A high-altitude infrared radiation simulation system for a drone

Abstract

The present application relates to the technical field of infrared radiation simulation, and particularly relates to a high-altitude infrared radiation simulation system for a UAV, comprising: an instruction generation module, which is used to acquire infrared radiation instructions of a target UAV; a high-altitude training segmentation module, which is used to determine initial trajectory paragraphs of the target UAV; a segmented execution module, which is used to determine a category of the trajectory paragraphs, and determine whether to perform infrared radiation instruction regulation or perform optimization analysis; an instruction regulation execution module, which is used to perform infrared radiation instruction regulation; a category analysis module, which is used to determine a judgment benchmark to acquire a posture category; and an instruction optimization execution module, which is used to perform infrared radiation instruction optimization, and determine whether to extend regulation adjustment to optimization analysis or to instruction coupling. The present application improves the simulation flexibility and smoothness of the infrared radiation simulation system.

Description

Technical Field

[0001] This invention relates to the field of infrared radiation simulation technology, and in particular to a high-altitude infrared radiation simulation system for unmanned aerial vehicles (UAVs). Background Technology

[0002] With the widespread application of UAV technology in military reconnaissance, target strike, and electronic warfare, the demand for high-altitude infrared radiation simulation is increasing. Simulation systems, by mounting infrared radiation sources on UAVs, simulate the infrared radiation characteristics of targets such as missiles and fighter jets during high-altitude flight, providing the necessary hardware conditions for performance testing of infrared search and tracking equipment and personnel training. Existing systems mostly focus on the hardware implementation of the infrared radiation source or the testing of static infrared characteristics, failing to adaptively adjust power adjustment commands based on the dynamic changes in the UAV's flight attitude across various training routes. During high-altitude training, UAVs frequently switch between various flight attitudes such as pitch, yaw, and roll. The infrared radiation characteristics of the target differ significantly under different attitude combinations. In actual training, frequent power adjustment commands may be generated, and the power adjustment of the infrared radiation source cannot be synchronized with these commands. Optimization for these commands must consider the infrared radiation characteristics of the actual training route. Fixed optimization methods are difficult to meet this requirement, easily leading to radiation intensity response lag and the accumulation of simulation errors, resulting in simulation failure. Therefore, how to improve the simulation accuracy and efficiency of infrared radiation simulation systems is a problem of great concern to those skilled in the art.

[0003] Chinese Patent Publication No. CN105468018A discloses a UAV target characteristic simulation system, including: a ground transceiver control platform, and an electromagnetic characteristic simulation device, an infrared characteristic simulation device, and a motion characteristic simulation device communicatively connected to the ground transceiver control platform. The system uses the ground electromagnetic characteristic simulation device, infrared characteristic simulation device, and motion characteristic simulation device in conjunction with the ground transceiver control platform to adjust the electromagnetic, infrared, and motion characteristics of the UAV in real time. It also simulates the target characteristics of multiple different types of flying targets and simultaneously calibrates and adjusts the actual flight parameters and trajectories of multiple targets. However, this technical solution suffers from the following problems: it fails to consider the simulation distortion caused by frequent command adjustments along different training routes; it cannot adaptively adjust the control and optimization methods of commands based on the attitude changes of the UAV along the training route; and it easily leads to low accuracy in infrared radiation simulation, resulting in poor UAV training effects. Summary of the Invention

[0004] To address this, the present invention provides a high-altitude infrared radiation simulation system for unmanned aerial vehicles (UAVs) to overcome the problems in existing technologies that fail to consider the frequent adjustment of commands along different training routes, resulting in simulation distortion, and are unable to adaptively adjust the control and optimization methods of commands according to the attitude changes of the UAV along the training route, which easily leads to low accuracy of infrared radiation simulation and poor training results for UAVs.

[0005] To achieve the above objectives, the present invention provides a high-altitude infrared radiation simulation system for unmanned aerial vehicles (UAVs), comprising: The instruction generation module is used to uniformly acquire several points on the preset flight path of the target UAV, as well as the flight parameter set corresponding to each point, and to acquire infrared radiation instructions to adjust the radiation intensity based on the flight parameter set of the target UAV. The high-altitude training segmentation module is used to divide the preset flight path into several initial trajectory segments based on the flight phase change values ​​of the target UAV. The segmented execution module is used to determine the category of the initial trajectory segment based on the number of flight attitudes of the target UAV and the degree of flight attitude difference in the initial trajectory segment, and to determine whether to adjust the infrared radiation command control to infrared radiation command optimization based on the category of the initial trajectory segment. The command control and execution module is used to extract the flight parameter set instantaneously to obtain the instantaneous flight parameter set, and to perform infrared radiation command control on the merged simulation segment and the smooth simulation segment based on the instantaneous flight parameter set. The category analysis module is used to combine continuous flight attitudes based on attitude combination conditions and calculate the combination repeatability, determine the judgment criterion based on the combination repeatability balance value, and determine whether the attitude category is a contributing attitude based on the judgment criterion. The instruction optimization execution module is used to perform infrared radiation instruction optimization. Based on the contribution attitude distribution density value, it determines the optimization analysis method as either extending and adjusting the infrared radiation instruction or coupling the instruction to adjacent reference attitude groups.

[0006] Furthermore, the high-altitude training segmentation module includes a segmentation point setting unit and a trajectory division unit; The segmentation point setting unit is used to move from the starting point to the end point of the preset flight route based on the preset trajectory scanning window, and sequentially detect the flight stage change value corresponding to the preset trajectory scanning window. The center point of the window where the cumulative value of the flight stage change value is greater than the preset cumulative value is recorded as the segmentation point, and the cumulative value is obtained again. A trajectory segmentation unit is used to define the trajectory segment between two adjacent segmentation points as the initial trajectory segment.

[0007] Furthermore, the change value of the flight phase is the magnitude of the change in the flight attitude vector between the end time and the start time of the preset trajectory scanning window; The flight attitude is a set of reference flight parameters determined based on the set of flight parameters for a single point. The set of flight parameters consists of the attitude parameters and motion parameters of the target UAV.

[0008] Furthermore, the segmented execution module includes a segment analysis unit and a segment execution determination unit; The segment analysis unit is used to identify initial trajectory segments with a number of flight attitudes greater than the preset number of flight attitudes or a flight attitude difference greater than the preset flight attitude difference as wave simulation segments, and initial trajectory segments other than wave simulation segments as smooth simulation segments. The paragraph execution determination unit is used to classify consecutive smooth simulated paragraphs as a merged simulated paragraph.

