Automatic track control simulation method and system for army unmanned aerial vehicle simulation system

Abstract

The invention provides an automatic track control simulation method and system for an army unmanned aerial vehicle simulation system. The automatic track control simulation method of the army unmanned aerial vehicle simulation system comprises the steps of obtaining longitude and latitude coordinates and a route deviation value according to a preset point selection logic in combination with the number of effective route points of an unmanned aerial vehicle; respectively and correspondingly acquiring a to-fly distance and a shortest distance of the unmanned aerial vehicle according to the longitude and latitude height coordinates and the route deviation value of the unmanned aerial vehicle; and acquiring the course of the unmanned aerial vehicle and a corrected expected course according to the longitude, latitude and height coordinates of the unmanned aerial vehicle, sending the corrected expected course to an autopilot, and controlling the unmanned aerial vehicle to fly along a track. The system comprises modules corresponding to the steps of the method.

Description

Technical Field

[0001] The invention proposes a trajectory automatic control simulation method and system for an army unmanned aerial vehicle simulation system, belonging to the technical field of trajectory automatic control. Background Art

[0002] With the rapid development of modern military technology, army drones are playing an increasingly important role in battlefield reconnaissance, target strike, material transportation and other fields. In order to improve the combat effectiveness and flight safety of drones, it is particularly important to simulate and test their trajectory automatic control systems. However, traditional drone trajectory simulation methods often focus on single-dimensional simulation, such as only considering the setting of waypoints or simple route deviation calculations, while ignoring the trajectory control effect under the combined effect of multiple factors.

[0003] In practical applications, UAVs need to face complex geographical environments and changeable meteorological conditions when performing tasks, which requires their trajectory automatic control systems to accurately and quickly respond to various changes to ensure that the UAV can fly efficiently and safely according to the predetermined route. Therefore, developing a simulation method that can comprehensively consider multiple factors such as the longitude and latitude coordinates of the UAV, route deviation, waiting distance, shortest distance, and heading correction is of great significance for improving the trajectory automatic control performance of the UAV. Summary of the invention

[0004] The present invention provides a method and system for simulating the trajectory automatic control of an army unmanned aerial vehicle simulation system, which is used to solve the above-mentioned technical problems in the prior art. The technical solutions adopted are as follows:

[0005] A method for simulating the trajectory automatic control of an army unmanned aerial vehicle simulation system, the method comprising:

[0006] According to the preset point selection logic and the number of valid waypoints of the drone, the latitude and longitude coordinates and route deviation values ​​are obtained;

[0007] According to the longitude and latitude coordinates of the UAV and the route deviation value, the waiting flight distance and the shortest distance of the UAV are obtained respectively;

[0008] The heading of the UAV and the corrected desired heading are obtained according to the longitude and latitude coordinates of the UAV, and the corrected desired heading is sent to the autopilot to control the trajectory flight of the UAV.

[0009] Furthermore, according to the preset point selection logic and the number of valid waypoints of the UAV, the latitude and longitude coordinates and the route deviation value are obtained, including:

[0010] Retrieve the preset point selection logic;

[0011] According to the point selection logic, select valid waypoints and the number of valid waypoints of the UAV;

[0012] Output the latitude and longitude coordinates of the last waypoint and the next waypoint of the drone in the valid waypoints according to the valid waypoints and the number of valid waypoints; wherein the latitude and longitude coordinates of the last waypoint are marked as LLA_n, and the latitude and longitude coordinates of the next waypoint are marked as LLA_n1;

[0013] The heading of the current route section and the deviation between the current heading of the drone and the route heading are obtained through the waypoint coordinates at both ends of a certain route section corresponding to the valid waypoints in the current route section of the drone.

[0014] Furthermore, the waiting flight distance and the shortest distance of the drone are obtained according to the latitude and longitude coordinates of the drone and the route deviation value, including:

[0015] Extract the longitude and latitude coordinates of the drone;

[0016] The distance to be flown from the drone to the next waypoint is obtained based on the longitude and latitude coordinates corresponding to the previous avionics of the drone and the longitude and latitude coordinates corresponding to the next waypoint;

[0017] Extract route deviation value;

[0018] The heading deviation distance between the current UAV position and the route to be flown is obtained by using trigonometric functions combined with the distance to be flown and the route deviation value; wherein the heading deviation distance is the shortest distance from the UAV position to the route.

[0019] Further, the heading and the corrected desired heading of the UAV are obtained according to the longitude and latitude coordinates of the UAV, and the corrected desired heading is sent to the autopilot to control the trajectory flight of the UAV, including:

[0020] According to the real-time longitude and latitude coordinates of the waypoint of the drone and the longitude and latitude coordinates of the next waypoint, the heading of the line connecting the real-time longitude and latitude coordinates of the waypoint and the longitude and latitude coordinates of the next waypoint is obtained;

[0021] Extract the heading deviation distance between the current drone position and the flight route;

[0022] Obtaining a corrected expected heading corresponding to the current UAV according to an expected deviation distance externally input as a heading deviation distance between the current UAV position and the flight route; wherein the expected deviation distance is set to a default value or a specific value, and the default value of the expected deviation distance is 0;

[0023] The corrected desired heading is sent to the autopilot, and the drone trajectory flight is controlled by the autopilot.

[0024] Furthermore, the specific value corresponding to the expected yaw distance is set by the following method, including:

[0025] Real-time monitoring of the flight speed and maximum speed of the drone during operation, as well as the turning radius data and acceleration parameters;

[0026] The speed parameter factor is obtained by using the flight speed and the maximum speed of the UAV during operation, wherein the speed parameter factor is obtained by the following formula:

[0027]

[0028] Among them, ξ v represents the speed parameter factor; n represents the number of unit times experienced during the operation of the UAV, and the unit time is 1s; V i represents the flight speed corresponding to the i-th unit time during the flight of the UAV; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the maximum non-flying speed to the maximum flight speed; V maxi V represents the speed value corresponding to the maximum flight speed for the i-th time; xi Indicates the specific flight speed value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time;

[0029] The turning radius data during the operation of the UAV is used to obtain the turning parameter factor, wherein the turning parameter factor is obtained by the following formula:

[0030]

[0031] Among them, ξ w represents the turning parameter factor; x represents the number of turning actions experienced by the UAV during operation; R i represents the turning radius data corresponding to the i-th turning action during the flight of the UAV; k represents the number of occurrences of the maximum turning radius experienced by the UAV during operation; w maxi represents the turning angle corresponding to the maximum turning radius for the i-th time; w xi V represents the angle between the flight heading and the target heading before the maximum turning radius appears for the i-th time; mi V represents the average flight speed corresponding to the maximum turning radius for the i-th time; mxi represents the flight speed before turning for the i-th time when the maximum turning radius appears;

[0032] The acceleration parameter factor is obtained by using the acceleration parameter during the operation of the UAV, wherein the acceleration parameter factor is obtained by the following formula:

[0033]

[0034] Among them, ξ a represents the acceleration parameter factor; n represents the number of unit time experienced during the operation of the UAV, and the unit time is 1s; a i represents the acceleration value corresponding to the i-th unit time; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the non-flying speed maximum to the flight speed maximum; a maxi represents the acceleration value corresponding to the maximum flight speed for the i-th time; a xi represents the flight acceleration value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; T i T represents the duration of the flight speed increase from the ith time to the maximum flight speed; c Indicates the preset duration reference value;

[0035] The speed parameter factor, the turning parameter factor and the acceleration parameter factor are used to obtain a specific value corresponding to the expected yaw distance of the UAV, wherein the specific value corresponding to the expected yaw distance is obtained by the following formula:

[0036]

[0037] Wherein, S represents a specific value corresponding to the expected yaw distance; S0 represents a preset initial value of the expected yaw distance; ΔS represents a preset compensation amount of the expected yaw distance.

