Aircraft whole-process multi-field simulation and real-time comprehensive management system

Abstract

The invention relates to the field of aircraft simulation management, and discloses an aircraft full-process multi-field simulation and real-time comprehensive management system, which is used for solving the problem that normal aircraft change is misjudged as a program fault when an aircraft simulation task is carried out, and comprises the following steps: carrying out unified configuration of a simulation scene, generating a standardized configuration file, and storing the standardized configuration file into a database; the method comprises the following steps: completing three-dimensional scene construction and target dynamic modeling, obtaining an image frame, carrying out image frame preliminary anomaly judgment according to the image frame, if the image frame is judged to be abnormal, carrying out image frame actual anomaly judgment according to aircraft data, and if the image frame is judged to be abnormal, carrying out image frame marking and sending out an early warning. The aircraft operation state is dynamically adjusted according to the simulation control instruction, the aircraft operation state is transmitted to the visual display module, an image output and aircraft operation state graphical display interface is provided, the probability of false touch early warning, simulation process interruption and invalid sample output is effectively reduced, and the credibility and stability of a simulation result are improved.

Description

Technical Field

[0001] The present invention relates to the field of aircraft simulation management, and more specifically to an aircraft full-process multi-domain simulation and real-time integrated management system. Background Art

[0002] Aircraft management is a key technical support means in the development and test verification of high-end equipment such as aerospace, UAVs, missile weapon systems, etc. It is widely used in multiple stages such as aerodynamic design, structural analysis, flight control development, mission planning, environmental simulation, load verification, etc. of aircraft, involving multiple engineering fields such as aerodynamics, flight dynamics, control systems, navigation and guidance, and communication links.

[0003] In the process of aircraft development, in order to achieve digital support for the entire life cycle from initial scheme demonstration to prototype flight test, it is necessary to build a complex simulation system for multiple disciplines, multiple models, and multiple granularities to collaboratively complete tasks such as multi-domain information coupling modeling, dynamic response calculation, and system behavior verification. At the same time, with the promotion of the concepts of "digital prototype" and "digital twin", the simulation platform has gradually evolved from an "offline analysis tool" to a "real-time simulation and mission execution support platform."

[0004] In recent years, multi-domain joint simulation platforms and high-performance simulation engines have made great progress. In the existing technology, the simulation-driven design of aircraft is usually initially realized through model library construction, interface standardization, process automation and other means, and the real-time status of the aircraft is simulated by collecting flight parameter data (such as position, speed, attitude, timestamp, etc.).

[0005] For example, the invention patent announcement number is: CN112560184B, which discloses a parallel computing system and method for an aircraft simulation model. The system includes N computing service nodes, a communication network between the N computing service nodes, and parallel computing software installed on each computing service node; the computing service node includes a GPU, an RMDA optical fiber communication network card, and parallel computing software; the first computing service node runs a master control terminal for the parallel computing software, and a node terminal for the parallel computing software runs on the GPU; the GPUs of the remaining N-1 computing service nodes respectively run node terminals for the parallel computing software; the GPU provides parallel solution for the aircraft simulation model set as a participating node; the RMDA optical fiber communication network card is used to build a communication network between the N computing service nodes, and distribute data between the aircraft simulation models through the above communication network. The present invention solves the problem that the current aircraft simulation model does not use GPU computing chips to perform parallel computing on the participating simulation nodes and the simulation data transmission efficiency is low.

[0006] However, the above technology has at least the following technical problems:

[0007] In complex flight simulation tasks, when image frames rotate, jitter or flicker during image output, they are usually directly judged as program failure or rendering failure. However, in actual applications, image fluctuations may also be caused by drastic changes in the aircraft, which belongs to the category of normal physical response. If they are directly judged as program failure or rendering failure, they will trigger error warnings, interrupt the simulation process or output invalid samples, affecting the credibility and stability of the simulation results. Summary of the invention

[0008] In order to overcome the above-mentioned defects of the prior art, the present invention provides an aircraft full-process multi-domain simulation and real-time integrated management system to solve the problems existing in the above-mentioned background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] An aircraft full-process multi-domain simulation and real-time integrated management system, the system includes: a scene editing module, which is used to uniformly configure the simulation scene, obtain unified configuration data, and uniformly configure to complete the visual configuration of the mission scene, terrain environment, meteorological conditions, target deployment, channel setting, interference parameters and sensor configuration parameters, generate standardized configuration files, and transmit the standardized configuration files to the scene generation engine module; the scene generation engine module is used to complete the three-dimensional scene construction and target dynamic modeling according to the standardized configuration files, obtain real-time dynamic flight scenes, obtain image frames according to the real-time dynamic flight scenes, transmit and distribute rendering tasks and image frames to the scene generation node module through a distributed computing structure, and transmit the image frames to the visual display module; a simulation control and execution module is used to input and execute simulation control instructions, the simulation control instructions are unified scheduling of the entire simulation process, and the simulation control instructions are transmitted to the scene generation node module; The scene generation node module is used to execute image generation tasks according to the distributed rendering tasks and image frames, realize real-time image generation, preview and transmission, dynamically adjust the aircraft operation status according to the simulation control instructions, and transmit the aircraft operation status to the visualization display module; the visualization display module is used to provide a graphical display interface for image output and aircraft operation status, receive image frames from the scene generation engine module, and combine the unified scheduling data of the entire simulation process of the simulation control and execution module to realize three-dimensional perspective switching, sensor situation preview and parameter monitoring functions.

