A weather simulation system based on a flight simulation system and a UE engine

Abstract

The present application relates to the field of flight simulation and virtual reality technology, in particular to a weather simulation system based on a flight simulation system and a UE engine; an aircraft meteorological environment simulation and visualization system based on QT meteorological modeling, DDS communication and Unreal Engine rendering, which realizes independent operation and real-time linkage of meteorological calculation and visualization rendering through modular decoupling design and high-performance data distribution mechanism, and dynamically and realistically reproduces complex and changeable weather environment in flight training, virtual display and meteorological visualization applications.

Description

Technical Field

[0001] This invention relates to the fields of flight simulation and virtual reality technology, and more specifically, to a weather simulation system based on a flight simulation system and a UE engine. Background Technology

[0002] With the rapid development of flight simulation, virtual training, and 3D visualization technologies, simulating weather changes in real-world environments has become a crucial component of flight simulation systems. Currently, most flight simulation systems integrate weather model calculations and rendering within the same engine (such as Unity or Unreal Engine, which directly controls weather parameters). While this approach enables basic weather change visualization in a standalone environment, it suffers from the following significant problems:

[0003] 1. Severe coupling between computation and rendering The meteorological calculation module is directly embedded in the rendering engine logic, with meteorological data and rendering threads sharing resources, resulting in a complex system architecture and poor maintainability. When new meteorological models or data interfaces need to be added, it is often necessary to modify the underlying engine code, limiting the system's scalability. Currently, most weather systems have a time delay between simulation calculations and visual updates, making it impossible to achieve millisecond-level parameter synchronization.

[0004] 2. Insufficient real-time performance and synchronization Especially in flight simulation, parameters such as wind speed, wind direction, and visibility need to interact with the aircraft dynamics model in real time; otherwise, the flight performance will be inconsistent with the visual environment.

[0005] 3. Difficulty in connecting with external data Existing meteorological modules typically lack data interfaces with external meteorological or simulation systems, making it difficult to flexibly access control signals from external meteorological models, real-time meteorological data, or other programs. This makes it difficult for the system to work collaboratively with professional meteorological simulation software (such as meteorological models written in MATLAB, Simulink, or QT).

[0006] 4. Insufficient grid-based and multi-terminal control capabilities Traditional stand-alone weather rendering systems mostly operate locally, lack standardized communication protocols, and cannot achieve multiple simulations. Meteorological data sharing between real nodes. In distributed flight simulation, ground station control, or virtual training network environments, it is impossible to guarantee the consistency of meteorological environments across different clients.

[0007] 5. Limited rendering details and low control precision Many systems achieve weather changes simply by switching parameters (such as enabling "rainy" or "foggy" materials), lacking fine-grained control over particle system intensity, wind direction, and lighting variations. They cannot achieve realistic physical representations such as "dynamic wind direction rotation over time," "fog density changes with altitude," or "lighting adjusts between day and night." Summary of the Invention

[0008] This invention addresses the problems of high architectural coupling, weak real-time synchronization capabilities, and lack of cross-platform communication and fine-grained visualization control in existing flight simulation weather systems. It proposes a weather simulation system based on a flight simulation system and a UE engine, which is an aircraft meteorological environment simulation and visualization system based on QT meteorological modeling, DDS communication, and Unreal Engine rendering. Through modular decoupling design and a high-performance data distribution mechanism, it realizes independent operation and real-time linkage of meteorological calculation and visualization rendering. It can dynamically and realistically reproduce complex and changeable weather environments in flight training, virtual display, and meteorological visualization applications.

