An accurate prediction method and system for an air drop release point and drop point of an aircraft

Abstract

The application discloses an accurate prediction and solution method and system for an airplane air-drop delivery point and a landing point, and belongs to the technical field of air-drop simulation and control. The method comprises the following steps: obtaining an initial delivery parameter set of an air-drop system; performing interpolation processing to obtain real-time environmental parameters; combining the multi-dimensional coupling air-drop dynamics three-dimensional motion model with the dynamics parameters of the stage-opening-parachute characteristics to adapt the dynamics parameters, and completing solution and updating to obtain the real-time motion state of the air-drop object; completing the parameter switching of the stage-opening-parachute, continuously solving until the air-drop object lands, and obtaining the prediction result of the initial landing point; calculating the landing point error based on the prediction result of the initial landing point, iteratively optimizing the delivery position, and completing corresponding solution and prediction until the landing point error meets a preset threshold, and outputting the optimal delivery position and the final accurate landing point prediction result. The motion solution is closer to the actual air-drop scene, the landing point prediction accuracy is improved, and the method can be adapted to various high-precision air-drop scenes such as unmanned aerial vehicle delivery, emergency rescue and delivery.

Description

Technical Field

[0001] This invention belongs to the field of airdrop simulation and control technology, specifically relating to a method and system for accurately predicting and calculating the drop point and landing point of an aircraft airdrop. Background Technology

[0002] In scenarios involving airdropped supplies and equipment, cargo undergoes multiple stages after being dropped from an aircraft, including unlocking, exiting the aircraft, parachute deployment (pilot parachute to main parachute), aerial movement, and landing. This movement is influenced by factors such as gravity, air resistance, wind speed, and aircraft attitude, making delivery accuracy relatively difficult to control. Current delivery schemes primarily rely on empirical estimations or simplified models, easily neglecting key factors such as air density stratification and the dynamic deployment process of the parachute, resulting in low simulation accuracy and overly simplified dynamic models. Furthermore, the impact of aircraft heading and wind speed on delivery errors is not considered, making precise delivery difficult. Moreover, current technologies do not fully consider the typical two-stage operation from pilot parachute deployment to main parachute deployment, making it difficult to accurately simulate the sudden changes in drag and transitions in motion state during parachute inflation, leading to poor control of motion calculation errors during the parachute opening phase. Additionally, there is a relative lack of closed-loop optimization mechanisms based on motion calculations. When environmental parameters fluctuate or the initial delivery point deviates, it is difficult to improve prediction accuracy through adaptive adjustments, resulting in a discrepancy between the actual landing point and the predicted value, making it difficult to meet the requirements for precise delivery. Therefore, in summary, the current drop operations suffer from oversimplification of the dynamic model and lack of dynamic adaptation in the parachute deployment process. This may lead to a large deviation between the drop point and the predicted value, affecting the reliability and accuracy of the airdrop mission and limiting the application of airdrops in high-precision scenarios. Summary of the Invention

[0003] This invention provides a method and system for accurately predicting and calculating the drop point and landing point of an aircraft airdrop. The purpose is to solve the problem that in current drop operations, due to insufficient utilization of parameters and inadequate dynamic adaptation of the parachute deployment process, the airdrop landing point deviates significantly from the predicted value, affecting the reliability and accuracy of the airdrop mission.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides a method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, comprising the following steps: S1. Obtain the parachute parameters, total mass parameters, layered environmental parameters, and target landing point parameters of the airdrop system, complete the initial deployment position and initial velocity of the airdropped object, and obtain the initial deployment parameter set; S2. Based on the initial deployment parameter set, interpolate the layered environmental parameters according to the current height of the airdropped object to obtain the real-time environmental parameters; S3. Based on the initial deployment parameter set and real-time environmental parameters, a preset multi-dimensional coupled airdrop dynamics three-dimensional motion model is adopted. The dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model are adapted to the phased parachute opening characteristics, and the solution is completed to update the real-time motion state of the airdropped object. S4. Based on the initial deployment parameter set and real-time motion status, complete the parameter switching for phased parachute opening, and continue to calculate until the airdrop lands to obtain the prediction result of the initial landing point. S5. Calculate the landing error based on the prediction result of the initial landing point, iteratively optimize the drop position and complete the corresponding solution prediction until the landing error meets the preset threshold, output the optimal drop position and the final accurate landing point prediction result, and complete the accurate prediction and solution of the aircraft airdrop drop point and landing point.