[0038] An army unmanned aerial vehicle simulation system trajectory automatic control simulation system, the army unmanned aerial vehicle simulation system trajectory automatic control simulation system comprises:

[0039] The coordinate and deviation information acquisition module is used to obtain the longitude and latitude coordinates and the route deviation value according to the preset point selection logic and the number of valid waypoints of the drone;

[0040] The distance data acquisition module is used to obtain the distance to be flown and the shortest distance of the drone according to the latitude and longitude coordinates and the route deviation value of the drone;

[0041] The flight control module is used to obtain the heading of the UAV and correct the expected heading according to the longitude and latitude coordinates of the UAV, and send the corrected expected heading to the autopilot to control the trajectory flight of the UAV.

[0042] Furthermore, the coordinate and deviation information acquisition module includes:

[0043] The point selection logic calling module is used to call the preset point selection logic;

[0044] A waypoint selection module, used to select valid waypoints and the number of valid waypoints of the UAV according to the point selection logic;

[0045] The waypoint coordinate acquisition module is used to output the longitude and latitude coordinates of the previous waypoint and the next waypoint of the drone in the valid waypoints according to the valid waypoints and the number of valid waypoints of the drone; wherein the longitude and latitude coordinates of the previous waypoint are marked as LLA_n, and the longitude and latitude coordinates of the next waypoint are marked as LLA_n1;

[0046] The deviation value acquisition module is used to obtain the heading of the current route interval and the deviation value between the current heading of the drone and the route heading through the waypoint coordinates at both ends of a certain route segment corresponding to the valid waypoints in the current route interval of the drone.

[0047] Furthermore, the distance data acquisition module includes:

[0048] Longitude and latitude high coordinates extraction module, used to extract the longitude and latitude high coordinates of the drone;

[0049] The waiting distance acquisition module is used to obtain the waiting distance from the drone to the next waypoint according to the longitude and latitude coordinates corresponding to the previous avionics of the drone in real time and the longitude and latitude coordinates corresponding to the next waypoint;

[0050] A route deviation value acquisition module is used to extract the route deviation value;

[0051] The heading deviation distance acquisition module is used to use trigonometric functions to combine the distance to be flown and the route deviation value to obtain the heading deviation distance between the current drone position and the route to be flown; wherein the heading deviation distance is the shortest distance from the drone position to the route.

[0052] Furthermore, the flight control module includes:

[0053] A heading information acquisition module is used to obtain the heading of the line connecting the real-time longitude and latitude coordinates of the waypoint and the next waypoint according to the longitude and latitude coordinates of the real-time waypoint and the next waypoint;

[0054] The heading deviation distance extraction module is used to extract the heading deviation distance between the current UAV position and the flight route;

[0055] A corrected expected heading acquisition module is used to obtain a corrected expected heading corresponding to the current UAV according to an expected deviation distance externally input as the heading deviation distance between the current UAV position and the flight route; wherein the expected deviation distance is set to a default value or a specific value, and the default value of the expected deviation distance is 0;

[0056] The autopilot control module is used to send the corrected desired heading to the autopilot and control the trajectory flight of the UAV through the autopilot.

[0057] Furthermore, the specific value corresponding to the expected yaw distance is set by the following method, including:

[0058] Real-time monitoring of the flight speed and maximum speed of the drone during operation, as well as the turning radius data and acceleration parameters;

[0059] The speed parameter factor is obtained by using the flight speed and the maximum speed of the UAV during operation, wherein the speed parameter factor is obtained by the following formula:

[0060]

[0061] Among them, ξ v represents the speed parameter factor; n represents the number of unit times experienced during the operation of the UAV, and the unit time is 1s; V i represents the flight speed corresponding to the i-th unit time during the flight of the UAV; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the maximum non-flying speed to the maximum flight speed; V maxi V represents the speed value corresponding to the maximum flight speed for the i-th time; xi Indicates the specific flight speed value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time;

[0062] The turning radius data during the operation of the UAV is used to obtain the turning parameter factor, wherein the turning parameter factor is obtained by the following formula:

[0063]

[0064] Among them, ξ w represents the turning parameter factor; x represents the number of turning actions experienced by the UAV during operation; R i represents the turning radius data corresponding to the i-th turning action during the flight of the UAV; k represents the number of occurrences of the maximum turning radius experienced by the UAV during operation; w maxi represents the turning angle corresponding to the maximum turning radius for the i-th time; w xi V represents the angle between the flight heading and the target heading before the maximum turning radius appears for the i-th time; mi V represents the average flight speed corresponding to the maximum turning radius for the i-th time; mxi represents the flight speed before turning for the i-th time when the maximum turning radius appears;

[0065] The acceleration parameter factor is obtained by using the acceleration parameter during the operation of the UAV, wherein the acceleration parameter factor is obtained by the following formula:

[0066]

[0067] Among them, ξ a represents the acceleration parameter factor; n represents the number of unit time experienced during the operation of the UAV, and the unit time is 1s; a i represents the acceleration value corresponding to the i-th unit time; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the non-flying speed maximum to the flight speed maximum; a maxi represents the acceleration value corresponding to the maximum flight speed for the i-th time; a xi represents the flight acceleration value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; T i T represents the duration of the flight speed increase from the ith time to the maximum flight speed; c Indicates the preset duration reference value;

[0068] The speed parameter factor, the turning parameter factor and the acceleration parameter factor are used to obtain a specific value corresponding to the expected yaw distance of the UAV, wherein the specific value corresponding to the expected yaw distance is obtained by the following formula:

[0069]

[0070] Wherein, S represents a specific value corresponding to the expected yaw distance; S0 represents a preset initial value of the expected yaw distance; ΔS represents a preset compensation amount of the expected yaw distance.

[0071] Beneficial effects of the present invention:

[0072] The present invention proposes a method and system for simulating the automatic control of the trajectory of an army unmanned aerial vehicle simulation system. By comprehensively considering the latitude and longitude coordinates of the unmanned aerial vehicle, the route deviation value and other factors, the flight trajectory of the unmanned aerial vehicle can be precisely controlled, the risk of deviation from the predetermined route can be reduced, and the flight safety can be improved. By calculating the distance to be flown and the shortest distance, the optimal flight path can be selected for the unmanned aerial vehicle, unnecessary flight time and energy consumption can be reduced, and flight efficiency can be improved. The simulation method can simulate the flight process of unmanned aerial vehicles in complex environments, provide reliable predictions and evaluations for the performance of unmanned aerial vehicles in actual tasks, and thus enhance their task execution capabilities. By continuously optimizing and improving the simulation method, the research and development and innovation of unmanned aerial vehicle trajectory automatic control technology can be promoted, providing strong support for the development of unmanned aerial vehicle technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1is a flow chart of the method of the present invention;

[0074] Figure 2 The system block diagram of the system of the present invention. DETAILED DESCRIPTION

[0075] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0076] The embodiment of the present invention proposes a trajectory automatic control simulation method for an army unmanned aerial vehicle simulation system, such as Figure 1 As shown, the trajectory automatic control simulation method of the army unmanned aerial vehicle simulation system includes:

[0077] S1. Obtain the latitude and longitude coordinates and route deviation values ​​according to the preset point selection logic and the number of valid waypoints of the drone;

[0078] S2. Obtain the waiting flight distance and the shortest distance of the UAV according to the latitude and longitude coordinates and the route deviation value of the UAV;

[0079] S3. Obtain the heading and corrected desired heading of the UAV according to the longitude and latitude coordinates of the UAV, and send the corrected desired heading to the autopilot to control the trajectory flight of the UAV.

