A fusion kinetics aircraft GNC system visual modeling method

Abstract

The application provides a kind of fusion kinetics aircraft GNC system visual modeling method, it is related to aircraft guidance control system modeling simulation technical field.The method divides aircraft GNC system model into dynamic model, kinematic model, environment model, rudder system model, seeker model, autopilot, target motion model, 3-DOF visual motion simulation model and guidance computer, models each model above and constitutes aircraft GNC system model, is used to solve trajectory when missile flies, required overload and actual overload, seeker tracking curve, instantaneous miss distance, flight attack angle, flight Mach number, rudder deflection angle parameter.The method of the application introduces visual modeling simulation and dynamic data table, considers the coupling influence between each subsystem and related system in GNC system explicitly, is convenient for the simplified modeling and simulation of different configurations guided aircraft, so that aircraft can obtain better flight performance and guidance precision.

Description

Technical Field

[0001] This invention relates to the field of modeling and simulation technology for aircraft guidance and control systems, and in particular to a visualization modeling method for aircraft GNC systems that integrates dynamics. Background Technology

[0002] The guidance, navigation and control (GNC) system is an integrated system in an aircraft responsible for navigation, guidance and control. It acquires the aircraft's status and environmental information through sensors, calculates control commands based on the predetermined flight mission, and then transmits these commands to the various actuators of the aircraft to achieve precise navigation, stable flight and accurate control. In reality, due to the highly dynamic and complex environment in which aircraft operate, aircraft systems typically face various uncertainties and nonlinear couplings. Moreover, the dynamic model of the aircraft itself is nonlinear, including nonlinear effects in aerodynamic models, inertial force models, and thrust models. In addition, the aircraft's GNC system consists of multiple subsystems composed of sensors, which are mutually coupled, increasing the complexity of the aircraft's GNC system. The aircraft's GNC system relies on sensors to acquire environmental information and executes control commands through actuators. However, both sensors and actuators are subject to their own limitations and uncertainties, such as sensor noise, sampling frequency limitations, and actuator dynamic response. These factors can lead to inaccuracies in the aircraft's GNC system model and uncertainties in parameters, posing challenges to modeling and control design.

[0003] Solving the modeling problem of GNC systems requires the comprehensive application of technologies from multiple disciplines such as mathematical modeling, control theory, and sensor technology. In order to consider the impact of guidance and control system performance on the overall flight process as realistically as possible during the overall design phase of the aircraft, digital experimental verification and simulation analysis are usually carried out in the early stages of design. An advanced mathematical simulation platform is established to conduct sufficient experimental verification of the control system. This can greatly optimize the performance and robustness of the control system, accelerate the model development speed, and significantly reduce the number of live-fire tests of the model.

[0004] Existing technical solutions for designing and modeling GNC systems for aircraft often require researchers to first design each subsystem individually, develop robust control algorithms, and implement fault detection and recovery strategies, as the GNC system needs to maintain robustness and reliability under conditions of uncertainty, noise, faults, and interference. Furthermore, GNC system design is highly dependent on other systems on the aircraft, especially since the overall aircraft design begins with aerodynamic design, and the GNC system, as a subsystem, is designed with aerodynamics at its core. This design approach neglects the matching relationship between the overall aerodynamics and the GNC subsystem and the individual aircraft. Currently, existing guidance systems based on mathematical models / semi-physical simulations tend to be independent of the seeker, inertial navigation, and flight control systems in the early design stages, lacking an integrated aerodynamic guidance and control design philosophy. Existing general simulation processes primarily simplify independent models, failing to cover many practical engineering applications, and the simulation process is relatively complex, making it difficult to quickly solve problems encountered in GNC system design. Currently, there is no comprehensive, visualized, integrated modeling method that includes the dynamics, aerodynamics, guidance and control, guidance, and decision-making models of guided aircraft. Summary of the Invention

[0005] Based on the above situation, the present invention provides a visualization modeling method for a guided vehicle GNC system that integrates dynamics. By introducing visualization modeling simulation and dynamic data tables, the coupling effects between various subsystems and related systems in the GNC system are explicitly considered, which facilitates simplified modeling and simulation of guided vehicles with different configurations, enabling the vehicle to obtain better flight performance and guidance accuracy.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention includes the following process:

[0007] Step 1: Set the parameters and aerodynamic coefficients of the aircraft, establish the dynamic model of the aircraft and determine the output parameters of the dynamic model, open the input interface of the dynamic model, use the output parameters of the dynamic model to establish the kinematic model, and output the kinematic parameters of the aircraft.

[0008] Step 2: Establish an environmental model, autopilot, and rudder system model according to the aircraft's usage requirements. Connect the output interfaces of the environmental model and the rudder system model to the input interface of the dynamics model. Input the aircraft's kinematic parameters into the autopilot and connect the autopilot's output interface to the input interface of the rudder system model. Use the autopilot's output to control the rudder system model.

[0009] Step 3: Set semi-physical parameters, construct a seeker model consisting of a detector antenna module, a radar antenna servo frame module, and a parasitic loop, and connect the seeker model to the kinematic model;

[0010] Step 4: Determine the guidance strategy and build a guidance computer. The guidance computer outputs missile normal overload commands to the autopilot model, and the guidance computer is connected to the seeker model built in Step 3. The guidance computer adjusts the seeker's working mode according to the guidance strategy, and the seeker switches the aircraft's flight state according to the state of the tracked target. In addition, a simplified model of the missile detonation system is built and an initiation strategy is set. The miss distance is calculated, and the aircraft user evaluates the miss distance of the guidance process based on the miss distance. The missile detonation system model is then nested into the guidance computer.

[0011] Step 5: Based on the mission requirements of the aircraft, build a target motion model. By setting the target motion azimuth, target overload limit, and target random maneuver strategy, calculate the target-missile distance R and target-missile line-of-sight angle q, and output them to the seeker model built in Step 3; simultaneously, calculate the target trajectory inclination angle θ. T and velocity v T The seeker model is input into the guidance computer; a 3-DOF visual kinematic model is constructed, and the outputs of the target motion model and the kinematic model are used as inputs to the 3-DOF visual kinematic model.

[0012] Step 6: Connect all the above models, determine the mission conditions and parameter settings of the aircraft, simulate the process of the aircraft attacking the target, and calculate the ballistic trajectory, required overload and actual overload, instantaneous miss distance, angle of attack, flight Mach number, and rudder deflection parameters in real time; check the performance of the aircraft's GNC system according to the mission requirements of the aircraft. If the performance of the aircraft's GNC system is not up to standard, the models in steps 1-5 need to be checked and modified, and the process should be returned to step 1 until the performance meets the standards.