[0005] In some implementations, in S1, the parachute parameters include the area of ​​the pilot parachute and the main parachute, the drag coefficient, and the parachute opening delay parameter; the layered environmental parameters include the layer height, the preset air density value corresponding to each layer height, and the preset wind speed vector value.

[0006] In some implementations, in S2, interpolation processing is performed on the stratified environmental parameters, including air density interpolation and wind speed interpolation. The interpolation formulas are as follows: ; ; in, air density, For height, , The height threshold for adjacent height layers. , The preset value for air density at the corresponding altitude level. The current altitude wind speed vector, , Preset values ​​for wind speed vectors at adjacent height levels.

[0007] In some implementations, in S3, the preset multi-dimensional coupled airdrop dynamics three-dimensional motion model is a three-dimensional motion model that includes added mass, directional drag, and layered environment, and its three-dimensional motion equations are as follows: ; ; ; in, The total mass of the airdrop system, For added mass, , , For the umbrella opening state weight, air density, Relative wind speed, The characteristic area of ​​the parachute, , , For directional drag coefficients, , , The damping coefficient is... , Let g be the wind force component, and g be the acceleration due to gravity. , , The directional velocity of the airdropped item.

[0008] In some implementations, in S3, the three-dimensional motion model of the multi-dimensional coupled airdrop dynamics is solved, including: solving the motion differential equations of the model using the fourth-order Runge-Kutta method; and updating the real-time position and real-time velocity of the airdropped object.

[0009] In some implementations, in S3, the dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model are adapted to the phased parachute opening characteristics; in S4, the parameter switching for phased parachute opening is completed; specifically including: Based on the preset phased parachute deployment delay parameters, the dynamic parameters of the parachute pilot stage and the main parachute stage are switched. The dynamic parameters include the parachute characteristic area, directional drag coefficient, and deployment state weight. The pilot parachute deployment stage uses the corresponding dynamic parameters, and the main parachute deployment stage switches to the corresponding dynamic parameters.

[0010] In some implementations, in S4, the continuous calculation until the airdrop lands specifically involves: continuously performing layered environmental parameter interpolation processing based on the real-time altitude of the airdrop, solving the multi-dimensional coupled airdrop dynamics three-dimensional motion model, updating the real-time position and real-time velocity, until the airdrop lands and the initial landing point prediction result is obtained.

[0011] In some implementations, the formula for calculating the landing point error in S5 is as follows: ; The formula for optimizing the placement is as follows: , ; in, For landing point error, , Predict the coordinates of the landing point. , The coordinates of the target landing point, , The optimal translation vector components for the delivery point. The preset learning rate.

[0012] In some implementations, in S5, the delivery location is iteratively optimized and the corresponding prediction is completed until the landing point error meets a preset threshold, specifically including: The landing point error is calculated based on the initial landing point prediction results and the target landing point parameters. The initial deployment position is then optimized based on the landing point error to obtain the optimized deployment position. Based on the optimized deployment location, the following steps are completed: interpolation of layered environmental parameters, multi-dimensional coupled three-dimensional motion model calculation of airdrop dynamics, switching of dynamic parameters, updating of position and velocity, and landing determination, resulting in the updated landing point prediction results and corresponding landing point errors. Determine whether the landing error meets the preset error threshold. If it does, stop iterative optimization. If it does not, continue to optimize the delivery position based on the current landing error and repeat the corresponding solution prediction and error calculation operations until the landing error meets the preset error threshold.

[0013] This invention also provides a system for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, to implement the aforementioned method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop. The system includes an initial drop parameter acquisition module, an interpolation processing module, a motion state update module, an initial landing point prediction module, and a prediction result output module, wherein: The initial deployment parameter acquisition module is used to: acquire the parachute parameters, total mass parameters, layered environmental parameters, and target landing point parameters of the airdrop system; initialize the initial deployment position and initial velocity of the airdropped object; and obtain the initial deployment parameter set. The interpolation module is used to: interpolate the layered environmental parameters based on the initial deployment parameter set and the current height of the airdropped object to obtain real-time environmental parameters; The motion state update module is used to: based on the initial deployment parameter set and real-time environmental parameters, adopt a preset multi-dimensional coupled airdrop dynamics three-dimensional motion model, combine the phased parachute opening characteristics to adapt the dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model, complete the calculation, and update the real-time motion state of the airdropped object. The initial landing point prediction module is used to: switch parameters for phased parachute deployment based on the initial deployment parameter set and real-time motion status, continuously calculate until the airdrop lands, and obtain the prediction result of the initial landing point; The prediction result output module is used to: calculate the landing error based on the prediction result of the initial landing point, iteratively optimize the drop position and complete the corresponding solution prediction until the landing error meets the preset threshold, output the optimal drop position and the final accurate landing point prediction result, and complete the accurate prediction solution of the aircraft airdrop drop point and landing point.