[0011] Preferably, the scene generation engine module includes a flight parameter processing unit, a three-dimensional scene construction unit and a sensor data generation unit; the flight parameter processing unit is used to receive real-time flight status data of the aircraft through the channel setting in the unified configuration, the flight status data includes the three-dimensional position coordinates, attitude angle, speed and timestamp of the aircraft, and pre-process the flight status data to obtain pre-processed flight status data, the three-dimensional position coordinates are the three-dimensional center point coordinates of the aircraft, the attitude angles include pitch angle, roll angle and yaw angle, and the pre-processed flight status data is transmitted to the three-dimensional scene construction unit and the sensor data generation unit; the three-dimensional scene construction unit is used to construct a dynamic three-dimensional space scene according to the unified configuration data, and drive the scene target in combination with the pre-processed flight status data, generate a natural background in combination with time and environment, obtain a scene construction result, and transmit the scene The scene construction result is transmitted to the sensor data generation unit; the sensor data generation unit is used to simulate and generate visible light, infrared and depth field images according to the scene construction result and the sensor configuration parameters in the unified configuration data, obtain image frames, obtain image frame related data, the image frame related data is the pixel gray value and timestamp of each pixel point in the image frame, calculate the degree of jitter according to the image frame related data, and make a preliminary abnormality judgment on the image frame according to the degree of jitter; if the preliminary abnormality judgment is that the image frame is normal, no marking is performed; if the preliminary abnormality judgment is that the image frame is abnormal, a flight state influence index is calculated according to the preprocessed flight state data, and an actual abnormality judgment on the image frame is performed according to the flight state influence index; if the actual abnormality judgment is that the image frame is abnormal, an abnormality warning is triggered, and the current image frame is marked as an abnormal frame; if the actual abnormality judgment is that the image frame is normal, no marking is performed.

[0012] Preferably, the step of obtaining the degree of jitter is as follows: converting each image frame into a grayscale image frame, obtaining the pixel grayscale values ​​of two adjacent grayscale image frames, and calculating the difference value of each pixel in the two adjacent grayscale image frames; calculating the variance of each pixel difference value according to the difference value of each pixel in the two adjacent grayscale image frames as the grayscale difference value; identifying the aircraft in the two adjacent grayscale image frames, extracting the aircraft contour, and calculating the structural similarity value according to the aircraft contour; obtaining the minimum circumscribed rectangular frame according to the aircraft contour in the two adjacent grayscale image frames, calculating the coordinates of the aircraft center point according to the minimum circumscribed rectangular frame, calculating the Euclidean distance of the aircraft center point in the two adjacent grayscale image frames, and recording it as the center target offset value; normalizing the grayscale difference value, the structural similarity value and the center target offset value, and calculating the degree of jitter according to the normalized grayscale difference value, the structural similarity value and the center target offset value.

[0013] Preferably, the steps for obtaining the structural similarity value are: using an edge detection method to obtain a binary edge map for two adjacent grayscale image frames; using a contour detection algorithm to obtain an aircraft boundary area for the binary edge map, recorded as a binary contour image; counting the number of pixel intersections of the two binary contour images and the number of pixel unions of the two binary contour images, and calculating the ratio of the number of pixel intersections of the two binary contour images to the number of pixel unions of the two binary contour images to obtain a structural similarity value.

[0014] Preferably, the step of making a preliminary abnormality judgment on the image frame based on the degree of jitter is: comparing the degree of jitter with the jitter threshold, if the degree of jitter is greater than or equal to the jitter threshold, then preliminarily judging the image frame to be abnormal; if the degree of jitter is less than the jitter threshold, then judging the image frame to be normal.

[0015] Preferably, the flight status influence index acquisition step is: acquiring the timestamps of two adjacent image frames, according to the timestamps of the two adjacent image frames, corresponding to the preprocessed flight status data, acquiring the three-dimensional position coordinates of the aircraft corresponding to the timestamps of the two adjacent image frames, calculating the position distance of the three-dimensional position coordinates of the aircraft corresponding to the two adjacent timestamps by Euclidean distance, and calculating the position influence coefficient according to the position distance; acquiring the attitude angle of the aircraft corresponding to the timestamps of the two adjacent image frames, using the quaternion rotation difference method to evaluate the attitude angle of the aircraft to obtain the attitude angle influence coefficient; acquiring the aircraft speed corresponding to the timestamps of the two adjacent image frames, evaluating the aircraft speed to obtain the speed influence coefficient; normalizing the position influence coefficient, the attitude angle influence coefficient and the speed influence coefficient, and calculating the flight status influence index according to the normalized position influence coefficient, the attitude angle influence coefficient and the speed influence coefficient. The specific acquisition steps are: ; In the formula, Expressed as the flight status impact index, Expressed as the normalized position influence coefficient, Expressed as the normalized attitude angle influence coefficient, Expressed as the normalized velocity influence coefficient, , , It is expressed as the weight coefficient of the position influence coefficient, the weight coefficient of the attitude angle influence coefficient, and the weight coefficient of the speed influence coefficient.

[0016] Preferably, the step of acquiring the attitude angle influence coefficient is: acquiring the aircraft attitude angle corresponding to the timestamps of two adjacent image frames; converting the attitude angle into radians, and constructing a quaternion according to the radians; obtaining the quaternions of two adjacent image frames according to the quaternion; and calculating the spherical angle rotation difference between two adjacent image frames using the quaternion dot multiplication formula. The specific acquisition steps are: ; In the formula Expressed as the spherical angle rotation difference, Represented as the quaternion of the tth image frame, It is expressed as the quaternion of the t-1th image frame; the attitude angle influence coefficient is calculated based on the spherical angle rotation difference.