[0013] Furthermore, step 1 includes:

[0014] Step 1.1: Set the parameters and aerodynamic coefficients of the aircraft, convert the parameters and aerodynamic coefficients to the vertical plane, and generate a data table;

[0015] The parameters of the aircraft include: the mass of the aircraft, the size of the aircraft, the moment of inertia of the aircraft about each axis, the aerodynamic layout of the missile body, the reference area of ​​the missile body, the reference area of ​​the control surfaces, the flight Mach number range, the flight angle of attack range, the engine thrust curve and atmospheric environmental parameters, and various parameters of the autopilot adjustable gain table.

[0016] The aerodynamic coefficients include the parameters in the aerodynamic coefficient table of the projectile body and the aerodynamic coefficient table of the control surfaces;

[0017] Step 1.2: Perform dynamic modeling on the aircraft to obtain a three-degree-of-freedom dynamic model, and determine the output parameters of the dynamic model, including: drag, lift and pitching moment acting on the projectile;

[0018] Step 1.3: Establish a kinematic model based on the dynamic model, and combine the dynamic and kinematic models to obtain the kinematic parameters of the aircraft in the inertial frame, including: the aircraft's trajectory tilt angle θ and attitude angular rate ω. z Center of mass position (x, z), velocity V, Mach number Ma, angle of attack α, missile normal overload A zm ;

[0019] The mathematical model of the three-degree-of-freedom dynamic model is expressed as follows:

[0020]

[0021] Where F x F z M represents drag, lift, and pitching moment acting on the projectile, respectively; C x C z C m All are dimensionless proportionality coefficients, representing the drag coefficient, lift coefficient, and pitching moment coefficient, respectively. All three proportionality coefficients are related to the flight angle of attack α, rudder deflection angle δ, and flight Mach number Ma; S ref The feature reference area; d ref ρ is the diameter of the axisymmetric projectile; ρ is the atmospheric density; V is the flight velocity;

[0022] When the angle of attack and rudder deflection satisfy the non-stall condition and are within a controllable range, i.e. -20° < α < 20°, -30° < δ < 30°, and the flight Mach number Ma < 0.95, C x C z C m As shown in formula (2):

[0023]

[0024] Where C x0 Zero-lift drag coefficient; C z0 C represents the lift coefficient term for asymmetric aircraft conditions. m0 The zero pitch moment coefficient; This is the induced drag coefficient; This is the lift coefficient at the angle of attack; The pitch moment coefficient caused by the angle of attack; The drag coefficient is the rudder deflection angle. The lift coefficient is the rudder deflection angle. This is the pitch control moment coefficient; The distance from the projectile's focal point to its center of mass;

[0025] When the flight Mach number satisfies 1.1 < Ma < 4, and the flight angle of attack and rudder deflection angle satisfy -20° < α < 20°, -30° < δ < 30°, a linear fitting curve is used to approximate the non-linear aerodynamic coefficient. According to formula (3), the lift coefficient and pitching moment coefficient are expressed as functions of the flight angle of attack and rudder deflection angle:

[0026]

[0027] where a z 、b z 、c z 、d z 、a m 、b m 、c m 、d m are all dimensionless coefficients;

[0028] Furthermore, the said step 2 includes:

[0029] Step 2.1: Construct an environmental model, and provide the local speed of sound a v and atmospheric density ρ output by the environmental model to the kinetic model;

[0030] Step 2.2: Construct an autopilot according to the kinematic parameters, obtain the mathematical model of the three-loop non-linear autopilot, and output the rudder deflection angle command δ f ;

[0031] Step 2.3: Construct a rudder system model, use the rudder deflection angle command δ f to control the rudder system model, and then solve the rudder deflection angle δ and provide it to the kinetic model;

[0032] The mathematical model of the three-loop non-linear autopilot is expressed as:

[0033] δ f = K∫u q dt - KK a ∫A zm dt + K I ∫ω z dt + K g ω z - K as (δ f0 - δ l ) (brackets) (6)

[0034] where δ f is the rudder deflection angle command; K, K a 、K I 、K g are all variable control gains; K as is the feedforward anti-saturation gain; u q is the missile normal overload command; Azm For missile normal overload; ω z δ represents the attitude angular rate. f0 -δ l The amount by which the command exceeds the maximum rudder deflection angle;

[0035] Furthermore, step 3 includes:

[0036] Step 3.1: Set up semi-physical parameters and build a detector antenna module to simulate the search and acquisition process of the seeker in the seeker model, including: missile-target distance detection module, relative velocity detection filter and offset angle filter module;

[0037] The projectile-target distance detection module is used to calculate the projectile-target distance R; the relative velocity detection filter is used to differentiate the projectile-target distance R and filter the output to obtain the projectile-target relative velocity. The offset angle filter module is used to filter the offset angle signal;

[0038] Step 3.2: Set the tracking loop time constant t and loop crossover frequency t of the seeker. s The natural frequency ω of a stable loop rate gyroscope ng A radar antenna servo frame module is constructed in the elevation plane to obtain mathematical models of the stabilization loop and the tracking loop.

[0039] Step 3.3: Model the parasitic loop of the seeker, incorporate the parasitic loop into the mathematical models of the stable loop and the tracking loop, and adjust the tracking loop time constant t and loop crossover frequency t. s The transfer function and natural frequency ω of a steady-loop rate gyroscope ng and the bandwidth ω of the offset angle filter h To reduce interference signals during the movement of the radar antenna servo frame, a well-constructed seeker model is obtained;

[0040] Step 3.4: Calculate the missile-target line-of-sight angular rate based on the seeker model.