[0014] Compared with existing technologies, the present invention provides a method and system for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, which has the following advantages: This invention provides a precise prediction and calculation method for aircraft airdrop drop points and landing points, improving upon the low accuracy, poor environmental adaptability, and insufficient versatility of existing airdrop systems. By constructing a multi-dimensional coupled dynamic model, dynamically adapting to the parachute deployment process, and introducing a layered environmental interpolation and drop point iterative optimization mechanism, it achieves precise calculation of the airdrop motion state and high-precision prediction of the landing point. This provides better drop points and relatively accurate landing point predictions for UAV or aircraft airdrop systems. This invention introduces added mass, directional drag, and layered environmental parameters, making the motion calculation relatively close to actual airdrop scenarios. Through phased parachute deployment parameter adaptation and drop point iterative optimization, it improves the accuracy of landing point prediction to a certain extent, keeping the error within a threshold. This improved accuracy enables relatively precise drop and, to a certain extent, adapts to various types of parachutes, payload masses, and environmental conditions, meeting the high-precision drop requirements in different scenarios. Attached Figure Description

[0015] The accompanying drawings are provided to further understand the invention and constitute a part of this invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0016] Figure 1 This is a schematic diagram of the calculation process in an embodiment of the accurate prediction and calculation method for aircraft airdrop drop points and landing points according to the present invention. Figure 2 This is a schematic diagram of the airdrop point optimization analysis in an embodiment of the accurate prediction and calculation method for aircraft airdrop drop points and landing points according to the present invention; Figure 3 This is a schematic diagram of layered environmental parameter interpolation in an embodiment of the accurate prediction and calculation method for aircraft airdrop drop points and landing points according to the present invention. Figure 4 This is a schematic diagram of the landing point error optimization curve in an embodiment of the accurate prediction and calculation method for aircraft airdrop drop points and landing points according to the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0018] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0019] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0020] It should be noted that the apparatus and methods disclosed in the embodiments herein can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments herein. In this regard, each block in a flowchart or block diagram may represent a module, program, or part of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system to perform the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0021] In addition, the functional modules in the various embodiments of this article can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0022] How can we provide a method for predicting the delivery and landing point of an airdrop, and improve the accuracy of landing point prediction by dynamically calculating the motion state and iteratively optimizing the delivery point, so as to achieve precise delivery?

[0023] This invention provides a method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, comprising the following steps: S1. Obtain the parachute parameters, total mass parameters, layered environmental parameters, and target landing point parameters of the airdrop system, complete the initial deployment position and initial velocity of the airdropped object, and obtain the initial deployment parameter set; S2. Based on the initial deployment parameter set, interpolate the layered environmental parameters according to the current height of the airdropped object to obtain the real-time environmental parameters; S3. Based on the initial deployment parameter set and real-time environmental parameters, a preset multi-dimensional coupled airdrop dynamics three-dimensional motion model is adopted. The dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model are adapted to the phased parachute opening characteristics, and the solution is completed to update the real-time motion state of the airdropped object. S4. Based on the initial deployment parameter set and real-time motion status, complete the parameter switching for phased parachute opening, and continue to calculate until the airdrop lands to obtain the prediction result of the initial landing point. S5. Calculate the landing error based on the prediction result of the initial landing point, iteratively optimize the drop position and complete the corresponding solution prediction until the landing error meets the preset threshold, output the optimal drop position and the final accurate landing point prediction result, and complete the accurate prediction and solution of the aircraft airdrop drop point and landing point.

