Large UAV Communication System, Communication System Resource Classification Method, and UAV

Abstract

The present invention relates to the technical field of UAV communication, specifically to a large UAV communication system, a method for classifying communication system resources, and a UAV. In the present invention, it includes a data collection module, a resource classification module, a hierarchical structure model construction and application module, and a resource analysis module. Among them, the data collection module obtains communication resource data and current environmental data; the resource classification module uses the hierarchical clustering algorithm to generate a hierarchical resource list; the hierarchical structure model construction and application module constructs a model in combination with the current environmental data and calculates the resource weights; the resource analysis module analyzes according to the weight priority and obtains the overall system score. This modular design improves the accuracy of resource allocation and environmental adaptability, provides a scientific basis for decision-making, significantly improves the performance and reliability of the UAV communication system in complex environments, and realizes the intelligence and high efficiency of resource management.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV communication, and specifically to a large UAV communication system, a method for classifying communication system resources, and a UAV. Background Art

[0002] Traditional UAV communication systems often face many technical challenges in the face of complex and changing communication environments.

[0003] First, the resource management lacks hierarchical and structured methods, resulting in difficulty in comprehensively grasping the relationships and importance among various communication resources.

[0004] Secondly, the influence of environmental factors is not fully considered, making it difficult for the system to adapt to the complexity of actual communication scenarios. In addition, there is a lack of clear priority guidance in the resource analysis process, which may lead to key resources not being evaluated in a timely and effective manner. At the same time, the resource evaluation results are often isolated, lacking a comprehensive scoring mechanism to reflect the performance of the overall communication system.

[0005] These problems limit the accuracy and adaptability of traditional systems in resource allocation and management, making it difficult to effectively meet the rapidly changing communication requirements. In addition, the lack of decision support and intuitive, quantitative performance indicators affects the efficiency of system optimization and management. These technical problems, taken together, limit the performance and reliability of traditional UAV communication systems in complex environments and make it difficult to meet the growing demand for efficient and flexible communication. Summary of the Invention

[0006] The purpose of the present invention is to provide a large UAV communication system, a method for classifying communication system resources, and a UAV to solve the problems raised in the above background art.

[0007] To achieve the above purpose, one of the purposes of the present invention is that a large UAV communication system includes a data collection module, a resource classification module, a hierarchical structure model construction and application module, and a resource analysis module, wherein:

[0008] The data collection module collects communication resource data and current environment data;

[0009] The resource classification module classifies it according to the communication resource data by using the hierarchical clustering algorithm to generate a hierarchical resource list, where the hierarchical resource list includes different types of resources;

[0010] The hierarchical structure model construction and application module constructs a hierarchical structure model according to the current environment data and the hierarchical resource list by using the analytic hierarchy process; and calculates the weights of different types of resources in the hierarchical resource list according to the constructed hierarchical structure model;

[0011] The resource analysis module performs resource analysis on different types of resources in the hierarchical resource list in order of weight from largest to smallest according to the weights of different types of resources, obtains the analysis results of different types of resources, performs weighted summation on the analysis results of different types of resources according to the weights to obtain an overall score, and outputs it to the front end.

[0012] As a further improvement of this technical solution, the data collection module collects communication resource data and current environment data, where the communication resource data includes but is not limited to hardware resources, software resources, spectrum resources, and data link resources; the current environment data includes but is not limited to electromagnetic environment, meteorological conditions, and geographical location.

[0013] As a further improvement of this technical solution, the resource classification module classifies it using a hierarchical clustering algorithm based on the communication resource data, generates a structured resource list, and the hierarchical clustering algorithm specifically includes:

[0014] For each type of communication resource data, extract key features and standardize the extracted features to form an N-dimensional feature vector, where is the total number of resource items in the communication resource data;

[0015] According to the N-dimensional feature vectors of each type of communication resource data, calculate the distance between any two types of communication resource data, and construct an N×N similarity matrix, where the distance calculation includes but is not limited to Euclidean distance and Manhattan distance;

[0016] Regard each type of communication resource data as a separate cluster, and according to the similarity matrix, find the two clusters with the highest similarity, merge these two clusters, update the similarity matrix, and repeat this step until the preset number of clusters is reached to generate a clustering result;

[0017] Construct a hierarchical tree according to the clustering result, where each node represents a communication resource category, and the leaf node is a specific resource item in the communication resource category;

[0018] Assign descriptive labels to each non-leaf node in the hierarchical tree. The labels are determined based on the common features of the resource items in this category, and convert the tree structure into a hierarchical resource list. The hierarchical resource list includes resource categories and specific resource items.

