CN108153332A - Trace simulation system based on big envelope curve game strategies - Google Patents

Abstract

The invention relates to the field of automatic control of aircraft, and proposes a trajectory simulation system method based on a large envelope game strategy, aiming to solve the problem of rapid estimation of the maneuvering decision-making strategy and trajectory of the flight device. The system includes: a situation awareness and decision-making module configured to obtain flight The attitude data of the device, and select different tactical tasks according to the above attitude data; the abnormality management module is configured to switch the flight task of the above-mentioned flying device according to the attitude data of the above-mentioned flying device and various preset maneuvering missions; the real-time maneuvering module configuration In order to calculate the control of each flight sub-action of the above-mentioned flying device in flight according to the above-mentioned attitude data and the flight trajectory, the formation of the target attitude and the target trajectory and the target trajectory calculation module are configured to perform the above-mentioned target attitude and the above-mentioned target trajectory using a multi-degree-of-freedom equation. Solve the calculation to realize the output of the target trajectory of the above-mentioned flying device; realize the rapid estimation of the maneuvering decision-making strategy of the flying device and its trajectory.

Description

Trajectory Simulation System Based on Large Envelope Game Strategy

technical field

The invention relates to the technical field of automatic control, in particular to aircraft flight trajectory prediction, in particular to a trajectory simulation system based on a large envelope game strategy.

Background technique

The flight envelope is a closed geometric figure bounded by flight speed, altitude and overload, which is used to represent the flight range and flight restrictions of an aircraft or aircraft. With the development of unmanned aerial vehicle technology, its functions are becoming more and more powerful, and the scope of use is expanding, making the flight envelope larger and larger. Usually flying in the atmosphere (within 20,000 meters) and near the edge of the atmosphere, the flight speed changes greatly, and there are active maneuvering strategies. In order to predict the behavior of this type of target, it is necessary to quickly simulate its game maneuvering decision-making behavior within the large envelope to predict its future trajectory.

At present, due to the flexible maneuvering flight strategy of intelligent aircraft, its flight trajectory changes in different ways due to different flight environments. In the game confrontation, the opponent needs to track and monitor the intelligent aerial vehicle, and expects to predict its trajectory in order to provide a basis for subsequent actions. Therefore, there is a need for a maneuvering decision-making strategy and a fast simulation method for the trajectory prediction of intelligent aircraft in the large-envelope game in order to predict the behavior and trajectory of the aircraft.

Contents of the invention

In order to solve the above problems in the prior art, that is, in order to solve the problem of quickly predicting the flight maneuver strategy and trajectory of the aircraft in the aircraft confrontation game, this application proposes a trajectory simulation system based on the large envelope game strategy to solve The above question:

In the first aspect, the present invention provides a trajectory simulation system based on a large envelope game strategy. The system includes: a situational awareness and decision-making module, an abnormality management module, a real-time maneuvering flight module, and a target trajectory calculation module; the above-mentioned situational awareness and decision-making module is configured to obtain the attitude data of the flying device, and select different tactics according to the above-mentioned attitude data Task; the above-mentioned abnormal management module is configured to switch the flight task of the above-mentioned flying device according to the attitude data of the above-mentioned flying device and the trigger conditions of various preset tactical tasks; the above-mentioned real-time flight module is configured to calculate according to the above-mentioned attitude data and flight trajectory The control of each flight sub-action of the above-mentioned flying device in flight forms a target attitude and a target trajectory; the above-mentioned target trajectory calculation module is configured to solve the above-mentioned target attitude and the above-mentioned target trajectory by using a multi-degree-of-freedom mechanical model and a motion equation, The output of the target trajectory of the above-mentioned flying device is realized.

In some examples, the aforementioned situational awareness and decision-making module includes: a situational awareness sub-module, a tactical decision-making sub-module, and a route planning sub-module, wherein the aforementioned situational awareness sub-module is configured to obtain the attitude data of the flying device, and determine according to the aforementioned attitude data The flight situation of the flying device; the above-mentioned tactical decision-making submodule is configured to determine the tactical task of the above-mentioned flying device according to the above-mentioned flight situation by using preset trigger conditions and priority calculations; The emergency flight route calculates the maneuver switching conditions of the above maneuver missions and the planning of tactical missions.

In some examples, the tactical submodule selects any of the following flight tactics from the tactical tasks according to preset trigger conditions and priority calculations: escape flight tactics, emergency maneuver avoidance tactics and normal flight tactics.