[0024] This invention provides data support for the calculation and prediction process by acquiring all-dimensional basic parameters of the airdrop and initializing the initial deployment state. It interpolates layered environmental parameters based on the real-time altitude of the airdropped object, ensuring the data closely matches the stratified changes in the actual atmospheric environment and making the environmental input more realistic. Simultaneously, it employs a pre-set multi-dimensional coupled three-dimensional airdrop dynamics model combined with phased parachute deployment characteristics and adaptive parameters, eliminating the need for repeated model construction to adapt to airdrop motion and simulate the aerial movement of the airdropped object. Through phased parachute deployment parameter switching and continuous calculation, it obtains a realistic initial landing point prediction result. Finally, it iteratively optimizes the deployment position through landing point error, continuously correcting deployment deviations until the error reaches the target level, outputting the optimal deployment position and precise landing point. This ensures the accuracy of airdrop motion calculation and landing point prediction, making it suitable for various high-precision airdrop scenarios such as drone delivery, emergency rescue, and general deployment.

[0025] Specifically, the multi-dimensional coupled three-dimensional motion model of airdrop dynamics pre-defined in this invention incorporates key physical factors such as added mass, directional drag, and layered environment into the model. This allows for a relatively complete reconstruction of the multi-physics coupling characteristics of airdrop motion, improving the realism and accuracy of the motion calculation. The specific formulas of the three-dimensional motion equations are as follows: ; ; ; in, This refers to the total mass of the airdrop system (parachute + cargo). This is added mass (reflecting the inertial effect of the air displaced by the canopy). , , The weight of the parachute deployment state (a parameter for dynamic switching between the pilot parachute and the main parachute during deployment). This is the air density (obtained via height interpolation). Relative wind speed (the difference between the speed of an object and the speed of the surrounding wind). The characteristic area of ​​the parachute (dynamic switching between pilot parachute / main parachute area). , , For directional drag coefficients, , , The damping coefficient is... , Let g be the wind force component, and g be the acceleration due to gravity. , , The directional velocity of the airdropped item.

[0026] Furthermore, this invention dynamically adjusts key parameters to adapt to the aerodynamic characteristics of the two-stage operation process from the deployment of the pilot chute to the deployment of the main parachute. Regarding the characteristic area... During the deployment phase of the guide parachute, the area of ​​the guide parachute is used. During the main parachute deployment phase, the main parachute area is switched to the main parachute area. For drag coefficient , , During the pilot parachute phase, the drag coefficient corresponding to the pilot parachute in each direction is used. The main parachute phase switches to the corresponding directional drag coefficient of the main parachute. Weights for the open parachute state , , The parameter switching is triggered by the preset parachute opening delay. The weight coefficient of the pilot parachute stage corresponds to the contribution of the pilot parachute parameters, and the main parachute stage switches to the contribution of the corresponding main parachute parameters.

[0027] Furthermore, this invention provides a method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop. Considering the nonlinear changes in air density and wind speed with altitude in the actual atmospheric environment, a linear interpolation method is used to obtain the environmental parameters corresponding to the current altitude, ensuring the realism of the environmental model. Air density interpolation formula: ; in, , The height threshold for adjacent height layers. , The preset value for air density at the corresponding altitude level. air density, For height; Wind speed interpolation formula: ; in, The current altitude wind speed vector, , Preset values ​​for wind speed vectors at adjacent height levels.

[0028] like Figure 3 The diagram shown illustrates the verification of the air density and wind speed layered interpolation method of this invention. By setting up measured sampling points within a typical airdrop altitude range, measured data on air density and horizontal wind speed (x and y directions) at different altitudes are collected. Then, a linear interpolation method is used to construct a continuous mapping curve between altitude and environmental parameters. It can be seen that the trajectory interpolation accuracy and continuity of this invention are good, the environmental parameter modeling is relatively accurate, and the robustness of trajectory prediction is improved to a certain extent.

[0029] On the other hand, the present invention improves the accuracy of landing point prediction and minimizes the error between the actual landing point and the target point by iteratively adjusting the initial deployment position. 1. Calculate the two-dimensional distance error between the landing point and the target point based on simulation results from the current deployment point. ; 2. Based on the error E and the aircraft heading, calculate the optimal translation vector for the drop point. Update the delivery point and re-simulate, repeating steps 1-2 above until the error meets the threshold.

