Launch vehicle debris avoidance pipeline-trajectory integrated planning method, equipment and medium

Abstract

The present application discloses a launch vehicle debris avoidance pipeline-trajectory integrated planning method, equipment and medium, and relates to the technical field of active space debris avoidance. The method comprises: determining a flight window set for each altitude layer according to the distribution of space debris at each altitude layer, and establishing a flight pipeline directed graph model based on the flight window set for each altitude layer, constructing a pipeline-trajectory integrated planning model based on the flight pipeline directed graph model, optimizing and solving the pipeline-trajectory integrated planning model to obtain an optimal flight pipeline and flight trajectory. The present application can achieve global optimization of the flight pipeline and flight trajectory by constructing and solving the pipeline-trajectory integrated planning model, and can further improve global optimality compared to the method of solving the flight pipeline and flight trajectory separately, thereby generating a better flight pipeline and flight trajectory and improving reliability.

Description

Technical Field

[0001] The present application relates to the technical field of active space debris avoidance, and in particular to a launch vehicle debris avoidance pipeline-trajectory integrated planning method, equipment and medium. Background Art

[0002] Space debris refers to space junk generated by human space launches, including giant constellations, abandoned orbital spacecraft or their components. With the increase in the frequency of space launches, the amount of space debris is also increasing rapidly. According to statistics, the number of cataloged space debris exceeds 30,000 pieces, which are mainly distributed in low-Earth orbits at an altitude of 700 to 1,100 kilometers, posing a collision threat to the ascent of launch vehicles.

[0003] At present, the debris avoidance method for launch vehicles during ascent adopts a passive avoidance strategy: assessing the collision threat between the planned orbit of the launch vehicle and the space debris in orbit, and changing the planned launch time to mitigate the collision threat. However, when the amount of space debris in the flight envelope is large, this method is inefficient, resulting in launch delays or even cancellations. In order to solve the above problems, an active avoidance strategy is needed. There are few existing active avoidance strategies, and they mainly use trajectory planning methods, but they are not globally optimal. Summary of the invention

[0004] The purpose of this application is to provide a launch vehicle debris avoidance pipeline-trajectory integrated planning method, equipment and medium, which can achieve global optimization of the flight pipeline and flight trajectory, generate better flight pipeline and flight trajectory, and improve reliability.

[0005] To achieve the above objectives, this application provides the following solutions.

[0006] In a first aspect, the present application provides a launch vehicle debris avoidance pipeline-trajectory integrated planning method, and the launch vehicle debris avoidance pipeline-trajectory integrated planning method includes the following steps.

[0007] According to the distribution of space debris at each altitude layer, a flight window set at each altitude layer is determined, and based on the flight window set at each altitude layer, a flight pipeline directed graph model is established; the flight window set includes a plurality of flight windows, and the flight window is an area through which a launch vehicle can pass; the flight pipeline directed graph model includes a directed node set and a directed edge set, the directed node set includes a plurality of nodes, and the nodes include an initial state node, a flight window node and a target orbit node, the flight window node is a node corresponding to the flight window, and the directed edge set includes an edge connecting two nodes in order of altitude.

[0008] Based on the flight pipeline directed graph model, a pipeline-trajectory integrated planning model is constructed; the pipeline-trajectory integrated planning model takes fuel optimization as the optimization goal, and takes rocket dynamics constraints, rocket initial constraints, rocket terminal orbit constraints, rocket thrust direction constraints, flight window motion constraints, flight pipeline connectivity constraints and flight window constraints as constraints.

[0009] The pipeline-trajectory integrated planning model is optimized and solved to obtain the optimal flight pipeline and flight trajectory; the flight pipeline is a traversable path from the initial state node to the target orbit node in the flight pipeline directed graph model; the flight trajectory is the flight path of the launch vehicle in the flight pipeline.

[0010] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned launch vehicle debris avoidance pipeline-trajectory integrated planning method.

[0011] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned launch vehicle debris avoidance pipeline-trajectory integrated planning method.

[0012] According to the specific embodiments provided in this application, this application has the following technical effects.

[0013] The present application provides a launch vehicle debris avoidance pipeline-trajectory integrated planning method, equipment and medium. According to the distribution of spatial debris at each altitude layer, the flight window set of each altitude layer is determined, and based on the flight window set of each altitude layer, a flight pipeline directed graph model is established. Based on the flight pipeline directed graph model, a pipeline-trajectory integrated planning model is constructed. The pipeline-trajectory integrated planning model takes fuel optimization as the optimization goal, and takes rocket dynamics constraints, rocket initial constraints, rocket terminal orbit constraints, rocket thrust direction constraints, flight window motion constraints, flight pipeline connectivity constraints and flight window constraints as constraints. The pipeline-trajectory integrated planning model is optimized and solved to obtain the optimal flight pipeline and flight trajectory. By constructing and solving the pipeline-trajectory integrated planning model, the present application can achieve global optimization of the flight pipeline and flight trajectory. Compared with the method of solving the flight pipeline and flight trajectory separately, the global optimality can be further improved, so that better flight pipelines and flight trajectories can be generated, and reliability can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 This is an application environment diagram of a launch vehicle debris avoidance pipeline-trajectory integrated planning method provided in Example 1 of the present application.

[0016] Figure 2 A schematic flow chart of a launch vehicle debris avoidance pipeline-trajectory integrated planning method provided in Example 1 of the present application.

[0017] Figure 3 A schematic diagram of modeling of the flight pipeline directed graph model provided in Example 1 of the present application.

[0018] Figure 4 Schematic diagram of the framework for solving the optimal control problem of pipeline-trajectory integrated planning provided in Example 1 of the present application.

[0019] Figure 5 A schematic diagram of the structure of a computer device provided in Example 2 of the present application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] Example 1.

[0022] The launch vehicle debris avoidance pipeline-trajectory integrated planning method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal communicates with the server through the network. The data storage system can store the data that the server needs to process. The data storage system can be set up separately, integrated on the server, or placed on the cloud or other servers. The terminal can send a pending integrated planning request (used to request the generation of the optimal flight pipeline and flight trajectory) to the server. After the server receives the pending integrated planning request, for the pending integrated planning request, the server determines the flight window set of each altitude layer according to the spatial fragmentation distribution of each altitude layer, and establishes a flight pipeline directed graph model based on the flight window set of each altitude layer; based on the flight pipeline directed graph model, a pipeline-trajectory integrated planning model is constructed; the pipeline-trajectory integrated planning model is optimized and solved to obtain the optimal flight pipeline and flight trajectory. The server can feedback the optimal flight pipeline and flight trajectory obtained for the integrated planning request to the terminal.

[0023] In addition, in some embodiments, the launch vehicle debris avoidance pipeline-trajectory integrated planning method can also be implemented independently by a server or a terminal. For example, the terminal can directly process the integrated planning request to be processed, or the server can obtain the integrated planning request to be processed from the data storage system and process the integrated planning request to be processed.

[0024] The terminals may be, but are not limited to, various desktop computers, laptops, smart phones, tablet computers, IoT devices and portable wearable devices. IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server may be implemented as an independent server or a server cluster consisting of multiple servers, or a cloud server.