[0009] The specific implementation details of this invention are as follows: A weather simulation system based on a flight simulation system and a UE engine, comprising a flight simulation subsystem and a UE simulation subsystem; The flight simulation subsystem includes a six-degree-of-freedom aerodynamic model, an automatic flight control model, an atmospheric model, and a navigation model; The six-degree-of-freedom aerodynamic model is used to simulate the aerodynamic characteristics of the UAV. All aerodynamic parameters are in coefficient form. The aerodynamic coefficients are interpolated based on the UAV's current speed, altitude, angle of attack, sideslip angle, angular velocity, center of gravity position, control surface positions, and landing gear positions to obtain aerodynamic lift, drag, side force, roll moment, pitch moment, and yaw moment. The various aerodynamic parameters of the UAV are in curve form, and the various aerodynamic coefficients of the UAV are obtained through interpolation calculation. The automatic flight control model is used to divide the UAV flight plan into 7 stages. The route and autopilot commands are only responded to during the cruise stage. When the system is initialized, the UAV is in the takeoff stage by default. When the flight control panel receives the command "release" and starts the engine, the UAV automatically executes the process from "takeoff" to "cruise". At this time, the UAV responds to the route and autopilot commands. The atmospheric model is used to calculate atmospheric data at the current altitude of the UAV, and the atmospheric data is calculated separately using a segmented calculation method. The navigation model is used to simulate the fact that the various software parts of the system need to obtain necessary data from many airborne systems, sensors and navigation systems. The flight simulation system simulates these data to calculate relevant information such as UAV barometric altitude, climb rate, static temperature, Mach number, indicated airspeed and vacuum speed. The UE simulation subsystem includes a meteorological environment rendering module and a meteorological particle rendering module; The meteorological environment rendering module is used to dynamically control the lighting, sky atmosphere, cloud effects and day-night cycle changes based on meteorological data to achieve realistic visualization of the weather environment in the scene. The meteorological particle rendering module is used to render rain, snow, dust, and fog weather effects in real time through a particle system, and adjust the particle direction, speed, and density based on wind field data.

[0010] To better realize the present invention, the construction of the meteorological particle rendering module further includes: The particle emission rate is calculated based on the basic emission rate of the particles, the set static intensity coefficient, the set dynamic intensity coefficient, the rate of change of intensity, the time step, and the severity of the weather.

[0011] To better realize the present invention, the construction of the meteorological particle rendering module further includes: Based on the particle's horizontal coordinates, vertical coordinates, vertical height coordinates, wind anisotropy coefficient, particle orientation angle, horizontal radial distance, reference particle density, vertical distribution standard deviation, and horizontal radial distribution standard deviation, a density distribution function in particle space is constructed.

[0012] To better realize the present invention, the construction of the meteorological particle rendering module further includes: constructing a turbulence model based on the amplitude coefficient of turbulence velocity, the reference turbulence intensity, the normalized noise field coefficient, and the nonlinear coefficient of turbulence variation with weather intensity.

[0013] To better realize the present invention, the construction of the meteorological particle rendering module further includes: The relationship between terminal speed and intensity is obtained based on the terminal speed when the weather intensity is 0 and the coefficient of terminal speed increasing with weather intensity. A particle velocity field model is constructed based on the ambient wind speed, the final falling velocity of particles relative to the air, and the velocity vector of random disturbances caused by turbulence.

[0014] To better realize the present invention, the construction of the six-degree-of-freedom aerodynamic model further includes: Calculate the lift coefficient based on the aerodynamic lift coefficient of the airframe itself, the lift coefficient generated by the change in pitch angle, the lift coefficient generated by the deflection of the rudder, and the lift coefficient generated by the deflection of the flaps; Calculate lift based on lift coefficient, atmospheric density, aircraft speed, and wing area.

[0015] To better realize this invention, further, establishing an aircraft dynamics model in the aircraft body coordinate system includes: Calculate the resultant torque based on the moment of inertia and the angular velocities of the three axes of the aircraft. Calculate the resultant force based on the total mass of the aircraft and the velocities of the three axes of the aircraft. Based on the aircraft's three-axis angular velocities, the quaternion representation is used to calculate the aircraft's attitude angles; Calculate the aircraft's vacuum speed, angle of attack, and yaw angle based on the aircraft's three axis velocities; Calculate the aircraft's latitude and longitude and altitude based on the initial latitude and longitude, initial altitude, UAV speed, and attitude angle.

[0016] To better realize the present invention, the construction of the atmospheric model further includes: Calculate the atmospheric temperature based on atmospheric altitude and average sea-level air temperature; Calculate the atmospheric pressure value based on atmospheric temperature and atmospheric altitude; Calculate atmospheric density based on atmospheric pressure, atmospheric temperature, and atmospheric altitude.