[0041] Furthermore, the mathematical models for the stable loop and the tracking loop described in step 3.2 are expressed as follows:

[0042] Guide head servo angle As the control variable, transfer function models for the stable loop and the tracking loop are established:

[0043]

[0044] Where s is the Laplace operator; For the guide head servo frame angle command; The ratio of the output to the input pull change of the seeker servo frame angle;

[0045] Furthermore, the model obtained by incorporating the parasitic loop into the mathematical model of the stable loop and the tracking loop as described in step 3.3 is as follows:

[0046]

[0047] Where k r For parasitic loop gain;

[0048] Furthermore, step 4 also includes: in the process of determining the guidance strategy, the flight state of the aircraft is divided into a cruise phase and a terminal guidance phase, and the optimal guidance law for the aircraft in the terminal guidance phase is established as the H∞ guidance law designed based on the line-of-sight angular rate. The mathematical model of the H∞ guidance law designed based on the line-of-sight angular rate is expressed as:

[0049]

[0050] Where R is the target distance; q is the target line-of-sight angle; u q This is a missile normal overload command, used as a system control variable to control the autopilot; w q External disturbance term;

[0051] And there is formula (12):

[0052]

[0053] Where v M v is the missile velocity; θ is the trajectory inclination angle of the spacecraft; T θ represents the target velocity. T The target trajectory inclination angle; v T -v M Considered as the relative velocity between the projectile and the target Also known as the rate of change of the distance between the projectile and the target;

[0054] Furthermore, the 3-DOF visualized kinematic model is used to receive the target position (x) in the target motion model. T ,z T ), target velocity V T Target-target distance R, target trajectory inclination angle θ T The parameters, including attitude angle θ, center of mass position (x,z), flight speed V, and angle of attack α, are used to simulate the process of a guided aircraft striking a target in real time.

[0055] The beneficial effects of adopting the above technical solution are as follows:

[0056] 1. The method of this invention can quickly, effectively, and comprehensively model and visualize the GNC system of aircraft and missiles, providing effective verification of the dynamic parameters obtained during missile design. The modeling process constructs a dynamic model, kinematic model, environmental model, autopilot, rudder system model, guidance computer, seeker model, and target motion model for the aircraft. A three-degree-of-freedom visualized motion simulation model between the missile and target is used for visualized digital simulation, and a miss distance is introduced to evaluate the overall model. This method is applicable to the modeling and simulation of various guided aircraft and missiles flying within the atmosphere, enabling thorough simulation verification of their GNC systems in the early design stages of the aircraft.

[0057] 2. The design and modeling method proposed in this invention is comprehensive, adopts the design concept of integrated aerodynamic guidance and control, and is simple to apply. It simplifies the flight and attack process of the aircraft to the vertical plane and simulates the flight and attack process from a three-degree-of-freedom perspective. This can reduce the huge computational pressure during the overall system simulation, facilitate the rapid modeling and simulation of different guided aircraft, and make it easier to find problems in the design process and optimize the system's performance and robustness.

[0058] 3. The method of this invention uses the concept of simulation visualization. During the simulation process, the flight trajectory and flight attitude of the aircraft can be observed in real time, and the miss distance, flight angle of attack and normal overload data can be displayed in real time, so as to solve errors in the design and simulation process.

[0059] 4. The method of this invention uses the idea of ​​combining simulation data visualization with guidance and control integration, which can effectively perform rapid modeling and effectively avoid the impact of some nonlinear cross-coupling on the GNC system model.

[0060] 5. The method of this invention avoids the problem of closed and incompatible interfaces during subsystem design. The data interfaces of each model are open, and the data of each model can be dynamically adjusted in real time in the interface according to the simulation evaluation effect during the simulation process. It can quickly model aircraft with different aerodynamic shapes and different guidance systems.

[0061] 6. The dynamic nonlinear autopilot proposed by the method of this invention is applicable to various types of guided aircraft. By providing control response feedback to the aircraft dynamics data table, it can dynamically adjust the control gain, resulting in good control effect and strong robustness. Attached Figure Description

[0062] Figure 1 This is a schematic diagram illustrating the visualization modeling method for the GNC system of an aircraft that integrates dynamics, as described in this embodiment.

[0063] Figure 2 This is a flowchart of the visualization modeling method for the aircraft GNC system that integrates dynamics in this embodiment;

[0064] Figure 3 This is a geometric diagram of the mathematical model of bullet-target engagement in this embodiment;

[0065] Figure 4 This is a ballistic curve diagram of the missile and the target in this embodiment;

[0066] Figure 5 Figure 1 shows the curves of the missile's commanded normal acceleration versus actual value, angle of attack, Mach number, and rudder deflection angle over time in this embodiment; Figure 2 shows the curves of the missile's commanded normal acceleration versus actual value over time; Figure 3 shows the curves of the missile's angle of attack over time; Figure 4 shows the curves of the missile's Mach number over time; and Figure 5 shows the curves of the missile's rudder deflection angle over time.

[0067] Figure 6 This is a dynamic window view of the aircraft's visual shape in this embodiment. Detailed Implementation

[0068] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0069] In this embodiment, such as Figure 1 As shown, the method of this invention divides the aircraft GNC system model into a dynamic model, a kinematic model, an environmental model, a rudder system model, a seeker model, an autopilot, a target motion model, a three-degrees-of-freedom (3-DOF) visual motion simulation model, and a guidance computer. These models are then combined to form the aircraft GNC system model, used to calculate the missile's trajectory, required and actual overloads, seeker tracking curve, instantaneous miss distance, angle of attack, Mach number, and rudder deflection parameters during flight. Since different aircraft possess all of these main models, determining the inputs and outputs of each model requires standardizing and streamlining the modeling process for each model, enabling rapid modeling of a specific aircraft simply by changing and correcting parameters. In this embodiment, Simulink is used for modeling and simulation.

[0070] The visualization modeling method for aircraft GNC systems based on fused dynamics provided in this embodiment, such as Figure 2 As shown, it includes the following steps:

[0071] Step 1: Set the parameters and aerodynamic coefficients of the aircraft, establish the dynamic model of the aircraft and determine the output parameters of the dynamic model, open the input interface of the dynamic model, use the output parameters of the dynamic model to establish the kinematic model, and output the kinematic parameters of the aircraft.

[0072] Step 1.1: Set the parameters and aerodynamic coefficients of the aircraft, convert the parameters and aerodynamic coefficients to the vertical plane, and generate a data table.

[0073] The parameters of the aircraft include: the mass of the aircraft, the size of the aircraft, the moment of inertia of the aircraft about each axis, the aerodynamic layout of the missile body, the reference area of ​​the missile body, the reference area of ​​the control surfaces, the flight Mach number range, the flight angle of attack range, the engine thrust curve and atmospheric environmental parameters, and various parameters of the autopilot adjustable gain table.

[0074] The aerodynamic coefficients include the parameters in the aerodynamic coefficient table of the projectile body and the aerodynamic coefficient table of the control surfaces;

[0075] In this embodiment, aerodynamic coefficients of the aircraft are obtained using aerodynamic analysis software, such as the aerodynamic coefficients of the projectile body (i.e., drag coefficient, lift coefficient, and pitching moment coefficient) and the aerodynamic coefficients of the control surfaces (i.e., control deflection angle drag coefficient, control deflection angle lift coefficient, and control deflection angle pitching moment coefficient). A table of aerodynamic coefficients of the projectile body and control surfaces corresponding to the above aerodynamic coefficients is generated in the form of an interpolation table. The parameters and aerodynamic coefficients of the aircraft are set, and the parameters and aerodynamic coefficients of the aircraft are converted into a vertical plane, retaining only the data in the pitch plane. All the set parameters and aerodynamic coefficients of the aircraft are converted into a two-dimensional dynamic data table to facilitate real-time adjustment of the data during the simulation process.