In some examples, the above route planning sub-module is further configured to implement the planning of the above maneuver switching conditions and tactical tasks through the A* algorithm by using planning constraints.

In some examples, the above abnormal management module includes a management scheduling submodule and a state estimation submodule, wherein the above management scheduling submodule is configured to perform typical fault and flight abnormal management on the flight mission according to the maneuver flight mission and attitude data, and or Realize the start, stop, and switch of flight tasks; the above-mentioned state estimation sub-module is configured to detect the operating conditions and abnormal motion of the target motion, and monitor and evaluate typical faults of the flight device according to the detection results.

In some examples, the real-time flight module includes a layered mode management submodule, an interface normalization submodule, and an instruction generation submodule, wherein the layered mode management submodule is configured to adopt a layered maneuver flight task The library controls the switching conditions, state monitoring and state transition management between the flight sub-actions; the above-mentioned interface normalization sub-module is configured to calculate the flying device according to the attitude parameters and the parameters related to the flight of the above-mentioned flying device detected by the sensor. load to form a unified target motion control input interface; the above command generation sub-module is configured to calculate the control parameters of different flight sub-actions and the switching relationship between sub-actions according to different flight trajectories.

In some examples, the above-mentioned multi-degree-of-freedom equation is used to solve the above-mentioned target attitude and the above-mentioned target trajectory to realize the output of the target trajectory, including: according to the target speed, trajectory inclination angle, trajectory yaw angle, and geographic location coordinates The multi-degree-of-freedom target motion dynamics model of state variables solves the above target trajectory:

Among them, V, x, y, z, θ, ψ, φ, n _x , n _z , g are in turn the velocity of the center of mass axis to the ground, the ground coordinates (x longitudinal distance, y lateral distance, z height), and track inclination angle , trajectory deflection angle, roll angle around velocity vector, tangential overload, normal overload and gravitational acceleration.

The above-mentioned use of multi-degree-of-freedom equations to solve the above-mentioned target attitude and the above-mentioned trajectory to realize the output of the target trajectory also includes the method of converting plane coordinates to spherical coordinates, converting the geographic coordinates XYZ obtained by the six-degree-of-freedom motion equation into earth coordinates Department of longitude, latitude, altitude.

The above-mentioned multi-degree-of-freedom equation is used to solve the above-mentioned target attitude and the above-mentioned trajectory to realize the output of the target trajectory, including: using the Euler method or the second-order interpolation calculation method, and using different interpolation frame rates to perform interpolation calculations on the target parameters. Frame rate target trajectory output.

In the trajectory simulation system based on the large envelope game strategy provided by the embodiment of the present application, the situation awareness and decision-making module of the system selects flight tactics through the attitude of the flight device; the abnormal management module is used to switch flight tasks; the real-time flight module is used to form the flight device The target attitude and target trajectory, the target trajectory calculation module realizes the data display of the target trajectory, realizes the rapid estimation of the maneuvering decision-making strategy and trajectory of the flying device in the confrontation game, and realizes the target movement under a certain time and space scale. The impact will be predicted in advance to improve the pertinence and effectiveness of flight countermeasures.

Description of drawings

FIG. 1 is an exemplary system architecture diagram to which the present application can be applied;

Fig. 2 is the structural representation of the trajectory simulation system embodiment based on the large envelope game strategy of the present application;

Fig. 3 is a schematic diagram of the tactical task flight mode decision-making of the trajectory simulation system based on the large envelope game strategy according to the present application;

Fig. 4 is a schematic diagram of the flight management scheduling state of the trajectory simulation system based on the large envelope game strategy according to the present application;

Fig. 5 is a schematic diagram of the hierarchical control of the maneuvering flight of the trajectory simulation system based on the large envelope game strategy according to the present application.

Detailed ways

Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

FIG. 1 shows an exemplary system architecture of an embodiment of the trajectory simulation system based on the large envelope game strategy of the present application that can be applied.

As shown in FIG. 1 , the system architecture may include a data collection device 101 , a network 102 , an execution mechanism 103 and a server 104 . The network 102 is used as a medium for providing a communication link between the data collection device 101 , the executing agency 103 and the server 104 . Network 102 may include various connection types, such as wires, wireless communication links, or fiber optic cables, among others.