[0009] Furthermore, the category analysis module includes a baseline analysis unit and a posture category determination unit; The benchmark analysis unit is used to respond to the condition that the combined repeatability equilibrium value of flight attitude in each fluctuation simulation segment is greater than the preset combined repeatability equilibrium value, and to determine that the judgment benchmark will be adjusted from the combined repeatability to the combined maneuver smoothness. The attitude category determination unit is used to record combined attitudes that are greater than the determination benchmark threshold as contributing attitudes, and combined attitudes other than contributing attitudes as benchmark attitudes.

[0010] Furthermore, the combined repetition equilibrium value is the ratio of the average of the combined repetition mean of each combined posture in the fluctuation simulation segment to the variance. The combined repeatability is the average of the cosine similarity between the flight change vector corresponding to a single combined flight attitude and the flight change vector of the combined attitude in each wave simulation segment. The combined maneuver smoothness is the ratio of the number of first-level maneuver attitudes to the number of flight attitudes in the combined attitude. The first-level maneuver attitude is the flight attitude in the combined attitude where the flight angular velocity is less than or equal to the average of the minimum flight angular velocities in each combined attitude.

[0011] Furthermore, the instruction optimization execution module includes a distribution state acquisition unit, which is used to determine the optimization analysis method as instruction extension adjustment for fluctuation simulation segments where the contribution posture distribution density value is less than or equal to the preset contribution posture distribution density value. For the fluctuation simulation segment where the contribution attitude distribution density value is greater than the preset contribution attitude distribution density value, the optimization analysis method is determined to be command coupling.

[0012] Furthermore, the contribution posture distribution density value is the ratio of the number of contribution postures to the number of combined postures in the fluctuation simulation segment.

[0013] Furthermore, the instruction optimization execution module also includes an instruction extension adjustment unit, which is used to determine to increase the training interval of adjacent contributing posture groups for adjacent contributing posture groups whose training interval is less than or equal to the preset training interval, with the adjustment range being the preset adjustment time. The training interval is the flight time corresponding to a preset flight path segment between two contributing postures in an adjacent contributing posture group, and the adjacent contributing posture group consists of two adjacent contributing postures.

[0014] Furthermore, the instruction optimization execution module also includes an instruction coupling unit, which is used to obtain adjacent reference attitude groups whose combined repetition mean is greater than the preset combined repetition mean and whose instruction coupling error is less than or equal to the preset instruction coupling error, and determine to perform instruction coupling. The adjacent reference attitude group includes two reference attitudes, which are located in the same wave simulation segment and are adjacent to each other.

[0015] Compared with the prior art, the beneficial effects of the present invention are that the present invention determines the initial trajectory segment by the flight phase change value of the target UAV. The cumulative value of the flight phase change value is used to determine the cumulative degree of change of each flight parameter within the preset trajectory scanning window. The center point of the window with a cumulative value greater than the preset cumulative value is recorded as the segmentation point and the cumulative value is obtained again. This realizes the adaptive division of the preset flight route, avoids the omission of key training actions or the over-segmentation of smooth segments due to fixed step size segmentation, and improves the segmentation flexibility of the trajectory segment and the matching accuracy of infrared radiation simulation and flight attitude change.

[0016] Furthermore, this invention determines the category of the initial trajectory segment and determines whether to perform infrared radiation command control or optimization analysis by using the number of flight attitudes and the degree of flight attitude difference. The number of flight attitudes is used to determine the number of flight attitudes within the initial trajectory segment, and the degree of flight attitude difference is used to determine the maximum dispersion between flight attitudes within the initial trajectory segment. The initial trajectory segment is divided into a fluctuation simulation segment and a smooth simulation segment. The smooth simulation segment performs infrared radiation command control based on the instantaneous flight attitude to reduce computational overhead, while the fluctuation simulation segment enters optimization analysis to achieve fine control. This realizes the differentiated allocation of computational resources and control accuracy among different trajectory segments.

[0017] Furthermore, this invention determines the judgment criterion by combining the repetition balance value to obtain the attitude category as the contributing attitude or the reference attitude. The combined repetition balance value is used to determine the balance of attitude repetition among the combined attitudes in each wave simulation segment. When the balance value is small, using the combined repetition degree as the judgment criterion can effectively filter out the combined attitudes with more prominent value. When the balance value is large, using the combined maneuver smoothness as the judgment criterion can improve the differentiation of the contribution level of the combined attitudes. This allows the attitude category determination method to flexibly match the structural characteristics of different wave simulation segments, avoiding the limitation of a single judgment criterion being difficult to effectively distinguish the attitude contribution level under complex flight data.

[0018] Furthermore, this invention determines the optimization analysis method as command extension adjustment or command coupling by determining the contribution attitude distribution density value. The contribution attitude distribution density value is determined based on the ratio of the number of contribution attitudes to the number of combined attitudes in the fluctuation simulation segment. When the contribution attitude distribution density is small, the command extension adjustment method is used to provide an independent adjustment buffer for each contribution attitude. When the contribution attitude distribution density is large, the command coupling method is used to merge adjacent reference attitude groups. This avoids command redundancy and execution delay caused by independent adjustment and improves the adaptive matching capability between infrared radiation command optimization and attitude distribution characteristics. Attached Figure Description

[0019] Figure 1 This is a module connection diagram of a high-altitude infrared radiation simulation system for unmanned aerial vehicles (UAVs) according to an embodiment of the present invention. Figure 2 This is a flowchart illustrating how the segment category is determined based on the number of flight attitudes and the degree of difference in flight attitudes, as described in an embodiment of the present invention. Figure 3 This is a flowchart illustrating how the optimization analysis method, either command extension adjustment or command coupling, is determined based on the contribution attitude distribution density value in an embodiment of the present invention. Figure 4 This is a flowchart illustrating how to determine whether to perform instruction coupling based on the combined repetition mean and instruction coupling error, according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives and advantages of this invention clearer, the invention will be further described below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of the invention.