[0076] Step 1.2: Perform dynamic modeling on the aircraft to obtain a three-degree-of-freedom dynamic model, and determine the output parameters of the dynamic model, including drag, lift and pitching moment acting on the aircraft body.

[0077] The mathematical model of the three-degree-of-freedom dynamic model is expressed as follows:

[0078]

[0079] Where F x F z M represents drag, lift, and pitching moment acting on the projectile, respectively; C x C z C m All are dimensionless proportionality coefficients, representing the drag coefficient, lift coefficient, and pitching moment coefficient, respectively. All three proportionality coefficients are related to the flight angle of attack α, rudder deflection angle δ, and flight Mach number Ma; S ref The feature reference area; dref is the projectile diameter of an axisymmetric projectile; ρ is the atmospheric density; V is the flight speed.

[0080] When the flight angle of attack and the rudder deflection angle satisfy the non-stall condition and are within the controllable range, that is, -20° < α < 20°, -30° < δ < 30° and the flight Mach number Ma < 0.95, C x 、C z 、C m are as shown in formula (2):

[0081]

[0082] Among them, C x0 is the zero-lift drag coefficient; C z0 is the lift coefficient term when the aircraft is asymmetric; C m0 is the pitch moment coefficient at zero deflection angle; is the induced drag coefficient; is the lift coefficient of the angle of attack; is the pitch moment coefficient caused by the angle of attack; is the drag coefficient of the rudder deflection angle; is the lift coefficient of the rudder deflection angle; is the pitch control moment coefficient; is the distance from the focus of the projectile to the center of mass of the projectile.

[0083] When the flight Mach number satisfies 1.1 < Ma < 4, and the flight angle of attack and the rudder deflection angle satisfy -20° < α < 20°, -30° < δ < 30°, a linear fitting curve is used to approximate the non-linear aerodynamic coefficients, and the lift coefficient and the pitch moment coefficient are expressed as functions of the flight angle of attack and the rudder deflection angle according to formula (3):

[0084]

[0085] Among them, a z 、b z 、c z 、d z 、a m 、b m 、c m 、d m are all dimensionless coefficients.

[0086] Step 1.3: Establish a kinematic model based on the dynamic model, and联立 the dynamic model and the kinematic model to obtain the kinematic parameters of the aircraft in the inertial system, including: the ballistic inclination angle θ of the aircraft, the attitude angular rate ω z 、the center of mass position (x, z), the flight speed V, the flight Mach number Ma, the flight angle of attack α, the normal overload A zm .

[0087] In this embodiment, such as Figure 3 As shown, the geometric relationship of the missile-target engagement mathematical model is expressed as the geometric relationship between the line-of-sight angle, velocity, and normal acceleration between the missile and the target in inertial space. In this embodiment, M and T represent the missile and the target, respectively; LOS represents the line of sight; R is the missile-target distance; q is the missile-target line-of-sight angle; θ is the trajectory inclination angle of the aircraft; θ T α is the target trajectory inclination angle. M and α T These represent the normal overload of the missile and the target, respectively.

[0088] The equations of the combined dynamic and kinematic models are expressed as follows:

[0089]

[0090] Where P is the engine thrust; g is the acceleration due to gravity; m is the missile mass; m c The amount of fuel consumed per second by the missile; a v The speed of sound at the local location; A zm For missile normal overload; ω is the rate of change of the angle of attack of the flight. z This refers to the attitude angular rate; J is the rate of change of attitude angular velocity; z denoted as , where x is the moment of inertia of the missile body rotating about its pitch axis; x is the horizontal position of the missile; and z is the vertical position of the missile.

[0091] In this embodiment, the model parameters are set according to the reasonable parameters of the actual missile system. Since the simulated aircraft is a medium-to-short-range surface-to-air missile, the thrust of the aircraft is set to P = 15kN, the thrust duration is 15s, and the gravitational acceleration is set to g = 9.8m / s². 2 The initial mass of the missile is m = 204 kg, and the fuel consumption per second is m. c =6kg / s, characteristic reference area S of axisymmetric aircraft ref =0.0409m 2 The diameter d of an axisymmetric projectile ref =0.2286m, the moment of inertia J of the projectile rotating about its pitch axis z = 247.4366 kg·m 2 .

[0092] Step 2: Establish an environmental model, autopilot, and rudder system model based on the aircraft's usage requirements. Connect the output interfaces of the environmental model and the rudder system model to the input interface of the dynamics model. Input the aircraft's kinematic parameters into the autopilot and connect the autopilot's output interface to the input interface of the rudder system model. Use the autopilot's output to control the rudder system model.

[0093] It should be noted that since different aircraft require different models when in use, for the aircraft to be used in this embodiment, the atmospheric environment, autopilot, rate gyroscope and rudder control system are modeled according to the usage requirements of the aircraft, and the environmental model, autopilot and rudder system models are built.

[0094] Step 2.1: Construct an environment model and output the local speed of sound a from the environment model. v The atmospheric density ρ is provided to the dynamic model.

[0095] The environment model is represented as follows:

[0096]

[0097] Where T0 is the absolute temperature at sea level; ρ0 is the atmospheric density at sea level; P0 is the atmospheric static pressure at sea level; h is the current altitude of the aircraft; T is the local atmospheric temperature; ρ is the atmospheric density; P n The local atmospheric static pressure; a v The speed of sound is the local speed; L represents the temperature lapse rate; R k γ represents the characteristic gas constant; γ is the air adiabatic index.

[0098] Step 2.2: Construct the autopilot based on kinematic parameters, obtain the mathematical model of the three-loop nonlinear autopilot, and output the rudder deflection angle command δ. f .

[0099] The mathematical model of the three-loop nonlinear autopilot is expressed as follows:

[0100] δ f =K∫u q dt-KK a ∫A zm dt+K I ∫ω z dt+K g ω z -K as (δ f0 -δ l (6)

[0101] Where δ f For rudder deflection commands; K, K a K I K g All are variable control gains; K as For feedforward anti-saturation gain; u q For missile normal overload command; δ f0 -δ l This refers to the amount by which the instruction exceeds the maximum rudder deflection angle.