[0017] To better realize the present invention, the navigation model further includes an atmospheric data model, an inertial reference model, a radio altimeter model, and a satellite navigation model; The atmospheric data model is used to calculate the UAV's barometric altitude, climb rate, static temperature, Mach number, indicated airspeed, and vacuum speed. The inertial reference model is used to calculate the UAV's attitude, angle of attack, and sideslip angle using the quaternion method based on the aircraft's three-axis angular velocities. The radio altimeter model is used to calculate the radio altitude of the UAV based on the UAV's actual altitude and terrain elevation data. The satellite navigation model is used to integrate the speed of the UAV using the geodetic coordinate system to obtain the displacement relative to the geodetic coordinate system. This displacement is then added to the initial position coordinates of the UAV and converted to a new coordinate system to obtain the current geographical location.

[0018] To better realize the present invention, the meteorological data further includes time and date, weather type; and data communication is established through DDS, and the specific weather type and day / night time are controlled according to the SSS-WEATHER-STA data packet name, WeatherType field, date field, and Time field.

[0019] The present invention has the following beneficial effects: This invention achieves independent operation and real-time linkage between meteorological calculation and visualization rendering through modular decoupling design and high-performance data distribution mechanism. It can dynamically and realistically reproduce complex and ever-changing weather environments in flight training, virtual display and meteorological visualization applications. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of a rainy daytime event provided for an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of nighttime flight provided for an embodiment of the present invention.

[0022] Figure 3 A schematic diagram of flight in a foggy environment provided for an embodiment of the present invention.

[0023] Figure 4 A schematic diagram of flight at dusk and dawn provided for an embodiment of the present invention. Detailed Implementation

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments, and therefore should not be regarded as a limitation on the scope of protection. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set up," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0026] Example 1: This embodiment proposes a weather simulation system based on a flight simulation system and a UE engine, including a flight simulation subsystem and a UE simulation subsystem; The flight simulation subsystem includes a six-degree-of-freedom aerodynamic model, an automatic flight control model, an atmospheric model, and a navigation model; The six-degree-of-freedom aerodynamic model is used to simulate the aerodynamic characteristics of the UAV. All aerodynamic parameters are in coefficient form. The aerodynamic coefficients are interpolated based on the UAV's current speed, altitude, angle of attack, sideslip angle, angular velocity, center of gravity position, control surface positions, and landing gear positions to obtain aerodynamic lift, drag, side force, roll moment, pitch moment, and yaw moment. The various aerodynamic parameters of the UAV are in curve form, and the various aerodynamic coefficients of the UAV are obtained through interpolation calculation. The automatic flight control model is used to divide the UAV flight plan into 7 stages. The route and autopilot commands are only responded to during the cruise stage. When the system is initialized, the UAV is in the takeoff stage by default. When the flight control panel receives the command "release" and starts the engine, the UAV automatically executes the process from "takeoff" to "cruise". At this time, the UAV responds to the route and autopilot commands. The atmospheric model is used to calculate atmospheric data at the current altitude of the UAV, and the atmospheric data is calculated separately using a segmented calculation method. The navigation model is used to simulate the fact that the various software parts of the system need to obtain necessary data from many airborne systems, sensors and navigation systems. The flight simulation system simulates these data to calculate relevant information such as UAV barometric altitude, climb rate, static temperature, Mach number, indicated airspeed and vacuum speed. The UE simulation subsystem includes a meteorological environment rendering module and a meteorological particle rendering module; The meteorological environment rendering module is used to dynamically control the lighting, sky atmosphere, cloud effects and day-night cycle changes based on meteorological data to achieve realistic visualization of the weather environment in the scene. The meteorological particle rendering module is used to render rain, snow, dust, and fog weather effects in real time through a particle system, and adjust the particle direction, speed, and density based on wind field data.

[0027] Working principle: This embodiment provides a deeply coupled, two-way interactive weather simulation system to ensure absolute synchronization between flight physics and visual performance, providing pilots with a comprehensive and highly immersive training environment; through modular decoupling design and high-performance data distribution mechanism, it realizes independent operation and real-time linkage between meteorological calculation and visualization rendering, and can dynamically and realistically reproduce complex and ever-changing weather environments in flight training, virtual display and meteorological visualization applications.

[0028] like Figure 1 , Figure 2 , Figure 3 , Figure 4 As shown, the aircraft meteorological environment simulation and visualization system based on QT meteorological modeling, DDS communication and Unreal Engine rendering achieves independent operation and real-time linkage of meteorological calculation and visualization rendering through modular decoupling design and high-performance data distribution mechanism. It can dynamically and realistically reproduce complex and changeable weather environments in flight training, virtual display and meteorological visualization applications.