[0017] Preferably, the speed influence coefficient acquisition step is: acquiring the aircraft speed corresponding to the timestamps of two adjacent image frames; calculating the speed change vector according to the aircraft speed, and calculating the modulus of the speed change vector according to the speed change vector; calculating the acceleration between two adjacent image frames according to the modulus of the speed change vector, and the specific acquisition steps are: ; In the formula, Expressed as the acceleration between two adjacent image frames, Expressed as the modulus of the velocity change vector, It is represented as the time interval between two adjacent image frames. Represented as the time of the t-th image frame, It is expressed as the time of the t-1th image frame; the velocity influence coefficient is calculated according to the acceleration between two adjacent image frames.

[0018] Preferably, the step of judging the actual abnormality of the image frame according to the flight status impact index is: comparing the flight status impact index with the impact threshold; if the flight status impact index is greater than or equal to the impact threshold, the image frame is judged to be normal and no warning is issued; if the flight status impact index is less than the impact threshold, the image frame is judged to be abnormal.

[0019] Technical effects and advantages of the present invention: Perform unified configuration of simulation scenes, generate standardized configuration files, complete 3D scene construction and target dynamic modeling, obtain image frames, make preliminary abnormality judgments based on image frames, and if the image frames are judged to be abnormal, make actual abnormality judgments based on aircraft data, and if the image frames are judged to be abnormal, mark the image frames and issue warnings. Dynamically adjust the aircraft operation status according to simulation control instructions, and transmit the aircraft operation status to the visualization display module, providing a graphical display interface for image output and aircraft operation status, effectively reducing the probability of false alarms, interrupting simulation processes, and outputting invalid samples, and improving the credibility and stability of simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A structural diagram of the aircraft full-process multi-domain simulation and real-time integrated management system provided in the embodiment of the present application; Figure 2 This is a structural diagram of the scene generation engine module provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative. The aircraft full-process multi-domain simulation and real-time integrated management system involved in the present invention is not limited to the various structures recorded in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0022] The present invention provides a multi-domain simulation and real-time integrated management system for the entire process of an aircraft, such as Figure 1 As shown, the system includes: The scenario editing module is used to uniformly configure the simulation scenario and obtain the uniform configuration data. The uniform configuration is responsible for completing the visual configuration of the mission scenario, terrain environment, meteorological conditions, target deployment, channel settings, interference parameters, sensor configuration parameters and other elements, generating a standardized configuration file, and transmitting the standardized configuration file to the scenario generation engine module; In this embodiment, it should be specifically explained that the unified configuration steps of the simulation scene are: The user can create a new project or import an existing configuration file through the scene editing control interface to enter the simulation task editing state, providing a project basis for subsequent configuration. This operation ensures that all configuration information is relevant and can be saved and output in a unified manner. The user sets the type of simulation scene (such as ground, water, and air) and the corresponding regional information in the scene configuration interface. The regional information includes longitude and latitude coordinates, scene name, terrain description, and thumbnail, which are used to define the scene space reference frame and background landform environment; In the environment configuration interface, configure the natural condition parameters that affect image generation and target visibility, including weather conditions (sunny, rainy, foggy, snowy, cloudy, etc.), wind speed and direction, atmospheric mode and transmittance, sea conditions, visibility, temperature, aerosol type, season, and time period. These parameters will be used as inputs to the environment model to affect the brightness, occlusion, blur, and other performances of the simulated image. Add aircraft targets in the target deployment interface, set their type, name, quantity, three-dimensional initial position (longitude, latitude, altitude) and attitude angle (pitch, roll, heading), and specify the motion mode (such as straight line, hover, fixed point) and simulation data source for each target; In the channel configuration interface, the user sets the corresponding sensor channel for each target, including the channel name and sensor type (infrared, visible light, depth field, etc.), simulation data source (such as DDS, UDP, trajectory file, hovering in the air, etc.), data output method (local, DDS, Socket, etc.) and output path, image format, time delay, etc. At the same time, the physical parameter configuration information of the associated detector, such as resolution, field of view, image frequency, etc.; In the interference information configuration interface, add interference objects such as smoke bombs, infrared decoy bombs, chaff strips, and angle reflections, and set their types, release units, release time, release positions, and motion parameters. Interference objects will interact with the target in the same scene, affecting the sensor perception effect and improving the simulation authenticity; Users edit detailed technical parameters of various sensors in the detection resource management interface, including band range, field of view, image resolution, frequency, image bit width, attitude offset, etc., which are used to drive the optical modeling process of the image generation engine; After completing the configuration of various parameters, the system will automatically perform model reference verification and parameter integrity check. The user clicks the "Export Configuration" button to generate a standardized configuration file, which contains all the above scene elements and is passed into the scene generation engine module and image generation node as input; After the configuration is completed, the user clicks "Start Instance" through the scene editing control interface, and the system will simultaneously send the configuration file and control instructions to each scene generation node module, officially starting the execution phase of the simulation task.

[0023] The scene generation engine module is used to complete the three-dimensional scene construction and target dynamic modeling according to the standardized configuration file, obtain the real-time dynamic flight scene, obtain the image frame according to the real-time dynamic flight scene, transmit the distribution rendering task and image frame to the scene generation node module through the distributed computing structure, and transmit the image frame to the visualization display module, such as Figure 2 As shown, it includes a flight parameter processing unit, a three-dimensional scene construction unit and a sensor data generation unit; The distributed computing structure refers to a multi-node collaborative computing architecture built in the scene generation engine module to cope with the high computing load of large-scale 3D scene rendering and multi-channel image generation. This structure deploys image generation subtasks among multiple computing nodes to achieve task decomposition and parallel processing of computing processes such as flight parameter analysis, 3D model loading, and sensor image generation.

