGA denote the influence matrices of the first design variable and the analytical optimization search pulse variable, respectively.

[0106] And construct the first influence matrix Φ(t0,t F )X(t0), where Φ(t0,t F ) is expressed as:

[0107]

[0108] Then, the second influence matrix Φ on the terminal state is constructed based on the influence matrix of the analytical optimization search pulse variable and the analytical optimization search pulse variable. xGA x GA,Δv .

[0109] Finally, the first design variable solution that satisfies the terminal equality constraint is calculated based on the first influence matrix, the second influence matrix, the analytical aiming state variables passed in by the maneuver analytical optimization model, and the influence matrix of the first design variable. The specific calculation formula is as follows:

[0110]

[0111] In formula (8), the superscript “-1” indicates matrix inversion, X′ Aim Represents the analytical aiming state variables passed in by the maneuver analytical optimization model.

[0112] In the maneuver parameter analytical calculation model, after obtaining the solution of the first design variable that satisfies the terminal equality constraint, the total velocity increment is calculated as fun(x) based on this solution and the value of the analytical optimization search pulse variable, preparing for the subsequent solution of the second design variable using the maneuver analytical optimization model.

[0113] When the first parameter analytical calculation is performed using the maneuvering parameter analytical calculation model, the first design variable is solved by taking the second design variable as a known quantity.

[0114] In this embodiment, the process of the maneuver parameter analytical calculation model performing analytical calculation on the first design variable is as follows: Figure 4 shown.

[0115] In step S240, the maneuver analytical optimization model uses the second design variable as the optimization variable and introduces the analytical aiming state variable. Based on the initial parameters and the first design variable solution and the total speed increment obtained by using the maneuver parameter analytical calculation model, the genetic algorithm is used to optimize the second design variable solution that satisfies the objective function, thereby obtaining the global optimal analytical approximate solution of the maneuver parameters.

[0116] Specifically, the mobile analytical optimization model is used to analytically optimize the search variable x GA As the optimization variable, X′ Aim In order to analyze the aiming state variables, the maneuver parameter analytical calculation model is used according to x GA Calculate x F With the objective function fun(x) (total speed increment), a real-coded genetic algorithm is used for optimization search.

[0117] In this embodiment, the first design variable solution and the second design variable solution obtained according to the maneuver parameter analytical calculation model and the maneuver analytical optimization model are used as the global optimization analytical approximate solution. In this method, the first maneuver high-precision optimization model is used to optimize them to obtain the high-precision orbit optimal solution.

[0118] In step S260, when the first maneuvering high-precision optimization model is used to iteratively optimize the global optimization analytical approximate solution, during each iteration, the currently obtained global optimization analytical approximate solution is first determined to determine whether it is the high-precision orbit optimal solution. If not, a determination is made as to whether the number of iterations has reached a preset upper limit. If so, the currently obtained global optimization analytical approximate solution is used as the high-precision orbit optimal solution. If not, the maneuvering parameter analytical calculation model and the maneuvering analytical optimization model are invoked to recalculate the global optimization analytical approximate solution, and the obtained result is used for the next iteration until the high-precision orbit optimal solution or the high-precision orbit optimal solution is obtained.

[0119] When judging whether the currently obtained global optimization analytical approximate solution is the high-precision orbit optimal solution, a high-precision orbit integral model is used for simulation based on the initial parameters, each maneuvering moment and maneuvering pulse in the global optimization analytical approximate solution to obtain the terminal state vector. The miss distance is then calculated based on the terminal state vector and the aiming state vector, and it is judged whether the miss distance is less than the convergence criterion based on the terminal equality constraint. If it is less than the convergence criterion, the global optimization analytical approximate solution obtained at this time is the high-precision orbit optimal solution.