[0030] In some embodiments, the present invention provides an accurate prediction and calculation method for aircraft airdrop drop points and landing points. To improve versatility and engineering adaptability, the following adaptation mechanism is designed: Supports load capacities up to 600 kg, adjustable by adding additional mass. With drag coefficient It achieves adaptability, allowing for larger parachute areas and additional mass for heavy payloads (300-600kg). It supports different models of pilot parachutes and main parachutes, and allows flexible configuration of parachute area, drag coefficient, inflation time, and other parameters via a parameter input module, without requiring modifications to the core algorithm. It supports airdrop missions at altitudes ranging from 0-5000m, and layered environmental parameters can be preset according to the atmospheric characteristics of different regions (such as plateaus, plains, and coastlines), and can also be dynamically updated by integrating real-time meteorological data.

[0031] Furthermore, the present invention provides a method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, which can incorporate a parameter anomaly detection mechanism. When the input parameters exceed the reasonable range (such as load mass > 1000 kg, wind speed > 16 m / s), an alarm is automatically triggered and the system is simulated using default safety parameters to avoid system crash.

[0032] This invention also provides a system for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, including an initial drop parameter acquisition module, an interpolation processing module, a motion state update module, an initial landing point prediction module, and a prediction result output module, wherein: The initial deployment parameter acquisition module is used to: acquire the parachute parameters, total mass parameters, layered environmental parameters, and target landing point parameters of the airdrop system; initialize the initial deployment position and initial velocity of the airdropped object; and obtain the initial deployment parameter set. The interpolation module is used to: interpolate the layered environmental parameters based on the initial deployment parameter set and the current height of the airdropped object to obtain real-time environmental parameters; The motion state update module is used to: based on the initial deployment parameter set and real-time environmental parameters, adopt a preset multi-dimensional coupled airdrop dynamics three-dimensional motion model, combine the phased parachute opening characteristics to adapt the dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model, complete the calculation, and update the real-time motion state of the airdropped object. The initial landing point prediction module is used to: switch parameters for phased parachute deployment based on the initial deployment parameter set and real-time motion status, continuously calculate until the airdrop lands, and obtain the prediction result of the initial landing point; The prediction result output module is used to: calculate the landing error based on the prediction result of the initial landing point, iteratively optimize the drop position and complete the corresponding solution prediction until the landing error meets the preset threshold, output the optimal drop position and the final accurate landing point prediction result, and complete the accurate prediction solution of the aircraft airdrop drop point and landing point.

[0033] The following detailed description of the accurate prediction and calculation method and system for aircraft airdrop points and landing points according to the present invention will be provided through specific embodiments.

[0034] I. Parameter Initialization Enter the following parameters: Parachute parameters: pilot chute area Main umbrella area Guiding parachute drag coefficient Main parachute drag coefficient Delayed opening of the pilot parachute Main umbrella opening delay ; System parameters: Total mass Additional mass ; Environmental parameters: Layer height Corresponding air density Corresponding wind speed ; Target parameters: Target point coordinates .

[0035] II. The motion calculation and landing point prediction process is as follows: 1. Initialize the initial position of the cargo Initial velocity ; 2. Calculate the current height Corresponding air density and wind speed ; 3. Based on the equations of motion, update position and velocity using the RK4 method: ; ; in, This is an intermediate quantity of the RK4 derivative of the position. RK4 intermediate quantity for the velocity derivative; 4. Check the umbrella opening delay; if it reaches... Then switch to the guiding umbrella parameters to achieve... Then switch to the main umbrella parameters; Repeat steps 2-4 above until the cargo lands (z≤0), and output the initial landing point prediction result; The deployment points are iteratively optimized based on the initial error, and the landing point prediction results are updated until the error meets the threshold.

[0036] III. Optimization process for delivery points, as detailed below: 1. Perform the above motion calculations to obtain the initial landing point prediction value. ; 2. Calculate the landing point error: ; 3. Based on the error Aircraft heading and preset learning rate Calculate the optimal translation vector of the delivery point. The calculation formula is: , ; 4. Update the coordinates of the delivery point to Repeat steps 1-3 above for iterative simulation.

[0037] 5. Continue iterating to obtain the second updated delivery point, and obtain the predicted landing point value and error value; 6. When the landing point error is ( When the preset error threshold is reached, the iteration stops, and the final landing point prediction result and the optimal delivery point are output.