[0024] Distributing rendering tasks refers to the process in which the scene generation engine module divides the image rendering-related computing tasks into several subtasks according to the sensor channel configuration and image generation requirements after building the real-time dynamic flight scene, and dispatches them to each scene generation node module for execution through a distributed computing structure. Each rendering task usually includes the specified viewing angle, sensor parameters (such as band, field of view, resolution, etc.), target position and attitude information, environmental conditions, etc., which are used to guide the scene generation node module to independently complete the image generation and output under the corresponding viewing angle. Through this mechanism, multi-view and multi-channel image parallel generation can be achieved, improving the overall image rendering efficiency and task responsiveness of the system.

[0025] The scene generation engine module builds a three-dimensional simulation scene with physical environment characteristics and target dynamic behavior by parsing standardized configuration files, and performs image rendering in combination with sensor modeling parameters. It uses a time-stepping mechanism to drive scene changes, generates image frames in real time at each time point, and outputs them to subsequent modules to achieve real-time acquisition of multi-channel and multi-type images, providing a basic image data source for image anomaly analysis.

[0026] A flight parameter processing unit, which is used to receive the real-time flight status data of the aircraft through the channel setting in the unified configuration. The flight status data includes the three-dimensional position coordinates, attitude angle, speed and timestamp of the aircraft, and pre-process the flight status data to obtain pre-processed flight status data. The pre-processing includes formatting, denoising and caching. It should be noted that the three-dimensional position coordinates are the three-dimensional center point coordinates of the aircraft, and the attitude angles include pitch angle, roll angle and yaw angle. The pre-processed flight status data is transmitted to the three-dimensional scene construction unit and the sensor data generation unit; The data channel refers to the communication link or data source used to receive the real-time flight status data of the aircraft. Its type and parameters are set by the channel information configuration module in the scenario editing module. According to the document content, the data channel may include DDS, TCP, UDP based on network communication protocols, shared memory channels based on shared memory mechanisms, fiber optic reflection memory channels based on special equipment, and local trajectory data files for offline simulation. The system establishes a corresponding data receiving process based on the selected channel type, passes the flight parameter data to the flight parameter processing unit, and uniformly parses it into a standard format including key fields such as position, attitude angle, speed and timestamp, which is used for subsequent simulation drive and image generation processing.

[0027] A three-dimensional scene construction unit is used to construct a dynamic three-dimensional space scene according to the unified configuration data, and drive the scene target in combination with the pre-processed flight status data, and generate a natural background in combination with time and environment to obtain a scene construction result, and transmit the scene construction result to the sensor data generation unit; Scene target drive refers to the dynamic update of the spatial position and motion state of each target model in the scene according to the pre-processed flight status data during the 3D scene construction process, so that it presents the same behavior as the actual flight status in the virtual environment. Through scene target drive, the target can achieve real dynamic changes such as translation, rotation, acceleration, and trajectory change in 3D space, thereby ensuring that the generated image frame is consistent with the actual operation status of the aircraft in time and space, improving the realism and effectiveness of the simulation scene.

[0028] A sensor data generation unit is used to simulate and generate visible light, infrared and depth field images according to the scene construction results and the sensor configuration parameters in the unified configuration data, obtain image frames, obtain image frame related data, the image frame related data is the pixel gray value and timestamp of each pixel point in the image frame, calculate the degree of jitter according to the image frame related data, and make a preliminary abnormality judgment on the image frame according to the degree of jitter; If the preliminary abnormality is determined to be normal, no marking is performed. If the preliminary abnormality is determined to be abnormal, the flight state impact index is calculated based on the preprocessed flight state data, and the actual abnormality of the image frame is determined based on the flight state impact index. If the actual abnormality is judged to be an abnormal image frame, an abnormal warning is triggered and the current image frame is marked as an abnormal frame. If the actual abnormality is judged to be a normal image frame, no marking is performed.

[0029] In this embodiment, it should be specifically explained that the image frame acquisition steps are: Receive the scene construction results and unified configuration data, initialize the corresponding virtual sensor model according to the sensor configuration parameters in the unified configuration data, and determine the observation position, orientation, and cone in three-dimensional space. Each simulated sensor model corresponds to an image channel, such as a visible light channel, an infrared channel, or a depth field channel. The initialization process also determines key parameters such as the output format, image size, and time step of each frame of the image; The sensor data generation unit calculates the imaging angle of view and projection area of ​​each sensor according to the current simulated scene state, that is, the range of the target and background "seen" by the sensor in the current frame. This area takes into account the spatial relationship of the sensor's position, orientation, target distance, field of view occlusion, etc., to ensure that the image generation has a real perspective; The system calls the corresponding image simulation rendering algorithm to generate images for the specified viewing area. Different image generation methods are used for different types of sensors. After the image rendering is completed, the system forms a complete frame of image data as an image frame.