The data acquisition device 101 is used to collect data related to the aircraft, and sends the collected data related to the aircraft to the server 104 for processing through the network 102; The status information of the actuator can also directly control the action of the actuator according to the collected data related to the aircraft. The above-mentioned data collection device 101 can be various types of sensing devices, such as collecting parameters such as speed, rotation angle, pitch angle, wind speed, altitude, and acceleration of the aircraft.

The server 104 may be a server that provides various services, for example, a processing server that processes the data collected by the data collection device 101 and controls the operation of the actuator 103 . The above-mentioned processing server may be various controllers that control the execution structure according to the collected data information according to preset logic or instructions. For example, it can be an electronic circuit composed of electronic components, or an electronic control device with a processor or microprocessor as the core, such as a single-chip microcomputer system, programmable logic controller, microcomputer, etc. It can also be a smart device with data processing and control functions, such as a smart phone, a tablet computer, a laptop computer, a desktop computer, and the like.

The above-mentioned actuator 103 can be various driving devices for controlling the movement of the aircraft, such as various pneumatic devices, electric devices and the like. It should be noted that the trajectory simulation system based on the large envelope game strategy provided in the embodiment of the present application is generally set in the server 104 .

It should be understood that the numbers of data acquisition devices, networks, actuators and servers in Fig. 1 are only illustrative. According to the realization needs, there can be any number of terminal devices, networks, executive agencies and servers.

Continuing to refer to FIG. 2 , it shows a schematic structure diagram of an embodiment of a trajectory simulation system based on a large envelope game strategy according to the present application. The trajectory simulation system based on the large envelope game strategy includes: a situation awareness and decision-making module, an abnormal management module, a real-time maneuvering flight module, and a target trajectory calculation module; wherein, the above-mentioned situation awareness and decision-making module is configured to obtain the attitude of the flying device data, and select different tactical tasks according to the above-mentioned attitude data; the above-mentioned abnormal management module is configured to perform flight task switching on the above-mentioned flying device according to the above-mentioned flying device attitude data and preset trigger conditions of various tactical tasks; the above-mentioned real-time flight module , configured to calculate the control of each flight sub-action of the above-mentioned flying device in flight according to the above-mentioned attitude data and flight trajectory, to form a target attitude and a target trajectory; the above-mentioned target trajectory calculation module is configured to use a multi-degree-of-freedom mechanical model and a motion equation to The target attitude and the target trajectory are calculated to realize the output of the target trajectory of the flying device.

In this embodiment, the above-mentioned situational awareness and decision-making module includes: a situational awareness sub-module, a tactical decision-making sub-module, and a route planning sub-module, wherein the above-mentioned situational awareness sub-module is configured to obtain the attitude data of the flying device, and according to the above-mentioned attitude The data determines the flight situation of the flight device; the above-mentioned tactical decision-making sub-module is configured to determine the tactical task of the above-mentioned flight device according to the above-mentioned flight situation by using preset trigger conditions and priority calculation; the above-mentioned route planning sub-module is configured to Mission and emergency flight routes are used to calculate the maneuver switching conditions of the above-mentioned maneuver missions and the planning of tactical missions.

The aforementioned situational awareness sub-module acquires the attitude data of the flying device, which may be the data collected by the sensing device, or the data related to the flight of the flying device stored in the storage unit of the server. The above-mentioned attitude data may be parameters in flight of the flying device, such as attitude angle obtained by using a gyroscope. The above-mentioned attitude angle is the angle between the body coordinate system and the ground inertial coordinate system, expressed by roll angle (roll), pitch angle (pitch), and yaw angle (yaw). The included angle between the vertical planes passing through the longitudinal axis of the aircraft body; the above-mentioned pitch angle θ is the angle between the body axis and the ground plane (horizontal plane), and the aircraft head is positive; the above-mentioned yaw angle ψ is the angle of the body axis on the horizontal plane The angle between the projection and the earth's axis is positive when the nose is deflected to the right. The flight attitude of the flying device or aircraft can be determined by using the above attitude angle.