[0019] As a further improvement of this technical solution, the hierarchical structure model construction and application module includes a hierarchical structure model construction unit. The hierarchical structure model construction unit constructs a hierarchical structure model using the analytic hierarchy process according to the current environment data and the hierarchical resource list, specifically including:

[0020] Obtain the current environmental data and use machine learning methods to identify the factors that have the greatest impact on communication effectiveness; perform quantization processing on each identified key factor and convert it into a numerical value between 0 and 1, where the quantization methods include but are not limited to linear mapping, non-linear functions, and discrete classification;

[0021] Based on the quantized key environmental factors and the hierarchical resource inventory, establish a hierarchical structure model, where the hierarchical structure model includes a top layer, a middle layer, and a bottom layer. The top layer is the overall goal, the middle layer uses the quantized key environmental factors as influencing factors, and the bottom layer uses the resource categories in the hierarchical resource inventory.

[0022] As a further improvement of this technical solution, the hierarchical structure model construction and application module includes a hierarchical structure model application unit. The hierarchical structure model application unit calculates the weights of different types of resources in the hierarchical resource inventory according to the constructed hierarchical structure model, specifically including:

[0023] Compare each pair of environmental factors in the middle layer of the hierarchical structure model pairwise to construct a judgment matrix A, and use the 1-9 scale method for comparison, where 1 represents equally important and 9 represents the most important;

[0024] Use the eigenvalue method to calculate the maximum eigenvalue λmax of the judgment matrix A and the corresponding eigenvector W, and normalize the eigenvector W to obtain the weight vector W_env of the environmental factors;

[0025] Calculate the consistency index CI = (λmax - n) / (n - 1), where n is the number of environmental factors, calculate the consistency ratio CR = CI / RI, where RI is the random consistency index. If CR < 0.1, then judge that it has acceptable consistency and evaluate the relative importance of resource categories to obtain the weight matrix B of each resource category relative to each environmental factor; otherwise, reconstruct the judgment matrix A;

[0026] Calculate the comprehensive contribution degree of the top layer in the hierarchical structure model according to different types of resources in the hierarchical resource inventory as the final weight vector. According to W_end = B * W_env, where W_end is the final weight vector of the resource category.

[0027] As a further improvement of this technical solution, the resource analysis module includes a primary analysis unit. The primary analysis unit performs resource analysis on the hierarchical resource inventory in order of weight from largest to smallest according to the weight sizes of different types of resources to obtain the analysis results of different types of resources, specifically including:

[0028] Sort the final weight vector \(W_{end}\) of the resource categories obtained by the hierarchical structure model application unit in descending order, and create a resource type index list corresponding to the weights.

[0029] Determine the priority order of resource analysis for the hierarchical resource list according to the sorted weights, and prepare corresponding analysis methods and evaluation indicators for each resource type.

[0030] As a further improvement of this technical solution, the resource analysis module includes a secondary analysis unit. The secondary analysis unit standardizes the evaluation indicators of each resource type calculated in the primary analysis unit; for each resource type, multiply its standardized analysis result by the corresponding weight to obtain an overall score, which is used to reflect the performance of the entire communication system, and output the overall score to the front end.