[0029] Example 2: This embodiment, based on the above embodiment 1, illustrates a six-degree-of-freedom aerodynamic model using a specific example.

[0030] The construction of the six-degree-of-freedom aerodynamic model includes: Calculate the lift coefficient based on the aerodynamic lift coefficient of the airframe itself, the lift coefficient generated by the change in pitch angle, the lift coefficient generated by the deflection of the rudder, and the lift coefficient generated by the deflection of the flaps; Calculate lift based on lift coefficient, atmospheric density, aircraft speed, and wing area.

[0031] Establishing an aircraft dynamics model in the aircraft body coordinate system includes: Calculate the resultant torque based on the moment of inertia and the angular velocities of the three axes of the aircraft. Calculate the resultant force based on the total mass of the aircraft and the velocities of the three axes of the aircraft. Based on the aircraft's three-axis angular velocities, the quaternion representation is used to calculate the aircraft's attitude angles; Calculate the aircraft's vacuum speed, angle of attack, and yaw angle based on the aircraft's three axis velocities; Calculate the aircraft's latitude and longitude and altitude based on the initial latitude and longitude, initial altitude, UAV speed, and attitude angle.

[0032] Working Principle: A six-degree-of-freedom aerodynamic model is used to simulate the aerodynamic characteristics of unmanned aerial vehicles (UAVs). All aerodynamic parameters are expressed in coefficient form. To simulate the nonlinear characteristics of aerodynamics, all aerodynamic parameters are expressed in coefficient form. Based on the UAV's current speed, altitude, angle of attack, sideslip angle, angular velocity, center of gravity position, and the positions of each control surface and landing gear, aerodynamic coefficients are interpolated to obtain aerodynamic lift, drag, side force, roll moment, pitch moment, yaw moment, etc. The various aerodynamic parameters of the UAV are in curve form and need to be obtained through software input, followed by interpolation calculations to obtain the various aerodynamic coefficients of the UAV.

[0033] Aerodynamic forces are divided into drag, side force, and lift, while aerodynamic moments are roll moment, pitch moment, and yaw moment. Taking lift calculation as an example, the formula for calculating lift L is as follows:

[0034] In the formula: —Atmospheric density; V – Aircraft speed; S—wing area; — Lift coefficient.

[0035] Lift coefficient The lift coefficient is calculated using the following formula:

[0036] In the formula: —The aerodynamic lift coefficient of the airframe itself; —The lift coefficient that generates lift from changes in pitch angle; —The lift coefficient generated by rudder deflection; —The lift coefficient generated by flap deflection.

[0037] Each aerodynamic coefficient was calculated using the same interpolation method. The data values ​​were modified based on the performance data of the Cloud Shadow UAV to make the model fit the performance of the Cloud Shadow UAV as closely as possible.

[0038] The aircraft's state parameters are calculated using a six-degree-of-freedom (6DOF) dynamic model. Employing the 6DOF equations of motion, the model accurately simulates the aircraft's motion response under aerodynamic forces and moments, ground reaction forces and moments, and engine forces and moments, thus calculating the flight state parameters. The dynamic equations are established in the aircraft's body coordinate system, and all external forces and moments are calculated in this system. The resultant forces and moments in the body coordinate system are then obtained.

[0039] Using the aircraft dynamics equations, the linear velocity and angular velocity in the body coordinate system are calculated. The aircraft dynamics equations are as follows:

[0040]

[0041] In the formula: —Moment of inertia; —The three-axis angular velocity of the machine body; —Resultant torque; —Total mass of the aircraft; —Aircraft three-axis speed; —Working together.

[0042] Based on the aircraft's three-axis angular velocity Using quaternion representation, the aircraft attitude angles can be calculated. The calculation formula is as follows:

[0043]

[0044] In the formula: It is a quaternion. These are the attitude angles: roll angle, pitch angle, and yaw angle.

[0045] Based on the linear velocity, the aircraft's vacuum speed, angle of attack, and yaw angle can be calculated.

[0046]

[0047] In the formula: For vacuum speed, angle of attack, and yaw angle.

[0048] The aircraft's latitude, longitude, and altitude are calculated from the initial latitude, longitude, initial altitude, UAV speed, and attitude angle.