[0025] like Figure 2 As shown, a launch vehicle debris avoidance pipeline-trajectory integrated planning method is provided. The method is executed by a computer device, and can be specifically executed by a computer device such as a terminal or a server alone, or can be executed by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The following steps are used to illustrate the server in the example.

[0026] Step S1, according to the distribution of space debris at each altitude layer, determine the flight window set of each altitude layer, and establish a flight pipeline directed graph model based on the flight window set of each altitude layer; the flight window set includes a plurality of flight windows, and the flight window is an area through which a launch vehicle can pass; the flight pipeline directed graph model includes a directed node set and a directed edge set, the directed node set includes a plurality of nodes, the nodes include an initial state node, a flight window node and a target orbit node, the flight window node is a node corresponding to the flight window, and the directed edge set includes an edge connecting two nodes in order of altitude.

[0027] Step S2, based on the flight pipeline directed graph model, construct a pipeline-trajectory integrated planning model; the pipeline-trajectory integrated planning model takes fuel optimization as the optimization goal, and takes rocket dynamics constraints, rocket initial constraints, rocket terminal orbit constraints, rocket thrust direction constraints, flight window motion constraints, flight pipeline connectivity constraints and flight window constraints as constraints.

[0028] Step S3, optimizing and solving the pipeline-trajectory integrated planning model to obtain the optimal flight pipeline and flight trajectory; the flight pipeline is a navigable path from the initial state node to the target orbit node in the flight pipeline directed graph model; the flight trajectory is the flight path of the launch vehicle in the flight pipeline.

[0029] By implementing the above steps S1 to S3, this embodiment can obtain the optimal flight pipeline and flight trajectory by constructing and solving the pipeline-trajectory integrated planning model, thereby realizing global optimization of the flight pipeline and flight trajectory, generating better flight pipelines and flight trajectories, and improving reliability.

[0030] The following is a further introduction to a launch vehicle debris avoidance pipeline-trajectory integrated planning method used in this embodiment through three steps.

[0031] (i) Establishing a launch vehicle debris avoidance flight pipeline, corresponding to step S1.

[0032] like Figure 3As shown in the figure, considering that the orbit of space debris is a circular orbit, the typical altitude layers of space debris are divided according to the orbit altitude. All space debris in the same altitude layer can be regarded as moving on a sphere with a fixed orbit altitude. The flight window can be modeled as a dynamic circular area with the Voronoi polygon vertex as the center and the distance from the minimum great circle of the space debris as the radius using the Voronoi diagram. In the order of altitude layers from low to high, the flight windows of each altitude layer are connected to form a flight pipeline directed graph model (also called a space-time flight pipeline directed graph model). In the flight pipeline directed graph model, the path from the initial state node to the target orbit node is an available flight pipeline (also called a space-time flight pipeline), which realizes the modeling of the debris avoidance flight pipeline.

[0033] The typical altitude layers of space debris orbits are denoted as the set H ={ H 1, H 2, ..., H n}, n ∈ is the total number of altitude layers, n ≥1, h i ∈ For the i Levels H i The corresponding orbital height, i =1, 2, ..., n , without loss of generality, it is stipulated that H p , H q ∈ H ,when p < q hour, h p < h q . Note the collection of space debris D ={ D 1, D 2, ..., D n}, ={ , , ..., } is the altitude layer H i Inner space debris collection, N i ∈ For altitude layer H i The total number of inner space fragments, Ni >3. Define the matrix =[ , , ..., ], =[ , , ..., ], ∈ It's space debris D ij The fixed threat radius is defined as ( t )=[ ( t ), ( t ), ..., ( t )], ( t )=[ ( t ), ( t ), ..., ( t )], ( t )∈ It's space debris D ij The center position vector of ( t )=[ ( t ), ( t ), ..., ( t )], ( t )=[ ( t ), ( t ), ..., ( t )], ( t )∈ It's space debris D ij The central velocity vector of j =1, 2, ..., N i , t ∈ is time, then the motion equation of space debris (also called the space debris dynamics model) is as shown in equation (1).

[0034] (1).

[0035] In formula (1), For the The altitude layer Space debris in time The first derivative of the central position vector of ; For the The altitude layer Space debris in time The central velocity vector of For the The altitude layer Space debris in time The first derivative of the central velocity vector; ∈ is the gravitational acceleration vector under the spherical gravitational field, for The gravitational acceleration vector at , For the The altitude layer Space debris in time The center position vector of .

[0036] For any typical altitude layer H i , according to this altitude layer H i Inner space debris collection D i Based on the motion equations of space debris, a space-time flight window model for launch vehicle debris avoidance is established.

[0037] According to this altitude H i Inner space debris collection D i middle N i The center position vector of the space debris , at altitude H i On the sphere, space debris gathers D i As a point set, the Delaunay triangulation algorithm is used to triangulate the space debris set. D i The convex hull of the midpoint (i.e. the center point of each space fragment) is segmented to obtain a unique spherical triangulation network, denoted as DT( D i ), and Δ D ip D iqD ir is DT( D i ) is a spherical triangle unit, D ip , D iq , D ir ∈ D i Therefore, the launch vehicle passes through this altitude layer H i The flight window can be described in each spherical triangle unit.

[0038] In order to keep the launch vehicle as far away from space debris as possible and reduce the risk of collision, the center of the flight window is set to the spherical triangle unit Δ D ip D iq D ir The intersection point of the perpendicular bisectors is the center of the circumscribed circle, and the radius of the flight window is selected as the maximum value of the radius of the circumscribed circle minus the fixed threat radius of the corresponding space debris.

[0039] According to the principle of Delaunay triangulation algorithm, DT( D i ) form a Voronoi diagram, denoted by Vor( D i ),and ,Vor( D ij ) D ij is the Voronoi polygon region of the generator, j =1, 2, ..., N i , satisfying the following formula (2).

[0040] (2).

[0041] In formula (2), the position vector ∈Vor( D ij ), s ( , )∈ is the great circle distance, satisfying the following formula (3).

[0042] (3).

[0043] In formula (3),R h ∈ , θ ∈ and ∈ They are the position vectors ∈ Radial distance, azimuth, and polar angle described in polar coordinates.

[0044] According to the above formula (2), the points on the edge of the Voronoi diagram satisfy the relationship shown in the following formula (4).

[0045] (4).

[0046] In formula (4), the position vector On the side D ip D iq on the perpendicular bisector of .

[0047] The vertices of the Voronoi polygon satisfy the relationship shown in the following equation (5).

[0048] (5).

[0049] In formula (5), the position vector ∈ In Δ D ip D iq D ir At the intersection of the perpendicular bisectors of .

[0050] Therefore, the center of the launch vehicle's flight window is also the vertex of the Voronoi polygon.