[0021] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0022] It should be noted that in the description of this invention, the terms "upper," "lower," "left," "right," "inner," and "outer," etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is merely for ease of description and does not indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0023] Please see Figure 1 The diagram shown is a module connection diagram of a high-altitude infrared radiation simulation system for unmanned aerial vehicles (UAVs) according to an embodiment of the present invention. The system includes: The instruction generation module is used to uniformly acquire several points on the preset flight path of the target UAV, as well as the flight parameter set corresponding to each point, and to acquire infrared radiation instructions to adjust the radiation intensity based on the flight parameter set of the target UAV. The high-altitude training segmentation module, which is connected to the instruction generation module, is used to divide the preset flight path based on the flight phase change values ​​of the target UAV to obtain several initial trajectory segments. The segmented execution module, which is connected to the high-altitude training segmented module, is used to determine the category of the initial trajectory segment based on the number of flight attitudes of the target UAV and the degree of flight attitude difference in the initial trajectory segment, and to determine whether to adjust the infrared radiation command control to infrared radiation command optimization based on the category of the initial trajectory segment. The command control and execution module is connected to the segmented execution module. It is used to extract the flight parameter set instantaneously to obtain the instantaneous flight parameter set, and to perform infrared radiation command control on the merged simulation segment and the smooth simulation segment based on the instantaneous flight parameter set. The category analysis module, which is connected to the segmented execution module, is used to combine continuous flight attitudes based on attitude combination conditions and calculate the combination repeatability, as well as determine the judgment criterion based on the combination repeatability balance value, and determine whether the attitude category is a contributing attitude based on the judgment criterion. The infrared radiation module, which is connected to the command control and execution module, is used to adjust the output power of the power supply compartment according to the infrared radiation command, so as to approach the target radiation intensity power corresponding to the infrared radiation command. The instruction optimization execution module is connected to the category analysis module and the infrared radiation module respectively. It is used to perform infrared radiation instruction optimization and determine the optimization analysis method based on the contribution attitude distribution density value, which is to extend and adjust the infrared radiation instruction or to couple the instruction to the adjacent reference attitude group. The simulation verification adjustment module is connected to the category analysis module and the instruction optimization execution module, respectively. It is used to determine the elimination segment based on the change smoothness after instruction optimization, and to determine the confirmation method of the elimination screening point in the elimination segment based on the maneuver change difference index.

[0024] In this embodiment of the invention, the preset flight route is either pre-stored in the simulation system by the user or designed by the user and uploaded to the simulation system for use as the flight route during the training of the target drone. The higher the user's training requirements for the target drone, the higher the complexity of the preset flight route.

[0025] The process of obtaining the number of points in the preset flight route includes: the more points in the preset flight route, the more flight parameter sets are obtained, and the higher the accuracy of segmenting the preset flight route and subsequent segment analysis. In this embodiment, the higher the user's requirements for the route fitting accuracy and smoothness of the simulation system, the more points are required. Specifically, the number of points for each preset flight route in historical qualified operating conditions is obtained, and the average number of points after removing outliers is calculated and recorded as the number of points for that preset flight route.

[0026] In this embodiment of the invention, the infrared radiation module works as follows: it receives infrared radiation commands and controls the power of the electrically heated omnidirectional infrared intensifier installed in the target UAV to simulate infrared radiation at various points. The infrared radiation commands are obtained by matching the flight parameter set corresponding to each point with an infrared simulation database. In this embodiment, for a single flight parameter set, the infrared radiation command is a signal to adjust the radiation intensity power of that flight parameter set to a target radiation intensity power. The target radiation intensity power is the radiation intensity power corresponding to that flight parameter set in the infrared simulation database, obtained through linear interpolation. The radiation intensity power is the output power of the power supply compartment in the electrically heated omnidirectional infrared intensifier. Specifically, the linear interpolation process includes: using the flight parameter set as a query index, determining multiple known sample points in the infrared simulation database that are closest to the flight parameter set in terms of Euclidean distance; linearly fitting the radiation intensity power in each sample point using a distance-inverse weighted method to obtain the target radiation intensity power corresponding to the flight parameter set. The sample points are key-value pairs in the infrared simulation database.

[0027] The electrically heated omnidirectional infrared intensifier includes a power supply compartment installed inside the target UAV cabin and a radiation compartment installed above the target UAV cabin. The power supply compartment provides the heating power required for the heating wires inside the radiation compartment. After receiving an infrared radiation command, the electrically heated omnidirectional infrared intensifier adjusts the output power of the power supply compartment to the target radiation intensity power in the infrared radiation command to simulate the set of flight parameters along the preset flight path. This is well known to those skilled in the art.

[0028] In this embodiment of the invention, the flight parameter set includes: the flight parameter set consists of the attitude parameters and motion parameters of the target UAV. The attitude parameters include the pitch angle, yaw angle, and roll angle of the target UAV, and the motion parameters include, but are not limited to, the flight speed, acceleration, and angular velocity of the target UAV. In this embodiment, for the flight parameter set corresponding to a single point, the corresponding flight attitude is confirmed as follows: when the flight parameter set is within the fluctuation range of the reference flight parameter set, the reference flight parameter set is recorded as the flight attitude of that point. The reference flight parameter set is uniformly selected during the training simulation of the target UAV. The more reference flight parameter sets there are, the more references there are for the flight attitude, and the higher the accuracy of the infrared radiation simulation. The higher the user's requirements for the accuracy of the infrared radiation simulation, the more reference flight parameter sets are selected.

[0029] In this embodiment of the invention, the construction of the infrared simulation database includes: solving the surface temperature field of the target UAV by establishing a thermal balance equation. The thermal balance equation includes at least a coupled analysis of key heat sources such as aerodynamic heat, solar radiation, engine waste heat, and internal equipment heating, and considers major heat dissipation methods such as surface convection and radiation. The infrared radiation intensity corresponding to each flight attitude is calculated using Planck's formula, and the output power of the power supply bay corresponding to the infrared radiation intensity is obtained. The set of flight parameters corresponding to each flight attitude is used as the index key in the key-value pair. The flight parameters of the target UAV, their corresponding infrared radiation intensity, and the output power of the power supply bay are used as the attribute values ​​in the key-value pair. Each key-value pair is stored in the database as the infrared simulation database, and linear interpolation is used for data retrieval. This is readily understood by those skilled in the art and will not be elaborated further.

[0030] Specifically, the high-altitude training segmentation module includes a segmentation point setting unit and a trajectory division unit; The segmentation point setting unit is used to move from the starting point to the end point of the preset flight route based on the preset trajectory scanning window, and sequentially detect the flight stage change value corresponding to the preset trajectory scanning window. The center point of the window where the cumulative value of the flight stage change value is greater than the preset cumulative value is recorded as the segmentation point, and the cumulative value is obtained again. A trajectory segmentation unit is used to define the trajectory segment between two adjacent segmentation points as the initial trajectory segment.

[0031] In this embodiment of the invention, the process of obtaining the cumulative value of flight phase change includes: the cumulative value of flight phase change is determined based on the flight phase change values ​​within each preset trajectory scanning window, and is positively correlated with the sum of the flight phase change values. In this embodiment, for the location of a single preset trajectory scanning window, the cumulative value of flight phase change is the sum of the flight phase change values ​​of each preset trajectory scanning window between that window and the nearest segment point. The flight phase change value is the modulus of the difference between the flight attitude vector at the end of the single preset trajectory scanning window and the flight attitude vector at the start. It is worth noting that the starting point of the preset flight route is the first segment point, and the flight attitude vector is a vector composed of the values ​​of each parameter in the flight parameter set, where the flight attitude vector = (pitch angle, yaw angle, roll angle, flight speed, acceleration, angular velocity). It can be understood that the high-altitude training segmentation module also includes a change value calculation unit to obtain the cumulative value of flight phase change. The cumulative value of the flight phase change value is used to determine the degree of cumulative change of each flight parameter between preset trajectory scanning windows. The larger the cumulative value of the flight phase change value, the more drastic the overall change of the flight parameter set between preset trajectory scanning windows. At this time, the center point of the preset trajectory scanning window is recorded as the segmentation point, realizing the adaptive division of the preset flight route, avoiding the omission of key training actions or the over-segmentation of smooth sections due to fixed-length segments, and improving the segmentation flexibility of trajectory segments.