[0120] Specifically, the number of target iterations Iter=1 is recorded, and based on the initial parameters, the maneuvering time and maneuvering pulse of the global optimal analytical approximate solution, a high-precision orbit integration model is used to simulate and calculate the terminal time t F , record the terminal state non-singular orbit parameters reached by the tracking satellite as NE CF (a CF ,λ CF ,e xCF ,e yCF ,i xCF ,i yCF ), the non-singular orbital element of the terminal state of the target star obtained by high-precision orbit integration calculation at this moment is NE TF (a TF ,λ TF ,e xTF ,e yTF ,i xTF ,i yTF ), the terminal state vector reached is calculated as:

[0121]

[0122] The value of the analytical aiming state variable used to calculate the global optimal analytical approximate solution is taken as X′ Aim =X Aim .

[0123] Calculate the off-target amount δ X =X(t F)-X aim , when |X q (t F )-X Aim,q |≤ε X,q (q=1,2,...,6), the current x GA with x F The values of each variable in are assigned to x, and the output is the high-precision optimal solution x for the maneuvering parameters. * .

[0124] When the miss amount is not less than the convergence standard, that is, the iteration does not converge, it is determined whether the number of iterations has reached the preset upper limit Iter max If it is achieved, the global optimal analytical approximate solution obtained at this time is used as the best solution of the high-precision orbit x tmp ;

[0125] If the preset upper limit is not reached, the analytical aiming state variables in the maneuver analytical optimization model are updated according to the miss amount, and then the second design variable and the first design variable are re-solved using the maneuver analytical optimization model and the maneuver parameter analytical calculation model. The solution is used as the current global optimization analytical approximate solution, and the next round of optimization iteration is performed based on the current global optimization analytical approximate solution.

[0126] In this embodiment, the process of iteratively optimizing the global optimization analytical approximate solution using the first mobile high-precision optimization model is as follows: Figure 5 shown.

[0127] In this embodiment, the method in this application also includes: if the miss amount calculated by the solution optimized by the first maneuverable high-precision optimization model cannot always be less than the convergence criterion, the optimization fails, and the solution obtained after the current optimization is output as the best high-precision orbit solution of the design variable, and the second maneuverable high-precision optimization model is used to optimize the best high-precision orbit solution of the design variable. In the second maneuverable high-precision optimization model, a sequential quadratic programming algorithm is used based on the initial parameters and the best high-precision orbit solution to optimize and solve the best high-precision orbit solution that meets the high-precision orbit terminal constraints. The process of the entire method is as follows: Figure 6 shown.

[0128] Specifically, the second maneuvering high-precision optimization model is based on the initial parameters and the temporary best solution of the high-precision orbit, and uses the sequential quadratic programming algorithm to optimize and solve the high-precision maneuvering parameters that meet the high-precision orbit terminal constraints. When the miss amount meets the preset convergence standard, the high-precision optimal solution of the maneuvering parameters is output; if the preset convergence standard is still not met at the end of the sequential quadratic programming algorithm solution, a solution failure message is output.

[0129] Furthermore, the design variable of the second maneuver high-precision optimization model is x=(xF T ,x GA T ) T , the objective function is the total velocity increment fun(x), and the constraint condition is |X q (t F )-X Aim,q |≤ε X,q (q=1,2,...,6), the initial value of the design variable is the best high-precision orbit solution x provided by the first maneuver high-precision optimization model tmp When the sequential quadratic programming algorithm is finished solving, if the terminal equality constraint is satisfied, the high-precision optimal solution x of the maneuvering parameters is output. * Otherwise, the output high-precision orbit is best solved by x tmp With the solution failure flag.

[0130] The method of this application is clearly described below with reference to a specific embodiment.

[0131] In one embodiment, the mission initial time is 04:00:00 on July 23, 2023, and the terminal time is 04:00:00 on August 2, 2023. The time format is UTC. The tracking orbit parameters and target orbit parameters at the initial time are shown in Table 1, the aiming parameters and convergence criteria are shown in Table 2, and other parameter settings are shown in Table 2.

[0132] As shown in Table 3.

[0133] Table 1 Track parameter settings

[0134]

[0135] Table 2 Aiming parameters and convergence criteria settings

[0136]

[0137] Table 3 Other parameter settings

[0138]

[0139] Using the method proposed in this application, the high-precision optimal solution of the final maneuvering parameters is obtained as shown in Table 4.