[0051] Remember the flying window collection W ={ W 1, W 2, ..., W n}, ={ , , ..., } is the altitude layer H i Inner flight window collection, M i ∈ For altitude layer H i The total number of flight windows. Define the matrix R w ( t)=[ R w1 ( t ), R w2 ( t ), ..., R wn ( t )], ( t )=[ ( t ), ( t ), ..., ( t )], ( t )∈ For flight window W ik The radius of the matrix ( t )=[ ( t ), ( t ), ..., ( t )], ( t )=[ ( t ), ( t ), ..., ( t )], ( t )∈ For flight window W ik The rate of change of the radius is defined as the matrix ( t )=[ ( t ), ( t ), ..., ( t )], ( t )=[ ( t ), ( t ), ..., ( t )], ( t )∈ For flight window W ik The center position vector of ( t )=[ ( t ), ( t ), ..., ( t )], ( t )=[ ( t ), ( t ), ..., ( t )], ( t )∈ For flight window W ik The central velocity vector of k =1, 2, ..., M i According to formula (5), let W ik is composed of spherical triangle units Δ D ip D iq D ir Determined flight window, r wik , R wik It can be written as r dip , r diq , r dir The compact form of the function is shown in the following equations (6) and (7).

[0052] (6).

[0053] (7).

[0054] In the above formula, oik ( t )∈ is Δ D ip D iq D ir The position vector of the center of the circumscribed circle; R oik ( t )∈ is Δ Dip D iq D ir The radius of the circumcircle of , The specific form of can be derived from the spherical triangle formula.

[0055] Substituting the space debris motion equation (i.e., equation (1)) into equations (6) and (7), and calculating the time derivative, we can obtain the flight window motion equation (i.e., the debris avoidance space-time flight window model), which is expressed as the following equations (8) and (9).

[0056] (8).

[0057] (9).

[0058] In the above formula, For the The altitude layer Flight windows in time The first derivative of the central position vector of ; For the The altitude layer Flight windows in time The central velocity vector of Respectively The altitude layer Three space debris corresponding to the flight window; is the first spherical triangle function; For the The altitude layer Space debris in time The center position vector of For the The altitude layer Space debris in time The central velocity vector of For the The altitude layer Flight windows in time The first derivative of the central velocity vector; For the The altitude layer Flight windows in time The central acceleration vector of For the The altitude layer Space debris in time The center position vector of for The gravitational acceleration vector at ; For the The altitude layer Flight windows in time The first derivative of the radius; For the The altitude layer Flight windows in time The rate of change of the radius; is the second spherical triangle function; For the The altitude layer Flight windows in time The first derivative of the rate of change of the radius; For the The altitude layer Flight windows in time The second derivative of the rate of change of the radius.

[0059] At this point, the launch vehicle has passed through the typical altitude layer H i Flight Window W i Modeled for M i The center position and radius of space debris D i Dynamically changing spherical circular area, i =1, 2, ..., n .

[0060] According to each typical altitude layer H ={ H 1, H 2, ..., H n}Flying window collection W ={ W 1, W 2, ..., W n}, connect the flight windows in order of altitude to form a flight pipeline directed graph model, denoted as ,in, is a directed set of nodes, It is a directed edge set, and the path from the initial state node to the target orbit node in the flight pipeline directed graph model is a flight pipeline available for the launch vehicle.

[0061] In-flight pipeline directed graph model In the directed node set Including the launch vehicle initial state node S l , Flight window nodeW and the target orbit node T l , as shown in formula (10).

[0062] (10).

[0063] In formula (10), m ∈ for The total number of nodes in the.

[0064] Directed edge set Include All possible ordered pairs of nodes in , as shown in equation (11).

[0065] (11).

[0066] In formula (11), if , then there is a slave node Point to Node The edge (also called directed edge) is called and are adjacent.

[0067] Flight pipeline directed graph model G The adjacency matrix of A = A ( G )∈ , whose elements a pq It is given by the following formula (12).

[0068] (12).

[0069] Specifically, assuming that the launch vehicle's flight altitude increases monotonically and that the launch vehicle is required to pass through the flight window of all altitude layers between the initial state and the target orbit, the flight pipeline directed graph model is G The connection rules of the middle edges are as follows.

[0070] (1) Launch vehicle initial state node and altitude layer H The flight window nodes of 1 are adjacent, as shown in equation (13).

[0071] (13).

[0072] According to equations (12) and (13), the corresponding elements in the adjacency matrix satisfy the following equation (14).

[0073] (14).

[0074] (2) Altitude layerH i The flight window node is at a higher altitude level H i+1 The flight window nodes are adjacent, i =1, 2, ..., n -1, as shown in formula (15).

[0075] (15).

[0076] According to equations (12) and (15), the corresponding elements in the adjacency matrix satisfy the following equation (16).

[0077] (16).

[0078] (3) Altitude layer H n The flight window node is adjacent to the launch vehicle target orbit node, as shown in Equation (17).

[0079] (17).

[0080] According to equations (12) and (17), the corresponding elements in the adjacency matrix satisfy the following equation (18).

[0081] (18).

[0082] (4) In addition to the above, The nodes are not adjacent, that is ,and .

[0083] Comprehensive case (1) to case (4), flight pipeline directed graph model G The adjacency matrix of A ( G ) can be given by the following formula (19).

[0084] (19).

[0085] It is worth noting that considering the monotonicity of the launch vehicle flight time, in the flight pipeline directed graph model G The launch vehicle passes through the flight window node W i Time t i According to the altitude H i Monotonically increasing, i =1, 2, ..., n , as shown in formula (20).

[0086] (20).

[0087] In the established flight pipeline directed graph model G The flight pipeline available to the launch vehicle can be recorded as starting from the initial state node S l To the target track node T l A path of, the path set consisting of all paths P ( G ) can be organized into the form of the following formula (21).

[0088] (twenty one).

[0089] At this point, the debris avoidance flight duct model can be constructed.

[0090] In this embodiment, according to the distribution of space debris at each altitude layer, the flight window set of each altitude layer is determined, specifically including: for each altitude layer, the following steps are performed: the center points of all space debris in the altitude layer are formed into a point set; the point set is segmented by using the Delaunay triangulation algorithm to obtain a spherical triangulation network, and the spherical triangulation network includes a plurality of spherical triangular units; for each spherical triangular unit, the center of the circumscribed circle of the spherical triangular unit is used as the center of the flight window corresponding to the spherical triangular unit, and the difference between the circumscribed circle radius of the spherical triangular unit and the maximum threat radius is used as the radius of the flight window corresponding to the spherical triangular unit, and the flight window corresponding to the spherical triangular unit is determined, and the maximum threat radius is the maximum value of the fixed threat radius of the space debris to which each vertex of the spherical triangular unit belongs; the flight windows corresponding to each spherical triangular unit are formed into a flight window set of the altitude layer. Based on this, according to the distribution of space debris at each altitude layer, the flight window set of each altitude layer can be determined, and the flight window set includes a plurality of flight windows, and the flight window is the area where the carrier rocket can pass.

[0091] In this embodiment, based on the flight window set of each altitude layer, a flight pipeline directed graph model is established, specifically including: taking the initial state, the flight window and the target orbit as nodes to form a directed node set, the node corresponding to the initial state is the initial state node, the node corresponding to the flight window is the flight window node, and the node corresponding to the target orbit is the target orbit node; connecting two nodes in the directed node set according to a preset connection rule to generate an edge, and forming all the edges into a directed edge set, the preset connection rule is: sorting the altitude layers in order from small to large in height, the initial state node is connected to the flight window node of the first altitude layer, the flight window node of each altitude layer is connected to the flight window node of the next altitude layer of the altitude layer, and the flight window node of the last altitude layer is connected to the target orbit node; the directed node set and the directed edge set form a flight pipeline directed graph model. Based on this, a flight pipeline directed graph model can be established based on the flight window set of each altitude layer. The flight pipeline directed graph model includes a directed node set and a directed edge set. The directed node set includes several nodes, and the nodes include initial state nodes, flight window nodes and target orbit nodes. The flight window nodes are nodes corresponding to the flight windows, and the directed edge set includes edges connecting two nodes in order of altitude.