[0030] In this embodiment, it should be specifically explained that the steps of obtaining the jitter degree are: Convert each image frame into a grayscale image frame, obtain the pixel grayscale values ​​of two adjacent grayscale image frames, and calculate the difference value of each pixel in the two adjacent grayscale image frames; According to each pixel difference in two adjacent grayscale image frames, the variance of each pixel difference is calculated as the grayscale difference value; Identify the aircraft in two adjacent grayscale image frames, extract the aircraft outline, and calculate the structural similarity value based on the aircraft outline; According to the contour of the aircraft in two adjacent grayscale image frames, the minimum circumscribed rectangular frame is obtained, and the coordinates of the center point of the aircraft are calculated according to the minimum circumscribed rectangular frame. The Euclidean distance of the center point of the aircraft in two adjacent grayscale image frames is calculated and recorded as the center target offset value. The Euclidean distance is a commonly used spatial distance measurement method used to calculate the straight-line distance between two points in two-dimensional or multi-dimensional space, and is used to measure the degree of position change of the center point of the aircraft in two adjacent grayscale image frames; The grayscale difference value, the structural similarity value and the center target offset value are normalized, and the jitter degree is calculated according to the grayscale difference value, the structural similarity value and the center target offset value after normalization. The specific acquisition steps are as follows: ; In the formula, Expressed as the degree of jitter, It is expressed as the normalized structural similarity value. It is expressed as the grayscale difference value after normalization. It is expressed as the center target offset value after normalization. When the image changes smoothly, the grayscale difference value and the center target offset value are small, the structural similarity value is close to 1, the denominator is large, and the final jitter degree is small. When the image jumps significantly or the target suddenly shifts, the grayscale difference value and the center target offset value become larger, and the structural similarity value decreases, resulting in a significant increase in the jitter degree. The use of logarithmic function can avoid extreme amplification of grayscale difference and control nonlinear growth. The use of square root function can make the position offset effect more obvious under small jumps and tend to be gentle under large offsets, which helps to alleviate the suppression of abnormal points on the results.

[0031] In this embodiment, it should be specifically explained that the steps for obtaining the structural similarity value are: The edge detection method is used to obtain a binary edge map for two adjacent grayscale image frames. The edge detection method is an image processing technology used to identify areas with significant grayscale changes in the image and extract the boundaries or contours of objects. In this scenario, the edge detection method is used to process two adjacent grayscale image frames to generate the corresponding binary edge map. It usually includes steps such as image smoothing, gradient calculation, non-maximum suppression and double threshold edge connection, which can effectively extract the clear contours of objects in the image as the basis for subsequent aircraft structure similarity analysis; Use the contour detection algorithm to obtain the boundary area of ​​the aircraft from the binary edge image, which is recorded as a binary contour image. The contour detection algorithm is an image analysis method used to extract continuous boundary information from a binary image, which can identify and extract the external boundary of objects in the image. It is used to analyze the binary image after edge detection, obtain the boundary area of ​​the aircraft, and generate a binary contour image representing its contour shape. The edge point set of the connected area is found through contour tracking technology, and it is represented as an ordered point set, which can be further used to calculate the contour area, bounding box, center position and other information, providing a data basis for structural similarity judgment and target motion analysis; The number of pixel intersections of the two binary contour images and the number of pixel unions of the two binary contour images are counted, and the ratio of the number of pixel intersections of the two binary contour images to the number of pixel unions of the two binary contour images is calculated to obtain a structural similarity value.

[0032] In this embodiment, it should be specifically explained that the steps of performing preliminary abnormality determination of the image frame according to the degree of jitter are: The jitter degree is compared with the jitter threshold. If the jitter degree is greater than or equal to the jitter threshold, the image frame is initially judged to be abnormal; if the jitter degree is less than the jitter threshold, the image frame is judged to be normal. The jitter threshold is obtained by the adaptive threshold method, which is a method that automatically determines the judgment standard according to the changing characteristics of the current image data. It does not rely on a preset fixed value, but analyzes the jitter degree between image frames over a period of time, such as calculating the average value, variance or a certain proportion of high-order digits of these jitter values, and dynamically generates a threshold that best suits the current scene. This allows the system to flexibly judge whether the image is abnormal under different flight conditions and different environmental complexities, thereby improving the accuracy and stability of the judgment.

[0033] In this embodiment, it should be specifically explained that the steps for obtaining the flight status impact index are: The timestamps of two adjacent image frames are obtained. The timestamps of the two adjacent image frames are matched with the preprocessed flight status data to obtain the three-dimensional position coordinates of the aircraft corresponding to the timestamps of the two adjacent image frames. The position distance of the three-dimensional position coordinates of the aircraft corresponding to the two adjacent timestamps is obtained by Euclidean distance calculation. The position influence coefficient is calculated according to the position distance. The specific acquisition steps are as follows: ; In the formula, Expressed as the position influence coefficient, It is expressed as position distance. By adding 1 to the Euclidean distance and taking the natural logarithm, a nonlinear response is achieved: when the position of the aircraft changes only slightly, the output value changes significantly, which improves the detection sensitivity of micro-jitter; when the position changes greatly, the exponential increase is suppressed by the logarithmic function to prevent a small number of extreme values ​​from dominating the overall judgment; Obtain the aircraft attitude angle corresponding to the timestamps of two adjacent image frames, evaluate the aircraft attitude angle using the quaternion rotation difference method, and obtain the attitude angle influence coefficient; The quaternion rotation difference method is a calculation method used to evaluate the degree of change in spatial attitude. It converts the attitude angles (pitch, roll, yaw) of the aircraft in adjacent image frames into quaternion form, and uses the dot product between quaternions to calculate the rotation angle between the two frames, thereby quantifying the magnitude of the attitude change. It avoids the gimbal lock problem existing in the Euler angle representation, and can more accurately reflect the overall rotation change of the aircraft in three-dimensional space. By comparing the attitude angles corresponding to the timestamps of two adjacent image frames, the quaternion rotation difference method is used to calculate the attitude angle rotation angle, and further construct the attitude angle influence coefficient to assist in judging the actual abnormality of the image frame.