[0049]

[0050]

[0051] In the formula: —Three-axis coordinates in a geocentric coordinate system; —Initial latitude, longitude, and altitude; , —Transformation matrix; —The average radius of the Earth; —Latitude, longitude, and altitude.

[0052] The other parts of this embodiment are the same as those in Embodiment 1 above, so they will not be described again.

[0053] Example 3: This embodiment, based on any one of Embodiments 1-2 above, provides a detailed description of the atmospheric model using a specific embodiment.

[0054] The construction of the atmospheric model includes: Calculate the atmospheric temperature based on atmospheric altitude and average sea-level air temperature; Calculate the atmospheric pressure value based on atmospheric temperature and atmospheric altitude; Calculate atmospheric density based on atmospheric pressure, atmospheric temperature, and atmospheric altitude.

[0055] Working principle: The atmospheric model is used to calculate atmospheric data at the current altitude of the UAV, such as current atmospheric pressure, current speed of sound, and current atmospheric density. Furthermore, considering the different atmospheric distributions in the troposphere and stratosphere, a segmented calculation method is used to calculate the atmospheric data separately.

[0056] The atmospheric model is used to calculate atmospheric data for the UAV at its current altitude, such as current atmospheric pressure, current speed of sound, and current atmospheric density. Furthermore, considering the different atmospheric distributions in the troposphere and stratosphere, a segmented calculation method is used to calculate the atmospheric data separately. Taking atmospheric temperature as an example:

[0057] In the formula: T—Atmospheric temperature (K); h — altitude (m); 288.16 — Average sea-level temperature; 0.0065 — On average, for every 1 meter of elevation gain, the atmospheric temperature decreases by 0.0065 K.

[0058] Atmospheric pressure value :

[0059] Atmospheric density :

[0060] The other parts of this embodiment are the same as any one of the above embodiments 1-2, so they will not be described again.

[0061] Example 4: This embodiment, based on any one of the above embodiments 1-3, provides a detailed description of the navigation model using a specific embodiment.

[0062] The navigation model includes an atmospheric data model, an inertial reference model, a radio altimeter model, and a satellite navigation model; The atmospheric data model is used to calculate the UAV's barometric altitude, climb rate, static temperature, Mach number, indicated airspeed, and vacuum speed. The inertial reference model is used to calculate the UAV's attitude, angle of attack, and sideslip angle using the quaternion method based on the aircraft's three-axis angular velocities. The radio altimeter model is used to calculate the radio altitude of the UAV based on the UAV's actual altitude and terrain elevation data. The satellite navigation model is used to integrate the speed of the UAV using the geodetic coordinate system to obtain the displacement relative to the geodetic coordinate system. This displacement is then added to the initial position coordinates of the UAV and converted to a new coordinate system to obtain the current geographical location.

[0063] The meteorological data includes time, date, and weather type; and data communication is established through DDS, with the specific weather type and day / night time controlled according to the SSS-WEATHER-STA data packet name, WeatherType field, date field, and Time field.

[0064] Working principle: The navigation model and various software components of the UAV simulation system require necessary data from numerous airborne systems, sensors, and navigation systems. Therefore, the flight simulation system simulates this data to calculate information such as UAV pressure altitude, climb rate, static temperature, Mach number, indicated airspeed, and vacuum speed. In other words, the atmospheric data system simulation calculates the UAV's flight parameters based on static pressure, total pressure, and total temperature.

[0065] (1) Atmospheric Data System (ADS) By establishing a mathematical model of atmospheric data, the system calculates information such as barometric altitude, climb rate, static temperature, Mach number, indicated airspeed, and vacuum speed of the UAV. In other words, the atmospheric data system simulation calculates the UAV's flight parameters based on static pressure, total pressure, and total temperature. Dynamic pressure, total pressure, and total temperature are calculated by the atmospheric model and the digital UAV.

[0066] Dynamic pressure :

[0067] vacuum speed :

[0068] Indicative airspeed :

[0069] Mach number :

[0070] (2) Inertial Reference System (IRS) Using quaternion algorithm

[0071] Calculate the drone's attitude:

[0072] Calculate the angle of attack and sideslip angle:

[0073] (3) Radio altimeter RA A radio altimeter uses radio waves to measure the vertical altitude of a drone above the ground. The radio altimeter simulation calculates the drone's radio altitude (0-5000ft) based on the drone's actual altitude and terrain elevation data.