[0092] (ii) Establish the optimal control problem of pipeline-trajectory integrated planning, corresponding to step S2.

[0093] Pipeline planning is a directed graph model of pipelines in flight G The optimal flight pipeline is searched in the pipeline, and trajectory planning is to generate a flight trajectory that satisfies the dynamic constraints and has the best fuel in the flight pipeline to complete the rocket's orbital mission. Pipeline planning and trajectory planning are mutually constrained: the pipeline planning process needs to consider the dynamic constraints and trajectory indicators of the launch vehicle to achieve the global optimization of the debris avoidance mission; trajectory planning needs to match the spatiotemporal flight pipeline constraints continuously output by pipeline planning to ensure the physical feasibility of the flight pipeline. Therefore, it is necessary to establish the optimal control problem of pipeline-trajectory integrated planning for debris avoidance.

[0094] Define the optimal control problem of pipeline-trajectory integrated planning as a directed graph model of a flying pipeline G The optimal flight pipeline is searched in the flight pipeline, and a flight trajectory that satisfies the dynamic constraints and has the best fuel is generated in the flight pipeline to complete the rocket orbital mission. G By establishing flight pipeline connectivity constraints and flight window constraints, the constraint relationship between the pipeline and the trajectory is characterized. Combined with rocket dynamics constraints, rocket initial constraints, rocket terminal orbit insertion constraints, rocket thrust direction constraints, flight window motion constraints, and fuel optimal indicators, a unified launch vehicle debris avoidance pipeline-trajectory integrated planning optimal control problem is obtained.

[0095] Pipeline planning requires additional decision variables to record the search of the flying pipeline. Define the binary integer variable =[ , , ..., ]∈{0,1} m-2 , =[ , , ..., ], i =1, 2, ..., n If the flight window node W ik is selected, then b ik =1, otherwise, b ik =0, k =1, 2, ..., M i The flight pipeline connectivity constraint can be written as shown in the following formula (22).

[0096] (twenty two).

[0097] Formula (22) indicates that at the altitude level H i There is only one flight window node on the flight pipeline. In formula (22), For the The total number of flight window nodes at each altitude level; To represent whether to select The altitude layer A binary integer variable for each flight window node; is the total number of altitude layers.

[0098] when b ik =1, the launch vehicle needs to be in the flight window W ik Internal crossing level H i , the flight trajectory needs to impose flight window constraints in the form shown in the following equations (23) and (24).

[0099] (twenty three).

[0100] (twenty four).

[0101] In the above formula, ( t )∈ , For the launch vehicle in time The position vector of For the launch vehicle to cross the Level H i time; For the The altitude layer Flight windows in time The center position vector of For the The altitude layer Flight windows in time The radius of is a large positive number, that is, a sufficiently large positive number; To represent whether to select The altitude layer A binary integer variable for each flight window node; For the The height of the altitude layer; is the average radius of the Earth.

[0102] According to formula (23), the flight window constraint is an inequality constraint in which one of the two conditions is applicable.

[0103] when b ik =1, formula (23) is equivalent to the following formula (25).

[0104] (25).

[0105] That is, the launch vehicle trajectory needs to enter the flight window W ik .

[0106] when b ik =0, formula (23) is equivalent to the following formula (26).

[0107] (26).

[0108] That is, the launch vehicle trajectory does not need to enter the flight window W ik .

[0109] On the basis of the flight pipeline connectivity constraints and flight window constraints, combined with rocket dynamics constraints, rocket initial constraints, rocket terminal orbit insertion constraints, rocket thrust direction constraints, flight window motion constraints, and fuel optimal indicators, the optimal control problem of launch vehicle debris avoidance pipeline-trajectory integrated planning can be modeled as follows, that is, the pipeline-trajectory integrated planning model is as follows.

[0110] (27).

[0111] (28).

[0112] (29).

[0113] (30).

[0114] (31).

[0115] (32).

[0116] (33).

[0117] (34).

[0118] (35).

[0119] (36).

[0120] (37).

[0121] In the above formula, is the objective function; is the target value; Terminal time for launch vehicle quality; , , is the rocket dynamics constraint; ( t )∈ , For the launch vehicle in time The first derivative of the position vector; ( t )∈ , For the launch vehicle in time The velocity vector of For the launch vehicle in time The first derivative of the velocity vector; ∈ , is the position vector The gravitational acceleration vector at ; T ∈ , is the engine thrust; ∈ , For time The direction of engine thrust; m L ( t )∈ , For the launch vehicle at time quality; For the launch vehicle at time The first derivative of the mass of V ex ∈ , is the engine exhaust velocity; is the initial constraint of the rocket; The launch vehicle at the initial time The position vector of is the initial position vector; The launch vehicle at the initial time The velocity vector of is the initial velocity vector; The launch vehicle at the initial time quality; is the initial mass; A compact form constrained for rocket terminal orbit insertion; ∈ , is the terminal orbit constraint function, specifically including the semi-major axis a f , eccentricity e f , orbital inclination i f , right ascension of ascending node Ω f and the argument of perigee ω f The terminal orbit constraint function; Terminal time for launch vehicle The position vector of Terminal time for launch vehicle The velocity vector of It is the thrust direction constraint of the rocket; is a compact form of the flight window motion constraint, which is a compact form of the space debris motion equation (i.e., equation (1)) and the flight window motion equation (i.e., equation (8) and equation (9)). ( t )and d ( t ) is calculated by formula (1), that is, the specific expressions of the flight window motion constraint are formula (1), formula (8) and formula (9); For space debris and flight windows in time The first derivative of the variable of motion; is the motion constraint function; For space debris and flight windows in time The motion variables, ; is the compact form of the flight pipeline connectivity constraint, which is the compact form of formula (22), that is, the specific expression of the flight pipeline connectivity constraint is formula (22); is the connectivity constraint function; is a binary integer variable representing whether the flight window node is selected; , is a compact form of the flight window constraint, is a compact form of the first constraint, is a compact form of the second constraint, which is a compact form of equations (23) and (24), that is, the specific expressions of the flight window constraint are equations (23) and (24), the specific expression of the first constraint is equation (23), and the specific expression of the second constraint is equation (24); is the flight window constraint function; For the launch vehicle at time The position vector of For the launch vehicle to cross the The time for each altitude level; For the The flight window for the altitude layer is within the time The center position vector of For the The flight window for the altitude layer is within the time The radius of To represent whether to select A binary integer variable representing the flight window node for each altitude level; is the total number of altitude layers; For the The height of the altitude layer; is the average radius of the Earth.

[0122] According to equations (27) to (37), the pipeline-trajectory integrated planning model is a nonlinear mixed integer optimal control problem. The variables to be planned include ( t ), , h , t f .

[0123] (iii) Design a pipeline-trajectory integrated planning algorithm based on mixed integer second-order cone programming, corresponding to step S3.

