A Monte Carlo method for calculating airdrop field capacity

Abstract

The present invention discloses a method for calculating the capacity of an airdrop field based on the Monte Carlo method, comprising the following steps: determining the structural parameters of an airdrop field in an air battlefield; determining the types, quantity, and performance parameters of aircraft that can participate in airdrop missions; wherein the performance parameters include speed values ​​of different aircraft types; establishing an airdrop field capacity model based on the Monte Carlo method; and determining the airdrop field capacity value based on the airdrop field capacity model. The structural parameters of the airdrop field include the size of the airdrop field and the number of available altitude layers; the method for determining the size of the airdrop field and the number of available altitude layers includes: determining the size of the airdrop field based on the combat mission and the scale of material supply required in the air battlefield; and determining the number of available altitude layers based on the airspace environment in the airdrop field. The invention uses the Monte Carlo method to establish an airdrop field capacity model to determine the airspace capacity, which can accurately measure the capacity of the airdrop field and ensure the safety and efficiency of the airdrop mission.

Description

Technical Field

[0001] The present invention belongs to the technical field of mathematical modeling, and in particular relates to a method for calculating the capacity of an airdrop field based on a Monte Carlo method. Background Art

[0002] In the field of civil aviation transportation, there are relatively mature technologies for capacity assessment. The main methods for determining airspace capacity include computer simulation assessment methods, assessment methods based on historical statistical data, and assessment methods based on mathematical calculation models. However, the capacity assessment technology related to airdrop sites is still in its infancy.

[0003] The advantage of using computer simulation and historical statistical data evaluation methods to determine airspace capacity is high accuracy, but its disadvantages are also obvious. The former relies on simulation software, and the latter requires statistics of sufficient historical data. Therefore, compared with the evaluation method based on mathematical calculation models, the first two methods not only require heavy evaluation tasks and a longer cycle, but also have the disadvantage that factors such as the controller's control habits cannot be taken into account, resulting in the simulation results cannot fully and truly reflect the actual operation of the airspace, and are difficult to apply to the capacity evaluation of combat airspace.

[0004] The mathematical model-based assessment method defines the maximum number of flights passing through a node per unit time, while ensuring safe separation between aircraft. This defines the theoretical capacity. This method is more efficient and has a wider range of applications. However, the mathematical calculation models for drop zones in combat airspace differ from those used in civil aviation. Due to various factors, the accuracy of existing airspace capacity assessments for drop zones in combat airspace is limited. Summary of the Invention

[0005] In response to the problems existing in the existing technology, the present invention provides a method for calculating the airdrop field capacity based on the Monte Carlo method, which has the advantage of high accuracy in evaluating the airdrop field capacity. It solves the problem that the mathematical calculation model of the airdrop field in the existing combat airspace is different from the mathematical calculation model in the field of civil aviation transportation. Under the influence of various factors, the accuracy of the airspace capacity evaluated by the airdrop field in the existing combat airspace is not high.

[0006] The present invention is implemented as follows: a method for calculating the capacity of an airdrop field based on the Monte Carlo method, comprising the following steps:

[0007] Determine the structural parameters of the airdrop field in the air battlefield;

[0008] Determine the types, quantity, and performance parameters of aircraft that can participate in the airdrop mission; wherein the performance parameters include speed values ​​for different aircraft types;

[0009] Establish an airdrop field capacity model based on the Monte Carlo method;

[0010] Determine the airdrop field capacity value according to the airdrop field capacity model.

[0011] As preferred aspects of the present invention, the structural parameters of the airdrop field include the size of the airdrop field and the number of usable height levels;

[0012] Methods for determining the size of the drop zone and the number of available altitude levels include:

[0013] Determine the size of the airdrop field based on combat missions and the scale of material supplies required for the air battlefield;

[0014] The number of available altitude layers is determined based on the airspace environment in the airdrop field.

[0015] As a preferred embodiment of the present invention, the method for determining the type, quantity and performance parameters of aircraft that can participate in the airdrop mission includes:

[0016] Determine the types and number of aircraft that can participate in airdrop missions, as well as the average flight speed of different aircraft types, based on the combat mission, the size of the airdrop site, and the scale of material supplies required for the airdrop site;

[0017] Determine the horizontal safety interval between aircraft based on relevant aircraft flight safety specifications, and determine the safety interval between adjacent aircraft at different altitudes based on the structural parameters of the drop site and the types of materials required for the drop site.