[0080] The working principle of the above technical solution is as follows: the logic is pre-set according to the mission requirements, terrain conditions, meteorological factors, etc., and is used to determine the key waypoints during the flight of the UAV. According to the complexity of the mission and the performance of the UAV, the number of waypoints to be considered is determined. The latitude and longitude coordinates of each valid waypoint are calculated by using the geographic information system (GIS) or global positioning system (GPS) technology, combined with the preset point selection logic. According to the current position of the UAV and the position of the predetermined waypoint, the route deviation value is calculated, that is, the degree to which the UAV deviates from the predetermined route. Based on the current latitude and longitude coordinates of the UAV and the latitude and longitude coordinates of the next waypoint, the straight-line distance of the UAV to be flown is calculated using a spatial geometry algorithm. In the case of multiple possible paths, by comparing the flight distances and flight conditions (such as terrain, weather, etc.) of different paths, the shortest or optimal path for the UAV to reach the target point is evaluated and selected. According to the current latitude and longitude coordinates of the UAV and the latitude and longitude coordinates of the target waypoint, the current heading of the UAV is calculated. According to the route deviation value and the flight mission requirements, the current heading of the UAV is corrected to obtain the desired heading. This correction process may involve complex algorithms, such as PID control, fuzzy control, etc., to ensure that the drone can fly along the predetermined route. The corrected desired heading is sent to the drone's autopilot, which controls the drone's flight attitude and speed according to the received instructions to achieve automatic trajectory control.

[0081] The effect of the above technical solution is: by comprehensively considering the longitude and latitude coordinates of the drone, the route deviation value and other factors, the flight trajectory of the drone can be accurately controlled, the risk of deviation from the predetermined route can be reduced, and flight safety can be improved. By calculating the distance to be flown and the shortest distance, the optimal flight path is selected for the drone, unnecessary flight time and energy consumption are reduced, and flight efficiency is improved. This simulation method can simulate the flight process of drones in complex environments, provide reliable predictions and evaluations for the performance of drones in actual tasks, and thus enhance their mission execution capabilities. By continuously optimizing and improving simulation methods, the research and development and innovation of drone trajectory automatic control technology can be promoted, providing strong support for the development of drone technology.

[0082] In one embodiment of the present invention, the latitude and longitude coordinates and the route deviation value are obtained according to the preset point selection logic combined with the number of valid waypoints of the drone, including:

[0083] S101, calling the preset point selection logic;

[0084] S102, selecting valid waypoints and the number of valid waypoints of the UAV according to the point selection logic;

[0085] S103, outputting the latitude and longitude coordinates of the previous waypoint and the latitude and longitude coordinates of the next waypoint of the UAV in the valid waypoints according to the valid waypoints and the number of valid waypoints of the UAV; wherein the latitude and longitude coordinates of the previous waypoint are marked as LLA_n, and the latitude and longitude coordinates of the next waypoint are marked as LLA_n1;

[0086] S104, obtaining the heading of the current route section and the deviation value between the current heading of the drone and the route heading through the waypoint coordinates at both ends of a certain route section corresponding to the valid waypoints in the current route section of the drone.

[0087] The working principle of the above technical solution is as follows: In the preparation stage of the above technical solution, the system retrieves the pre-set point selection logic from the storage or database. These logics are based on multiple factors such as mission requirements, terrain, and weather conditions to guide the selection of UAV waypoints.

[0088] Based on the retrieved point selection logic, the system analyzes and determines the valid waypoints and their number that need to be considered during the UAV flight process. These waypoints are key nodes in the UAV flight trajectory. Based on the selected valid waypoints, the system outputs the longitude and latitude coordinates of the previous waypoint (recorded as LLA_n) and the next waypoint (recorded as LLA_n1) in the current route interval of the UAV. These coordinates are the basis for the UAV flight trajectory control. The system uses the coordinates of the previous waypoint and the next waypoint to calculate the heading of the current route interval. At the same time, the system will also obtain the current heading of the UAV in real time, and compare it with the route heading to obtain the deviation value. This deviation value is an important basis for subsequent trajectory control.

[0089] The effect of the above technical solution is: through the preset point selection logic, the system can more accurately select effective waypoints that meet the mission requirements and flight conditions. The system can obtain the longitude and latitude coordinates and route deviation values ​​of the UAV in real time, providing strong support for the precise control of the flight trajectory. By real-time monitoring of the deviation value between the current heading of the UAV and the route heading, the system can promptly detect and correct the deviation of the flight trajectory, thereby reducing the risk of deviation from the scheduled route and improving flight safety. Accurate waypoint selection and flight trajectory control can reduce unnecessary flight time and energy consumption, and improve the flight efficiency of the UAV.

[0090] In summary, this technical solution achieves precise control of the UAV's flight trajectory by accurately selecting waypoints, acquiring longitude and latitude coordinates and route deviation values ​​in real time, and accurately calculating heading and deviation values, thereby improving flight safety, efficiency and mission execution capabilities.

[0091] In one embodiment of the present invention, the distance to be flown and the shortest distance of the drone are obtained according to the latitude and longitude coordinates and the route deviation value of the drone, respectively, including:

[0092] S201, extracting the longitude and latitude coordinates of the UAV;

[0093] S202, obtaining the distance to be flown from the drone to the next waypoint according to the longitude and latitude coordinates corresponding to the previous avionics of the drone in real time and the longitude and latitude coordinates corresponding to the next waypoint;

[0094] S203, extracting the route deviation value;

[0095] S204, using trigonometric functions in combination with the distance to be flown and the route deviation value to obtain a heading deviation distance between the current UAV position and the route to be flown; wherein the heading deviation distance is the shortest distance from the UAV position to the route.

[0096] The working principle of the above technical solution is as follows: The above technical solution is to obtain the longitude and latitude coordinates of the current position of the drone, which is the basic data for calculating the distance to be flown and the shortest distance. According to the longitude and latitude coordinates corresponding to the real-time previous waypoint of the drone and the longitude and latitude coordinates corresponding to the next waypoint, the distance to be flown from the drone to the next waypoint is obtained: the system uses the longitude and latitude coordinates of the current position of the drone (i.e. the previous waypoint) and the longitude and latitude coordinates of the next waypoint, and calculates the straight-line distance from the drone to the next waypoint, i.e. the distance to be flown, through a spatial geometry algorithm.

[0097] Get the deviation value between the current heading of the drone and the scheduled route. This deviation value reflects the degree to which the drone deviates from the scheduled route. Use trigonometric functions to combine the distance to be flown and the route deviation value to obtain the heading deviation distance between the current drone position and the route to be flown; wherein, the heading deviation distance is the shortest distance from the drone position to the route: the system uses the trigonometric function relationship, combined with the distance to be flown and the route deviation value, to calculate the shortest distance from the current position of the drone to the scheduled route, i.e. the heading deviation distance. This distance is an important indicator for evaluating the degree to which the drone deviates from the route, and is also an important basis for subsequent trajectory control.

[0098] The effect of the above technical solution is: by accurately extracting the longitude and latitude coordinates and route deviation values ​​of the drone, the system can more accurately calculate the distance to be flown and the shortest distance, providing strong support for the precise control of the flight trajectory. Real-time acquisition and calculation of the distance to be flown and the shortest distance enable the system to more accurately control the flight trajectory of the drone and ensure that the drone can fly along the predetermined route. By real-time monitoring of the deviation distance between the current position of the drone and the predetermined route, the system can promptly detect and correct the deviation of the flight trajectory, thereby reducing the risk of deviation from the predetermined route and improving flight safety. Accurate distance calculation and control can reduce unnecessary flight time and energy consumption, and improve the flight efficiency of the drone. At the same time, by optimizing the flight trajectory, the flight cost can be further reduced.