[0124] Through relaxation, equivalent linearization, sequence linearization and normalized duration processing, and using Gaussian pseudo-spectral method for discretization, the pipeline-trajectory integrated planning optimal control problem is transformed into a mixed integer second-order cone programming subproblem. By iteratively solving a series of mixed integer second-order cone programming subproblems, the solution obtained in the previous iteration is used as the reference trajectory for the next iteration until the sequence converges, and the global convergence of the algorithm is improved by designing the neighboring operator, and the flight pipeline and flight trajectory with global fuel optimal debris avoidance are obtained.

[0125] Note that according to equation (34), the center position vector of the space debris is d ( t ) and the velocity vector d ( t ), the center position vector of the flight window w ( t ) and radius R w ( t ) is independent of the variables to be planned and becomes a deterministic function of time. Therefore, the flight window motion constraint described in equation (34) can be eliminated and w ( t )and R w ( t ) is substituted into formula (36) as a known quantity to simplify the problem structure and reduce the problem scale, which is conducive to theoretical analysis.

[0126] (1) Lossless relaxation of thrust direction constraints.

[0127] Equation (33) can be relaxed to the second-order cone constraint shown in equation (38).

[0128] (38).

[0129] In formula (38), For time The direction of engine thrust.

[0130] And the relaxed problem is equivalent to the optimal control problem of pipeline-trajectory integrated planning.

[0131] (2) Equivalent linearization of point equality constraints within the flight window.

[0132] Formula (23) can be equivalently written as the constraint shown in the following formula (39).

[0133] (39).

[0134] Since for anyi =1, 2, ..., n , flight window W ik ∈ W i At the same altitude level, and the track height is h i , k =1, 2, ..., M i , according to formula (24), we can get the following formula (40).

[0135] (40).

[0136] Substituting equation (40) into equation (39), we can obtain the following equation (41).

[0137] (41).

[0138] Therefore, in the optimal control problem of pipeline-trajectory integrated planning, Equation (36) can be equivalently written as the compact form shown in the following Equation (42).

[0139] (42).

[0140] In formula (42), is the first compact function; is the second most compact function.

[0141] remember is the multiplier vector corresponding to the inequality constraint (i.e., Equation (41)), =[ 1, 2, ..., n ] T , =[ , , ..., ],when b ik =0, η ik =0; when b ik =1, η ik ≥0, equation (41) degenerates into the following equation (43).

[0142] (43).

[0143] And when equation (43) is positive, η ik>0, equation (43) can be transformed into the following interior point equality constraint.

[0144] (44).

[0145] In formula (44), For the The altitude layer Flight windows in time The center position vector of For the launch vehicle to cross the The time for each altitude level; For the launch vehicle at time The position vector of For the The altitude layer Flight windows in time The radius of .

[0146] Note that according to formula (22), there is only one k ∈{1, 2, ..., M i},satisfy b ik =1, so in the pipeline-trajectory integrated planning optimal control problem, there is only n The trajectory is divided into n +1 stage, one stage for each altitude layer.

[0147] (3) Sequential linearization of equations of motion and non-convex constraints.

[0148] The sequence linearization technique is used to estimate the non-convex rocket dynamic constraints (i.e., Equations (28) to (30)), the rocket terminal orbit insertion constraint (i.e., Equation (32)) and the second constraint (i.e., Equation (37)), and the following Equations (45) to (47) are obtained.

[0149] (45).

[0150] (46).

[0151] (47).

[0152] In the above formula, =[ T , T , m L ] T is the state quantity; L Depend on i , i , m L The differential equations of (p) =[ (p)T , (p )T , m L (p) ] T , (p) Based on p The reference trajectory obtained by the iterative solution is determined; is the control quantity, which is the direction of engine thrust; f , f , ψ , ψ is the Jacobian matrix. Specifically, is the first-order derivative of the state quantity; is a system of differential equations; Based on The state quantity determined by the reference trajectory obtained by the iteration; Based on The control quantity determined by the reference trajectory obtained by the iteration; is the first Jacobian matrix; is the state quantity; is the second Jacobian matrix; To control the amount; is the terminal orbit constraint function; Based on The reference trajectory obtained by the iterations determines the launch vehicle at the terminal time The position vector of Based on The reference trajectory obtained by the iterations determines the launch vehicle at the terminal time The velocity vector of is the third Jacobian matrix; Terminal time for launch vehicle The position vector of is the fourth Jacobian matrix; Terminal time for launch vehicle The velocity vector of Based on The reference trajectory obtained by the iterations determines the launch vehicle at time The position vector of For the launch vehicle to cross the The time for each altitude level; For the launch vehicle in time The position vector of For the The height of the altitude layer; is the average radius of the Earth.

[0153] (4) Duration of the normalization phase.

[0154] Since the time at the inner point t h = [ t 1, t 2, ..., t n ] and terminal time t f All are free, making it difficult to further discretize the optimal control problem of pipeline-trajectory integrated planning. n The internal points are segmentation points, and multiple stages are divided. Then the flight window constraint (i.e., equations (36) and (37)) can be regarded as the previous n The terminal constraints of each stage are met, and the state quantity and the control quantity have connection constraints, as shown in the following formula (48).

[0155] (48).

[0156] In formula (48), t i - , t i + are the terminal time of the previous stage and the initial time of the next stage, respectively. i =1, 2, ..., n .

[0157] The duration of the variable phase to be planned is defined as follows (49).

[0158] (49).

[0159] In formula (49), For the The duration of the phase, For the stage moment, For the stage moment, t n+1 = t f , theni The equation of motion for the stage launch vehicle can be rewritten as follows: τ ∈[0, 1].

[0160] (50).

[0161] In formula (50), i =[ i T , i T , m Li ] T For the i The state quantity of the stage, i For the i The control quantity of the stage. At this time, equation (45) can be rewritten as equation (51).

[0162] (51).

[0163] In formula (51), For the The first-order derivative of the state quantity of the stage, ’ fi , ’ fi , fi is the Jacobian matrix after time planning; fi is the parameter item related to the reference trajectory; i (p) =[ i (p)T , i (p)T , m Li (p) ] T , i (p) , T i (p) For the p The iterative solution is i The reference trajectory of the stage, i =1, 2, ..., n +1.

[0164] In addition, the stage duration must meet the following constraints.

[0165] (52).

[0166] (53).

[0167] In the above formula, T max is the maximum flight time.

[0168] Note that due to the addition of new planning variables T= [ T 1, T 2, ..., T n+1 ], which increases the nonlinearity of the rocket motion equation and may cause iterative convergence difficulties. To this end, the neighboring operator is designed κ Satisfies the following formula (54).

[0169] (54).

[0170] In formula (54), is the planning variable; Based on The planning variables are determined by the reference trajectory obtained by the iteration; is the neighboring operator.

[0171] The objective function can be converted into the following formula (55).

[0172] (55).

[0173] In formula (55), ξ is the neighbor term coefficient.

[0174] (5) Sequential mixed integer second-order cone programming algorithm.