[0018] As a preferred embodiment of the present invention, the method for determining the horizontal safety interval between aircraft includes:

[0019] Based on the combat mission, the size of the airdrop field and the amount of supplies required, determine the types and quantity of aircraft that can be used to perform airdrop missions, and obtain the proportion of aircraft types that can be deployed to the airdrop field to perform airdrop missions;

[0020] The safety interval between the aircraft types is determined by the proportion of aircraft types that can be deployed to the airdrop field to perform airdrop missions and the average flight speed of each aircraft type, and in accordance with the relevant flight safety interval regulations.

[0021] As a preferred embodiment of the present invention, the method for establishing an airdrop field capacity model based on the Monte Carlo method includes:

[0022] Establish the objective function of the airdrop field capacity model;

[0023] Combining the drop zone structure parameters and aircraft performance parameters, the constraints of the drop zone capacity model are established;

[0024] Among them, the objective function of establishing the airdrop field capacity model is as follows:

[0025]

[0026] Among them, T m is the set time period; T ij It represents the time interval before and after the leading aircraft i and the trailing aircraft j enter the airdrop area, P ij It represents the probability that the leading aircraft i and the following aircraft j enter the airdrop field.

[0027] As a preferred embodiment of the present invention, the constraints of the airdrop field capacity model established by combining the airdrop field structural parameters and the aircraft performance parameters include: environmental constraints, safety interval constraints and airdrop constraints;

[0028] The environmental constraint condition is as follows: According to the influence of the environment on the aircraft speed, it is assumed that the speed of aircraft i obeys the mean μ i The variance is σ i 2 Gaussian distribution, that is, v i ~N(μ i ,σ i 2 ), so the flight speeds of different aircraft types i and j are different when flying at the same altitude and at different altitudes, and the speed of aircraft i satisfies the following formula: μ i -σ i 2 vv i ≤μ i +σ i 2 ;

[0029] The safety interval constraint condition is: Assume that the safety horizontal interval between transport aircraft of type i at the same altitude is S i , the horizontal safety interval between transport aircraft of type i and j is S ij , satisfying the following conditions:

[0030]

[0031] Among them, T ij is the time interval between aircraft at the same altitude entering the drop zone; v j is the speed of the following aircraft of aircraft type j; L is the length of the airdrop field;

[0032] The airdrop constraint condition is that the safe distance between aircraft operating at different altitudes should not be less than S h .

[0033] As a preferred embodiment of the present invention, the method for determining the airdrop field capacity value according to the airdrop field capacity model includes: setting a statistical time threshold based on the airdrop field capacity model, calculating the average number of aircraft performing airdrop tasks per unit time through multiple random samplings, and solving the airdrop field capacity value using the Monte Carlo method.

[0034] As a preferred embodiment of the present invention, the airdrop field capacity value is repeatedly calculated multiple times, and the average of the multiple airdrop field capacity values ​​is obtained, which is the average capacity value of the airdrop field.

[0035] As a preferred embodiment of the present invention, combined with the airdrop field capacity model, the Monte Carlo algorithm mainly selects aircraft to enter the available altitude layer through random sampling. When the corresponding constraints are met, it means that the aircraft can enter the airdrop field to perform the airdrop mission. Finally, the same steps are performed through repeated sampling to count the maximum number of airdrop field flights per unit time and obtain the maximum capacity value of the airdrop field.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. In this invention, considering the scale of material supply required for the airdrop field and the fact that combat airspace operations do not require controllers, the environmental factors when aircraft enter the airdrop field and the impact of airdrops on aircraft are taken into consideration. It is proposed to combine aircraft performance parameters and airdrop field structural parameters, establish an airdrop field capacity model based on the Monte Carlo method, and finally determine the airdrop field capacity value, so that the evaluation result is more accurate.

[0038] 2. The present invention flexibly uses the Monte Carlo method to establish a drop zone capacity model based on the structural characteristics of the drop zone and aircraft performance characteristics, combined with the safety spacing requirements between aircraft, and further determines the drop zone capacity. Directly using the Monte Carlo method to establish the drop zone capacity model to determine airspace capacity can accurately measure the drop zone capacity and ensure the safety and efficiency of airdrop missions.

[0039] 3. In the present invention, the structural parameters of the airdrop field, aircraft performance parameters and environmental factors are taken into consideration, and the assessment of the combat airspace capacity is more accurate, intuitive and realistic, and the results can be directly used to guide the execution of airdrop missions.