[0032] In this embodiment of the invention, the process of acquiring the preset trajectory scanning window includes: simulating multiple preset flight route data with different maneuver intensities and flight speed ranges; setting different combinations of trajectory scanning window parameters for segment point identification tests; and selecting the average value of the window duration and step size of the trajectory scanning window parameters that meet the user's requirements for the infrared radiation simulation relative error as the preset trajectory scanning window. The infrared radiation simulation relative error is the percentage of the absolute value of the difference between the actual radiation intensity power and the target radiation intensity power to the target radiation intensity power. The smaller the infrared radiation simulation relative error, the higher the simulation accuracy of the system. The more sensitive the user is to the accuracy of the infrared radiation simulation, the lower the error requirement should be when selecting the preset value using the infrared radiation simulation relative error as an evaluation index. That is, the closer the error is to 0%, the better it meets the user's needs. The setting of the evaluation index is content already mastered by those skilled in the art and will not be elaborated further. In this embodiment, the higher the user's requirement for the precision of the training trajectory segmentation, the smaller the window duration and step size of the preset trajectory scanning window should be set.

[0033] In this embodiment of the invention, the acquisition of the preset cumulative value includes: obtaining training routes with different training types, different maneuver intensities, and different flight speed ranges through simulation as preset flight routes; arranging the flight parameter sets on each preset flight route in a time series; calculating the cumulative value of the flight stage change value within each preset trajectory scanning window; simulating the fitting error of the infrared radiation intensity simulation under different cumulative values; selecting the average value of the cumulative value whose relative error of the infrared radiation simulation meets the user's requirements as the preset cumulative value; the higher the user's requirement for the precision of the flight route segmentation, the smaller the value of the preset cumulative value.

[0034] Please see Figure 2 As shown, it is a flowchart of an embodiment of the present invention for determining the segment category based on the number of flight attitudes and the degree of flight attitude difference. The segment execution module includes a segment analysis unit and a segment execution determination unit. The segment analysis unit is used to identify initial trajectory segments with a number of flight attitudes greater than the preset number of flight attitudes or a flight attitude difference greater than the preset flight attitude difference as wave simulation segments, and initial trajectory segments other than wave simulation segments as smooth simulation segments. The paragraph execution determination unit is used to classify consecutive smooth simulated paragraphs as a merged simulated paragraph.

[0035] In this embodiment of the invention, the segmented execution module further includes an attitude calculation unit to obtain the number of flight attitudes and the flight attitude difference degree. The process of obtaining the flight attitude difference degree includes: the flight attitude difference degree is determined based on the maximum angular distance between adjacent groups of flight attitudes in the initial trajectory segment, and the flight attitude difference degree and the maximum angular distance are positively correlated. In this embodiment, the flight attitude difference degree is the maximum angular distance between adjacent groups of flight attitudes in the initial trajectory segment. The adjacent group of flight attitudes consists of a set of flight parameters corresponding to two random points, and the angular distance is the distance between attitude parameters in the two flight parameter sets calculated using an inverse trigonometric function. It can be understood that a larger number of flight attitudes indicates more different flight attitudes within the initial trajectory segment, and a higher degree of detail in the changes in the target UAV's movements within this interval. The flight attitude difference degree is used to determine the maximum degree of difference between flight attitudes within the initial trajectory segment. A larger flight attitude difference degree indicates more drastic attitude changes and more significant maneuvering amplitude for the target UAV within the initial trajectory segment, requiring optimized analysis of infrared radiation commands for the initial trajectory segment to achieve fine-grained control.

[0036] In this embodiment of the invention, the process of obtaining the preset number of flight attitudes includes: collecting data from multiple preset flight routes, setting different threshold values ​​for the number of flight attitudes to simulate the classification of initial trajectory segments, and selecting the average value of the flight attitude number threshold values ​​whose relative error in infrared radiation simulation meets user requirements as the preset number of flight attitudes. In this embodiment, the higher the user's requirement for the accuracy of infrared radiation simulation, the smaller the preset number of flight attitudes should be.

[0037] In this embodiment of the invention, the process of obtaining the preset flight attitude difference degree includes: collecting data from multiple preset flight routes, setting different flight attitude difference degree thresholds for each route, simulating the classification of initial trajectory segments, and using the minimum flight attitude difference degree that satisfies user requirements for segment classification accuracy as the preset flight attitude difference degree. The segment classification accuracy is the ratio of the number of correctly classified initial trajectory segments to the total number of initial trajectory segments. A higher segment classification accuracy means a more accurate classification of trajectory segments by the system. Since users are more sensitive to the accuracy of infrared radiation simulation, the requirement for accuracy is higher when selecting a preset value based on segment classification accuracy. In this embodiment, the higher the user's requirement for the accuracy of infrared radiation simulation, the smaller the value of the preset flight attitude difference degree.

[0038] In this embodiment of the invention, the process of obtaining merged simulation segments is as follows: Smooth simulation segments are sequentially analyzed using continuous conditional analysis in descending order of starting distance to obtain merged simulation segments. The starting distance is the length of the training segment between the midpoint of the smooth simulation segment and the starting point of the preset flight path. Continuous analysis for a single smooth simulation segment includes: designating adjacent smooth simulation segments as segments to be analyzed; if the number of flight attitudes in the smooth simulation segment and the segment to be analyzed is less than or equal to the preset number of flight attitudes, and the flight attitude difference is less than or equal to the preset flight attitude difference, then the segment to be analyzed is merged into the smooth simulation segment and recorded as one smooth simulation segment. Continuous analysis continues on the merged smooth simulation segment until no more segments to be analyzed that meet the continuous analysis criteria appear, at which point merging stops, and the merged smooth simulation segment is recorded as a merged simulation segment. It is worth noting that if a single smooth simulation segment has participated in merging, continuous analysis will not be performed again.

[0039] Specifically, the command control execution module performs infrared radiation command control, including: the command control execution module acquires the target radiation intensity power corresponding to the instantaneous flight parameter set every second and controls it to adjust to the target radiation intensity power. The instantaneous flight parameter set is the flight parameter set acquired by the command control execution module every second from the beginning of the merged simulation segment or the end of the smooth simulation segment.