[0102] In this embodiment, the designed autopilot utilizes the missile's normal acceleration and attitude angular rate information measured by the aircraft's onboard rate gyroscope, combined with variable gain, to generate a stable response, enabling it to robustly track control commands. The autopilot is then established within a nonlinear model. The controller gain in the autopilot needs to be adjusted based on the aircraft's flight altitude, angle of attack, and Mach number. Simulink is used to derive a linear state-space model for testing the autopilot under different dynamic environments.

[0103] Step 2.3: Construct the rudder system model and use the rudder deflection command δ f The rudder system model is controlled to calculate the rudder deflection angle δ and provide it to the dynamic model.

[0104] The rudder system model is represented as follows:

[0105]

[0106] Where s is the Laplace operator; ξ is the ratio of the output to the input of the rudder deflection angle; ξ is the equivalent damping ratio; ω n It is the undamped natural frequency.

[0107] In this embodiment, the rudder system model is a servo motor controlled by angular rate and with angle feedback. The rudder system also includes a rudder deflection angle limiter and a rudder deflection angular rate limiter, which control the deflection of the rudder surface according to the drive signal output by the autopilot. By designing the parameters of the rudder system transfer function, a mathematical model of the rudder system transfer function is established according to formula (7) to obtain the desired bandwidth and performance. According to the rudder system parameters of the aircraft in this embodiment, the equivalent damping ratio of the rudder system is set to ξ = 0.707, and the natural frequency is set to ω. n =150Hz.

[0108] Step 3: Set semi-physical parameters, construct a seeker model consisting of a detector antenna module, a radar antenna servo frame module, and a parasitic loop, and connect the seeker model to the kinematic model;

[0109] The semi-physical specifications include: seeker antenna detection range, main lobe beamwidth, typical target acquisition range, and projectile-target velocity.

[0110] Step 3.1: Set up semi-physical parameters and build a detector antenna module to simulate the search and acquisition process of the seeker in the seeker model, including: missile-target distance detection module, relative velocity detection filter and offset angle filter module;

[0111] In this embodiment, based on the parameters of the seeker model designed according to the semi-physical specifications, a detector antenna module is established, including: a projectile-target distance detection module, used to calculate the projectile-target distance R; and a relative velocity detection filter, used to differentiate the projectile-target distance R and filter the output to obtain the projectile-target relative velocity. The offset angle filter module is used to filter the offset angle signal. By simplifying the model of the seeker, such as a radar seeker, parameters such as the detection beamwidth, acquisition range, and velocity filter bandwidth are obtained to form the various subsystems in the seeker model.

[0112] In this embodiment, based on the parameters of an existing semi-physical model for teaching, the semi-physical specifications are set as follows: seeker antenna detection range, i.e., the servo frame can swing at an angle of ±30° from the center of the projectile axis; main lobe beamwidth of 0.8°; and target acquisition distance d. l =15km, the bandwidth of the relative velocity detection filter is ω b =7Hz, offset angle filter bandwidth ω h =2.65Hz; both the velocity filter and the offset angle filter are set to a first-order inertial element; if other aircraft models are to be built, other indicators can also be used to build the seeker, and the built seeker model can be verified by simulation to see if it meets the guidance requirements of the missile.

[0113] Step 3.2: Set the tracking loop time constant t and loop crossover frequency t of the seeker. s The natural frequency ω of a stable loop rate gyroscope ng A radar antenna servo frame module is constructed in the elevation plane to obtain mathematical models of the stabilization loop and the tracking loop.

[0114] In this embodiment, the tracking loop time constant, loop crossover frequency, and offset angle filter bandwidth of the tracker (i.e., the tracking loop) and the natural frequency of the stable loop rate gyroscope are determined by hardware-in-the-loop simulation.

[0115] In this embodiment, the radar antenna servo frame module is a sub-module of the seeker model. The core of the seeker is a radar dish antenna controlled by a servo motor, namely the seeker dish. The radar antenna servo frame can control the radar antenna to deflect in the elevation plane. The seeker has two states: stable state and tracking state. In the stable state, no matter how the projectile rotates, the stabilization loop must control the radar antenna to remain stable in inertial space. After the radar is powered on, the tracking loop controls the antenna to rotate. In the tracking state, the radar antenna has detected and locked onto the target. The radar antenna servo frame must control the radar antenna to always track the target and prevent the target from escaping the radar main lobe beam.

[0116] Specifically, for a frame-type seeker, the servo frame model includes two parts: a stabilization loop and a tracking loop; for a strapdown seeker, there is no servo frame, and this part of the modeling can be omitted.

[0117] Set the seeker tracking loop time constant t = 0.05s, and the loop crossover frequency t s =125.67Hz, the natural frequency ω of a steady-loop rate gyroscope. ng =628.32Hz.

[0118] The mathematical models for the stabilizing loop and the tracking loop are expressed as follows:

[0119] The angle of the guide head servo frame As the control variable, transfer function models for the stable loop and the tracking loop are established:

[0120]

[0121] Where s is the Laplace operator; For the guide head servo frame angle command; The ratio of the output to the input pull change of the seeker servo frame angle;

[0122] Step 3.3: Model the parasitic loop of the seeker, incorporate the parasitic loop into the mathematical models of the stable loop and the tracking loop, and adjust the tracking loop time constant t and loop crossover frequency t. s The natural frequency ω of a stable loop rate gyroscope ng and the bandwidth ω of the offset angle filter h To reduce interference signals during the movement of the radar antenna servo frame, a well-constructed seeker model is obtained;

[0123] In this embodiment, the parasitic loop is caused by the aberration of radar waves refracted by the radar-transparent material used in the missile's nose cone radome. This aberration introduces a linear error into the servo frame angle control of the seeker. That is, in this parasitic loop, there is a linear relationship between the missile's line-of-sight angle and the servo frame control angle error caused by the aberration, and this linear proportionality coefficient is used as the parasitic loop gain k. r Set to k r =0.02. Considering that factors such as wire pulling, bearing friction, and servo platform control quality will cause interference in the movement of the radar antenna servo frame, this parasitic loop is introduced into the models of the stable loop and tracking loop established in step 3.2, and formula (8) is rewritten as:

[0124]

[0125] Where k r This is the parasitic loop gain, i.e., the linear proportional gain;

[0126] Step 3.4: Calculate the missile-target line-of-sight angular rate based on the seeker model.