[0040] 4. The present invention reduces a lot of work such as previous simulation analysis and historical statistical data analysis, greatly shortening the airspace capacity assessment time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flowchart of a method for calculating airdrop field capacity based on the Monte Carlo method provided in an embodiment of the present invention;

[0042] Figure 2 is a flowchart of a method for determining the size of an airdrop field and the number of available altitude levels provided by an embodiment of the present invention;

[0043] Figure 3 This is a flowchart of a method for determining the types, quantity, and performance parameters of aircraft that can participate in an airdrop mission, provided by an embodiment of the present invention;

[0044] Figure 4 is a flowchart of a method for determining horizontal safety intervals between aircraft provided by an embodiment of the present invention;

[0045] Figure 5 This is a flowchart of a method for establishing an airdrop field capacity model based on the Monte Carlo method provided by an embodiment of the present invention;

[0046] Figure 6 This is a flowchart of a method for calculating airdrop field capacity based on the Monte Carlo method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to further understand the content, features and effects of the present invention, the following embodiments are given as examples and described in detail with reference to the accompanying drawings.

[0048] The structure of the present invention is described in detail below with reference to the accompanying drawings.

[0049] Example 1

[0050] See also Figure 1 The embodiment of the present invention provides a method for calculating the capacity of an airdrop field based on the Monte Carlo method, comprising the following steps:

[0051] Step S1, determining the structural parameters of the airdrop field in the air battlefield;

[0052] Step S2: determining the types, quantity, and performance parameters of aircraft that can participate in the airdrop mission; wherein the performance parameters include speed values ​​of different aircraft types;

[0053] Step S3: establishing an airdrop field capacity model based on the Monte Carlo method;

[0054] Step S4: Determine the airdrop field capacity value according to the airdrop field capacity model.

[0055] This setup allows the Monte Carlo method to be used to establish a drop zone capacity model to determine airspace capacity. This accurately measures drop zone capacity and ensures the safety and efficiency of airdrop missions. By considering drop zone structural parameters, aircraft performance parameters, and environmental factors, the assessment of operational airspace capacity is more accurate, intuitive, and realistic, and the results can be directly used to guide airdrop mission execution. This reduces the extensive workload of previous simulation analysis and historical statistical data analysis, significantly shortening the time required for airspace capacity assessment.

[0056] See also Figure 2 In step S1, the structural parameters of the airdrop field include the size of the airdrop field and the number of available altitude floors. The method for determining the size of the airdrop field and the number of available altitude floors includes:

[0057] Step S11: Determine the size of the airdrop field based on the combat mission and the scale of material supply required for the air battlefield;

[0058] Step S12: Determine the available altitude layers according to the airspace environment in the airdrop field.

[0059] In this embodiment, the size of the airdrop field includes the length and width of the airdrop field; the number of available altitude levels is the number of available altitude levels for routes above the airdrop field.

[0060] See also Figure 3 In step S2, the method for determining the types, quantity, and performance parameters of aircraft that can participate in the airdrop mission includes:

[0061] Step S21: Determine the aircraft types and quantities that can participate in the airdrop mission, as well as the average flight speed of different aircraft types, based on the combat mission, the size of the airdrop field, and the scale of material supplies required for the airdrop field.

[0062] Step S22: Determine the horizontal safety interval between aircraft according to relevant aircraft flight safety regulations, and determine the safety interval between adjacent aircraft at different altitudes based on the structural parameters of the airdrop field and the types of materials required by the airdrop field.

[0063] See also Figure 4 In step S22, the method for determining the horizontal safety interval between aircraft includes:

[0064] Step S221: Determine the types and quantities of aircraft that can be deployed to perform the airdrop mission based on the combat mission, the size of the airdrop field, and the amount of supplies required, and obtain the proportion of aircraft types that can be deployed to the airdrop field to perform the airdrop mission.

[0065] Step S222: Determine the safety interval between the aircraft types based on the ratio of aircraft types that can be deployed to the airdrop field to perform airdrop missions and the average flight speed of each aircraft type, and in accordance with relevant flight safety interval regulations.