[0038] like Figure 2 The image shown is a verification diagram of the implementation effect of the airdrop point optimization method of the present invention. By constructing a dynamic model of the entire process of UAV airdrop, and taking the target landing point as the benchmark, the initial drop point is iteratively optimized and solved, and the trajectory and error data before and after optimization are recorded. It can be seen that the trajectory optimization effect of the present invention is significant, the state parameters are stable and controllable, and the optimization efficiency and accuracy are high.

[0039] like Figure 4 The figure shown illustrates the convergence effect of the iterative optimization method for deployment points according to this invention. By repeatedly executing an iterative process of landing point prediction, error calculation, deployment point correction, and re-simulation using the target point as a reference, the figure records that with each iteration, the landing point error decreases rapidly, with each iteration reducing the error by ≥30%, and quickly converging to the preset accuracy threshold. It can be seen that this invention exhibits high iterative optimization efficiency and landing point prediction accuracy, fast convergence speed, and automatic optimization of the deployment location.

[0040] In summary, this invention provides a precise prediction and calculation method for aircraft airdrop drop points and landing points. It employs a multi-dimensional coupled three-dimensional motion model, adapting to the real physical process of airdrops without requiring repetitive modeling. Furthermore, by dynamically adjusting parameters based on the phased deployment characteristics of the pilot and main parachutes, it can, to a certain extent, recreate the entire lifecycle of the airdropped object from ejection, parachute deployment, to landing. Based on altitude-layered environmental interpolation, this invention relatively accurately matches actual atmospheric density and wind speed changes, improving environmental adaptability and calculation realism. Through iterative optimization of landing point errors, a correction mechanism is formed, effectively reducing drop deviations. This method is widely applicable to scenarios such as UAV material delivery, emergency rescue, and the deployment of certain equipment, improving airdrop accuracy and mission reliability while possessing significant engineering application value.

[0041] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Anyone skilled in the art can readily implement the present invention according to the description and above. Any modifications, alterations, or equivalent variations made using the technical content disclosed above are equivalent embodiments of the present invention. Furthermore, any modifications, alterations, or variations made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the present invention.

Claims

1. An accurate prediction method for air drop delivery point and impact point of an aircraft, characterized in that, Includes the following steps: S1. Obtain the parachute parameters, total mass parameters, layered environmental parameters, and target landing point parameters of the airdrop system, complete the initial deployment position and initial velocity of the airdropped object, and obtain the initial deployment parameter set; S2. Based on the initial deployment parameter set, interpolate the layered environmental parameters according to the current height of the airdropped object to obtain the real-time environmental parameters; S3. Based on the initial deployment parameter set and real-time environmental parameters, a preset multi-dimensional coupled airdrop dynamics three-dimensional motion model is adopted. The dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model are adapted to the phased parachute opening characteristics, and the solution is completed to update the real-time motion state of the airdropped object. S4. Based on the initial deployment parameter set and real-time motion status, complete the parameter switching for phased parachute opening, and continue to calculate until the airdrop lands to obtain the prediction result of the initial landing point. S5. Calculate the landing error based on the prediction result of the initial landing point, iteratively optimize the drop position and complete the corresponding solution prediction until the landing error meets the preset threshold, output the optimal drop position and the final accurate landing point prediction result, and complete the accurate prediction and solution of the aircraft airdrop drop point and landing point.

2. The method for precise prediction solution of the drop point and the landing point of the aircraft air-drop according to claim 1, characterized in that, In S1, the parachute parameters include the area of ​​the pilot parachute and the main parachute, the drag coefficient, and the parachute opening delay parameter; the layered environmental parameters include the layer height, the preset air density value corresponding to each layer height, and the preset wind speed vector value.

3. The method of claim 1, wherein the method further comprises: In step S2, interpolation processing is performed on the stratified environmental parameters, including air density interpolation and wind speed interpolation. The interpolation formulas are as follows: ； ； wherein, is the air density, is the height, , is the height threshold of the adjacent height layer, , is the air density preset value of the corresponding height layer, is the current height wind speed vector, , is the wind speed vector preset value of the adjacent height layer.