[0040] Specifically, the category analysis module includes a baseline analysis unit and a posture category determination unit; The benchmark analysis unit is used to respond to the condition that the combined repeatability equilibrium value of flight attitude in each fluctuation simulation segment is greater than the preset combined repeatability equilibrium value, and to determine that the judgment benchmark will be adjusted from the combined repeatability to the combined maneuver smoothness. And the condition that the combined repeatability equilibrium value of the flight attitude in each wave simulation segment is less than or equal to the preset combined repeatability equilibrium value is determined by using the combined repeatability as the criterion. The attitude category determination unit is used to record combined attitudes that are greater than the determination benchmark threshold as contributing attitudes, and combined attitudes other than contributing attitudes as benchmark attitudes.

[0041] In this embodiment of the invention, the segmented execution module further includes a combination calculation unit for obtaining the combination repeatability, the combination repeatability mean, and the combination repeatability balance value of the combined postures.

[0042] in, The process of obtaining the combined repetition equilibrium value includes: the combined repetition equilibrium value is determined based on the average value and variance of the combined repetition mean of each combined attitude in the wave simulation segment, and is positively correlated with the average value of the combined repetition mean, and negatively correlated with the variance of the combined repetition mean. In this embodiment, the combined repetition equilibrium value is the ratio of the average value of the combined repetition mean of each combined attitude in the wave simulation segment to the variance.

[0043] The process of obtaining the combined repetition mean includes: the combined repetition mean is the average of the combined repetition of each combined attitude in a single wave simulation segment. For a single combined attitude, the combined repetition is the average of the cosine similarity between its corresponding flight change vector and the flight change vectors of the combined attitudes in each wave simulation segment.

[0044] The combined attitude includes a first combination and a second combination. The first combination is the flight maneuver of the target UAV between two adjacent second combinations, and the second combination is the continuous flight attitude.

[0045] Continuous flight attitude refers to a continuous single flight attitude. A single flight attitude is a set of flight parameters within a fluctuating simulation segment whose change range is less than or equal to a preset change range. The change range of the flight parameter set is the maximum value of the magnitude of the difference between the flight attitude vectors corresponding to any two flight parameter sets within the preset trajectory scanning window. For a single combined attitude, the flight change vector consists of the angular distance change value, average flight speed, flight speed difference value, average flight acceleration value, and average flight angular velocity value corresponding to each flight parameter set in the combined attitude. Among them, the angular distance change value is the maximum angular distance between any two flight parameter sets in a single combined attitude; the average flight speed is the average speed of the target UAV in a single combined attitude; the flight speed difference value is the maximum difference between the flight speeds of any two flight parameter sets in a single combined attitude; the average flight acceleration is the average acceleration of the target UAV in a single combined attitude; and the average flight angular velocity is the average angular velocity of the target UAV in a single combined attitude. The flight change vector = (angular distance change value, average flight speed, flight speed difference value, average flight acceleration value, average flight angular velocity value).

[0046] Understandably, the combined repetition balance value is used to determine the balance of repetition degree among the combined postures in the wave simulation segment. The smaller the combined repetition balance value, the greater the difference in the combined repetition degree among the combined postures in the wave simulation segment. Using the combined repetition degree as the criterion can effectively screen out the combined postures with more prominent value. The larger the combined repetition balance value, the higher the uniformity of the distribution of the combined repetition degree among the combined postures in the wave simulation segment. Using the combined maneuver smoothness as the criterion can enhance the distinguishability of the contribution level of the combined postures, so that the posture category determination method can flexibly match the structural characteristics of different wave simulation segments.

[0047] In this embodiment of the invention, the segmented execution module further includes a maneuver calculation unit for obtaining the combined maneuver smoothness of the combined attitudes. The process of obtaining the combined maneuver smoothness includes: the combined maneuver smoothness is determined based on the ratio of the number of first-level maneuver attitudes to the number of flight attitudes in the combined attitudes, and is positively correlated with the number of first-level maneuver attitudes and negatively correlated with the number of flight attitudes. In this embodiment, the combined maneuver smoothness is the ratio of the number of first-level maneuver attitudes in the combined attitudes to the number of flight attitudes in the combined attitudes. The first-level maneuver attitude is the flight attitude in the combined attitudes whose flight angular velocity is less than or equal to the minimum value of the average flight angular velocity in each combined attitude. It can be understood that the combined maneuver smoothness is used to determine the degree of low-maneuver changes in the combined attitudes. The larger the combined maneuver smoothness, the smoother the maneuver changes of the target UAV in the wave simulation segment, and the lower the control accuracy requirement for infrared simulation.

[0048] In this embodiment of the invention, the process of obtaining the preset combined repetition balance value includes: simulating attitude category determination by setting different threshold values ​​for the combined repetition balance value, and selecting the average value of the combined repetition balance value whose relative error in infrared radiation simulation meets the user's requirements as the preset combined repetition balance value. In this embodiment, the higher the user's requirement for the accuracy of attitude contribution recognition, the smaller the value of the preset combined repetition balance value.

[0049] In this embodiment of the invention, the process of obtaining the judgment benchmark threshold includes: when the judgment benchmark is the combined repeatability, the larger the judgment benchmark, the higher the degree of repetition of the combined attitude in each fluctuation simulation segment, the stronger the common characteristics with other combined attitudes, and the smaller the influence on the flight attitude; when the judgment benchmark is the combined maneuver smoothness, the larger the judgment benchmark, the smaller the maneuver changes of the combined attitude, the smoother the flight action of the target UAV, and the lower its influence on the flight of the entire segment. Therefore, the larger the judgment benchmark, the lower the probability that the combined attitude will be judged as a contributing attitude, the lower the control accuracy of the infrared radiation simulation, and the higher the user's requirements for the accuracy of the infrared radiation simulation, the smaller the judgment benchmark threshold should be set. In this embodiment, by collecting data from multiple preset flight routes, different judgment benchmark thresholds are set for attitude category judgment simulation, and the average value of the judgment benchmark thresholds whose relative error of the infrared radiation simulation meets the user's requirements is selected as the judgment benchmark threshold.

[0050] In this embodiment of the invention, the process of obtaining the preset flight parameter set includes: collecting data from multiple preset flight routes, setting different selection numbers for each flight parameter set to conduct infrared radiation simulation tests, and selecting the average value of the selection numbers of flight parameter sets whose relative error in the infrared radiation simulation meets the user's requirements as the preset flight parameter set. In this embodiment, the higher the user's requirement for attitude division precision, the smaller the preset variation range should be set.