[0066] According to the combat mission and the scale of material supply required for the airdrop field, the number of available aircraft, aircraft models and the average flight speed of different aircraft models are determined. The horizontal separation between aircraft is determined according to the relevant specifications for aircraft flight safety. In combination with the structural characteristics of the airdrop field and the types of materials required for the airdrop field, the safety separation between adjacent aircraft at different altitudes is clarified. Considering that aircraft are affected by environmental factors such as airflow during operation in the air, which manifests in the form of changes in aircraft speed, the present invention assumes that the speed of the aircraft on the route satisfies the Gaussian distribution. Since the length of the airdrop field is relatively small relative to the length of the aircraft's operating route, the present invention assumes that the instantaneous speed value of the aircraft entering the airdrop field is the aircraft's operating speed on the airdrop field.

[0067] See also Figure 5 In step S3, the method for establishing the airdrop field capacity model based on the Monte Carlo method includes:

[0068] S31. Establishing the objective function of the airdrop field capacity model;

[0069] S32. Establish the constraint conditions of the airdrop field capacity model by combining the airdrop field structural parameters and the aircraft performance parameters;

[0070] Among them, the objective function of establishing the airdrop field capacity model is as follows:

[0071]

[0072] Among them, T m is the set time period; T ij It represents the time interval before and after the leading aircraft i and the trailing aircraft j enter the airdrop area, P ij It represents the probability that the leading aircraft i and the following aircraft j enter the airdrop field.

[0073] In step S32, the constraints of the airdrop field capacity model are established by combining the airdrop field structural parameters and the aircraft performance parameters. The constraints of the airdrop field capacity model include: environmental constraints, safety interval constraints, and airdrop constraints.

[0074] The environmental constraint condition is as follows: According to the influence of the environment on the aircraft speed, it is assumed that the speed of aircraft i obeys the mean μ i The variance is σ i 2 Gaussian distribution, that is, v i ~N(μ i ,σ i 2 ), so the flight speeds of different aircraft types i and j are different when flying at the same altitude and at different altitudes, and the speed of aircraft i satisfies the following formula:

[0075] Specifically, in the actual airdrop process, different aircraft types will be affected by different external environmental factors (such as airflow) when flying at a certain altitude. These factors are manifested in the form of changes in aircraft speed. Therefore, the present invention assumes that the speed of aircraft i obeys a mean of μ i The variance is σ i 2 Gaussian distribution, that is, v i ~N(μ i ,σ i 2 ), so the flight speeds of different aircraft types i and j are different when they fly at the same altitude and at different altitudes, so the speed of aircraft i satisfies the equation:

[0076] The safety interval constraint condition is: Assume that the safety horizontal interval between transport aircraft of type i at the same altitude is S i , the horizontal safety interval between transport aircraft of type i and j is S ij , satisfying the following conditions:

[0077]

[0078] Among them, T ij is the time interval between aircraft at the same altitude entering the drop zone; v j is the speed of the following aircraft of aircraft type j; L is the length of the airdrop field.

[0079] Specifically, the horizontal safety interval between aircraft is determined according to the aircraft flight safety regulations. Due to the different operating performance of aircraft, the speed during the route operation is different. Therefore, the horizontal safety interval must be met before and after entering the airdrop field. The present invention assumes that the horizontal safety interval between transport aircraft of type i at the same altitude is S i , the horizontal safety interval between transport aircraft of type i and j is S ij , that is, the following conditions must be met:

[0080]

[0081] Among them, T ij is the time interval between aircraft at the same altitude entering the drop zone; v j is the speed of the following aircraft of aircraft type j; L is the length of the airdrop field.

[0082] The airdrop constraint condition is that the safe distance between aircraft operating at different altitudes should not be less than S h .

[0083] Specifically, the capacity of an airdrop field with multiple altitude levels is inevitably affected by the type of airdrop and the landing. When the airdrop is operated at the lowest altitude, its descent has almost no effect on the capacity of the airdrop field. However, when the airdrop is dropped at a high altitude, it will inevitably affect the aircraft at a lower altitude. Therefore, the safety distance between adjacent aircraft at different altitudes must be considered to ensure that when the airdrop descends to a low altitude, it will not affect the aircraft at that altitude. The safety distance that must be maintained when operating at different altitudes is S h .

[0084] Furthermore, the method for determining the airdrop field capacity value according to the airdrop field capacity model includes:

[0085] Based on the airdrop field capacity model, the statistical time threshold is set, and the average number of aircraft performing airdrop missions per unit time is calculated through multiple random sampling. The airdrop field capacity value is solved using the Monte Carlo method.