[0074] (4) Satellite Navigation System (GPS) The GPS simulation calculates the real-time latitude and longitude of the UAV based on its position changes and the Earth model. The Earth model used is the WGS-84 model.

[0075] The navigation model is used to calculate the current geographical location (longitude, latitude, and altitude) of the UAV model. By integrating the UAV's velocity using the geodetic coordinate system, the displacement relative to the geodetic coordinate system is obtained. This displacement is then added to the UAV's initial position coordinates, and the coordinate system is converted to obtain the current geographical location.

[0076] The other parts of this embodiment are the same as any one of the embodiments 1-3 above, so they will not be described again.

[0077] Example 5: This embodiment describes the meteorological environment rendering module based on any one of the above embodiments 1-4.

[0078] The meteorological data includes time, date, and weather type; and data communication is established through DDS, with the specific weather type and day / night time controlled according to the SSS-WEATHER-STA data packet name, WeatherType field, date field, and Time field.

[0079] Working principle: The meteorological environment rendering module dynamically controls lighting, sky atmosphere, cloud effects and day-night cycle changes based on meteorological data to achieve realistic visualization of the weather environment in the scene.

[0080] Meteorological data includes time and date, weather type, and the data is transmitted from atmospheric model calculations.

[0081] Data communication is established using DDS communication, and the specific weather type and day / night time are controlled by the packet name SSS-WEATHER-STA and the WeatherType, date, and Time fields. The original time encoding is a compact decimal system, broken down into specific hours, minutes, seconds, and milliseconds for calculation. Step 1: Hourly Extraction (HH) Obtain the first two digits by dividing by 107107 (10000000). For example: 235959999 ÷ 10000000 = 23 (rounded down) Step 2: Minute Extraction (MM) First, divide 105105 (100000) to get the first four digits: 235959999 ÷ 100000 = 2359 Taking the modulo 100 again to get the last two digits: 2359 % 100 = 59 Step 3: Second Extraction (SS) First, divide 103103 by 1000 to get the first six digits: 235959999 ÷ 1000 = 235959 Taking the modulo 100 again to get the last two digits: 235959 % 100 = 59 Step 4: Millisecond extraction (mmm) Take the modulo 1000 directly to get the last three digits: 235959999 % 1000 = 999.

[0082] The other parts of this embodiment are the same as any one of the embodiments 1-4 above, so they will not be described again.

[0083] Example 6: This embodiment describes the meteorological particle rendering module based on any one of the above embodiments 1-5, using a specific embodiment.

[0084] The construction of the meteorological particle rendering module includes: The particle emission rate is calculated based on the basic emission rate of the particles, the set static intensity coefficient, the set dynamic intensity coefficient, the rate of change of intensity, the time step, and the severity of the weather.

[0085] The construction of the meteorological particle rendering module also includes: Based on the particle's horizontal coordinates, vertical coordinates, vertical height coordinates, wind anisotropy coefficient, particle orientation angle, horizontal radial distance, reference particle density, vertical distribution standard deviation, and horizontal radial distribution standard deviation, a density distribution function in particle space is constructed.

[0086] The construction of the meteorological particle rendering module also includes: constructing a turbulence model based on the amplitude coefficient of turbulence velocity, the baseline turbulence intensity, the normalized noise field coefficient, and the nonlinear coefficient of turbulence variation with weather intensity.

[0087] The construction of the meteorological particle rendering module also includes: The relationship between terminal speed and intensity is obtained based on the terminal speed when the weather intensity is 0 and the coefficient of terminal speed increasing with weather intensity. A particle velocity field model is constructed based on the ambient wind speed, the final falling velocity of particles relative to the air, and the velocity vector of random disturbances caused by turbulence.

[0088] Working principle: The meteorological particle rendering module renders weather effects such as rain, snow, dust, and fog in real time through a particle system, and adjusts the particle direction, speed, and density based on wind field data.

[0089] The WeatherDensity field in the wind field data communication field controls the severity of the weather; large changes in the value indicate severe rain or snow.

[0090] Particle emission rate calculation:

[0091] Parameter definition: This represents the base emission rate (the rate when W_d = 0.1). This represents the static intensity coefficient (particle density in a steady state). Indicates the dynamic intensity coefficient (sensitivity to intensity changes); Indicates the rate of change of intensity; Indicates the time step; It represents the severity of weather conditions and is a normalized dimensionless parameter with a value range of [0,1]. The intensity of weather not only affects the number of particles, but also the spatial distribution characteristics of particles.