[0051] Please see Figure 3 As shown, it is a flowchart of the optimization analysis method for determining the contribution attitude distribution density value in an embodiment of the present invention, which is either instruction extension adjustment or instruction coupling. The instruction optimization execution module includes a distribution state acquisition unit, which is used to determine the optimization analysis method as instruction extension adjustment for the fluctuation simulation segment where the contribution attitude distribution density value is less than or equal to the preset contribution attitude distribution density value. For the fluctuation simulation segment where the contribution attitude distribution density value is greater than the preset contribution attitude distribution density value, the optimization analysis method is determined to be command coupling.

[0052] In this embodiment of the invention, the process of obtaining the contribution attitude distribution density value includes: the contribution attitude distribution density value is determined based on the number of contribution attitudes and the number of combined attitudes in the wave simulation segment. The contribution attitude distribution density value is positively correlated with the number of contribution attitudes and negatively correlated with the number of combined attitudes. In this embodiment, the contribution attitude distribution density value is the ratio of the number of contribution attitudes to the number of combined attitudes in the wave simulation segment. It can be understood that the instruction optimization execution module also includes a contribution calculation unit to obtain the contribution attitude distribution density value of the contribution attitudes. The contribution attitude distribution density value is used to determine the distribution density of contribution attitudes in the wave simulation segment. The larger the contribution attitude distribution density value, the higher the proportion of contribution attitudes in the wave simulation segment. Instruction simplification is needed to reduce the mutual influence between adjacent contribution attitudes. The optimization analysis method is determined to be instruction coupling, avoiding instruction redundancy and execution delay caused by independent adjustment of the reference attitude.

[0053] In this embodiment of the invention, the process of obtaining the preset contribution attitude distribution density value includes: collecting flight data of the target UAV under different contribution attitude distribution density characteristics, setting different threshold values ​​for the contribution attitude distribution density value for optimization analysis to determine the simulation, and selecting the minimum threshold value for the infrared radiation simulation relative error that meets the user's requirements as the preset contribution attitude distribution density value. In this embodiment, the higher the user's requirement for the smoothness of the radiation simulation response, the smaller the preset contribution attitude distribution density value should be.

[0054] Specifically, the instruction optimization execution module also includes an instruction extension adjustment unit, which is used to determine to increase the training interval of adjacent contributing posture groups whose training interval is less than or equal to the preset training interval, with the adjustment range being the preset adjustment time.

[0055] The process of obtaining the training interval includes: the training interval is the flight time corresponding to the preset flight path segment between two contributing postures in the adjacent contributing posture group. The adjacent contributing posture group consists of two adjacent contributing postures. For the adjacent contributing posture group whose training interval is less than or equal to the preset training interval, it is determined that the infrared radiation commands of the contributing postures that occur later will be delayed by a preset adjustment time to obtain more sufficient command adjustment time and heating buffer time.

[0056] In this embodiment of the invention, the process of obtaining the preset training interval and preset adjustment time includes: the higher the user's requirement for the smoothness of infrared radiation intensity changes, the larger the preset training interval should be set, and the smaller the preset adjustment time should be set. In this embodiment, by obtaining the training interval and adjustment time in historical qualified working conditions with different contribution posture time distribution characteristics and different adjustment time parameters, the average values ​​of the training interval and adjustment time after removing outliers are calculated and recorded as the preset training interval and preset adjustment time, respectively.

[0057] Please see Figure 4 As shown, it is a flowchart of an embodiment of the present invention for determining whether to perform instruction coupling based on the combined repetition mean and instruction coupling error. The instruction optimization execution module also includes an instruction coupling unit, which is used to obtain adjacent reference attitude groups whose combined repetition mean is greater than a preset combined repetition mean and whose instruction coupling error is less than or equal to a preset instruction coupling error, and determine whether to perform instruction coupling. The adjacent reference attitude group includes two reference attitudes, which are located in the same wave simulation segment and are adjacent to each other.

[0058] In this embodiment of the invention, the instruction optimization execution module further includes a coupling execution unit, which is used to perform instruction coupling. The process of performing instruction coupling includes: unifying the flight parameter sets in each optimization group to adopt the same infrared radiation instruction; for a single optimization group, adding the parameters in the flight parameter sets of two points in the optimization group and taking the average value, which are then recorded as the flight parameter sets of the two points. Here, an optimization group consists of two adjacent points in the wave simulation segment. It is worth noting that when constructing optimization groups, the initial distances of each point are arranged in ascending order, and a single point only participates in the construction of one optimization group. If a single point cannot participate in the construction of an optimization group, instruction coupling is not performed.

[0059] In this embodiment of the invention, the instruction optimization execution module further includes a coupling calculation unit for obtaining the instruction coupling error of adjacent reference attitude groups. The process of obtaining the instruction coupling error includes: the instruction coupling error is determined based on the absolute value of the difference between the maximum target radiation intensity power corresponding to the two reference attitudes in the adjacent reference attitude groups before coupling, and the instruction coupling error is positively correlated with the absolute value of the difference. In this embodiment, the instruction coupling error is the absolute value of the difference between the maximum target radiation intensity power corresponding to the two reference attitudes in the adjacent reference attitude groups before coupling. It can be understood that the instruction coupling error is used to determine the degree of difference in the target radiation intensity values ​​of adjacent reference attitude groups before instruction coupling. The larger the instruction coupling error, the more significant the difference in target radiation intensity power corresponding to the two reference attitudes. Direct instruction coupling can easily lead to a decrease in radiation simulation accuracy. It is determined that instruction coupling is performed on the adjacent reference attitude groups when the instruction coupling error is less than or equal to the preset instruction coupling error to avoid simulation distortion caused by excessive difference in radiation intensity.

[0060] In this embodiment of the invention, the process of obtaining the preset command coupling error includes: collecting data from multiple sets of adjacent reference attitude groups with different radiation intensity differences, setting different thresholds for command coupling error to perform command coupling determination simulation, and selecting the minimum threshold that satisfies the user's requirements for the relative error of infrared radiation simulation as the preset command coupling error. In this embodiment, the higher the user's requirements for the accuracy of infrared radiation simulation, the smaller the preset command coupling error should be set.

[0061] Specifically, the simulation verification and adjustment module includes a smoothing verification unit, which is used to perform instruction smoothing verification for each fluctuation simulation segment. Fluctuation simulation segments with a change smoothness less than or equal to a preset change smoothness are recorded as elimination segments, and elimination posture selection is performed for the elimination segments.