In the above-mentioned tactical decision-making sub-module, trigger conditions and priorities are used to determine tactical tasks according to flight attitude. The above-mentioned trigger conditions are pre-set conditions, and when the flight parameters or flight attitude meet the above-mentioned trigger conditions, corresponding actions or corresponding tactics are executed. The above priority is the preset action level or tactical level. When two tactical tasks satisfy the trigger conditions at the same time, the tactical task with higher priority will be executed first. The above-mentioned tactical tasks are flight tasks preset by the flight device, such as normal flight, escape flight, emergency maneuver avoidance, route re-planning, etc. As an example, reference may be made to FIG. 3 , which shows the flight modes of tactical missions, including automatic flight and commanded flight. Normal flight, malfunction abnormal flight and escape maneuver in automatic flight. Target motion training tasks such as level flight, ascent and descent, acceleration and deceleration, and turning can be performed during normal flight. Escape maneuvers can be target movements such as U-turns, snake maneuvers, maximum turn escapes, minimum radar exposure escapes, dive terrain following, etc. In normal flight, if the detected attitude data and flight data trigger a dangerous trigger condition, it enters the escape maneuver flight mode. By triggering the fault abnormal condition, the fault abnormal flight mode is entered, as shown in FIG. 4 .

The above-mentioned route planning sub-module calculates the routes of maneuvering flight and emergency flight for the flying device according to the flight parameters and attitude parameters of the flying device. The route calculation sub-module uses planning constraints to plan routes for the flight device through dynamic programming, heuristic optimization search, genetic algorithm, artificial neural network, and swarm intelligence algorithm. Specifically, the A* algorithm is used to realize the planning of the maneuver switching conditions and tactical tasks. Here, the A* algorithm is the A-star algorithm, which is an algorithm to obtain the flight path through partition search and search based on the detected environmental parameters, flight parameters and attitude parameters using the evaluation function constructed according to the preset constraints. The above constraints may be conditions such as geographical terrain, meteorological conditions, the radar of the opposing player, and no-fly zones. The above-mentioned evaluation function may be composed of weights of threat, distance, maneuverability, and the like.

The above-mentioned exception management module includes a management scheduling submodule and a state estimation submodule. Among them, the above-mentioned management scheduling sub-module is configured to manage the typical faults and flight abnormalities of the flight tasks according to the maneuvering flight tasks and attitude data, so as to realize the start, stop and switch of the flight tasks; the above-mentioned state estimation sub-module is configured to monitor the target movement The operating conditions and motion abnormalities are detected, and the typical faults of the flying device are monitored and evaluated according to the detection results.

The management and scheduling sub-module manages the flight target tasks of the flying device according to the maneuvering flight tasks and attitude data. The above-mentioned maneuver flight tasks may be tasks or actions such as level flight, ascent and descent, acceleration and deceleration, turning, and rotation. The maneuvering missions described above can be used to form training missions for target motion. The above-mentioned management and scheduling sub-module performs emergency management on typical faults and flight abnormalities. Specifically, it may be starting, stopping, and switching of flight tasks.

The above-mentioned state track sub-module evaluates the flight state and is used for the emergency management of the above-mentioned typical faults, flight abnormalities and other flight tasks. The above evaluation of the flight state can be based on the collected flight parameters and attitude parameters, using the initial conditions of the target movement, switching conditions, termination conditions and movement abnormalities to detect the flying device, and to detect task switching, flight abnormalities and typical faults to evaluate. The aforementioned task switching may be switching of flight modes, and the flight modes may be flight modes such as command maneuver, defensive maneuver, and ground planning. The switching between modes can be actively selected according to the flight mission or the current flight state, or can be entered automatically according to the state of the system. The above-mentioned flight abnormality can be a game against abnormal situations such as collisions between two parties, collisions with mountains, and ground. Typical faults of the aircraft can be fuel shortage, power shortage, abnormality of radar equipment, abnormality of radar warning equipment, etc. The above-mentioned flight task state switching and fault emergency processing can use a finite state machine for management and scheduling.

The real-time flight module includes a layered mode management submodule, an interface normalization submodule and an instruction generation submodule, wherein the layered mode management submodule is configured to use a layered maneuver flight task library to control the flight submodule Switching conditions between actions, state monitoring and state transition management; the above-mentioned interface normalization sub-module is configured to calculate the load of the flying device according to the attitude parameters and the parameters related to the flight of the above-mentioned flying device detected by the sensor, forming A unified target motion control input interface; the above command generation sub-module is configured to calculate the control parameters of different flight sub-actions and the switching relationship between sub-actions according to different flight trajectories.