[0175] The Gaussian pseudospectral method is used to discretize the optimal control problem of pipeline-trajectory integrated planning. The number of discrete points is O , the discretized variables to be planned are =[ , , ..., ] T =[ , , ], =[ , , ..., ] T ,in, =[ , , ..., ] T , =[ , , ..., ] T , =[ , , ..., ] T , the normalized time after discretization is =[ , , ..., ] T ,in, =0, = 1. The compact form of the right side of equation (45) is the function , the equation of motion at the discrete point =[ , , ..., ] T ,in, , j =1, 2, ..., O , i =1, 2, ..., n +1, then equation (51) can be transformed into the following discretized form.

[0176] (56).

[0177] In formula (56), x and y is a constant related to the Gaussian pseudospectral method.

[0178] The pipeline-trajectory integrated planning optimal control problem is discretized into the following mixed integer second-order cone programming subproblems, that is, the mixed integer second-order cone programming model is as follows.

[0179] (57).

[0180] (58).

[0181] (59).

[0182] (60).

[0183] (61).

[0184] (62).

[0185] (63).

[0186] (64).

[0187] In the above formula, formula (59) is the discretized rocket initial constraint, formula (60) is the compact form of formula (46) after discretization, the first term of formula (61) is the compact form of formula (44) after discretization, the second term of formula (61) is the discretized flight window connectivity constraint, formula (62) is the compact form of formula (47) after discretization, formula (63) is the compact form of formula (38) after discretization, and formula (64) is the discretized stage duration constraint and neighboring operator constraint. Among them, is the target value; For the launch vehicle The quality of the last discrete point of the stage; is the coefficient of the neighboring term; is the neighboring operator; is the first constant associated with the Gaussian pseudospectral method; For the The state quantity of the stage; is the second constant associated with the Gaussian pseudospectral method; For the Equations of motion for the phases; is the total number of altitude layers; is the state quantity of the first discrete point in the first stage; is the initial state quantity; For the The state quantity of the last discrete point of the stage; For the The state quantity of the first discrete point in the stage; For the The control quantity of the last discrete point of the stage; For the The control quantity of the first discrete point in the stage; is the third Jacobian matrix; For the launch vehicle The position vector of the last discrete point in the stage; is the fourth Jacobian matrix; For the launch vehicle The velocity vector of the last discrete point of the stage; is the fifth Jacobian matrix; For the The value of the first compact function in the stage; For the launch vehicle The position vector of the last discrete point in the stage; For the The value of the second compact function in stage; is a large positive number; To represent whether to select A binary integer variable representing the flight window node for each altitude level; is the connectivity constraint function; is a binary integer variable representing whether the flight window node is selected; For the The value of the third compact function of the stage, which is a compact function in the compact form of equation (47); For the The value of the fourth compact function of stage 4, which is another compact function in the compact form of equation (47); For the Phase I The control quantity of discrete points; is the total number of discrete points; For the The duration of the phase; is the maximum flight time; is the planning variable; Based on The planning variables are determined by the reference trajectory obtained by the iteration; is the neighboring operator.

[0188] This embodiment requires calculating the center position vector of the space debris at the discrete point dij and the velocity vector dij , flight window center position vector wij and radius R wij , the motion trajectory of space debris and flight window can be obtained offline through equation (34). When used, the discrete point moment is found based on linear interpolation. The value at j =1, 2, ..., O , i =1, 2, ..., n +1.

[0189] It can be seen that Equation (57) to Equation (64) is a mixed integer second-order cone programming subproblem (abbreviated as MISOCP), as Figure 4 As shown, the MISOCP problem can be solved iteratively, and the solution obtained in the previous iteration is used as the reference trajectory for the next iteration. i (p) , i (p) , T i (p) , until the sequence converges, thus approaching the solution to the optimal control problem of pipeline-trajectory integrated planning. Among them, the mixed integer second-order cone programming subproblem is solved by the solver MOSEK, and the converged solution is the optimal solution, i =1, 2, ..., n +1.

[0190] In this embodiment, the pipeline-trajectory integrated planning model is optimized and solved to obtain the optimal flight pipeline and flight trajectory, which specifically includes: converting the pipeline-trajectory integrated planning model to obtain a mixed integer second-order cone programming model; optimizing and solving the mixed integer second-order cone programming model to obtain the optimal flight pipeline and flight trajectory.

[0191] Among them, the pipeline-trajectory integrated planning model is transformed to obtain a mixed integer second-order cone programming model, which specifically includes: relaxing the rocket thrust direction constraint to obtain a lossless relaxed thrust direction constraint (i.e., formula (38)); equivalently linearizing the first constraint to obtain an equivalent linearized flight window interior point equality constraint (i.e., formula (44)); sequentially linearizing the rocket dynamics constraint, the rocket terminal orbit constraint and the second constraint to obtain a sequential linearized dynamics constraint (i.e., formula (45)), a sequential linearized terminal orbit constraint (i.e., formula (46)) and a sequential linearized second constraint (i.e., formula (47)); normalizing the sequential linearized dynamics constraint to obtain a normalized duration dynamics constraint (i.e., formula (51)), and designing the stage duration constraint (i.e., formula (52)). Equations (52) and (53)); the objective function is processed by the neighboring operator to obtain the neighboring objective function (i.e., Equation (55)), and the neighboring operator constraint is designed (i.e., Equation (54)); the neighboring objective function, normalized duration dynamics constraint, sequence linearization terminal orbit constraint, lossless relaxation thrust direction constraint, equivalent linearization flight window interior point equality constraint and sequence linearization second constraint are used to replace the objective function, rocket dynamics constraint, rocket terminal orbit constraint, rocket thrust direction constraint, first constraint and second constraint in the pipeline-trajectory integrated planning model, and the stage duration constraint and the neighboring operator constraint are introduced into the pipeline-trajectory integrated planning model to obtain the converted model; the Gaussian pseudospectral method is used to discretize the converted model to obtain a mixed integer second-order cone programming model.

[0192] Among them, the mixed integer second-order cone programming model is optimized and solved to obtain the optimal flight pipeline and flight trajectory, which specifically includes: initially generating a reference trajectory; taking the reference trajectory as input, optimizing and solving the mixed integer second-order cone programming model to obtain the flight pipeline and flight trajectory of the current iteration; judging whether the iteration termination condition is met; if not, taking the flight trajectory of the current iteration as the reference trajectory of the next iteration, and returning to the step of "taking the reference trajectory as input, optimizing and solving the mixed integer second-order cone programming model to obtain the flight pipeline and flight trajectory of the current iteration"; if so, taking the flight pipeline and flight trajectory of the current iteration as the optimal flight pipeline and flight trajectory.

[0193] The iteration termination condition can be that the neighboring operator is less than the preset value .

[0194] The current active avoidance strategy requires an initial guess trajectory, but due to the principle of local optimization, the selection of the initial guess trajectory directly affects the performance of the final generated trajectory and does not have global optimality. This embodiment establishes a new flight pipeline directed graph model, including flight window modeling and connectivity modeling, to achieve the construction of a global search model for the launch vehicle debris avoidance strategy. Based on the flight pipeline directed graph model, the coupling relationship between pipeline planning and trajectory planning is analyzed, and a pipeline-trajectory integrated planning optimal control problem with fuel optimization as the performance indicator is established to solve the local optimality of the continuous trajectory planning method. At the same time, an iterative mixed integer second-order cone programming algorithm is designed to solve the pipeline-trajectory integrated planning optimal control problem. The efficient solution of the problem is achieved through sequence convexification, and the global convergence of the algorithm is enhanced by adding neighboring operators, so that the obtained trajectory performance does not depend on the selection of the initial guess trajectory.