[0092] Spatial density distribution function:

[0093] Physical meaning: Vertical distribution expansion: During heavy rainfall / snowfall, particles can reach higher altitudes; The horizontal coverage has expanded: severe weather now covers a wider area; Wind direction correlation: Particle distribution exhibits directionality during strong winds; Parameter definition: X: Horizontal coordinate (vertical along the wind direction), unit: meters; Y: Horizontal coordinate along the wind direction, in meters; Z: Vertical height coordinate, in meters; Wind direction anisotropy coefficient; Particle orientation angle; r: Horizontal radial distance; ρ0: Reference particle density; z: Standard deviation of vertical distribution, in meters. The vertical distribution range of particles increases with the increase of Wd. r: Standard deviation of horizontal radial distribution, in meters; the distribution range of particles in the horizontal direction, which increases with the increase of Wd. The motion characteristics of a particle are jointly controlled by four fields: windSpeed, windDirection, onFlowState, and gustState. Particle velocity field model:

[0094] Parameter definition: Ambient wind speed, measured in m / s, is the average wind speed provided by meteorological data and determines the overall drift velocity of particles. The final velocity of a particle relative to the air. : The velocity vector of random disturbances caused by turbulence, the random disturbances superimposed on the wind field, and the vector of disordered motion; Relationship between terminal velocity and intensity:

[0095] Parameter definition: Terminal velocity when Wd = 0; : A coefficient that controls the degree to which the terminal velocity increases with weather intensity; Turbulence model:

[0096]

[0097] Physical meaning: Terminal velocity increases with intensity: large raindrops / snowflakes fall faster; Turbulence intensity increases nonlinearly with intensity: particle motion is more chaotic during severe weather. When Wd>0.7, the turbulent component dominates, exhibiting the rotating updraft characteristic of storms; Parameter definition: The amplitude coefficient of turbulent velocity indicates the overall degree of turbulent disturbance; : Baseline turbulence intensity, the baseline velocity of atmospheric turbulence; : Nonlinear coefficient of turbulence variation with the severity of weather conditions; : Normalized noise field coefficients, simulating the spatiotemporal correlation and randomness of turbulence.

[0098] The other parts of this embodiment are the same as any one of the above embodiments 1-5, so they will not be described again.

[0099] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A weather simulation system based on a flight simulation system and a UE engine, characterized in that, Includes a flight simulation subsystem and a UE simulation subsystem; The flight simulation subsystem includes a six-degree-of-freedom aerodynamic model, an automatic flight control model, an atmospheric model, and a navigation model; The six-degree-of-freedom aerodynamic model is used to simulate the aerodynamic characteristics of the UAV. All aerodynamic parameters are in coefficient form. The aerodynamic coefficients are interpolated based on the UAV's current speed, altitude, angle of attack, sideslip angle, angular velocity, center of gravity position, control surface positions, and landing gear positions to obtain aerodynamic lift, drag, side force, roll moment, pitch moment, and yaw moment. The various aerodynamic parameters of the UAV are in curve form, and the various aerodynamic coefficients of the UAV are obtained through interpolation calculation. The automatic flight control model is used to divide the UAV flight plan into 7 stages. The route and autopilot commands are only responded to during the cruise stage. When the system is initialized, the UAV is in the takeoff stage by default. When the flight control panel receives the command "release" and starts the engine, the UAV automatically executes the process from "takeoff" to "cruise". At this time, the UAV responds to the route and autopilot commands. The atmospheric model is used to calculate atmospheric data at the current altitude of the UAV, and the atmospheric data is calculated separately using a segmented calculation method. The navigation model is used to simulate and demonstrate the system's need to obtain necessary data from the airborne system, sensors, and navigation system to calculate relevant information such as UAV barometric altitude, climb rate, static temperature, Mach number, indicated airspeed, and vacuum speed. The UE simulation subsystem includes a meteorological environment rendering module and a meteorological particle rendering module; The meteorological environment rendering module is used to dynamically control the lighting, sky atmosphere, cloud effects and day-night cycle changes based on meteorological data to achieve realistic visualization of the weather environment in the scene. The meteorological particle rendering module is used to render rain, snow, dust, and fog weather effects in real time through a particle system, and adjust the particle direction, speed, and density based on wind field data.