4. The method of precise prediction of the drop point and the landing point of the aircraft according to claim 1, characterized in that, In S3, the preset multi-dimensional coupled airdrop dynamics three-dimensional motion model is a three-dimensional motion model that includes added mass, directional drag, and layered environment, and its three-dimensional motion equations are as follows: ； ； ； wherein is the total mass of the delivery system, is the additional mass, is the open parachute state weight, is the air density, is the relative wind speed, is the parachute characteristic area, is the directional drag coefficient, is the damping coefficient, is the wind field force component, g is the gravitational acceleration, is the delivery object directional velocity.​​​​​​​​​ 5. The method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop according to claim 1, characterized in that, In S3, the solution of the three-dimensional motion model of the multi-dimensional coupled airdrop dynamics is completed, including: solving the motion differential equations of the model using the fourth-order Runge-Kutta method; and updating the real-time position and real-time velocity of the airdropped object.

6. The method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop according to claim 1, characterized in that, In step S3, the dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model are adapted to the phased parachute opening characteristics. In step S4, the parameter switching for phased parachute opening is completed; specifically, this includes: Based on the preset phased parachute deployment delay parameters, the dynamic parameters of the parachute pilot stage and the main parachute stage are switched. The dynamic parameters include the parachute characteristic area, directional drag coefficient, and deployment state weight. The pilot parachute deployment stage uses the corresponding dynamic parameters, and the main parachute deployment stage switches to the corresponding dynamic parameters.

7. The method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop according to claim 1, characterized in that, In S4, the continuous calculation until the airdrop lands specifically involves: continuously performing layered environmental parameter interpolation processing based on the real-time altitude of the airdrop, solving the multi-dimensional coupled airdrop dynamics three-dimensional motion model, updating the real-time position and real-time velocity, until the airdrop lands and the initial landing point prediction result is obtained.

8. The method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop according to claim 1, characterized in that, In step S5, the formula for calculating the landing point error is as follows: ； The formula for optimizing the placement is as follows: ， ； in, For landing point error, , Predict the coordinates of the landing point. , The coordinates of the target landing point, , The optimal translation vector components for the delivery point. The preset learning rate.

9. The method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop according to claim 1, characterized in that, In step S5, the delivery location is iteratively optimized and the corresponding prediction is completed until the landing point error meets a preset threshold, specifically including: The landing point error is calculated based on the initial landing point prediction results and the target landing point parameters. The initial deployment position is then optimized based on the landing point error to obtain the optimized deployment position. Based on the optimized deployment location, the following steps are completed: interpolation of layered environmental parameters, multi-dimensional coupled three-dimensional motion model calculation of airdrop dynamics, switching of dynamic parameters, updating of position and velocity, and landing determination, resulting in the updated landing point prediction results and corresponding landing point errors. Determine whether the landing error meets the preset error threshold. If it does, stop iterative optimization. If it does not, continue to optimize the delivery position based on the current landing error and repeat the corresponding solution prediction and error calculation operations until the landing error meets the preset error threshold.

10. A system for accurately predicting and calculating the drop point and landing point of an aircraft airdrop, used to implement the method for accurately predicting and calculating the drop point and landing point of an aircraft airdrop as described in any one of claims 1-9, characterized in that, It includes an initial deployment parameter acquisition module, an interpolation processing module, a motion state update module, an initial landing point prediction module, and a prediction result output module, wherein: The initial deployment parameter acquisition module is used to: acquire the parachute parameters, total mass parameters, layered environmental parameters, and target landing point parameters of the airdrop system; initialize the initial deployment position and initial velocity of the airdropped object; and obtain the initial deployment parameter set. The interpolation module is used to: interpolate the layered environmental parameters based on the initial deployment parameter set and the current height of the airdropped object to obtain real-time environmental parameters; The motion state update module is used to: based on the initial deployment parameter set and real-time environmental parameters, adopt a preset multi-dimensional coupled airdrop dynamics three-dimensional motion model, combine the phased parachute opening characteristics to adapt the dynamic parameters of the multi-dimensional coupled airdrop dynamics three-dimensional motion model, complete the calculation, and update the real-time motion state of the airdropped object. The initial landing point prediction module is used to: switch parameters for phased parachute deployment based on the initial deployment parameter set and real-time motion status, continuously calculate until the airdrop lands, and obtain the prediction result of the initial landing point; The prediction result output module is used to: calculate the landing error based on the prediction result of the initial landing point, iteratively optimize the drop position and complete the corresponding solution prediction until the landing error meets the preset threshold, output the optimal drop position and the final accurate landing point prediction result, and complete the accurate prediction solution of the aircraft airdrop drop point and landing point.

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