[0062] In this embodiment of the invention, the simulation verification adjustment module further includes a smoothing calculation unit for obtaining the smoothness of change in the fluctuation simulation segment. The process of obtaining the smoothness of change includes: the smoothness of change is determined based on the average value and standard deviation of the radiation intensity change values ​​of each adjacent flight parameter set pair in the optimized fluctuation simulation segment, and is positively correlated with the average value of the radiation intensity change values ​​and negatively correlated with the standard deviation of the radiation intensity change values. In this embodiment, the smoothness of change is the ratio of the average value of the radiation intensity change values ​​of each adjacent flight parameter set pair in the optimized fluctuation simulation segment to the standard deviation. The radiation intensity change value is the absolute value of the difference between the target radiation intensity power corresponding to the two flight parameter sets in the adjacent flight parameter set pair, and the adjacent flight parameter set pair consists of two adjacent flight parameter sets. Understandably, the smoothness of change is used to determine the degree of stability of radiation intensity fluctuations between adjacent flight parameter sets after optimization of the fluctuation simulation segment. The greater the smoothness of change, the more uniform the radiation intensity changes between adjacent flight parameter sets, and the smaller the degree of fluctuation. This indicates that the command smoothness of the fluctuation simulation segment meets the requirements and does not need to be eliminated. The smaller the smoothness of change, the more drastic the radiation intensity changes, and the existence of points where the radiation intensity changes abruptly. This indicates that the fluctuation simulation segment is recorded as a segment to be eliminated and the elimination attitude selection is performed to avoid simulation distortion caused by abrupt changes in local radiation intensity.

[0063] In this embodiment of the invention, obtaining the preset smoothness of change includes: acquiring the smoothness of change in historical qualified operating conditions with different smoothness of change characteristics, calculating the average smoothness of change after removing outliers, and recording it as the preset smoothness of change. In this embodiment, the higher the user's requirement for the continuity of infrared radiation simulation results, the larger the preset smoothness of change should be set.

[0064] Specifically, the simulation verification adjustment module also includes a difference analysis unit and a motorized elimination unit; The difference analysis unit is used to respond to the condition that the difference index of maneuver change in the elimination paragraph is greater than the preset difference index of maneuver change, and to determine the elimination method as maneuver elimination. The maneuver rejection unit is used to mark the set of flight parameters with a maneuver change rate greater than a preset maneuver change rate as rejection screening points, and to reject the rejection screening points with the highest outlier coefficient.

[0065] In this embodiment of the invention, the simulation verification and adjustment module further includes a maneuver change calculation unit, used to calculate the maneuver change difference index of the elimination segment and the outlier coefficient of the elimination screening point. The process of obtaining the maneuver change difference index includes: the maneuver change difference index is determined based on the maneuver change rate of each adjacent flight parameter set pair in the elimination segment, and is positively correlated with the standard deviation of the maneuver change rate. In this embodiment, the maneuver change difference index is the standard deviation of the maneuver change rate of each adjacent flight parameter set pair, and the maneuver change rate is the average of the flight angular velocities in the adjacent flight parameter set pairs. It can be understood that the maneuver change difference index is used to determine the dispersion of the maneuver change rate between each adjacent flight parameter set pair in the elimination segment. The larger the maneuver change difference index, the more significant the difference in the maneuver change rate of each flight parameter set pair in the elimination segment, and the greater the fluctuation of the maneuver intensity. The elimination method is determined to be maneuver elimination, avoiding radiation simulation distortion caused by drastic maneuver changes. The smaller the maneuver change difference index, the more uniform the distribution of the maneuver change rate in the elimination segment, and the smoother the fluctuation of the maneuver intensity. The elimination method is determined to be radiation anomaly elimination, thereby achieving adaptive matching between the elimination strategy and the maneuver characteristics of the segment.

[0066] The process of obtaining the outlier coefficient includes: for a single rejection screening point, the outlier coefficient is the number of local maneuvering attitudes within the outlier length corresponding to that rejection screening point. A local maneuvering attitude is a set of flight parameters whose flight angular velocity is less than or equal to the maneuvering average. The maneuvering average is the average of the flight angular velocities of the flight parameter sets within the outlier length corresponding to each rejection screening point. The outlier length is obtained by extending outwards from the rejection screening point as the center. The process of obtaining the outlier length includes: simulating multiple preset flight path data with different maneuvering variation distribution characteristics, setting different outlier lengths for outlier coefficient calculation tests, and selecting the average outlier length corresponding to the simulation result where the relative error of the infrared radiation simulation meets the user's requirements as the outlier length. In this embodiment, the higher the user's requirements for the precision and local sensitivity of abnormal attitude rejection, the smaller the outlier length should be set.

[0067] In this embodiment of the invention, the process of obtaining the preset maneuver variation difference index includes: collecting multiple sets of data on segments to be eliminated with different degrees of maneuver variation dispersion, setting different threshold values ​​for the maneuver variation difference index for each segment, simulating the elimination method, and selecting the minimum threshold value for which the relative error of the infrared radiation simulation after elimination meets the user's requirements as the preset maneuver variation difference index. In this embodiment, the higher the user's requirement for the matching degree between the elimination strategy and the segment maneuver characteristics, the smaller the preset maneuver variation difference index should be set.

[0068] In this embodiment of the invention, the process of obtaining the preset maneuver change rate includes: obtaining the maneuver change rate from historical qualified operating conditions with different maneuver change distribution characteristics, and calculating the average value of the maneuver change rate after removing outliers, which is then recorded as the preset maneuver change rate. In this embodiment, the higher the user's requirement for the accuracy of infrared radiation simulation, the smaller the preset maneuver change rate should be set.

[0069] Specifically, the simulation verification adjustment module also includes an anomaly removal unit; The difference analysis unit is also used to determine the elimination method as radiation anomaly elimination in response to the condition that the difference index of maneuvering change in the elimination paragraph is less than or equal to the preset difference index of maneuvering change. The anomaly removal unit is used to record the set of flight parameters whose radiation gradient anomalies are greater than the preset radiation gradient anomalies as removal screening points and remove them.

[0070] In this embodiment of the invention, the simulation verification and adjustment module further includes a gradient calculation unit for obtaining radiation gradient anomalies for each flight parameter set within the outlier length. The process of obtaining radiation gradient anomalies includes: the radiation gradient anomaly is determined based on the difference between the target radiation intensity power corresponding to a single flight parameter set and the average target radiation intensity power of each flight parameter set within the outlier length. The absolute value of the radiation gradient anomaly is positively correlated with the difference. In this embodiment, the radiation gradient anomaly is the difference between the target radiation intensity power corresponding to a single flight parameter set and the average target radiation intensity power of each flight parameter set within the outlier length. It can be understood that the radiation gradient anomaly is used to determine the degree of difference in the target radiation intensity of a single flight parameter set. The larger the radiation gradient anomaly, the more significant the difference between the target radiation intensity of the flight parameter set and the average radiation intensity of other flight parameter sets within the outlier length. This flight attitude is then recorded as a rejection point and rejected to avoid simulation distortion caused by prominent anomalies in target radiation intensity.