[0031] The second object of the present invention is to provide a method for classifying resources in a large unmanned aerial vehicle communication system, including the following method steps:

[0032] S1. Collect communication resource data and current environment data;

[0033] S2. Classify the communication resource data according to the hierarchical clustering algorithm to generate a hierarchical resource list, where the hierarchical resource list includes different types of resources;

[0034] S3. According to the current environment data and the hierarchical resource list, use the analytic hierarchy process to construct a hierarchical structure model; according to the constructed hierarchical structure model, calculate the weights of different types of resources in the hierarchical resource list;

[0035] S4. According to the weight sizes of different types of resources, in the order of descending weights, perform resource analysis on different types of resources in the hierarchical resource list in turn to obtain analysis results of different types of resources, and perform weighted summation on the analysis results of different types of resources according to the weight sizes to obtain an overall score, and output it to the front end.

[0036] The third object of the present invention is to provide an unmanned aerial vehicle for a large unmanned aerial vehicle communication system, including a processor and a memory storing a computer program.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. The large UAV communication system, the communication system resource classification method, and the UAV classify communication resource data by using the hierarchical clustering algorithm to generate a hierarchical resource list, laying a structured foundation for subsequent analysis. This hierarchical resource list not only provides a clear classification of resources but also retains the hierarchical relationship between resources. Subsequently, the system ingeniously combines the current environmental data with this hierarchical resource list and constructs a hierarchical structure model that comprehensively considers environmental factors and resource distribution by using the analytic hierarchy process. This method enables the model to more accurately reflect the complexity of the actual communication scenario. Based on this model, the system further calculates the weights of different types of resources in the hierarchical resource list. This process not only considers the importance of the resources themselves but also incorporates the influence of environmental factors. Through this multiple application, the hierarchical resource list becomes the key link connecting the original data, environmental factors, and resource importance, greatly improving the accuracy and adaptability of resource allocation and management, enabling the system to better cope with the complex and changing communication environment.

[0039] 2. After the large UAV communication system, the communication system resource classification method, and the UAV complete the calculation of the weights of different types of resources in the hierarchical resource list, the system further exploits the value of these weight data. First, the system sorts the resources from large to small according to the calculated weights, providing clear priority guidance for subsequent resource analysis. Then, the system strictly follows this priority order and deeply analyzes different types of resources in turn, ensuring that the most important resources are evaluated first and fully. This analysis order based on weights not only improves the analysis efficiency but also enables concentrating on the most critical resources within a limited time. Subsequently, the system innovatively combines the analysis results of various resources with their corresponding weights and obtains a comprehensive overall score by weighted summation. This score, as a quantitative indicator of the performance of the entire communication system, is output to the front end for decision-makers to refer to. This method of multiple application of weights enables the system to comprehensively and prominently evaluate the resource status, while providing an intuitive and comprehensive performance indicator, greatly enhancing the scientificity and efficiency of decision-making and providing strong data support for the optimization and management of the large UAV communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the overall module unit of the present invention;

[0041] Figure 2 It is a schematic diagram of the overall method flow of the present invention.

[0042] In the figure: 100, data collection module; 200, resource classification module; 300, hierarchical structure model construction and application module; 301, hierarchical structure model construction unit; 302, hierarchical structure model application unit; 400, resource analysis module; 401, primary analysis unit; 402, secondary analysis unit. Detailed implementation manners

[0043] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] Unless otherwise specified, the terms (including scientific and technical terms) used herein have the ordinary meaning understood by those skilled in the technical field to which they belong. In addition, it can be understood that the terms defined in the commonly used dictionary should be understood as having a meaning consistent with the context of their related fields, and should not be understood as having an idealized or overly formal meaning.

[0045] The following are definitions of some terms:

[0046] Hierarchical resource list: It refers to a hierarchical resource list generated by classifying communication resource data through a hierarchical clustering algorithm. It contains resource categories and specific resource items at different levels, forming a tree structure. For example, the top layer in the tree structure may be major resource categories (such as hardware resources, software resources, etc.), the next layer is specific categories (such as antennas, processors, etc.), and the bottom layer is specific resource items (such as bandwidth, CPU speed, etc.).