[0140] Table 4 High-precision optimal solution of final maneuver parameters

[0141]

[0142] The relative state changes between the tracking satellite and the target satellite are as follows: Figure 7 As shown, Figure 7 (a) is the change of Δa, Figure 7 (b) is the change of Δλ, Figure 7 (c) is Δe x change, Figure 7 (d) is Δe y change, Figure 7 (e) is Δi x change, Figure 7 (f) is Δi y change. Figure 7 The figures in the middle show that all components of the relative states of the two spacecraft at the terminal moment are within the convergence range.

[0143] The above-mentioned method for obtaining maneuvering parameters for long-distance rendezvous in a low-inclination orbit constructs a maneuvering optimization model, a maneuvering parameter analytical calculation module, a maneuvering analytical optimization model, and a first maneuvering high-precision optimization model respectively through the obtained initial parameters of the rendezvous mission. In the maneuvering optimization model, the mean right ascension of the maneuvering point of each maneuver, the track direction and normal component of the maneuvering pulse in the LVLH coordinate system are used as design variables. The design variable is only the yaw combined maneuvering parameter that needs to be solved in this method, and it is necessary to simultaneously satisfy the objective function of minimizing the total speed increment and the terminal equality constraint. In this method, the design variables are divided into the following types to satisfy the terminal equality constraint: The first design variable constrained by the equation and the second design variable for analytical optimization search are used. The first design variable is solved using the maneuver parameter analytical calculation module to obtain a solution that satisfies the terminal equality constraint. The second design variable is then solved using the maneuver analytical optimization model to obtain a solution that satisfies the objective function. This results in a global optimal analytical approximate solution for the maneuver parameters. The first maneuver high-precision model is then used to iteratively optimize the global optimal analytical approximate solution as the initial solution until the miss distance converges to the preset convergence criterion. The solution corresponding to the current moment is then output as the high-precision orbit optimal solution to obtain the high-precision maneuver parameters. This method is suitable for solving the yaw-only combined maneuver parameters for long-range rendezvous on low-inclination orbits.

[0144] It should be understood that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0145] In one embodiment, Figure 8As shown, a device for acquiring maneuvering parameters for a remote rendezvous on a low-inclination orbit is provided, comprising: an initial parameter acquisition module 300, a maneuvering optimization model construction module 310, a design variable division module 320, a first design variable solution module 330, a second design variable solution module 340, a global optimization analytical approximate solution acquisition module 350, and a maneuvering parameter acquisition module 360, wherein:

[0146] An initial parameter acquisition module 300 is used to acquire initial parameters of the rendezvous mission, wherein the initial parameters include an aiming state vector, a convergence criterion, and a number of maneuvers;

[0147] A maneuver optimization model construction module 310 is configured to construct a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuvering point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, minimizes the total velocity increment as the objective function, and uses the terminal miss distance not exceeding the convergence standard as the terminal equality constraint;

[0148] A design variable partitioning module 320 for partitioning the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0149] A first design variable solving module 330 is configured to construct a maneuvering parameter analytical calculation model, set the second design variable as a known quantity, and solve the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies the terminal equality constraint;

[0150] A second design variable solving module 340 is configured to construct a maneuver analytical optimization model using the second design variable as an optimization variable and introducing an analytical aiming state variable. The maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function.

[0151] A global optimization analytical approximate solution obtaining module 350 is configured to use the first design variable solution and the second design variable solution as a global optimization analytical approximate solution;

[0152] The maneuvering parameter acquisition module 360 is used to iteratively optimize the global optimization analytical approximate solution using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, and then output it as the high-precision orbit optimal solution of the design variable to obtain the maneuvering parameters.