[0099] In summary, this technical solution achieves precise control of the UAV's flight trajectory by accurately extracting the UAV's longitude and latitude coordinates and route deviation values, and calculating the distance to be flown and the shortest distance in real time, thereby improving flight safety, efficiency and mission execution capabilities.

[0100] In one embodiment of the present invention, the heading and the corrected desired heading of the drone are obtained according to the longitude and latitude coordinates of the drone, and the corrected desired heading is sent to the autopilot to control the trajectory flight of the drone, including:

[0101] S301, obtaining the heading of the line connecting the real-time longitude and latitude coordinates of the waypoint and the longitude and latitude coordinates of the next waypoint according to the real-time longitude and latitude coordinates of the waypoint and the longitude and latitude coordinates of the next waypoint of the drone;

[0102] S302, extracting the heading deviation distance between the current UAV position and the flight route;

[0103] S303, obtaining a corrected expected heading corresponding to the current UAV according to an expected deviation distance externally input as the heading deviation distance between the current UAV position and the flight route; wherein the expected deviation distance is set to a default value or a specific value, and the default value of the expected deviation distance is 0;

[0104] S304: Send the corrected desired heading to the autopilot, and control the trajectory flight of the UAV through the autopilot.

[0105] The working principle of the above technical solution is: during the flight of the drone, its real-time position (i.e., real-time waypoint) and the longitude and latitude coordinates of the next target waypoint are known. The system uses these two coordinate points and calculates the heading of the line between them through a spatial geometry algorithm, that is, the direction the drone should currently be facing.

[0106] In the actual flight of the drone, due to various factors, its current heading may deviate from the predetermined route. The system extracts the heading deviation distance between the current drone position and the flight route through real-time monitoring and calculation, which is a key indicator for evaluating the degree of deviation of the drone from the predetermined route.

[0107] The external input desired deviation distance is an adjustable parameter, which represents the maximum distance that the drone is allowed to deviate from the predetermined route. By default, this distance can be set to 0, which means that the drone should strictly fly along the predetermined route. The system calculates the corrected desired heading based on the heading deviation distance between the current drone and the route to be flown and the expected deviation distance. This corrected desired heading is the system's instruction to the drone's next flight direction, aiming to return the drone to or approach the predetermined route. The system sends the calculated corrected desired heading to the drone's autopilot. After receiving the instruction, the autopilot adjusts the drone's flight attitude and speed to control the drone to fly according to the corrected desired heading, thereby achieving precise control of the drone's trajectory.

[0108] The effect of the above technical solution is: by calculating and correcting the desired heading of the drone in real time, the system can more accurately control the flight direction of the drone and ensure that the drone can fly along the predetermined route. The introduction of the correction of the desired heading enables the drone to adjust its flight direction in time when it is subject to external interference or internal errors, and maintain the stability of the flight trajectory. By real-time monitoring and correcting the heading deviation of the drone, the system can promptly detect and correct potential flight safety issues and reduce the risk of flight accidents. Accurate heading control and trajectory control can reduce the energy consumption and time waste of the drone during flight and improve flight efficiency.

[0109] In summary, this technical solution achieves precise control of the UAV's flight direction and stable control of its trajectory by calculating and correcting the UAV's desired heading in real time and sending it to the autopilot to control the UAV's trajectory flight, thereby improving flight safety, efficiency and mission execution capabilities.

[0110] In one embodiment of the present invention, the specific value corresponding to the expected yaw distance is set by the following method, including:

[0111] Step 1: Real-time monitoring of the flight speed and maximum speed of the drone as well as the turning radius data and acceleration parameters during operation;

[0112] Step 2: Obtain a speed parameter factor using the flight speed and maximum speed of the UAV during operation, wherein the speed parameter factor is obtained by the following formula:

[0113]

[0114] Among them, ξ v represents the speed parameter factor; n represents the number of unit times experienced during the operation of the UAV, and the unit time is 1s; V i represents the flight speed corresponding to the i-th unit time during the flight of the UAV; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the maximum non-flying speed to the maximum flight speed; V maxi V represents the speed value corresponding to the maximum flight speed for the i-th time; xi Indicates the specific flight speed value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time;

[0115] Step 3: Obtain a turning parameter factor using the turning radius data during the operation of the UAV, wherein the turning parameter factor is obtained by the following formula:

[0116]

[0117] Among them, ξ w represents the turning parameter factor; x represents the number of turning actions experienced by the UAV during operation; R i represents the turning radius data corresponding to the i-th turning action during the flight of the UAV; k represents the number of occurrences of the maximum turning radius experienced by the UAV during operation; w maxi represents the turning angle corresponding to the maximum turning radius for the i-th time; w xi V represents the angle between the flight heading and the target heading before the maximum turning radius appears for the i-th time; mi V represents the average flight speed corresponding to the maximum turning radius for the i-th time;mxi represents the flight speed before turning for the i-th time when the maximum turning radius appears;

[0118] Step 4: Obtain an acceleration parameter factor using the acceleration parameter during the operation of the drone, wherein the acceleration parameter factor is obtained by the following formula:

[0119]

[0120] Among them, ξ a represents the acceleration parameter factor; n represents the number of unit time experienced during the operation of the UAV, and the unit time is 1s; a i represents the acceleration value corresponding to the i-th unit time; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the non-flying speed maximum to the flight speed maximum; a maxi represents the acceleration value corresponding to the maximum flight speed for the i-th time; a xi represents the flight acceleration value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; T i T represents the duration of the flight speed increase from the ith time to the maximum flight speed; c Indicates the preset duration reference value;

[0121] Step 5: Using the speed parameter factor, the turning parameter factor, and the acceleration parameter factor, a specific value corresponding to the expected yaw distance of the UAV is obtained, wherein the specific value corresponding to the expected yaw distance is obtained by the following formula:

[0122]

[0123] Wherein, S represents a specific value corresponding to the expected yaw distance; S0 represents a preset initial value of the expected yaw distance; ΔS represents a preset compensation amount of the expected yaw distance.

[0124] The working principle of the above technical solution is as follows: the system monitors the flight speed and acceleration of the UAV in real time during operation, and records the flight speed and acceleration values ​​of each unit time (such as per second). Pay special attention to the situation where the flight speed suddenly rises from a non-maximum value to a maximum value, and record the speed and acceleration values ​​at these key time points, as well as the corresponding increase duration. Monitor the turning action of the UAV during flight, record the radius data, turning angle, the angle between the flight heading before and after the turn and the target heading, and the average flight speed during the turn. Pay special attention to the situation where the maximum turning radius occurs, and record the relevant data of these key points. The speed parameter factor is calculated by formula, which comprehensively considers the speed change of the UAV during flight, especially the sudden increase in speed, and reflects the impact of speed change on the expected yaw distance setting. The turning parameter factor is calculated by formula, which combines multiple factors such as turning radius, turning angle, heading angle before and after the turn, and flight speed during turning, reflecting the impact of turning action on the expected yaw distance setting. The acceleration parameter factor is calculated by formula, which considers the change in acceleration, especially the change in acceleration related to the sudden increase in speed, and reflects the impact of acceleration change on the expected yaw distance setting.

[0125] Using the calculated speed parameter factor, turning parameter factor and acceleration parameter factor, combined with the preset expected yaw distance initial value (S0) and compensation amount (ΔS), the specific value (S) corresponding to the expected yaw distance of the UAV is calculated through a formula. According to the calculated specific value of the expected yaw distance, the system dynamically adjusts the flight trajectory of the UAV to ensure that the UAV can maintain a certain deviation range from the predetermined route during the flight, while optimizing flight efficiency and safety. The adjusted flight instructions are sent to the autopilot, and the autopilot controls the actual flight of the UAV. This technical solution achieves precise control and optimization of UAV flight by real-time monitoring of the UAV's flight status, calculating parameter factors, setting the expected yaw distance, and dynamically adjusting the flight trajectory.