[0047] Hierarchical structure model: It is a model constructed by using the analytic hierarchy process based on the current environmental data and the hierarchical resource list. This model includes the top layer (total goal, such as the optimal communication effect), the middle layer (quantified key environmental factors), and the bottom layer (resource categories in the hierarchical resource list). It is used to analyze the influence of environmental factors on different resource categories and provide a basis for resource weight calculation.

[0048] Weight magnitudes of different types of resources: It refers to the relative importance of each resource category to the total goal calculated through the hierarchical structure model. These weights reflect the contribution degrees of different types of resources to the performance of the communication system under the current environment. The larger the weight value, the more important this type of resource is in the current situation and should be analyzed and optimized preferentially.

[0049] Next, please refer to Figures 1 - 2, One of the purposes of this embodiment is a large - scale UAV communication system, including a data collection module 100, a resource classification module 200, a hierarchical structure model construction and application module 300, and a resource analysis module 400.

[0050] The data collection module 100 collects communication resource data and current environment data. The communication resource data includes, but is not limited to, hardware resources (such as hardware parameters of antennas, processors, storage devices, etc.), software resources (such as software information of communication protocols, algorithms, operating systems, etc.), spectrum resources (such as available frequency bands, bandwidth, etc.), and data link resources (such as status and performance parameters of various communication links); the current environment data includes, but is not limited to, electromagnetic environment (such as signal - to - noise ratio, interference sources, etc.), meteorological conditions (such as visibility, wind speed, temperature, etc.), and geographical location (such as GPS coordinates, altitude, distance from the ground station, etc.).

[0051] The resource classification module 200 classifies the communication resource data according to the communication resource data by using the hierarchical clustering algorithm, and generates a structured resource list. The hierarchical clustering algorithm specifically includes:

[0052] For each type of communication resource data, extract key features (such as processing capacity, bandwidth, power consumption, etc.), and standardize the extracted features to form an N - dimensional feature vector;

[0053] According to the N - dimensional feature vectors of each type of communication resource data, calculate the distance between any two types of communication resource data, and construct an N×N similarity matrix (N is the total number of resource items). The distance calculation includes, but is not limited to, Euclidean distance and Manhattan distance;

[0054] Regard each type of communication resource data as a separate cluster, and according to the similarity matrix, find the two clusters with the highest similarity, merge these two clusters, update the similarity matrix, repeat this step until the preset number of clusters is reached, and generate a clustering result;

[0055] Construct a hierarchical tree according to the clustering result. Each node represents a communication resource category, and the leaf node is a specific resource item in the communication resource category. For example, if the communication resource category is spectrum resources, the specific resource item is bandwidth;

[0056] Assign descriptive labels to each non - leaf node (i.e., each category) in the hierarchical tree. The labels are determined based on the common features of the resource items in this category, and convert the tree - like structure into a hierarchical resource list. The hierarchical resource list includes resource categories and specific resource items.

[0057] The hierarchical structure model construction unit 301 in the hierarchical structure model construction and application module 300 constructs a hierarchical structure model according to the current environment data and the hierarchical resource list by using the analytic hierarchy process, specifically including:

[0058] Obtain the current environmental data and use machine learning methods (such as principal component analysis PCA) to identify the factors that have the greatest impact on communication effectiveness. For example, identify signal quality, environmental complexity, and temperature as key factors; perform quantization processing on each identified key factor and convert it into a value between 0 and 1. The quantization methods include but are not limited to linear mapping (such as linearly mapping the signal-to-noise ratio from dB to the 0-1 range), non-linear functions (such as using the sigmoid function to map the temperature impact to 0-1), and discrete classification (such as mapping the environmental type (urban, suburban, rural) to specific values).

[0059] Based on the quantized key environmental factors and the hierarchical resource inventory, establish a hierarchical structure model. The hierarchical structure model includes a top layer, a middle layer, and a bottom layer. The top layer is the overall goal (such as optimal communication effectiveness), the middle layer uses the quantized key environmental factors as influencing factors, and the bottom layer uses the resource categories in the hierarchical resource inventory.