[0153] Regarding the specific definition of the maneuvering parameter acquisition device for remote rendezvous on a low-inclination orbit, please refer to the definition of the maneuvering parameter acquisition method for remote rendezvous on a low-inclination orbit above, which will not be repeated here. Each module in the above-mentioned maneuvering parameter acquisition device for remote rendezvous on a low-inclination orbit can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0154] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 9 As shown. The computer device includes a processor, memory, network interface, display screen and input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for obtaining maneuvering parameters for remote rendezvous in a low-inclination orbit is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0155] Those skilled in the art will understand that Figure 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0156] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0157] Acquiring initial parameters of the rendezvous mission, the initial parameters including an aiming state vector, a convergence criterion, and a number of maneuvers;

[0158] Constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuver point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, takes minimizing the total velocity increment as the objective function, and takes the terminal miss distance not exceeding the convergence standard as the terminal equality constraint;

[0159] dividing the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0160] Constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint;

[0161] Constructing a maneuver analytical optimization model that uses the second design variable as an optimization variable and introduces an analytical aiming state variable, wherein the maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function;

[0162] The first design variable solution and the second design variable solution are used as global optimization analytical approximate solutions;

[0163] The global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

[0164] In one 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 following steps are implemented:

[0165] Acquiring initial parameters of the rendezvous mission, the initial parameters including an aiming state vector, a convergence criterion, and a number of maneuvers;

[0166] Constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuver point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, minimizes the total speed as an objective function, and uses the terminal miss distance not exceeding the convergence standard as a terminal equality constraint;

[0167] dividing the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search;

[0168] Constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint;

[0169] Constructing a maneuver analytical optimization model that uses the second design variable as an optimization variable and introduces an analytical aiming state variable, wherein the maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function;

[0170] The first design variable solution and the second design variable solution are used as global optimization analytical approximate solutions;

[0171] The global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

[0172] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0173] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0174] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for obtaining maneuvering parameters for a low-inclination orbit long-distance rendezvous, characterized in that: The method comprises: Acquiring initial parameters of the rendezvous mission, the initial parameters including an aiming state vector, a convergence criterion, and a number of maneuvers; Constructing a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuver point of each maneuver, the track direction and normal component of the maneuver pulse in the LVLH coordinate system as design variables, takes minimizing the total velocity increment as the objective function, and takes the terminal miss distance not exceeding the convergence standard as the terminal equality constraint; dividing the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search; Constructing a maneuvering parameter analytical calculation model, setting the second design variable as a known variable, and solving the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint; Constructing a maneuver analytical optimization model that uses the second design variable as an optimization variable and introduces an analytical aiming state variable, wherein the maneuver analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function; Taking the first design variable solution and the second design variable solution as global optimization analytical approximate solutions; The global optimization analytical approximate solution is iteratively optimized using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence criterion, which is then output as the high-precision orbit optimal solution of the design variables to obtain the maneuvering parameters.

2. The method for obtaining maneuvering parameters according to claim 1, characterized in that: If the miss distance calculated using the solution optimized by the first maneuverable high-precision optimization model cannot always be less than the convergence criterion, the optimization fails, and the solution obtained after the current optimization is output as the best high-precision orbit solution of the design variable, and the second maneuverable high-precision optimization model is used to optimize the best high-precision orbit solution of the design variable.

3. The method for obtaining maneuvering parameters according to claim 2, characterized in that: The initial parameters also include: initial time, terminal time, initial time tracking and target satellite orbit parameters, initial time tracking and target satellite small inclination non-odd orbit parameters, initial tracking and target satellite total mass, number of maneuvering circles and tracking satellite engine parameters.

4. The method for obtaining maneuvering parameters according to claim 3, characterized in that: The first design variables are the tracking and normal components of the first pulse, the tracking component of the second pulse, the tracking component of the N-1th pulse, and the tracking and normal components of the Nth pulse; The second design variables are all the remaining design variables except the first design variable among the design variables, and the second design variables are divided into analytical optimization search position variables and analytical optimization search pulse variables; Wherein, N represents the number of maneuvers.