The above-mentioned layering manages the above-mentioned maneuvering flight, flight mode switching and state management layering. Specifically, any flight mode of the flying device can be managed hierarchically, which can be an instruction generation layer, a conversion layer, and a trajectory calculation layer. The instruction generation layer can be an instruction that decomposes maneuver instructions into a single movement mode. The parameters of the body coordinate system are generated through the normalized management of instructions; the conversion layer converts the parameters of the body coordinate system into parameters of the ground inertial coordinate system; the trajectory calculation layer uses the parameters of the ground inertial coordinate system to display the flight trajectory.

As an example, as shown in Figure 5, the flight trajectory of the maneuvering flight mode is controlled hierarchically. The first is the modal management algorithm of the sub-actions of the maneuvering flight, and the switching conditions, state monitoring and state transition between sub-actions are performed. manage. The second layer is the overload normalization generation algorithm, which converts the parameters, and the third layer solves the trajectory.

The above-mentioned interface normalization sub-module calculates the target overload according to the attitude parameters and flight parameters, and forms a unified target motion control input interface. Specifically, the above-mentioned interface normalization sub-module can use parameters such as target thrust, angle of attack, acceleration and deceleration, lift-drag coefficient, dynamic pressure, air density, aircraft mass, and wing surface to calculate target overload.

The above command generation sub-module calculates the control parameters of sub-actions in different stages (overload, roll angle, pitch angle, yaw angle and speed, etc.) and the switching relationship between sub-actions in different stages according to different trajectories.

The target trajectory calculation module uses a multi-degree-of-freedom mechanical model and a motion equation to calculate the target attitude and the target trajectory to realize the output of the target trajectory. Specifically, it can be a maneuvering flight six-degree-of-freedom dynamics model and a motion equation algorithm. According to a multi-degree-of-freedom target motion dynamics model with target speed, trajectory inclination angle, trajectory yaw angle, and geographic location coordinates XYZ as state variables, the Calculate the target trajectory. Tangential overload, normal overload, and roll angle of velocity vector can be brought into the following calculation formula as input to calculate the derivative of the state variable;

Among them, V, x, y, z, θ, ψ, φ, n _x , n _z , g are in turn the velocity of the center of mass axis to the ground, the ground coordinates (x longitudinal distance, y lateral distance, z height), and track inclination angle , trajectory deflection angle, roll angle around velocity vector, tangential overload, normal overload and gravitational acceleration.

The method of transforming plane coordinates to spherical coordinates can be used to transform the geographic coordinates XYZ of the six-degree-of-freedom motion equation into the longitude, latitude, and height of the earth coordinate system.

Realizing the output of the target trajectory includes: using the Euler method or the second-order interpolation calculation method to perform interpolation calculation on the target parameters with different interpolation frame rates, so as to realize the variable frame rate target trajectory output.

According to the derivatives of the above variables, the above target trajectory is solved by using the nonlinear ordinary differential equation numerical integration algorithm of the fourth-order Runge-Kutta algorithm. Specifically, it can be:

On the premise that the derivative of the equation and the initial value information are known, the numerical integration algorithm for solving the differential equation; let the initial value be expressed as follows:

y'=f(t,y), y(t ₀ )=y ₀

Then, RK4 for this problem is given by the following equation:

in,

k ₁ = f(t _n , y _n )

k ₄ ＝f(t _n +h,y _n +hk ₃ )

y _n+1 is determined from the current value of y _n plus the product of the time interval (h) and an estimated slope. The slope is a weighted average of the following slopes: k1 is the slope at the beginning of the time period; k2 is the slope at the midpoint of the time period, and slope k1 is used by Euler's method to determine y at point k3 is also the slope of the midpoint, but this time the slope k2 is used to determine the y value; k4 is the slope of the end of the time period, and its y value is determined by k3. When the four slopes are averaged, the slope at the midpoint has more weight:

The RK4 method is a fourth-order method, the error of each step is h5 order, and the total accumulated error is h4 order.

In the system provided by the above-mentioned embodiments of the present application, the situational awareness and decision-making module selects flight tactics through the attitude of the flying device; the abnormal management module is used to switch flight tasks; the real-time flight module is used to form the target attitude and target trajectory of the flying device, and the target trajectory The calculation module realizes the data display of the target trajectory, and the invention realizes the rapid estimation of the maneuvering decision-making strategy and the trajectory of the flying device in the confrontation game.