[0126] The effect of the above technical solution is: by real-time monitoring of the flight speed, maximum speed, turning radius data and acceleration parameters of the UAV during operation, and taking these factors into consideration to set the expected yaw distance, the setting of the distance is more scientific and reasonable. By using the speed parameter factor, the turning parameter factor and the acceleration parameter factor to obtain the specific value of the expected yaw distance, it can be ensured that the UAV can maintain a stable flight state during flight even in the face of speed changes, turning movements and acceleration changes.

[0127] By accurately setting the expected yaw distance, it can be ensured that the UAV can adjust its flight direction in a timely and accurate manner when it deviates from the scheduled route, thereby avoiding potential flight safety risks. Scientific setting of the expected yaw distance can reduce unnecessary heading adjustments of the UAV during flight, thereby reducing energy consumption and improving flight efficiency. This technical solution can monitor the flight status of the UAV in real time and dynamically adjust the expected yaw distance according to changes in the flight status, so that the UAV can better adapt to different flight environments and mission requirements.

[0128] In summary, this technical solution scientifically and reasonably sets the expected yaw distance by comprehensively considering the UAV's flight speed, turning radius, acceleration and other parameters, thereby improving the stability, safety and efficiency of the UAV's flight, and enhancing the UAV's adaptability to different flight environments and tasks.

[0129] The embodiment of the present invention provides an army unmanned aerial vehicle simulation system trajectory automatic control simulation system, such as Figure 2 As shown, the trajectory automatic control simulation system of the army unmanned aerial vehicle simulation system includes:

[0130] The coordinate and deviation information acquisition module is used to obtain the longitude and latitude coordinates and the route deviation value according to the preset point selection logic and the number of valid waypoints of the drone;

[0131] The distance data acquisition module is used to obtain the distance to be flown and the shortest distance of the drone according to the latitude and longitude coordinates and the route deviation value of the drone;

[0132] The flight control module is used to obtain the heading of the UAV and correct the expected heading according to the longitude and latitude coordinates of the UAV, and send the corrected expected heading to the autopilot to control the trajectory flight of the UAV.

[0133] The working principle of the above technical solution is as follows: the logic is pre-set according to the mission requirements, terrain conditions, meteorological factors, etc., and is used to determine the key waypoints during the flight of the UAV. According to the complexity of the mission and the performance of the UAV, the number of waypoints to be considered is determined. The latitude and longitude coordinates of each valid waypoint are calculated by using the geographic information system (GIS) or global positioning system (GPS) technology, combined with the preset point selection logic. According to the current position of the UAV and the position of the predetermined waypoint, the route deviation value is calculated, that is, the degree to which the UAV deviates from the predetermined route. Based on the current latitude and longitude coordinates of the UAV and the latitude and longitude coordinates of the next waypoint, the straight-line distance of the UAV to be flown is calculated using a spatial geometry algorithm. In the case of multiple possible paths, by comparing the flight distances and flight conditions (such as terrain, weather, etc.) of different paths, the shortest or optimal path for the UAV to reach the target point is evaluated and selected. According to the current latitude and longitude coordinates of the UAV and the latitude and longitude coordinates of the target waypoint, the current heading of the UAV is calculated. According to the route deviation value and the flight mission requirements, the current heading of the UAV is corrected to obtain the desired heading. This correction process may involve complex algorithms, such as PID control, fuzzy control, etc., to ensure that the drone can fly along the predetermined route. The corrected desired heading is sent to the drone's autopilot, which controls the drone's flight attitude and speed according to the received instructions to achieve automatic trajectory control.

[0134] The effect of the above technical solution is: by comprehensively considering the longitude and latitude coordinates of the drone, the route deviation value and other factors, the flight trajectory of the drone can be accurately controlled, the risk of deviation from the predetermined route can be reduced, and flight safety can be improved. By calculating the distance to be flown and the shortest distance, the optimal flight path is selected for the drone, unnecessary flight time and energy consumption are reduced, and flight efficiency is improved. This simulation method can simulate the flight process of drones in complex environments, provide reliable predictions and evaluations for the performance of drones in actual tasks, and thus enhance their mission execution capabilities. By continuously optimizing and improving simulation methods, the research and development and innovation of drone trajectory automatic control technology can be promoted, providing strong support for the development of drone technology.

[0135] In one embodiment of the present invention, the coordinate and deviation information acquisition module includes:

[0136] The point selection logic calling module is used to call the preset point selection logic;

[0137] A waypoint selection module, used to select valid waypoints and the number of valid waypoints of the UAV according to the point selection logic;

[0138] The waypoint coordinate acquisition module is used to output the longitude and latitude coordinates of the previous waypoint and the next waypoint of the drone in the valid waypoints according to the valid waypoints and the number of valid waypoints of the drone; wherein the longitude and latitude coordinates of the previous waypoint are marked as LLA_n, and the longitude and latitude coordinates of the next waypoint are marked as LLA_n1;

[0139] The deviation value acquisition module is used to obtain the heading of the current route interval and the deviation value between the current heading of the drone and the route heading through the waypoint coordinates at both ends of a certain route segment corresponding to the valid waypoints in the current route interval of the drone.

[0140] The working principle of the above technical solution is as follows: In the preparation stage of the above technical solution, the system retrieves the pre-set point selection logic from the storage or database. These logics are based on multiple factors such as mission requirements, terrain, and weather conditions to guide the selection of UAV waypoints.

[0141] Based on the retrieved point selection logic, the system analyzes and determines the valid waypoints and their number that need to be considered during the UAV flight process. These waypoints are key nodes in the UAV flight trajectory. Based on the selected valid waypoints, the system outputs the longitude and latitude coordinates of the previous waypoint (recorded as LLA_n) and the next waypoint (recorded as LLA_n1) in the current route interval of the UAV. These coordinates are the basis for the UAV flight trajectory control. The system uses the coordinates of the previous waypoint and the next waypoint to calculate the heading of the current route interval. At the same time, the system will also obtain the current heading of the UAV in real time, and compare it with the route heading to obtain the deviation value. This deviation value is an important basis for subsequent trajectory control.

[0142] The effect of the above technical solution is: through the preset point selection logic, the system can more accurately select effective waypoints that meet the mission requirements and flight conditions. The system can obtain the longitude and latitude coordinates and route deviation values ​​of the UAV in real time, providing strong support for the precise control of the flight trajectory. By real-time monitoring of the deviation value between the current heading of the UAV and the route heading, the system can promptly detect and correct the deviation of the flight trajectory, thereby reducing the risk of deviation from the scheduled route and improving flight safety. Accurate waypoint selection and flight trajectory control can reduce unnecessary flight time and energy consumption, and improve the flight efficiency of the UAV.

[0143] In summary, this technical solution achieves precise control of the UAV's flight trajectory by accurately selecting waypoints, acquiring longitude and latitude coordinates and route deviation values ​​in real time, and accurately calculating heading and deviation values, thereby improving flight safety, efficiency and mission execution capabilities.