2. The weather simulation system based on a flight simulation system and a UE engine according to claim 1, characterized in that, The construction of the meteorological particle rendering module includes: The particle emission rate is calculated based on the basic emission rate of the particles, the set static intensity coefficient, the set dynamic intensity coefficient, the rate of change of intensity, the time step, and the severity of the weather.

3. A weather simulation system based on a flight simulation system and a UE engine according to claim 2, characterized in that, The construction of the meteorological particle rendering module also includes: Based on the particle's horizontal coordinates, vertical coordinates, vertical height coordinates, wind anisotropy coefficient, particle orientation angle, horizontal radial distance, reference particle density, vertical distribution standard deviation, and horizontal radial distribution standard deviation, a density distribution function in particle space is constructed.

4. A weather simulation system based on a flight simulation system and a UE engine according to claim 2, characterized in that, The construction of the meteorological particle rendering module also includes: constructing a turbulence model based on the amplitude coefficient of turbulence velocity, the baseline turbulence intensity, the normalized noise field coefficient, and the nonlinear coefficient of turbulence variation with weather intensity.

5. A weather simulation system based on a flight simulation system and a UE engine according to claim 4, characterized in that, The construction of the meteorological particle rendering module also includes: The relationship between terminal speed and intensity is obtained based on the terminal speed when the weather intensity is 0 and the coefficient of terminal speed increasing with weather intensity. A particle velocity field model is constructed based on the ambient wind speed, the final falling velocity of particles relative to the air, and the velocity vector of random disturbances caused by turbulence.

6. A weather simulation system based on a flight simulation system and a UE engine according to claim 2, characterized in that, The meteorological data includes time, date, and weather type; and data communication is established through DDS, with the specific weather type and day / night time controlled according to the SSS-WEATHER-STA data packet name, WeatherType field, date field, and Time field.

7. A weather simulation system based on a flight simulation system and a UE engine according to claim 1, characterized in that, The construction of the six-degree-of-freedom aerodynamic model includes: Calculate the lift coefficient based on the aerodynamic lift coefficient of the airframe itself, the lift coefficient generated by the change in pitch angle, the lift coefficient generated by the deflection of the rudder, and the lift coefficient generated by the deflection of the flaps; Calculate lift based on lift coefficient, atmospheric density, aircraft speed, and wing area.

8. A weather simulation system based on a flight simulation system and a UE engine according to claim 7, characterized in that, Establishing an aircraft dynamics model in the aircraft body coordinate system includes: Calculate the resultant torque based on the moment of inertia and the angular velocities of the three axes of the aircraft. Calculate the resultant force based on the total mass of the aircraft and the velocities of the three axes of the aircraft. Based on the aircraft's three-axis angular velocities, the quaternion representation is used to calculate the aircraft's attitude angles; Calculate the aircraft's vacuum speed, angle of attack, and yaw angle based on the aircraft's three axis velocities; Calculate the aircraft's latitude and longitude and altitude based on the initial latitude and longitude, initial altitude, UAV speed, and attitude angle.

9. A weather simulation system based on a flight simulation system and a UE engine according to claim 1, characterized in that, The construction of the atmospheric model includes: Calculate the atmospheric temperature based on atmospheric altitude and average sea-level air temperature; Calculate the atmospheric pressure value based on atmospheric temperature and atmospheric altitude; Calculate atmospheric density based on atmospheric pressure, atmospheric temperature, and atmospheric altitude.

10. A weather simulation system based on a flight simulation system and a UE engine according to claim 1, characterized in that, The navigation model includes an atmospheric data model, an inertial reference model, a radio altimeter model, and a satellite navigation model; The atmospheric data model is used to calculate the UAV's barometric altitude, climb rate, static temperature, Mach number, indicated airspeed, and vacuum speed. The inertial reference model is used to calculate the UAV's attitude, angle of attack, and sideslip angle using the quaternion method based on the aircraft's three-axis angular velocities. The radio altimeter model is used to calculate the radio altitude of the UAV based on the UAV's actual altitude and terrain elevation data. The satellite navigation model is used to integrate the speed of the UAV using the geodetic coordinate system to obtain the displacement relative to the geodetic coordinate system. This displacement is then added to the initial position coordinates of the UAV and converted to a new coordinate system to obtain the current geographical location.

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