[0086] Specifically, Monte Carlo can directly solve problems of a statistical nature and can handle continuous problems without discretization. The more samples it takes, the closer it is to the optimal solution. Its main idea is to use the frequency of an event as an approximation of its probability. This can be roughly divided into three steps: first, constructing a random probability based on the event, then randomly sampling from a known probability distribution, and finally solving the estimator through multiple sampling processes.

[0087] Since the combat styles of air battlefields are varied, the location of airdrop sites is random, and the aircraft entering the airdrop sites are also random. Therefore, the present invention takes the aircraft entering the airdrop site to perform airdrop missions as a random event and solves the maximum capacity of a certain airdrop site based on the Monte Carlo method.

[0088] Furthermore, the capacity value of the airdrop field is calculated repeatedly for multiple times, and the average of the multiple airdrop field capacity values ​​is obtained, which is the average capacity value of the airdrop field.

[0089] Furthermore, combined with the airdrop field capacity model, the Monte Carlo algorithm mainly selects aircraft to enter the available altitude layer through random sampling. When the corresponding constraints are met, it means that the aircraft can enter the airdrop field to perform the airdrop mission. Finally, the same steps are performed through repeated sampling to count the maximum number of airdrop field flights per unit time and obtain the maximum capacity value of the airdrop field.

[0090] In summary, the present invention addresses the specificities of an airdrop site, such as the scale of material supplies required, the fact that combat airspace operations do not require controllers, and the environmental factors affecting aircraft entering the airdrop site, as well as the impact of airdrops on aircraft. This approach proposes combining aircraft performance parameters with airdrop site structural parameters to establish an airdrop site capacity model based on the Monte Carlo method, ultimately determining the airdrop site capacity value. This results in a more accurate assessment of combat airspace capacity. This makes the assessment of combat airspace capacity more intuitive and realistic, and its results can be directly used to guide the execution of airdrop missions. This reduces the extensive workload of previous simulation analysis and historical statistical data analysis, significantly shortening the time required for airspace capacity assessment.

[0091] Example 2

[0092] See also Figure 6 , is a flowchart of a method for calculating airdrop field capacity based on the Monte Carlo method provided in an embodiment of the present invention.

[0093] Step S41: Determine the size of the airdrop field based on the scale of material supply required for the air battlefield, determine the number of available altitude layers based on the airspace environment within the airdrop field, and then determine the structural parameters of the airdrop field;

[0094] Step S42: Based on the combat mission, the size of the airdrop field, and the required supplies, determine the types and number of aircraft available for the airdrop mission, as well as the average flight speed of each type of aircraft. The horizontal safety interval between aircraft is determined according to relevant flight safety interval specifications. Based on the size of the airdrop field and the number of available altitude levels, the safety interval between adjacent aircraft at different altitude levels is determined.

[0095] Step S43: Combine the drop zone structural parameters and aircraft performance parameters, taking into account the impact of environmental factors such as airflow during the flight of the aircraft route, and assuming that the speed of the aircraft entering the designated altitude layer of the drop zone follows a Gaussian distribution, randomly generate a speed value that satisfies the Gaussian distribution and the aircraft model ratio;

[0096] Step S44: Perform random sampling based on the speed value, and combine step S41 and step S42 to establish a drop zone capacity model based on the Monte Carlo method;

[0097] Step S45: According to the airdrop field capacity model obtained in step S44, a statistical time threshold (in hours) is set, and then the airdrop field capacity value is determined;

[0098] Step S46: Repeat the calculation of the airdrop field capacity value in step S45 multiple times to obtain the average of the above capacity values ​​to obtain the airdrop field capacity value.

[0099] Example 3

[0100] Based on the combat mission and the required scale of material supply, the size of the airdrop field and the number of available altitude layers are determined. By counting the proportion of aircraft types that can be deployed to the airdrop field to perform airdrop missions and the average flight speed of each aircraft type, and determining the safety intervals between different altitude layers or aircraft types according to relevant specifications, a drop field capacity calculation model is finally established based on the Monte Carlo method. The specific steps include: determining the airdrop field structural parameters in the air battlefield; determining the number and performance parameters of aircraft that can participate in the airdrop mission; establishing an airdrop field capacity model based on the Monte Carlo method; and calculating the average number of aircraft performing airdrop missions per unit time through multiple random sampling to determine the airdrop field capacity value.