[0144] In one embodiment of the present invention, the distance data acquisition module includes:

[0145] Longitude and latitude high coordinates extraction module, used to extract the longitude and latitude high coordinates of the drone;

[0146] The waiting distance acquisition module is used to obtain the waiting distance from the drone to the next waypoint according to the longitude and latitude coordinates corresponding to the previous avionics of the drone in real time and the longitude and latitude coordinates corresponding to the next waypoint;

[0147] A route deviation value acquisition module is used to extract the route deviation value;

[0148] The heading deviation distance acquisition module is used to use trigonometric functions to combine the distance to be flown and the route deviation value to obtain the heading deviation distance between the current drone position and the route to be flown; wherein the heading deviation distance is the shortest distance from the drone position to the route.

[0149] The working principle of the above technical solution is as follows: The above technical solution is to obtain the longitude and latitude coordinates of the current position of the drone, which is the basic data for calculating the distance to be flown and the shortest distance. According to the longitude and latitude coordinates corresponding to the real-time previous waypoint of the drone and the longitude and latitude coordinates corresponding to the next waypoint, the distance to be flown from the drone to the next waypoint is obtained: the system uses the longitude and latitude coordinates of the current position of the drone (i.e. the previous waypoint) and the longitude and latitude coordinates of the next waypoint, and calculates the straight-line distance from the drone to the next waypoint, i.e. the distance to be flown, through a spatial geometry algorithm.

[0150] Get the deviation value between the current heading of the drone and the scheduled route. This deviation value reflects the degree to which the drone deviates from the scheduled route. Use trigonometric functions to combine the distance to be flown and the route deviation value to obtain the heading deviation distance between the current drone position and the route to be flown; wherein, the heading deviation distance is the shortest distance from the drone position to the route: the system uses the trigonometric function relationship, combined with the distance to be flown and the route deviation value, to calculate the shortest distance from the current position of the drone to the scheduled route, i.e. the heading deviation distance. This distance is an important indicator for evaluating the degree to which the drone deviates from the route, and is also an important basis for subsequent trajectory control.

[0151] The effect of the above technical solution is: by accurately extracting the longitude and latitude coordinates and route deviation values ​​of the drone, the system can more accurately calculate the distance to be flown and the shortest distance, providing strong support for the precise control of the flight trajectory. Real-time acquisition and calculation of the distance to be flown and the shortest distance enable the system to more accurately control the flight trajectory of the drone and ensure that the drone can fly along the predetermined route. By real-time monitoring of the deviation distance between the current position of the drone and the predetermined route, the system can promptly detect and correct the deviation of the flight trajectory, thereby reducing the risk of deviation from the predetermined route and improving flight safety. Accurate distance calculation and control can reduce unnecessary flight time and energy consumption, and improve the flight efficiency of the drone. At the same time, by optimizing the flight trajectory, the flight cost can be further reduced.

[0152] In summary, this technical solution achieves precise control of the UAV's flight trajectory by accurately extracting the UAV's longitude and latitude coordinates and route deviation values, and calculating the distance to be flown and the shortest distance in real time, thereby improving flight safety, efficiency and mission execution capabilities.

[0153] In one embodiment of the present invention, the flight control module comprises:

[0154] A heading information acquisition module is used to obtain the heading of the line connecting the real-time longitude and latitude coordinates of the waypoint and the next waypoint according to the longitude and latitude coordinates of the real-time waypoint and the next waypoint;

[0155] The heading deviation distance extraction module is used to extract the heading deviation distance between the current UAV position and the flight route;

[0156] A corrected expected heading acquisition module is used to obtain a corrected expected heading corresponding to the current UAV according to an expected deviation distance externally input as the heading deviation distance between the current UAV position and the flight route; wherein the expected deviation distance is set to a default value or a specific value, and the default value of the expected deviation distance is 0;

[0157] The autopilot control module is used to send the corrected desired heading to the autopilot and control the trajectory flight of the UAV through the autopilot.

[0158] The working principle of the above technical solution is: during the flight of the drone, its real-time position (i.e., real-time waypoint) and the longitude and latitude coordinates of the next target waypoint are known. The system uses these two coordinate points and calculates the heading of the line between them through a spatial geometry algorithm, that is, the direction the drone should currently be facing.

[0159] In the actual flight of the drone, due to various factors, its current heading may deviate from the predetermined route. The system extracts the heading deviation distance between the current drone position and the flight route through real-time monitoring and calculation, which is a key indicator for evaluating the degree of deviation of the drone from the predetermined route.

[0160] The external input desired deviation distance is an adjustable parameter, which represents the maximum distance that the drone is allowed to deviate from the predetermined route. By default, this distance can be set to 0, which means that the drone should strictly fly along the predetermined route. The system calculates the corrected desired heading based on the heading deviation distance between the current drone and the route to be flown and the expected deviation distance. This corrected desired heading is the system's instruction to the drone's next flight direction, aiming to return the drone to or approach the predetermined route. The system sends the calculated corrected desired heading to the drone's autopilot. After receiving the instruction, the autopilot adjusts the drone's flight attitude and speed to control the drone to fly according to the corrected desired heading, thereby achieving precise control of the drone's trajectory.

[0161] The effect of the above technical solution is: by calculating and correcting the desired heading of the drone in real time, the system can more accurately control the flight direction of the drone and ensure that the drone can fly along the predetermined route. The introduction of the correction of the desired heading enables the drone to adjust its flight direction in time when it is subject to external interference or internal errors, and maintain the stability of the flight trajectory. By real-time monitoring and correcting the heading deviation of the drone, the system can promptly detect and correct potential flight safety issues and reduce the risk of flight accidents. Accurate heading control and trajectory control can reduce the energy consumption and time waste of the drone during flight and improve flight efficiency.

[0162] In summary, this technical solution achieves precise control of the UAV's flight direction and stable control of its trajectory by calculating and correcting the UAV's desired heading in real time and sending it to the autopilot to control the UAV's trajectory flight, thereby improving flight safety, efficiency and mission execution capabilities.

[0163] In one embodiment of the present invention, the specific value corresponding to the expected yaw distance is set by the following method, including:

[0164] Real-time monitoring of the flight speed and maximum speed of the drone during operation, as well as the turning radius data and acceleration parameters;

[0165] The speed parameter factor is obtained by using the flight speed and the maximum speed of the UAV during operation, wherein the speed parameter factor is obtained by the following formula:

[0166]

[0167] Among them, ξ v represents the speed parameter factor; n represents the number of unit times experienced during the operation of the UAV, and the unit time is 1s; V irepresents the flight speed corresponding to the i-th unit time during the flight of the UAV; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the maximum non-flying speed to the maximum flight speed; V maxi V represents the speed value corresponding to the maximum flight speed for the i-th time; xi Indicates the specific flight speed value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time;

[0168] The turning radius data during the operation of the UAV is used to obtain the turning parameter factor, wherein the turning parameter factor is obtained by the following formula:

[0169]

[0170] Among them, ξ w represents the turning parameter factor; x represents the number of turning actions experienced by the UAV during operation; R i represents the turning radius data corresponding to the i-th turning action during the flight of the UAV; k represents the number of occurrences of the maximum turning radius experienced by the UAV during operation; w maxi represents the turning angle corresponding to the maximum turning radius for the i-th time; w xi V represents the angle between the flight heading and the target heading before the maximum turning radius appears for the i-th time; mi V represents the average flight speed corresponding to the maximum turning radius for the i-th time; mxi represents the flight speed before turning for the i-th time when the maximum turning radius appears;

[0171] The acceleration parameter factor is obtained by using the acceleration parameter during the operation of the UAV, wherein the acceleration parameter factor is obtained by the following formula:

[0172]

[0173] Among them, ξ a represents the acceleration parameter factor; n represents the number of unit time experienced during the operation of the UAV, and the unit time is 1s; a i represents the acceleration value corresponding to the i-th unit time; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the non-flying speed maximum to the flight speed maximum; a maxi represents the acceleration value corresponding to the maximum flight speed for the i-th time; a xi represents the flight acceleration value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; T i T represents the duration of the flight speed increase from the ith time to the maximum flight speed;c Indicates the preset duration reference value;

[0174] The speed parameter factor, the turning parameter factor and the acceleration parameter factor are used to obtain a specific value corresponding to the expected yaw distance of the UAV, wherein the specific value corresponding to the expected yaw distance is obtained by the following formula:

[0175]

[0176] Wherein, S represents a specific value corresponding to the expected yaw distance; S0 represents a preset initial value of the expected yaw distance; ΔS represents a preset compensation amount of the expected yaw distance.