[0034] Obtain the aircraft speed corresponding to the timestamps of two adjacent image frames, evaluate the aircraft speed, and obtain the speed influence coefficient; The position influence coefficient, attitude angle influence coefficient and speed influence coefficient are normalized, and the flight state influence index is calculated according to the normalized position influence coefficient, attitude angle influence coefficient and speed influence coefficient. The specific acquisition steps are as follows: ; In the formula, Expressed as the flight status impact index, It is expressed as the normalized position influence coefficient. The more dramatic the spatial position change of the aircraft in adjacent image frames, the greater the impact on the image change. In actual scenes, when the aircraft undergoes rapid translation, jump transfer or discontinuous displacement, it often causes obvious changes in image content, such as sudden changes in perspective, background dislocation or target out of view. Therefore, the greater the position change, the stronger the flight state's ability to explain image jitter, and the greater its contribution to the flight state influence index, reflecting that image frame anomalies are more likely to be caused by physical movement rather than image generation anomalies. It is expressed as the normalized attitude angle influence coefficient. The more dramatic the change of the aircraft's attitude angle in adjacent image frames, the greater the impact on the change of image content. In actual flight scenarios, the rapid rotation or turning of the aircraft's attitude will cause significant changes in the target's perspective, angle, and composition in the image, and even cause the image to rotate, shake, or visually dislocate. Therefore, the greater the change in attitude angle, the more likely the image anomaly is caused by the aircraft's own movement rather than a system error, and thus occupies a higher proportion in the flight status influence index. Expressed as the normalized speed influence coefficient, the more obvious the speed change of the aircraft in adjacent image frames, the greater its potential impact on the image change. In some simulations or real scenes, the rapid increase or decrease of the aircraft speed may be accompanied by maneuvers, perspective switching or tracking instability, which may indirectly cause image blur, frame skipping or sudden changes in content between frames. Therefore, the more drastic the speed change, the more likely it is to cause image anomalies. , , It is expressed as the weight coefficient of the position influence coefficient, the weight coefficient of the attitude angle influence coefficient and the weight coefficient of the speed influence coefficient. , , , Obtained through the analytic hierarchy process, which is a commonly used multi-factor decision-making method used to establish a weight relationship of relative importance between multiple evaluation indicators. By constructing a pairwise comparison judgment matrix of factors, each factor is compared pairwise based on experience or actual importance to quantify the contribution of each factor to the overall goal. The eigenvector of the matrix is ​​extracted through mathematical calculation and normalized to obtain the weight value of each factor.

[0035] In this embodiment, it should be specifically explained that the steps for obtaining the attitude angle influence coefficient are: Get the aircraft attitude angle corresponding to the timestamps of two adjacent image frames. The aircraft attitude angle is , , It is represented as the vehicle attitude angle of the t-th image frame, It is represented as the vehicle attitude angle of the t-1th image frame, , , It is represented by the pitch angle, roll angle and yaw angle of the aircraft corresponding to the t-th image frame, , , It is represented by the pitch angle, roll angle and yaw angle of the aircraft corresponding to the t-1th image frame; Convert the attitude angle into radians. The specific steps are as follows: ; ; ; Construct a quaternion based on radians. The specific steps are: ; ; ; ; The quaternions of two adjacent image frames are obtained according to the quaternion, specifically: , , where Represented as the quaternion of the tth image frame, Represented as the quaternion of the t-1th image frame, , , , are respectively represented as the four elements of the t-th image frame, , , , They are represented as the four elements of the t-1th image frame; The quaternion point multiplication formula is used to calculate the spherical angle rotation difference between two adjacent image frames. The specific acquisition steps are: ; In the formula Expressed as the spherical angle rotation difference, Represented as the quaternion of the tth image frame, Represented as the t-1th image frame quaternion, where , the outermost layer of the formula is multiplied by 2, representing the complete spatial rotation angle; The attitude angle influence coefficient is calculated based on the spherical angle rotation difference. The specific acquisition steps are as follows: ; In the formula, Expressed as the attitude angle influence coefficient, It is expressed as the spherical angle rotation difference. The attitude angle influence coefficient is generated by solving the arc cosine of the three-dimensional rotation difference between adjacent frames of the aircraft and processing it through the square root function. The larger the value, the more drastic the aircraft rotation change is, and the greater the impact on the stability of the image frame; when the rotation change is small, the square root function can enhance the coefficient change caused by small rotation and improve the detection sensitivity of slight attitude jitter. The formula as a whole shows a nonlinear growth characteristic that is more sensitive to small disturbances and more stable to large rotations. The square root function has a strong low-value amplification effect, which can improve the responsiveness to slight attitude changes, while suppressing the expansion of abnormal values ​​under large rotation conditions and effectively controlling the output range.