[0101] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0102] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for calculating the capacity of an airdrop field based on the Monte Carlo method, characterized in that: The following steps are involved: Determine the structural parameters of the airdrop field in the air battlefield; Determine the types, quantity, and performance parameters of aircraft that can participate in the airdrop mission; wherein the performance parameters include speed values ​​for different aircraft types; Establish an airdrop field capacity model based on the Monte Carlo method; Determining the airdrop field capacity value according to the airdrop field capacity model; The structural parameters of the airdrop field include the size of the airdrop field and the number of usable altitude layers; Methods for determining the size of the drop zone and the number of available altitude levels include: Determine the size of the airdrop field based on combat missions and the scale of material supplies required for the air battlefield; The number of available altitude levels is determined based on the airspace environment of the drop zone. The size of the drop zone includes its length and width. The number of available altitude levels refers to the number of available altitude levels for routes above the drop zone. Methods for establishing airdrop field capacity models based on the Monte Carlo method include: Establish the objective function of the airdrop field capacity model; Combining the drop zone structure parameters and aircraft performance parameters, the constraints of the drop zone capacity model are established; Among them, the objective function of establishing the airdrop field capacity model is as follows: in, For a set time period; Indicates that the front machine is The rear machine is The time interval before and after entering the airdrop area, Indicates that the front machine is The rear machine is The probability of entering the airdrop zone; The constraints of the airdrop field capacity model established by combining the airdrop field structural parameters and the aircraft performance parameters include: environmental constraints, safety interval constraints, and airdrop constraints; The environmental constraint condition is: according to the influence of the environment on the aircraft speed, assuming that the aircraft The speed of The variance is Gaussian distribution, that is , so different models and The flight speeds at the same altitude and at different altitudes are different, and the aircraft The speed satisfies the following formula: ; Among them, the safety interval constraint condition is: Assuming the aircraft model The safe horizontal separation between transport aircraft at the same altitude is ,model and The horizontal safety interval between transport aircraft is , satisfying the following conditions: in, The time interval between aircraft at the same altitude entering the drop zone; For models The speed of the rear machine; is the length of the drop zone; The airdrop constraint condition is that the safe distance between aircraft operating at different altitudes should not be less than .

2. The Monte Carlo method for calculating the capacity of an airdrop field according to claim 1, wherein: The method for determining the type, quantity and performance parameters of aircraft that can participate in the airdrop mission includes: Determine the types and number of aircraft that can participate in airdrop missions, as well as the average flight speed of different aircraft types, based on the combat mission, the size of the airdrop site, and the scale of material supplies required for the airdrop site; Determine the horizontal safety interval between aircraft based on relevant aircraft flight safety specifications, and determine the safety interval between adjacent aircraft at different altitudes based on the structural parameters of the drop site and the types of materials required for the drop site.

3. The Monte Carlo method for calculating the capacity of an airdrop field according to claim 1, wherein: Methods for determining safe horizontal separation between aircraft include: Based on the combat mission, the size of the airdrop field and the amount of supplies required, determine the types and quantity of aircraft that can be used to perform airdrop missions, and obtain the proportion of aircraft types that can be deployed to the airdrop field to perform airdrop missions; The safety interval between the aircraft types is determined by the proportion of aircraft types that can be deployed to the airdrop field to perform airdrop missions and the average flight speed of each aircraft type, and in accordance with the relevant flight safety interval regulations.

4. The Monte Carlo method for calculating the capacity of an airdrop field according to claim 1, wherein: According to the airdrop field capacity model, the methods for determining the airdrop field capacity value include: Based on the airdrop field capacity model, the statistical time threshold is set, and the average number of aircraft performing airdrop missions per unit time is calculated through multiple random sampling. The airdrop field capacity value is solved using the Monte Carlo method.

5. The Monte Carlo method for calculating the capacity of an airdrop field according to claim 4, wherein: The capacity value of the airdrop field is calculated repeatedly, and the average of the multiple airdrop field capacity values ​​is obtained, which is the average capacity value of the airdrop field.

6. The Monte Carlo method for calculating the capacity of an airdrop field according to claim 5, wherein: Combined with the airdrop field capacity model, the Monte Carlo algorithm mainly selects aircraft to enter the available altitude layer through random sampling. When the corresponding constraints are met, it means that the aircraft can enter the airdrop field to perform the airdrop mission. Finally, the same steps are performed through repeated sampling to count the maximum number of airdrop field flights per unit time and obtain the maximum capacity value of the airdrop field.

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