[0177] The working principle of the above technical solution is as follows: the system monitors the flight speed and acceleration of the UAV in real time during operation, and records the flight speed and acceleration values ​​of each unit time (such as per second). Pay special attention to the situation where the flight speed suddenly rises from a non-maximum value to a maximum value, and record the speed and acceleration values ​​at these key time points, as well as the corresponding increase duration. Monitor the turning action of the UAV during flight, record the radius data, turning angle, the angle between the flight heading before and after the turn and the target heading, and the average flight speed during the turn. Pay special attention to the situation where the maximum turning radius occurs, and record the relevant data of these key points. The speed parameter factor is calculated by formula, which comprehensively considers the speed change of the UAV during flight, especially the sudden increase in speed, and reflects the impact of speed change on the expected yaw distance setting. The turning parameter factor is calculated by formula, which combines multiple factors such as turning radius, turning angle, heading angle before and after the turn, and flight speed during turning, reflecting the impact of turning action on the expected yaw distance setting. The acceleration parameter factor is calculated by formula, which considers the change in acceleration, especially the change in acceleration related to the sudden increase in speed, and reflects the impact of acceleration change on the expected yaw distance setting.

[0178] Using the calculated speed parameter factor, turning parameter factor and acceleration parameter factor, combined with the preset expected yaw distance initial value (S0) and compensation amount (ΔS), the specific value (S) corresponding to the expected yaw distance of the UAV is calculated through a formula. According to the calculated specific value of the expected yaw distance, the system dynamically adjusts the flight trajectory of the UAV to ensure that the UAV can maintain a certain deviation range from the predetermined route during the flight, while optimizing flight efficiency and safety. The adjusted flight instructions are sent to the autopilot, and the autopilot controls the actual flight of the UAV. This technical solution achieves precise control and optimization of UAV flight by real-time monitoring of the UAV's flight status, calculating parameter factors, setting the expected yaw distance, and dynamically adjusting the flight trajectory.

[0179] The effect of the above technical solution is: by real-time monitoring of the flight speed, maximum speed, turning radius data and acceleration parameters of the UAV during operation, and taking these factors into consideration to set the expected yaw distance, the setting of the distance is more scientific and reasonable. By using the speed parameter factor, the turning parameter factor and the acceleration parameter factor to obtain the specific value of the expected yaw distance, it can be ensured that the UAV can maintain a stable flight state during flight even in the face of speed changes, turning movements and acceleration changes.

[0180] By accurately setting the expected yaw distance, it can be ensured that the UAV can adjust its flight direction in a timely and accurate manner when it deviates from the scheduled route, thereby avoiding potential flight safety risks. Scientific setting of the expected yaw distance can reduce unnecessary heading adjustments of the UAV during flight, thereby reducing energy consumption and improving flight efficiency. This technical solution can monitor the flight status of the UAV in real time and dynamically adjust the expected yaw distance according to changes in the flight status, so that the UAV can better adapt to different flight environments and mission requirements.

[0181] In summary, this technical solution scientifically and reasonably sets the expected yaw distance by comprehensively considering the UAV's flight speed, turning radius, acceleration and other parameters, thereby improving the stability, safety and efficiency of the UAV's flight, and enhancing the UAV's adaptability to different flight environments and tasks.

[0182] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A trajectory automatic control simulation method for an army unmanned aerial vehicle simulation system, characterized in that: The trajectory automatic control simulation method of the army unmanned aerial vehicle simulation system comprises: According to the preset point selection logic and the number of valid waypoints of the drone, the latitude and longitude coordinates and route deviation values ​​are obtained; According to the longitude and latitude coordinates of the UAV and the route deviation value, the waiting flight distance and the shortest distance of the UAV are obtained respectively; The heading of the UAV and the corrected desired heading are obtained according to the longitude and latitude coordinates of the UAV, and the corrected desired heading is sent to the autopilot to control the trajectory flight of the UAV.

2. According to claim 1, the trajectory automatic control simulation method of the army unmanned aerial vehicle simulation system is characterized in that: According to the preset point selection logic and the number of valid waypoints of the drone, the latitude and longitude coordinates and route deviation values ​​are obtained, including: Retrieve the preset point selection logic; According to the point selection logic, select valid waypoints and the number of valid waypoints of the UAV; Output the latitude and longitude coordinates of the last waypoint and the next waypoint of the drone in the valid waypoints according to the valid waypoints and the number of valid waypoints; wherein the latitude and longitude coordinates of the last waypoint are marked as LLA_n, and the latitude and longitude coordinates of the next waypoint are marked as LLA_n1; The heading of the current route section and the deviation between the current heading of the drone and the route heading are obtained through the waypoint coordinates at both ends of a certain route section corresponding to the valid waypoints in the current route section of the drone.

3. According to claim 1, the trajectory automatic control simulation method of the army unmanned aerial vehicle simulation system is characterized in that: According to the latitude and longitude coordinates of the UAV and the route deviation value, the UAV's waiting distance and shortest distance are obtained respectively, including: Extract the longitude and latitude coordinates of the drone; The distance to be flown from the drone to the next waypoint is obtained based on the longitude and latitude coordinates corresponding to the previous avionics of the drone and the longitude and latitude coordinates corresponding to the next waypoint; Extract route deviation value; The heading deviation distance between the current UAV position and the route to be flown is obtained by using trigonometric functions combined with the distance to be flown and the route deviation value; wherein the heading deviation distance is the shortest distance from the UAV position to the route.

4. According to claim 1, the trajectory automatic control simulation method of the army unmanned aerial vehicle simulation system is characterized in that: Obtain the heading of the drone and the corrected desired heading according to the longitude and latitude coordinates of the drone, and send the corrected desired heading to the autopilot to control the trajectory flight of the drone, including: According to the real-time longitude and latitude coordinates of the waypoint of the drone and the longitude and latitude coordinates of the next waypoint, the heading of the line connecting the real-time longitude and latitude coordinates of the waypoint and the longitude and latitude coordinates of the next waypoint is obtained; Extract the heading deviation distance between the current drone position and the flight route; Obtaining a corrected expected heading corresponding to the current UAV according to an expected deviation distance externally input as a heading deviation distance between the current UAV position and the flight route; wherein the expected deviation distance is set to a default value or a specific value, and the default value of the expected deviation distance is 0; The corrected desired heading is sent to the autopilot, and the drone trajectory flight is controlled by the autopilot.