[0071] In this embodiment of the invention, the process of obtaining the preset radiation gradient anomaly value includes: obtaining the radiation gradient anomaly values ​​from historical operating conditions with different radiation intensity deviation characteristics, and calculating the average value of the radiation gradient anomaly values ​​after removing the anomalies, which is then recorded as the preset radiation gradient anomaly value. In this embodiment, the higher the user's requirement for the accuracy of infrared radiation simulation, the smaller the preset radiation gradient anomaly value should be.

[0072] In this embodiment of the invention, the historical operating conditions refer to the parameter records of infrared enhancement simulations used during the training of the target UAV in the past. These records document the parameter values ​​used in the system. For any historical operating condition, if the simulation accuracy of the infrared enhancement simulation system meets the training requirements of the UAV, then that historical operating condition is considered a qualified historical operating condition. Whether the infrared enhancement simulation accuracy corresponding to the historical operating condition meets the training requirements of the UAV can be determined based on, but not limited to, the relative error between the simulated output radiation intensity and the theoretical radiation intensity. How to determine whether the training requirements of the UAV are met is a matter already understood by those skilled in the art and will not be elaborated further.

[0073] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A high-altitude infrared radiation simulation system for unmanned aerial vehicles (UAVs), characterized in that, include: The instruction generation module is used to uniformly acquire several points on the preset flight path of the target UAV, as well as the flight parameter set corresponding to each point, and to acquire infrared radiation instructions to adjust the radiation intensity based on the flight parameter set of the target UAV. The high-altitude training segmentation module is used to divide the preset flight path into several initial trajectory segments based on the flight phase change values ​​of the target UAV. The segmented execution module is used to determine whether the initial trajectory segment is a fluctuating simulation segment or a smooth simulation segment based on the number of flight attitudes of the target UAV and the degree of flight attitude difference in the initial trajectory segment, and to determine whether to adjust the infrared radiation command control to infrared radiation command optimization based on the category of the initial trajectory segment. The command control and execution module is used to extract the flight parameter set instantaneously to obtain the instantaneous flight parameter set, and to perform infrared radiation command control on the merged simulation segment and the smooth simulation segment based on the instantaneous flight parameter set. The category analysis module is used to combine continuous flight attitudes based on attitude combination conditions and calculate the combination repeatability, determine the judgment criterion based on the combination repeatability balance value, and determine whether the attitude category is a contributing attitude based on the judgment criterion. The instruction optimization execution module is used to perform infrared radiation instruction optimization. Based on the contribution attitude distribution density value, it determines the optimization analysis method as either extending and adjusting the infrared radiation instruction or coupling the instruction to adjacent reference attitude groups.

2. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 1, characterized in that, The high-altitude training segmentation module includes a segmentation point setting unit and a trajectory division unit; The segmentation point setting unit is used to move from the starting point to the end point of the preset flight route based on the preset trajectory scanning window, and sequentially detect the flight stage change value corresponding to the preset trajectory scanning window. The center point of the window where the cumulative value of the flight stage change value is greater than the preset cumulative value is recorded as the segmentation point, and the cumulative value is obtained again. A trajectory segmentation unit is used to define the trajectory segment between two adjacent segmentation points as the initial trajectory segment.

3. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 2, characterized in that, The change value of the flight phase is the magnitude of the change in the flight attitude vector between the end time and the start time of the preset trajectory scanning window; The flight attitude is a set of reference flight parameters determined based on the set of flight parameters for a single point. The set of flight parameters consists of the attitude parameters and motion parameters of the target UAV.

4. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 2, characterized in that, The segmented execution module includes a segment analysis unit and a segment execution determination unit; The segment analysis unit is used to identify initial trajectory segments with a number of flight attitudes greater than the preset number of flight attitudes or a flight attitude difference greater than the preset flight attitude difference as wave simulation segments, and initial trajectory segments other than wave simulation segments as smooth simulation segments. The paragraph execution determination unit is used to classify consecutive smooth simulated paragraphs as a merged simulated paragraph.

5. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 1, characterized in that, The category analysis module includes a baseline analysis unit and a posture category determination unit; The benchmark analysis unit is used to respond to the condition that the combined repeatability equilibrium value of flight attitude in each fluctuation simulation segment is greater than the preset combined repeatability equilibrium value, and to determine that the judgment benchmark will be adjusted from the combined repeatability to the combined maneuver smoothness. The attitude category determination unit is used to record combined attitudes that are greater than the determination benchmark threshold as contributing attitudes, and combined attitudes other than contributing attitudes as benchmark attitudes.

6. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 5, characterized in that, The combined repetition equilibrium value is the ratio of the average of the combined repetition mean of each combined posture in the fluctuation simulation segment to the variance. The combined repeatability is the average of the cosine similarity between the flight change vector corresponding to a single combined flight attitude and the flight change vector of the combined attitude in each wave simulation segment. The combined maneuver smoothness is the ratio of the number of first-level maneuver attitudes to the number of flight attitudes in the combined attitude. The first-level maneuver attitude is the flight attitude in the combined attitude where the flight angular velocity is less than or equal to the average of the minimum flight angular velocities in each combined attitude.

7. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 6, characterized in that, The instruction optimization execution module includes a distribution state acquisition unit, which is used to determine the optimization analysis method as instruction extension adjustment for fluctuation simulation segments where the contribution posture distribution density value is less than or equal to the preset contribution posture distribution density value. For the fluctuation simulation segment where the contribution attitude distribution density value is greater than the preset contribution attitude distribution density value, the optimization analysis method is determined to be command coupling.

8. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 7, characterized in that, The contribution posture distribution density value is the ratio of the number of contribution postures to the number of combined postures in the fluctuation simulation segment.

9. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 7, characterized in that, The instruction optimization execution module also includes an instruction extension adjustment unit, which is used to determine to increase the training interval of adjacent contributing posture groups whose training interval is less than or equal to the preset training interval, with the adjustment range being the preset adjustment time. The training interval is the flight time corresponding to a preset flight path segment between two contributing postures in an adjacent contributing posture group, and the adjacent contributing posture group consists of two adjacent contributing postures.

10. The high-altitude infrared radiation simulation system for unmanned aerial vehicles according to claim 7, characterized in that, The instruction optimization execution module also includes an instruction coupling unit, which is used to obtain adjacent reference attitude groups whose combined repetition mean is greater than the preset combined repetition mean and whose instruction coupling error is less than or equal to the preset instruction coupling error, and determine to perform instruction coupling. The adjacent reference attitude group includes two reference attitudes, which are located in the same wave simulation segment and are adjacent to each other.

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