[0127] The line-of-sight rate of the bullet Calculate according to formula (10):

[0128]

[0129] Step 4: Determine the guidance strategy and build a guidance computer. The guidance computer outputs missile normal overload commands to the autopilot model, and the guidance computer is connected to the seeker model built in Step 3. The guidance computer adjusts the seeker's working mode according to the guidance strategy, and the seeker switches the aircraft's flight state according to the state of the tracked target. In addition, a simplified model of the missile detonation system is built and an initiation strategy is set. The miss distance is calculated, and the aircraft user evaluates the miss distance of the guidance process based on the miss distance. The missile detonation system model is then nested into the guidance computer.

[0130] In this embodiment, the guidance strategy is as follows: since the flight state of the aircraft is divided into a cruise phase and a terminal guidance phase, the guidance computer determines whether the seeker's working state is a search state or a closed-loop tracking state based on the aircraft's flight state; after the aircraft takes off, when the aircraft is in the cruise phase, the guidance computer sends periodic seeker servo frame angle commands to the seeker model. and utilize The seeker antenna frame angle is controlled to periodically oscillate within ±30°, thereby searching for the target by oscillating the target; once the target falls within the antenna main lobe beam range, and the missile-target distance is less than the acquisition distance d, the seeker will search for the target. l When the seeker detects a target, it immediately switches to closed-loop tracking mode, and its tracking loop controls the antenna to align with the target direction. After establishing stable tracking, the missile-target line-of-sight angular rate is calculated according to formula (10). The data is then output to the guidance computer, which simultaneously controls the aircraft to enter the terminal guidance phase. During the terminal guidance phase, if the seeker loses the target, it controls the aircraft to re-enter the cruise phase. The guidance computer determines that terminal guidance has ended and searches for the target again using the above method until the target is detected again or the simulation time runs out.

[0131] In this embodiment, the cruise guidance law during the seeker's search phase is set to a simple gravity acceleration cruise, that is, ensuring that the normal overload is 0 and the missile maintains level flight, at which time the seeker is searching for the target; other guidance laws can be used when establishing other models.

[0132] After the seeker detects the target, it enters the terminal guidance phase. At this time, the H∞ guidance law based on the line-of-sight angular rate is established as the optimal guidance law for the terminal guidance phase.

[0133] The mathematical model of the H∞ guidance law based on the line-of-sight angular rate is expressed as follows:

[0134]

[0135] Where R is the target distance; q is the target line-of-sight angle; u q This is a missile normal overload command, used as a system control variable to control the autopilot; w q External disturbance term;

[0136] And there is formula (12):

[0137]

[0138] Where v M v is the missile velocity; θ is the trajectory inclination angle of the spacecraft; T θ represents the target velocity. T The target trajectory inclination angle; v T -v M Considered as the relative velocity between the projectile and the target That is, the rate of change of the distance between the projectile and the target;

[0139] In this embodiment, the guidance computer model is mainly responsible for switching between the cruise search state and the closed-loop tracking state of the guidance system. The guidance decision machine is built using the Stateflow state machine model in the Simulink toolbox. The guidance decision machine has two states: cruise state and closed-loop tracking state. Cruise state refers to the aircraft flying according to the cruise guidance law during the seeker search phase. Closed-loop tracking state refers to the aircraft flying according to the optimal guidance law in the terminal guidance phase after the seeker establishes closed-loop tracking. The switching of the above state modes is triggered by events generated inside the Stateflow state machine model. By changing the values ​​of the variables passed to the guidance decision machine, the guidance computer is controlled to execute different normal overload commands.

[0140] In this embodiment, the warhead system, i.e., the fuse and warhead system, determines whether the warhead should disengage and detonate based on the relative distance between the projectile and the target measured by the seeker. The strategy for this process is as follows: the warhead system simultaneously detects the rate of change of the projectile-target distance in real time. When the projectile-target distance is less than the preset effective kill range, and the relative velocity between the projectile and the target is... When the value is greater than 0, that is, when the missile and the target begin to move away from each other, it is determined that this is the closest point between the missile and the target, and the missile can be detonated, the simulation stops, and the missile-target distance at the time of detonation is taken as the closest distance between the missile trajectory and the target. This distance is also called the "miss distance", which is used as an indicator to evaluate the quality of the guidance process.

[0141] Step 5: Based on the mission requirements of the aircraft, build a target motion model. By setting the target motion azimuth, target overload limit, and target random maneuver strategy, calculate the target-missile distance R and target-missile line-of-sight angle q, and output them to the seeker model built in Step 3; simultaneously, calculate the target trajectory inclination angle θ. T and velocity v T The seeker model is input into the guidance computer; a 3-DOF visual kinematic model is constructed, and the outputs of the target motion model and the kinematic model are used as inputs to the 3-DOF visual kinematic model.

[0142] In this embodiment, the parameters output from the target motion model and the aircraft motion parameters are input together into the 3-DOF visualized kinematic model to generate the corresponding ballistic trajectory. Based on the aircraft's mission requirements, the target is set to be a stationary target, a target moving in a uniform straight line, a target with variable maneuverability, or a supersonic high-maneuverability target, and parameters such as the target's speed, available overload, turning rate, and maneuvering strategy are set.

[0143] The target motion model is used to output the target's position in the inertial frame. It generates the target's trajectory by setting the target's azimuth, overload limit, and random maneuver strategy. The target azimuth includes the target trajectory inclination angle θ. T and the target's velocity v T ; Set the target trajectory inclination angle θ T and the target's velocity v T These two parameters are input into the guidance computer in step 4 through the seeker model to provide the information required for guidance.

[0144] The 3-DOF visualization kinematic model is used to receive the target position (x) output by the target motion model. T ,z T ), target velocity V T Target-target distance R, target trajectory inclination angle θ T The system simulates the process of a guided aircraft striking a target in real time, using kinematic parameters such as attitude angle θ, center of mass position (x,z), flight speed V, and angle of attack α.

[0145] In this embodiment, the 3-DOF visualized kinematic model receives the missile's kinematic parameters from step 1, including: attitude angle θ, center of mass position (x, z), flight velocity V, and angle of attack α, as well as the target's kinematic parameters, including: target position (x, z). T ,z T ), target velocity v TThe target distance R is calculated, and an s-function is used to visualize the size and appearance of the aircraft to generate a visual motion model for real-time simulation of the guided aircraft striking the target.