5. According to claim 4, the trajectory automatic control simulation method of the army unmanned aerial vehicle simulation system is characterized in that: The specific value corresponding to the expected yaw distance is set by the following method, including: Real-time monitoring of the flight speed and maximum speed of the drone during operation, as well as the turning radius data and acceleration parameters; The speed parameter factor is obtained by using the flight speed and the maximum speed of the UAV during operation, wherein the speed parameter factor is obtained by the following formula: Among them, ξ v represents the speed parameter factor; n represents the number of unit times experienced during the operation of the UAV, and the unit time is 1s; V i represents the flight speed corresponding to the i-th unit time during the flight of the UAV; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the maximum non-flying speed to the maximum flight speed; V maxi V represents the speed value corresponding to the maximum flight speed for the i-th time; xi Indicates the specific flight speed value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; The turning radius data during the operation of the UAV is used to obtain the turning parameter factor, wherein the turning parameter factor is obtained by the following formula: Among them, ξ w represents the turning parameter factor; x represents the number of turning actions experienced by the UAV during operation; R i represents the turning radius data corresponding to the i-th turning action during the flight of the UAV; k represents the number of occurrences of the maximum turning radius experienced by the UAV during operation; w maxi represents the turning angle corresponding to the maximum turning radius for the i-th time; w xi V represents the angle between the flight heading and the target heading before the maximum turning radius appears for the i-th time; mi V represents the average flight speed corresponding to the maximum turning radius for the i-th time; mxi represents the flight speed before turning for the i-th time when the maximum turning radius appears; The acceleration parameter factor is obtained by using the acceleration parameter during the operation of the UAV, wherein the acceleration parameter factor is obtained by the following formula: Among them, ξ a represents the acceleration parameter factor; n represents the number of unit time experienced during the operation of the UAV, and the unit time is 1s; a i represents the acceleration value corresponding to the i-th unit time; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the non-flying speed maximum to the flight speed maximum; a maxi represents the acceleration value corresponding to the maximum flight speed for the i-th time; a xi represents the flight acceleration value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; T i T represents the duration of the flight speed increase from the ith time to the maximum flight speed; c Indicates the preset duration reference value; The speed parameter factor, the turning parameter factor and the acceleration parameter factor are used to obtain a specific value corresponding to the expected yaw distance of the UAV, wherein the specific value corresponding to the expected yaw distance is obtained by the following formula: Wherein, S represents a specific value corresponding to the expected yaw distance; S0 represents a preset initial value of the expected yaw distance; ΔS represents a preset compensation amount of the expected yaw distance.

6. An Army UAV simulation system trajectory automatic control simulation system, characterized in that: The trajectory automatic control simulation system of the army unmanned aerial vehicle simulation system includes: The coordinate and deviation information acquisition module is used to obtain the longitude and latitude coordinates and the route deviation value according to the preset point selection logic and the number of valid waypoints of the drone; The distance data acquisition module is used to obtain the distance to be flown and the shortest distance of the drone according to the latitude and longitude coordinates and the route deviation value of the drone; The flight control module is used to obtain the heading of the UAV and correct the expected heading according to the longitude and latitude coordinates of the UAV, and send the corrected expected heading to the autopilot to control the trajectory flight of the UAV.

7. The trajectory automatic control simulation system of the army unmanned aerial vehicle simulation system according to claim 6 is characterized in that: The coordinate and deviation information acquisition module includes: The point selection logic calling module is used to call the preset point selection logic; A waypoint selection module, used to select valid waypoints and the number of valid waypoints of the UAV according to the point selection logic; The waypoint coordinate acquisition module is used to output the longitude and latitude coordinates of the previous waypoint and the next waypoint of the drone in the valid waypoints according to the valid waypoints and the number of valid waypoints of the drone; wherein the longitude and latitude coordinates of the previous waypoint are marked as LLA_n, and the longitude and latitude coordinates of the next waypoint are marked as LLA_n1; The deviation value acquisition module is used to obtain the heading of the current route interval and the deviation value between the current heading of the drone and the route heading through the waypoint coordinates at both ends of a certain route segment corresponding to the valid waypoints in the current route interval of the drone.

8. The trajectory automatic control simulation system of the army unmanned aerial vehicle simulation system according to claim 6 is characterized in that: The distance data acquisition module comprises: Longitude and latitude high coordinates extraction module, used to extract the longitude and latitude high coordinates of the drone; The waiting distance acquisition module is used to obtain the waiting distance from the drone to the next waypoint according to the longitude and latitude coordinates corresponding to the previous avionics of the drone in real time and the longitude and latitude coordinates corresponding to the next waypoint; A route deviation value acquisition module is used to extract the route deviation value; The heading deviation distance acquisition module is used to use trigonometric functions to combine the distance to be flown and the route deviation value to obtain the heading deviation distance between the current drone position and the route to be flown; wherein the heading deviation distance is the shortest distance from the drone position to the route.

9. The trajectory automatic control simulation system of the army unmanned aerial vehicle simulation system according to claim 6 is characterized in that: The flight control module comprises: A heading information acquisition module is used to obtain the heading of the line connecting the real-time longitude and latitude coordinates of the waypoint and the next waypoint according to the longitude and latitude coordinates of the real-time waypoint and the next waypoint; The heading deviation distance extraction module is used to extract the heading deviation distance between the current UAV position and the flight route; A corrected expected heading acquisition module is used to obtain a corrected expected heading corresponding to the current UAV according to an expected deviation distance externally input as the heading deviation distance between the current UAV position and the flight route; wherein the expected deviation distance is set to a default value or a specific value, and the default value of the expected deviation distance is 0; The autopilot control module is used to send the corrected desired heading to the autopilot and control the trajectory flight of the UAV through the autopilot.

10. The trajectory automatic control simulation system of the army unmanned aerial vehicle simulation system according to claim 9 is characterized in that: The specific value corresponding to the expected yaw distance is set by the following method, including: Real-time monitoring of the flight speed and maximum speed of the drone during operation, as well as the turning radius data and acceleration parameters; The speed parameter factor is obtained by using the flight speed and the maximum speed of the UAV during operation, wherein the speed parameter factor is obtained by the following formula: Among them, ξ v represents the speed parameter factor; n represents the number of unit times experienced during the operation of the UAV, and the unit time is 1s; V i represents the flight speed corresponding to the i-th unit time during the flight of the UAV; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the maximum non-flying speed to the maximum flight speed; V maxi V represents the speed value corresponding to the maximum flight speed for the i-th time; xi Indicates the specific flight speed value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; The turning radius data during the operation of the UAV is used to obtain the turning parameter factor, wherein the turning parameter factor is obtained by the following formula: Among them, ξ w represents the turning parameter factor; x represents the number of turning actions experienced by the UAV during operation; R i represents the turning radius data corresponding to the i-th turning action during the flight of the UAV; k represents the number of occurrences of the maximum turning radius experienced by the UAV during operation; w maxi represents the turning angle corresponding to the maximum turning radius for the i-th time; w xi V represents the angle between the flight heading and the target heading before the maximum turning radius appears for the i-th time; mi V represents the average flight speed corresponding to the maximum turning radius for the i-th time; mxi represents the flight speed before turning for the i-th time when the maximum turning radius appears; The acceleration parameter factor is obtained by using the acceleration parameter during the operation of the UAV, wherein the acceleration parameter factor is obtained by the following formula: Among them, ξ a represents the acceleration parameter factor; n represents the number of unit time experienced during the operation of the UAV, and the unit time is 1s; a i represents the acceleration value corresponding to the i-th unit time; m represents the number of unit times during which the flight speed of the UAV increases suddenly from the non-flying speed maximum to the flight speed maximum; a maxi represents the acceleration value corresponding to the maximum flight speed for the i-th time; a xi represents the flight acceleration value of the maximum non-flying speed corresponding to the maximum flight speed for the i-th time; T i T represents the duration of the flight speed increase from the ith time to the maximum flight speed; c Indicates the preset duration reference value; The speed parameter factor, the turning parameter factor and the acceleration parameter factor are used to obtain a specific value corresponding to the expected yaw distance of the UAV, wherein the specific value corresponding to the expected yaw distance is obtained by the following formula: Wherein, S represents a specific value corresponding to the expected yaw distance; S0 represents a preset initial value of the expected yaw distance; ΔS represents a preset compensation amount of the expected yaw distance.

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