5. The method for obtaining maneuvering parameters according to claim 4, characterized in that: Setting the second design variable as a known variable and solving the first design variable using the maneuver parameter analytical calculation model includes: An initial state vector is obtained by calculating the small-angle non-singular orbit parameters of the target satellite according to the initial moment tracking; The influence matrix of the pulse track component and normal component of each maneuver is calculated based on the mean right ascension of each maneuver position and the number of maneuver circles; Constructing the influence matrix of the first design variable and the analytical optimization search pulse variable according to the influence matrix of the pulse track component and the normal component of each maneuver; Constructing a first influence matrix on the terminal state according to the initial state vector; Constructing a second influence matrix on the terminal state according to the influence matrix of the analytical optimization search pulse variable and the analytical optimization search pulse variable; The first design variable solution that satisfies the terminal equality constraint is calculated based on the first influence matrix, the second influence matrix, the analytical aiming state variable input by the maneuver analytical optimization model, and the influence matrix of the first design variable.

6. The method for obtaining maneuvering parameters according to claim 5, characterized in that: The method of using the first maneuverable high-precision optimization model to iteratively optimize the global optimization analytical approximate solution until the miss distance calculated by the optimized solution is less than the convergence criterion includes: A high-precision orbit integration model is used to perform simulation based on the initial parameters, the mean right ascension of each maneuvering point, and the maneuvering pulse in the global optimization analytical approximate solution to obtain a terminal state vector; A miss distance is calculated based on the terminal state vector and the aiming state vector, and whether the miss distance is less than a convergence criterion is determined based on the terminal equality constraint. If the miss distance is less than the convergence criterion, the global optimization analytical approximate solution obtained at this time is the high-precision trajectory optimal solution. If the miss distance is not less than the convergence criterion, it is determined whether the number of iterations has reached a preset upper limit. If so, the global optimization analytical approximate solution obtained at this time is used as the best solution for the high-precision trajectory. If the preset upper limit is not reached, updating the analytical aiming state variables in the maneuver analytical optimization model according to the miss amount; Then, the second design variable and the first design variable are re-solved using the maneuver analytical optimization model and the maneuver parameter analytical calculation model, and the solution is used as the current global optimization analytical approximate solution; The next round of optimization iteration is performed based on the current global optimal analytical approximate solution.

7. The method for obtaining maneuvering parameters according to claim 6, characterized in that: In the second maneuver high-precision optimization model, a sequential quadratic programming algorithm is used based on the initial parameters and the best high-precision orbit solution to optimize and solve the high-precision orbit optimal solution that meets the high-precision orbit terminal constraints.

8. A device for acquiring maneuvering parameters for a low-inclination orbit long-distance rendezvous, characterized in that: The device comprises: An initial parameter acquisition module is used to obtain initial parameters of the rendezvous mission, wherein the initial parameters include an aiming state vector, a convergence criterion, and a number of maneuvers; a maneuver optimization model construction module, configured to construct a maneuver optimization model based on the initial parameters, wherein the maneuver optimization model uses the mean right ascension of the maneuvering point of each maneuver, the track direction and normal component of the maneuvering pulse in the LVLH coordinate system as design variables, minimizes the total velocity increment as an objective function, and uses the terminal miss distance not exceeding the convergence standard as a terminal equality constraint; a design variable partitioning module for partitioning the design variables into first design variables for satisfying terminal equality constraints and second design variables for analytical optimization search; a first design variable solving module, configured to construct a maneuvering parameter analytical calculation model, set the second design variable as a known quantity, and solve the first design variable using the maneuvering parameter analytical calculation model to obtain a first design variable solution that satisfies a terminal equality constraint; a second design variable solving module, configured to construct a maneuvering analytical optimization model using the second design variable as an optimization variable and introducing an analytical aiming state variable, wherein the maneuvering analytical optimization model uses a real-coded genetic algorithm to perform an optimization search to obtain a second design variable solution that satisfies the objective function; A global optimization analytical approximate solution obtaining module, configured to use the first design variable solution and the second design variable solution as a global optimization analytical approximate solution; The maneuvering parameter acquisition module is used to iteratively optimize the global optimization analytical approximate solution using the first maneuvering high-precision optimization model until the miss distance calculated by the optimized solution is less than the convergence standard, and then output it as the high-precision orbit optimal solution of the design variable to obtain the maneuvering parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. 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 any one of claims 1 to 7 are implemented.

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