[0195] This embodiment proposes a new pipeline-trajectory integrated planning model and designs a sequential mixed integer second-order cone programming algorithm to achieve iterative solution, aiming to generate a trajectory that meets orbital accuracy, debris avoidance and global fuel optimization.

[0196] The present application also provides an application scenario, which applies the above-mentioned launch vehicle debris avoidance pipeline-trajectory integrated planning method. Specifically, the launch vehicle debris avoidance pipeline-trajectory integrated planning method provided in this embodiment can be applied in a rocket operation scenario. The rocket operation scenario includes a planning link and an operation link. The planning link is used to simultaneously plan the flight pipeline and the flight trajectory, and the operation link is used to control the launch vehicle to fly according to the planned flight pipeline and flight trajectory. The launch vehicle debris avoidance pipeline-trajectory integrated planning method provided in this embodiment belongs to the planning link.

[0197] Example 2.

[0198] This embodiment provides a computer device, which may be a server or a terminal. Its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, 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, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a launch vehicle debris avoidance pipeline-trajectory integrated planning method is implemented.

[0199] Those skilled in the art will understand that Figure 5 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 those shown in the figure, or combine certain components, or have a different arrangement of components.

[0200] In an exemplary 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 launch vehicle debris avoidance pipeline-trajectory integrated planning method in Example 1 is implemented.

[0201] Example 3.

[0202] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which, when executed by a processor, implements the launch vehicle debris avoidance pipeline-trajectory integrated planning method in Example 1.

[0203] The technical features of the above embodiments may 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.

[0204] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A launch vehicle debris avoidance pipeline-trajectory integrated planning method, characterized in that: The launch vehicle debris avoidance pipeline-trajectory integrated planning method comprises: According to the distribution of space debris at each altitude layer, a flight window set at each altitude layer is determined, and based on the flight window set at each altitude layer, a flight pipeline directed graph model is established; the flight window set is a flight window set consisting of flight windows corresponding to each spherical triangle unit in a spherical triangulation network including multiple spherical triangle units obtained by segmenting a point set consisting of the center points of all space debris in each altitude layer using a Delaunay triangulation algorithm; the flight window set includes a plurality of flight windows, and the flight window is an area through which a launch vehicle can pass; the flight pipeline directed graph model includes a directed node set and a directed edge set, the directed node set includes a plurality of nodes, the nodes include an initial state node, a flight window node and a target orbit node, the flight window node is a node corresponding to the flight window, and the directed edge set includes an edge connecting two nodes in order of altitude; Based on the flight pipeline directed graph model, a pipeline-trajectory integrated planning model is constructed; the pipeline-trajectory integrated planning model takes fuel optimization as the optimization goal, and takes rocket dynamics constraints, rocket initial constraints, rocket terminal orbit constraints, rocket thrust direction constraints, flight window motion constraints, flight pipeline connectivity constraints and flight window constraints as constraints; The pipeline-trajectory integrated planning model is optimized and solved to obtain the optimal flight pipeline and flight trajectory; the flight pipeline is a traversable path from the initial state node to the target orbit node in the flight pipeline directed graph model; the flight trajectory is the flight path of the launch vehicle in the flight pipeline.

2. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 1, characterized in that: The method for determining the flight window corresponding to the spherical triangle unit includes: taking the center of the circumscribed circle of the spherical triangle unit as the center of the flight window corresponding to the spherical triangle unit, and taking the difference between the radius of the circumscribed circle of the spherical triangle unit and the maximum threat radius as the radius of the flight window corresponding to the spherical triangle unit, to determine the flight window corresponding to the spherical triangle unit; the maximum threat radius is the maximum value of the fixed threat radius of the space debris to which each vertex of the spherical triangle unit belongs.

3. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 1, characterized in that: Based on the flight window set of each altitude layer, a flight pipeline directed graph model is established, including: The initial state, flight window and target track are all taken as nodes to form a directed node set; the node corresponding to the initial state is the initial state node, the node corresponding to the flight window is the flight window node, and the node corresponding to the target track is the target track node; Connect two nodes in the directed node set according to a preset connection rule to generate edges, and form all the edges into a directed edge set; the preset connection rule is: sort the altitude layers in order from low to high, the initial state node is connected to the flight window node of the first altitude layer, the flight window node of each altitude layer is connected to the flight window node of the next altitude layer of the altitude layer, and the flight window node of the last altitude layer is connected to the target orbit node; The directed node set and the directed edge set are combined into a flight pipeline directed graph model.

4. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 1, characterized in that: The pipeline-trajectory integrated planning model is: ； ； ； ； ； ； ； ； ； ； ； in, is the objective function; is the target value; Terminal time for launch vehicle quality; , , is the rocket dynamics constraint; For the launch vehicle at time The first derivative of the position vector; For the launch vehicle at time The velocity vector of For the launch vehicle at time The first derivative of the velocity vector; is the position vector The gravitational acceleration vector at ; is the engine thrust; For time The direction of engine thrust; For the launch vehicle at time quality; For the launch vehicle at time The first derivative of the mass of is the engine exhaust velocity; is the initial constraint of the rocket; The launch vehicle at the initial time The position vector of is the initial position vector; The launch vehicle at the initial time The velocity vector of is the initial velocity vector; The launch vehicle at the initial time quality; is the initial mass; A compact form constrained for rocket terminal orbit insertion; is the terminal orbit constraint function; Terminal time for launch vehicle The position vector of Terminal time for launch vehicle The velocity vector of It is the thrust direction constraint of the rocket; A compact form of motion constraints for flying windows; For space debris and flight windows in time The first derivative of the variable of motion; is the motion constraint function; For space debris and flight windows in time The motion variables; A compact form of the connectivity constraints for the flight ducts; is the connectivity constraint function; is a binary integer variable representing whether the flight window node is selected; , is a compact form of the flight window constraint, is a compact form of the first constraint, is the compact form of the second constraint; is the flight window constraint function; For the launch vehicle at time The position vector of For the launch vehicle to cross the The time for each altitude level; For the The flight window for the altitude layer is within the time The center position vector of For the The flight window for the altitude layer is within the time The radius of To represent whether to select A binary integer variable representing the flight window node for each altitude level; is the total number of altitude layers; For the The height of the altitude layer; is the average radius of the Earth; The specific expression of the flight window motion constraint is: ； ； ； in, For the The altitude layer Space debris in time The first derivative of the central position vector of ; For the The altitude layer Space debris in time The central velocity vector of For the The altitude layer Space debris in time The first derivative of the central velocity vector; for The gravitational acceleration vector at , For the The altitude layer Space debris in time The center position vector of For the The altitude layer Flight windows in time The first derivative of the central position vector of ; For the The altitude layer Flight windows in time The central velocity vector of Respectively The altitude layer Three space debris corresponding to the flight window; is the first spherical triangle function; For the The altitude layer Flight windows in time The first derivative of the central velocity vector; For the The altitude layer Flight windows in time The central acceleration vector of For the The altitude layer Space debris in time The center position vector of For the The altitude layer Flight windows in time The first derivative of the radius; For the The altitude layer Flight windows in time The rate of change of the radius; is the second spherical triangle function; For the The altitude layer Flight windows in time The first derivative of the rate of change of the radius; For the The altitude layer Flight windows in time The second derivative of the rate of change of the radius; The specific expression of the flight pipeline connectivity constraint is: ； in, For the The total number of flight window nodes at each altitude level; To represent whether to select The altitude layer A binary integer variable for each flight window node; is the total number of altitude layers; The specific expression of the flight window constraint is: ； ； in, For the launch vehicle at time The position vector of For the launch vehicle to cross the The time for each altitude level; For the The altitude layer Flight windows in time The center position vector of For the The altitude layer Flight windows in time The radius of is a large positive number; To represent whether to select The altitude layer A binary integer variable for each flight window node; For the The height of the altitude layer; is the average radius of the Earth.

5. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 4, characterized in that: The pipeline-trajectory integrated planning model is optimized and solved to obtain the optimal flight pipeline and flight trajectory, specifically including: Converting the pipeline-trajectory integrated planning model to obtain a mixed integer second-order cone programming model; The mixed integer second-order cone programming model is optimized and solved to obtain the optimal flight pipeline and flight trajectory.

6. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 5, characterized in that: The pipeline-trajectory integrated planning model is converted to obtain a mixed integer second-order cone programming model, which specifically includes: The rocket thrust direction constraint is relaxed to obtain a lossless relaxed thrust direction constraint; Performing equivalent linearization processing on the first constraint to obtain an equivalent linearized flight window interior point equality constraint; The rocket dynamics constraint, the rocket terminal orbit insertion constraint and the second constraint are sequentially linearized to obtain sequential linearized dynamics constraint, sequential linearized terminal orbit insertion constraint and sequential linearized second constraint; Perform normalized duration processing on the sequence linearized dynamic constraints to obtain normalized duration dynamic constraints, and design the stage duration constraints; The objective function is processed by using the proximity operator to obtain the proximity objective function, and the proximity operator constraint is designed; Respectively replacing the objective function, rocket dynamics constraint, rocket terminal orbit constraint, rocket thrust direction constraint, first constraint and second constraint in the pipeline-trajectory integrated planning model with the neighboring objective function, normalized duration dynamics constraint, sequence linearization terminal orbit constraint, lossless relaxation thrust direction constraint, equivalent linearization flight window interior point equality constraint and sequence linearization second constraint, and introducing the stage duration constraint and the neighboring operator constraint into the pipeline-trajectory integrated planning model to obtain a converted model; The converted model is discretized using Gaussian pseudospectral method to obtain a mixed integer second-order cone programming model.

7. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 6, characterized in that: The lossless relaxation thrust direction constraint is: ； in, For time The direction of engine thrust; The equivalent linearized flight window internal point equality constraint is: ； in, For the The altitude layer Flight windows in time The center position vector of For the launch vehicle to cross the The time for each altitude level; For the launch vehicle in time The position vector of For the The altitude layer Flight windows in time The radius of The sequential linearized dynamics constraints are: ； in, is the first-order derivative of the state quantity; is a system of differential equations; Based on The state quantity determined by the reference trajectory obtained by the iteration; Based on The control quantity determined by the reference trajectory obtained by the iteration; is the first Jacobian matrix; is the state quantity; is the second Jacobian matrix; To control the amount; The sequence linearization terminal orbit constraint is: ； in, is the terminal orbit constraint function; Based on The reference trajectory obtained by the iterations determines the launch vehicle at the terminal time The position vector of Based on The reference trajectory obtained by the iterations determines the launch vehicle at the terminal time The velocity vector of is the third Jacobian matrix; Terminal time for launch vehicle The position vector of is the fourth Jacobian matrix; Terminal time for launch vehicle The velocity vector of The second constraint of sequence linearization is: ； in, Based on The reference trajectory obtained by the iterations determines the launch vehicle at time The position vector of For the launch vehicle to cross the The time for each altitude level; For the launch vehicle in time The position vector of For the The height of the altitude layer; is the average radius of the Earth; The normalized duration dynamics constraint is: ； in, For the The first-order derivative of the state quantity of the stage; is the first Jacobian matrix after time planning; For the The state quantity of the stage; is the second Jacobian matrix after time planning; For the The amount of control in the stage; is the third Jacobian matrix after time planning; For the The duration of the phase, , For the stage moment, For the stage moments; is the parameter item related to the reference trajectory; The phase duration constraints are: ； ； in, For the the duration of the phase; is the total number of altitude layers; is the maximum flight time; The neighboring operator constraints are: ； in, is the planning variable; Based on The planning variables are determined by the reference trajectory obtained by the iteration; is the neighboring operator; The mixed integer second-order cone programming model is: ； ； ； ； ； ； ； ； in, is the target value; For the launch vehicle The quality of the last discrete point of the stage; is the coefficient of the neighboring term; is the neighboring operator; is the first constant associated with the Gaussian pseudospectral method; For the The state quantity of the stage; is the second constant associated with the Gaussian pseudospectral method; For the Equations of motion for the phases; is the total number of altitude layers; is the state quantity of the first discrete point in the first stage; is the initial state quantity; For the The state quantity of the last discrete point of the stage; For the The state quantity of the first discrete point in the stage; For the The control quantity of the last discrete point of the stage; For the The control quantity of the first discrete point in the stage; is the third Jacobian matrix; For the launch vehicle The position vector of the last discrete point in the stage; is the fourth Jacobian matrix; For the launch vehicle The velocity vector of the last discrete point of the stage; is the fifth Jacobian matrix; For the The value of the first compact function in the stage; For the launch vehicle The position vector of the last discrete point in the stage; For the The value of the second compact function in stage; is a large positive number; To represent whether to select A binary integer variable representing the flight window node for each altitude level; is the connectivity constraint function; is a binary integer variable representing whether the flight window node is selected; For the The value of the third compact function in stage; For the The value of the fourth compact function in stage; For the Phase I The control quantity of discrete points; is the total number of discrete points; For the the duration of the phase; is the maximum flight time; is the planning variable; Based on The planning variables are determined by the reference trajectory obtained by the iteration; is the neighboring operator.

8. The launch vehicle debris avoidance pipeline-trajectory integrated planning method according to claim 5, characterized in that: The mixed integer second-order cone programming model is optimized and solved to obtain the optimal flight pipeline and flight trajectory, specifically including: Initially generate reference trajectory; Taking the reference trajectory as input, optimizing and solving the mixed integer second-order cone programming model to obtain the flight pipeline and flight trajectory of the current iteration; Determine whether the iteration termination condition is reached; If not, the flight trajectory of the current iteration is used as the reference trajectory of the next iteration, and the process returns to the step of "using the reference trajectory as input, optimizing and solving the mixed integer second-order cone programming model, and obtaining the flight pipeline and flight trajectory of the current iteration"; If so, the flight pipeline and flight trajectory of the current iteration are used as the optimal flight pipeline and flight trajectory.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the launch vehicle debris avoidance pipeline-trajectory integrated planning method as described in any one of claims 1 to 8.

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 launch vehicle debris avoidance pipeline-trajectory integrated planning method described in any one of claims 1-8 is implemented.

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