[0036] In this embodiment, it should be specifically explained that the steps for obtaining the speed influence coefficient are: Get the aircraft speed corresponding to the timestamps of two adjacent image frames. The aircraft speed includes the speed in the x, y, and z coordinate directions. The aircraft speed is , ,in Expressed as the aircraft speed in the tth image frame, Expressed as the aircraft speed in the t-1th image frame, , , It is expressed as the velocity of the aircraft in the x, y, and z coordinate directions of the t-th image frame, , , It is expressed as the velocity of the aircraft in the x, y, and z coordinate directions of the t-1th image frame; The speed change vector is calculated based on the aircraft speed. The specific acquisition steps are: ; In the formula, Expressed as a velocity change vector, Expressed as the aircraft speed in the tth image frame, Expressed as the aircraft speed in the t-1th image frame; Calculate the modulus of the velocity change vector. The specific steps are as follows: ; In the formula, Expressed as the modulus of the velocity change vector; The acceleration between two adjacent image frames is calculated according to the modulus of the velocity change vector. The specific acquisition steps are as follows: ; In the formula, Expressed as the acceleration between two adjacent image frames, Expressed as the modulus of the velocity change vector, It is represented as the time interval between two adjacent image frames. Represented as the time of the t-th image frame, It is represented as the time of the t-1th image frame; The velocity influence coefficient is calculated based on the acceleration between two adjacent image frames. The specific acquisition steps are as follows: ; In the formula, Expressed as the speed influence coefficient, It is expressed as the acceleration between two adjacent image frames. By calculating the three-dimensional velocity change and time interval between consecutive image frames, the acceleration magnitude is derived, and the square root function is introduced to construct the velocity influence coefficient. This coefficient maintains a low value in a low-speed stable state, but has a strong response to sudden maneuvers, emergency stops or speed fluctuations, and can be effectively used to identify potential abnormal image frames caused by speed jumps in images.

[0037] In this embodiment, it should be specifically explained that the steps of determining the actual abnormality of the image frame according to the flight status impact index are as follows: The flight status impact index is compared with the impact threshold. If the flight status impact index is greater than or equal to the impact threshold, the image frame is judged to be normal and no warning is issued; if the flight status impact index is less than the impact threshold, the image frame is judged to be abnormal. The impact threshold is obtained through the adaptive threshold.

[0038] The simulation control and execution module is used to input and execute simulation control instructions. The simulation control instructions are the unified scheduling of the entire simulation process, such as providing control operation interfaces such as start, pause and reset, while monitoring the simulation status, progress and data consistency. It can also link the scene generation engine module and the scene generation node module to execute cross-module instructions, realize unified control logic, and transmit the simulation control instructions to the scene generation node module; The scene generation node module is used to perform image generation tasks according to the distribution of rendering tasks and image frames, realize real-time image generation, preview and transmission output, dynamically adjust the aircraft operation status according to the simulation control instructions, and transmit the aircraft operation status to the visualization display module; The visualization display module is used to provide a graphical display interface for image output and aircraft operation status, receive image frames from the scene generation engine module, and combine the unified scheduling data of the entire simulation process of the simulation control and execution module to realize functions such as three-dimensional perspective switching, sensor situation preview, and parameter monitoring, providing users with intuitive task perception and interaction capabilities.

[0039] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0040] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. The aircraft full-process multi-domain simulation and real-time integrated management system is characterized by: The system comprises: The scenario editing module is used to uniformly configure the simulation scenario and obtain the uniform configuration data. The uniform configuration is responsible for completing the visual configuration of the mission scenario, terrain environment, meteorological conditions, target deployment, channel settings, interference parameters and sensor configuration parameters, generating a standardized configuration file, and transmitting the standardized configuration file to the scenario generation engine module; The scene generation engine module is used to complete the three-dimensional scene construction and target dynamic modeling according to the standardized configuration file, obtain the real-time dynamic flight scene, obtain the image frame according to the real-time dynamic flight scene, transmit and distribute the rendering tasks and image frames to the scene generation node module through the distributed computing structure, and transmit the image frames to the visualization display module; The simulation control and execution module is used to input and execute simulation control instructions. The simulation control instructions are the unified scheduling of the entire simulation process, and the simulation control instructions are transmitted to the scene generation node module; The scene generation node module is used to perform image generation tasks according to the distribution of rendering tasks and image frames, realize real-time image generation, preview and transmission, dynamically adjust the aircraft operation status according to the simulation control instructions, and transmit the aircraft operation status to the visualization display module; The visualization display module is used to provide a graphical display interface for image output and aircraft operation status, receive image frames from the scene generation engine module, and combine the unified scheduling data of the entire simulation process of the simulation control and execution module to realize three-dimensional perspective switching, sensor situation preview and parameter monitoring functions.

2. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 1, characterized in that: The scene generation engine module includes a flight parameter processing unit, a three-dimensional scene construction unit and a sensor data generation unit; A flight parameter processing unit, used for receiving real-time flight status data of the aircraft through the channel setting in the unified configuration, the flight status data including the three-dimensional position coordinates, attitude angle, speed and timestamp of the aircraft, and preprocessing the flight status data to obtain preprocessed flight status data, the three-dimensional position coordinates are the three-dimensional center point coordinates of the aircraft, and the attitude angles include pitch angle, roll angle and yaw angle, and transmitting the preprocessed flight status data to the three-dimensional scene construction unit and the sensor data generation unit; A three-dimensional scene construction unit is used to construct a dynamic three-dimensional space scene according to the unified configuration data, and drive the scene target in combination with the pre-processed flight status data, generate a natural background in combination with time and environment, obtain a scene construction result, and transmit the scene construction result to the sensor data generation unit; A sensor data generation unit is used to simulate and generate visible light, infrared and depth field images according to the scene construction results and the sensor configuration parameters in the unified configuration data, obtain image frames, obtain image frame related data, the image frame related data is the pixel gray value and timestamp of each pixel point in the image frame, calculate the degree of jitter according to the image frame related data, and make a preliminary abnormality judgment on the image frame according to the degree of jitter; If the preliminary abnormality is determined to be normal, no marking is performed. If the preliminary abnormality is determined to be abnormal, the flight state impact index is calculated based on the preprocessed flight state data, and the actual abnormality of the image frame is determined based on the flight state impact index. If the actual abnormality is judged to be an abnormal image frame, an abnormal warning is triggered and the current image frame is marked as an abnormal frame. If the actual abnormality is judged to be a normal image frame, no marking is performed.

3. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 2 is characterized in that: The jitter degree acquisition steps are: Convert each image frame into a grayscale image frame, obtain the pixel grayscale values ​​of two adjacent grayscale image frames, and calculate the difference value of each pixel in the two adjacent grayscale image frames; According to each pixel difference in two adjacent grayscale image frames, the variance of each pixel difference is calculated as the grayscale difference value; Identify the aircraft in two adjacent grayscale image frames, extract the aircraft outline, and calculate the structural similarity value based on the aircraft outline; According to the contour of the aircraft in two adjacent grayscale image frames, the minimum circumscribed rectangular frame is obtained, the coordinates of the center point of the aircraft are calculated according to the minimum circumscribed rectangular frame, and the Euclidean distance of the center point of the aircraft in two adjacent grayscale image frames is calculated, which is recorded as the center target offset value; The grayscale difference value, the structural similarity value and the center target offset value are normalized, and the degree of jitter is calculated according to the grayscale difference value, the structural similarity value and the center target offset value after the normalization process.

4. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 3 is characterized in that: The steps for obtaining the structural similarity value are: Using edge detection method on two adjacent grayscale image frames to obtain a binary edge map; Use contour detection algorithm to obtain the boundary area of ​​the aircraft from the binary edge image, which is recorded as a binary contour image; The number of pixel intersections of the two binary contour images and the number of pixel unions of the two binary contour images are counted, and the ratio of the number of pixel intersections of the two binary contour images to the number of pixel unions of the two binary contour images is calculated to obtain a structural similarity value.

5. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 2, characterized in that: The steps of performing preliminary abnormality judgment on the image frame according to the degree of jitter are as follows: The jitter degree is compared with the jitter threshold. If the jitter degree is greater than or equal to the jitter threshold, the image frame is preliminarily judged to be abnormal; if the jitter degree is less than the jitter threshold, the image frame is judged to be normal.

6. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 2, characterized in that: The steps for obtaining the flight status impact index are as follows: Obtaining the timestamps of two adjacent image frames, matching the timestamps of the two adjacent image frames with the preprocessed flight status data, obtaining the three-dimensional position coordinates of the aircraft corresponding to the timestamps of the two adjacent image frames, calculating the position distance of the three-dimensional position coordinates of the aircraft corresponding to the two adjacent timestamps through Euclidean distance, and calculating the position influence coefficient based on the position distance; Obtain the aircraft attitude angle corresponding to the timestamps of two adjacent image frames, evaluate the aircraft attitude angle using the quaternion rotation difference method, and obtain the attitude angle influence coefficient; Obtain the aircraft speed corresponding to the timestamps of two adjacent image frames, evaluate the aircraft speed, and obtain the speed influence coefficient; The position influence coefficient, attitude angle influence coefficient and speed influence coefficient are normalized, and the flight state influence index is calculated according to the normalized position influence coefficient, attitude angle influence coefficient and speed influence coefficient. The specific acquisition steps are as follows: ； In the formula, Expressed as the flight status impact index, Expressed as the normalized position influence coefficient, Expressed as the normalized attitude angle influence coefficient, Expressed as the normalized velocity influence coefficient, , , It is expressed as the weight coefficient of the position influence coefficient, the weight coefficient of the attitude angle influence coefficient, and the weight coefficient of the speed influence coefficient.

7. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 6 is characterized by: The steps for obtaining the attitude angle influence coefficient are: Obtain the aircraft attitude angle corresponding to the timestamps of two adjacent image frames; Convert the attitude angle into radians and construct a quaternion based on the radians. Obtain the quaternions of two adjacent image frames according to the quaternion; The quaternion point multiplication formula is used to calculate the spherical angle rotation difference between two adjacent image frames. The specific acquisition steps are: ； In the formula Expressed as the spherical angle rotation difference, Represented as the quaternion of the tth image frame, Represented as the quaternion of the t-1th image frame; The attitude angle influence coefficient is calculated based on the spherical angle rotation difference.

8. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 6, characterized in that: The steps for obtaining the speed influence coefficient are as follows: Get the aircraft speed corresponding to the timestamps of two adjacent image frames; A velocity change vector is obtained according to the speed of the aircraft, and a modulus length of the velocity change vector is obtained according to the velocity change vector; The acceleration between two adjacent image frames is calculated according to the modulus of the velocity change vector. The specific acquisition steps are as follows: ； In the formula, Expressed as the acceleration between two adjacent image frames, Expressed as the modulus of the velocity change vector, It is represented as the time interval between two adjacent image frames. Represented as the time of the t-th image frame, It is represented as the time of the t-1th image frame; The velocity influence coefficient is calculated based on the acceleration between two adjacent image frames.

9. The aircraft full-process multi-domain simulation and real-time integrated management system according to claim 2, characterized in that: The steps of judging the actual abnormality of the image frame according to the flight status impact index are as follows: The flight status impact index is compared with the impact threshold. If the flight status impact index is greater than or equal to the impact threshold, the image frame is judged to be normal and no warning is issued; if the flight status impact index is less than the impact threshold, the image frame is judged to be abnormal.

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