So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings, but those skilled in the art will easily understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims (9)

1. A trajectory simulation system based on a big envelope game strategy is characterized by comprising: the system comprises a situation perception and decision module, an exception management module, a real-time maneuvering flight module and a target track resolving module;

the situation perception and decision module is configured to acquire attitude data of the flight device and select different tactical tasks according to the attitude data;

the anomaly management module is configured to switch the flight mission of the flight device according to the attitude data of the flight device and preset triggering conditions of various tactical missions;

the real-time flight module is configured to calculate control of each flight sub-action of the flight device in flight according to the attitude data and the flight track to form a target attitude and a target track;

the target track calculating module is configured to calculate the target attitude and the target track by using a multi-degree-of-freedom mechanical model and a motion equation, so as to output the target track of the flight device.

2. The big-envelope gaming strategy-based trajectory simulation system of claim 1, wherein the situational awareness and decision module comprises: a situation perception sub-module, a tactical decision sub-module and a route planning sub-module,

the situation perception sub-module is configured to acquire attitude data of the flight device and determine the flight situation of the flight device according to the attitude data;

the tactical decision sub-module is configured to determine a tactical task of the flight device according to the flight situation by utilizing a preset trigger condition and priority calculation;

and the route planning submodule is configured to calculate the maneuver switching condition of the maneuver task and plan the tactical task according to the maneuver task and the emergency flight route.

3. The trajectory simulation system based on the big envelope game strategy of claim 2, wherein the tactical sub-module calculates any one of the following flying tactics from the tactical mission according to a preset trigger condition and a priority: escape flight tactics, emergency maneuver evasion tactics, and normal flight tactics.

4. The trajectory simulation system based on the big envelope gaming strategy of claim 2, wherein the routing sub-module is further configured to implement the planning of the maneuver switching condition and the tactical mission by an a-algorithm using a planning constraint condition.

5. The big-envelope gaming strategy-based trajectory simulation system of claim 1, wherein the anomaly management module comprises a management scheduling sub-module and a state estimation sub-module,

the management scheduling submodule is configured to perform typical fault and flight abnormity management on the flight task according to the maneuvering flight task and the attitude data so as to realize starting, stopping and switching of the flight task;

the state estimation submodule is configured to detect the operation condition and the motion abnormality of the target motion, and monitor and evaluate typical faults of the flight device according to the detection result.

6. The big envelope gaming strategy based trajectory simulation system of claim 4, wherein the real-time flight module comprises a layered modality management sub-module, an interface normalization sub-module, and an instruction generation sub-module,

the layered mode management submodule is configured to adopt a layered maneuvering flight task library to control switching conditions, state monitoring and state transition management among the flight submotions;

the interface normalization sub-module is configured to calculate the load of the flight device according to the attitude parameters and the parameters related to the flight of the flight device detected by the sensor, so as to form a uniform target motion control input interface;

and the instruction generation submodule is configured to calculate control parameters of the flight subactions at different stages and switching relations among the subactions according to different flight trajectories.

7. The trajectory simulation system based on the large envelope game strategy of claim 1, wherein the resolving the target attitude and the target trajectory using the multiple degree of freedom equation to achieve the output of the target trajectory comprises: according to a multi-degree-of-freedom target motion dynamics model with target speed, a track inclination angle, a track yaw angle and geographic position coordinates XYZ as state variables, calculating the target track:

wherein V, x, y, z, theta, psi, phi, n_x,n_zG is in turn the mass axis ground speed, ground coordinates (x longitudinal distance, y lateral distance, z height), trajectory tilt angle, trajectory yaw angle, yaw vector roll angle, tangential overload, normal overload, and gravitational acceleration.

8. The trajectory simulation system based on the large envelope game strategy of claim 7, wherein the target attitude and the trajectory are solved by using a multiple degree of freedom equation to realize the output of a target trajectory, further comprising:

and transforming the longitude, the latitude and the height of the earth coordinate system by adopting a method of transforming a plane coordinate into a spherical coordinate, and transforming the geographic coordinate XYZ solved by the six-degree-of-freedom motion equation into the longitude, the latitude and the height of the earth coordinate system.

9. The trajectory simulation system based on the large envelope game strategy of claim 8, wherein the resolving the target attitude and the trajectory using the multiple degree of freedom equation to achieve the output of the target trajectory comprises: and performing interpolation calculation on the target parameters by using an Eulerian method or a second-order interpolation calculation method and adopting different interpolation frame rates to realize variable-frame-rate target track output.