[0146] Step 6: Connect all the above models, determine the mission conditions and parameter settings of the aircraft, simulate the process of the aircraft attacking the target, and calculate the ballistic trajectory, required overload and actual overload, instantaneous miss distance, flight angle of attack, flight Mach number, and rudder deflection parameters in real time; check the performance of the aircraft's GNC system according to the mission requirements of the aircraft. If the performance of the aircraft's GNC system does not meet the standards, the models in steps 1-5 need to be checked and modified, and the process should be returned to step 1 until the performance meets the standards.

[0147] In this embodiment, such as Figure 1 As shown, the GNC system of the aircraft is obtained by connecting the dynamic model, kinematic model, environmental model, rudder system model, seeker model, autopilot, target motion model, 3-DOF visual motion simulation model and guidance computer. The performance of the aircraft GNC system is tested according to the mission requirements of the aircraft. Each aircraft has different evaluation criteria according to its own situation. The general evaluation criteria are whether it can fly stably, whether it can accurately and quickly track control commands after stabilizing flight, whether it can hit the target, whether the miss distance when hitting the target meets the requirements, or whether the trajectory is within the usable overload. If the performance of the aircraft GNC system does not meet the standards, the operator needs to check whether there are any missing parameters or input errors in the model in steps 1-5 and make corrections and adjustments. After checking and confirming that there are no errors, return to step 1 until the performance meets the standards.

[0148] In this embodiment, the initial conditions for the aircraft and the target are set as follows:

[0149] In the inertial coordinate system, with (0,0) as the origin, the missile launches from point (0,0) with an initial trajectory inclination angle θ = 70°; the target velocity v T =328m / s, performing a serpentine maneuver with a maximum normal overload of 3g and a frequency of 0.3rad / s, the initial horizontal distance to the target is x. T =20.5km, vertical height z T =8km, initial target trajectory inclination angle θ T =180°;

[0150] from Figure 4 As can be seen, the GNC system successfully guided the aircraft to rendezvous with the target, and the trajectory was smooth throughout, verifying the reliability of the GNC system.

[0151] Figure 5 The figure shows the curves of the missile’s commanded normal acceleration and actual value, flight angle of attack, flight Mach number and rudder deflection angle over time in this embodiment.

[0152] Furthermore, from Figure 5 As can be seen from (a), the guidance commands given by the guidance computer in the GNC system of the aircraft in this embodiment are in good agreement with the actual response of the missile body, and the designed autopilot can track the commands well; from Figure 5 As can be seen from (b), the average angle of attack throughout the flight is not large, and the maximum angle of attack during flight is 15.4°, at which point good control performance is still maintained; from Figure 5 As can be seen from (c), the maximum Mach number throughout the flight was 3.4 Mach, reaching its maximum speed at the end of the 15th second when the engine ceased operation. The final speed upon impact with the target was 2.65 Mach, and the final miss distance was 1.22m. Figure 5 As can be seen in (d), the maximum rudder deflection angle occurs during the rapid turn in level flight after the missile takes off. Subsequently, the autopilot outputs a stable rudder deflection angle command, and the rudder deflection angle remains within the usable limit when approaching the target, thus meeting the guidance requirements.

[0153] In this embodiment, such as Figure 6 As shown in the figure, the changes in attitude, angle of attack, and velocity of the aircraft during flight, as well as the guided trajectory status when encountering the target, can be observed in real time. The autopilot gain can then be adjusted based on the aircraft's attitude response throughout the trajectory to better track the guidance computer's guidance commands. Simultaneously, the aircraft's aerodynamic characteristics can be directly adjusted in the adjacent interpolation tables in the Simulink workspace, such as drag coefficient, lift coefficient, pitch moment coefficient, rudder deflection drag coefficient, rudder deflection lift coefficient, and rudder deflection pitch moment coefficient.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A visualization modeling method for a vehicle GNC system integrating dynamics, characterized in that, Includes the following steps: Step 1: Set the parameters and aerodynamic coefficients of the aircraft, establish the dynamic model of the aircraft and determine the output parameters of the dynamic model, open the input interface of the dynamic model, use the output parameters of the dynamic model to establish the kinematic model, and output the kinematic parameters of the aircraft. Step 2: Establish an environmental model, autopilot, and rudder system model according to the aircraft's usage requirements. Connect the output interfaces of the environmental model and the rudder system model to the input interface of the dynamics model. Input the aircraft's kinematic parameters into the autopilot and connect the autopilot's output interface to the input interface of the rudder system model. Use the autopilot's output to control the rudder system model. Step 3: Set semi-physical parameters, construct a seeker model consisting of a detector antenna module, a radar antenna servo frame module, and a parasitic loop, and connect the seeker model to the kinematic model; Step 4: Determine the guidance strategy and build a guidance computer. The guidance computer outputs missile normal overload commands to the autopilot model, and the guidance computer is connected to the seeker model built in Step 3. The guidance computer adjusts the seeker's working mode according to the guidance strategy, and the seeker switches the aircraft's flight state according to the state of the tracked target. In addition, a simplified model of the missile detonation system is built and a detonation strategy is set to calculate the miss distance. The aircraft user evaluates the miss distance of the guidance process based on the miss distance, and the missile detonation system model is nested into the guidance computer. Step 5: According to the task requirements of the aircraft, the target motion model is built, the missile-target distance R and the missile-target line-of-sight angle q are calculated by setting the target motion orientation, the target overload limit and the target random maneuver strategy, and are output to the seeker model built in Step 3; at the same time, the target trajectory inclination θ T and the motion speed v T are input into the guidance computer through the seeker model; the 3-DOF visual kinematics model is constructed, and the outputs of the target motion model and the kinematics model are taken as the inputs of the 3-DOF visual kinematics model; Step 6: Connect all the above models, determine the mission conditions and parameter settings of the aircraft, simulate the process of the aircraft attacking the target, and calculate the ballistic trajectory, required overload and actual overload, instantaneous miss distance, flight angle of attack, flight Mach number, and rudder deflection parameters in real time; check the performance of the aircraft's GNC system according to the mission requirements of the aircraft. If the performance of the aircraft's GNC system does not meet the standards, the models in steps 1-5 need to be checked and modified, and the process should be returned to step 1 until the performance meets the standards.

2. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 1, characterized in that, Step 1 includes: Step 1.1: Set the parameters and aerodynamic coefficients of the aircraft, convert the parameters and aerodynamic coefficients to the vertical plane, and generate a data table; The parameters of the aircraft include: the mass of the aircraft, the size of the aircraft, the moment of inertia of the aircraft about each axis, the aerodynamic layout of the missile body, the reference area of ​​the missile body, the reference area of ​​the control surfaces, the flight Mach number range, the flight angle of attack range, the engine thrust curve and atmospheric environmental parameters, and various parameters of the autopilot adjustable gain table. The aerodynamic coefficients include the parameters in the aerodynamic coefficient table of the projectile body and the aerodynamic coefficient table of the control surfaces; Step 1.2: Perform dynamic modeling on the aircraft to obtain a three-degree-of-freedom dynamic model, and determine the output parameters of the dynamic model, including: drag, lift and pitching moment acting on the projectile; Step 1.3: Establishing the kinematics model according to the dynamics model, and solving the dynamics model and the kinematics model to obtain the kinematics parameters of the aircraft in the inertial system, including: the flight trajectory inclination angle θ, the attitude angular rate ω z , the center of mass position (x, z), the velocity V, the Mach number Ma, the flight angle of attack α, the missile normal overload A zm .

3. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 2, characterized in that, The mathematical model of the three-degree-of-freedom dynamic model is expressed as follows: where F x , F z , M represent the drag force, lift force and pitching moment acting on the elastic body respectively; C x , C z , C m are all dimensionless proportional coefficients, representing the drag coefficient, lift coefficient and pitching moment coefficient respectively, and the above three proportional coefficients are all related to the flight attack angle α, rudder deflection angle δ and flight Mach number Ma; S ref is the characteristic reference area; d ref ρ is the diameter of the axisymmetric projectile; ρ is the atmospheric density; V is the flight velocity; When the angle of attack and rudder deflection satisfy the non-stall condition and are within a controllable range, i.e. -20° < α < 20°, -30° < δ < 30°, and the flight Mach number Ma < 0.95, C x C z C m As shown in formula (2): Where C x0 Zero-lift drag coefficient; C z0 C represents the lift coefficient term for asymmetric aircraft conditions. m0 The zero pitch moment coefficient; This is the induced drag coefficient; This is the lift coefficient at the angle of attack; The pitch moment coefficient caused by the angle of attack; The drag coefficient is the rudder deflection angle. The lift coefficient is the rudder deflection angle. This is the pitch control moment coefficient; The distance from the projectile's focal point to its center of mass; When the flight Mach number satisfies 1.1 < Ma < 4, and the flight angle of attack and rudder deflection angle satisfy -20° < α < 20°, -30° < δ < 30°, the linear fitting curve is used to approximate the non-linear aerodynamic coefficient. According to formula (3), the lift coefficient and pitching moment coefficient are expressed as functions of the flight angle of attack and rudder deflection angle: Where a z b z c z d z a m b m c m d m All are dimensionless coefficients.

4. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 3, characterized in that, The said step 2 includes: Step 2.1: Construct an environment model and output the local speed of sound a from the environment model. v The atmospheric density ρ is provided to the dynamic model; Step 2.2: Construct the autopilot based on kinematic parameters, obtain the mathematical model of the three-loop nonlinear autopilot, and output the rudder deflection angle command δ. f ; Step 2.3: Construct the rudder system model and use the rudder deflection command δ f The rudder system model is controlled to calculate the rudder deflection angle δ and provide it to the dynamic model.

5. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 4, characterized in that, The mathematical model of the three-loop non-linear autopilot is expressed as: δ f =K∫u q dt-KK a ∫A zm dt+K I ∫ω z dt+K g ω z -K as (δ f0 -δ l ) (6) Where δ f For rudder deflection commands; K, K a K I K g All are variable control gains; K as For feedforward anti-saturation gain; u q For missile normal overload command; A zm For missile normal overload; ω z δ represents the attitude angular rate. f0 -δ l This refers to the amount by which the instruction exceeds the maximum rudder deflection angle.

6. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 5, characterized in that, The said step 3 includes: Step 3.1: Set the semi-physical index, establish the detector antenna module to simulate the search and capture process of the seeker in the seeker model, including: the missile-target distance detection module, the relative velocity detection filter and the misalignment angle filter module; The projectile-target distance detection module is used to calculate the projectile-target distance R; the relative velocity detection filter is used to differentiate the projectile-target distance R and filter the output to obtain the projectile-target relative velocity. The offset angle filter module is used to filter the offset angle signal; Step 3.2: Set the tracking loop time constant t and loop crossover frequency t of the seeker. s The natural frequency ω of a stable loop rate gyroscope ng A radar antenna servo frame module is constructed in the elevation plane to obtain mathematical models of the stabilization loop and the tracking loop. Step 3.3: Model the parasitic loop of the seeker, incorporate the parasitic loop into the mathematical models of the stable loop and the tracking loop, and adjust the tracking loop time constant t and loop crossover frequency t. s The transfer function and natural frequency ω of a steady-loop rate gyroscope ng and the bandwidth ω of the offset angle filter h To reduce interference signals during the movement of the radar antenna servo frame, a well-constructed seeker model is obtained; Step 3.4: Calculate the missile-target line-of-sight angular rate based on the seeker model.

7. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 6, characterized in that, The mathematical models of the stabilization loop and the tracking loop described in step 3.2 are expressed as: Guide head servo angle As the control variable, transfer function models for the stable loop and the tracking loop are established: Where s is the Laplace operator; For the guide head servo frame angle command; It is the ratio of the output angle of the seeker servo frame to the input angle.

8. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 7, characterized in that, The model obtained by introducing the parasitic loop into the mathematical models of the stabilization loop and the tracking loop in step 3.3 is: Where k r This is the parasitic loop gain.

9. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 8, characterized in that, The said step 4 also includes: during the process of determining the guidance strategy, the flight state of the aircraft is divided into the cruise stage and the terminal guidance stage. The optimal guidance law of the aircraft in the terminal guidance stage is the H∞ guidance law designed based on the line-of-sight angle rate. The mathematical model of the H∞ guidance law designed based on the line-of-sight angle rate is expressed as: Where R is the target distance; q is the target line-of-sight angle; u q This is a missile normal overload command, used as a system control variable to control the autopilot; w q External disturbance term; And there is formula (12): Where v M v is the missile velocity; θ is the trajectory inclination angle of the spacecraft; T θ represents the target velocity. T The target trajectory inclination angle; v T -v M Considered as the relative velocity between the projectile and the target Also known as the rate of change of bullet-target distance.

10. The visual modeling method for a vehicle GNC system based on fused dynamics according to claim 9, characterized in that, The 3-DOF visualized kinematic model is used to receive the target position (x) in the target motion model. T ,z T ), target velocity V T Target-target distance R, target trajectory inclination angle θ T The parameters, including attitude angle θ, center of mass position (x,z), flight speed V, and angle of attack α, are used to simulate the process of a guided aircraft striking a target in real time.

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