[0060] The hierarchical structure model application unit 302 in the hierarchical structure model construction and application module 300 calculates the weights of different types of resources in the hierarchical resource inventory according to the constructed hierarchical structure model. Specifically, it includes:

[0061] Compare each pair of environmental factors in the middle layer of the hierarchical structure model pairwise to construct a judgment matrix A, and use the 1-9 scale method for comparison, where 1 means equally important and 9 means the most important;

[0062] Use the eigenvalue method to calculate the maximum eigenvalue λmax of the judgment matrix A and the corresponding eigenvector W, normalize the eigenvector W to obtain the weight vector W_env of the environmental factors;

[0063] Calculate the consistency index CI=(λmax - n) / (n - 1), where n is the number of environmental factors, calculate the consistency ratio CR = CI / RI, where RI is the random consistency index. If CR < 0.1, it is judged to have acceptable consistency, and evaluate the relative importance of resource categories to obtain the weight matrix B of each resource category relative to each environmental factor; otherwise, reconstruct the judgment matrix A;

[0064] Calculate the comprehensive contribution degree of the top layer in the hierarchical structure model for different types of resources in the hierarchical resource inventory as the final weight vector. According to W_end = B * W_env, where W_end is the final weight vector of the resource category.

[0065] The primary analysis unit 401 in the resource analysis module 400 performs resource analysis on the hierarchical resource list in order of weight from largest to smallest according to the weights of different types of resources, and obtains the analysis results of different types of resources, specifically including:

[0066] Sort the final weight vector W_end of the resource categories calculated by the hierarchical structure model application unit 302 in descending order, and create a resource type index list corresponding to the weights;

[0067] Determine the priority order of resource analysis for the hierarchical resource list according to the sorted weights, and prepare corresponding analysis methods and evaluation indicators for each resource type, such as:

[0068] Hardware resource analysis: Evaluate the processor performance (such as CPU speed, number of cores), analyze the storage capacity and read / write speed, evaluate the antenna parameters (such as gain, directivity), and calculate the utilization rate of hardware resources;

[0069] Software resource analysis: Evaluate the efficiency and applicability of communication protocols, analyze the complexity and execution time of algorithms, evaluate the stability and resource management capabilities of operating systems, and check software version compatibility;

[0070] Spectrum resource analysis: Calculate the total bandwidth of available frequency bands, analyze the spectrum utilization efficiency, evaluate the frequency band interference situation, and consider the possibility of spectrum sharing;

[0071] Data link resource analysis: Evaluate the throughput of each communication link, analyze the link stability and reliability, calculate the link utilization rate, and evaluate the link delay and jitter.

[0072] The secondary analysis unit 402 in the resource analysis module 400 performs weighted summation on the analysis results of different types of resources according to the weights and outputs them to the front end; by standardizing the evaluation indicators of each resource type calculated in the primary analysis unit 401; for each resource type, multiply its standardized analysis result by the corresponding weight to obtain an overall score, which is used to reflect the performance of the entire communication system, and output the overall score to the front end for further maintenance by management personnel.

[0073] The second objective of this embodiment is a method for classifying resources in a large UAV communication system, including the following method steps:

[0074] S1. Collect communication resource data and current environment data;

[0075] S2. Classify the communication resource data using the hierarchical clustering algorithm to generate a hierarchical resource list, where the hierarchical resource list includes different types of resources;

[0076] S3. Based on the current environmental data and the hierarchical resource inventory, use the analytic hierarchy process to construct a hierarchical structure model; according to the constructed hierarchical structure model, calculate the weights of different types of resources in the hierarchical resource inventory.

[0077] S4. According to the weights of different types of resources, in the order from largest to smallest, analyze different types of resources in the hierarchical resource inventory in turn to obtain the analysis results of different types of resources, and perform weighted summation on the analysis results of different types of resources according to the weights to obtain an overall score, and output it to the front end.

[0078] The third objective of this embodiment is to provide an unmanned aerial vehicle for a large unmanned aerial vehicle communication system, including a processor and a memory storing a computer program. When the processor executes the computer program, it implements the unmanned aerial vehicle communication system provided in each of the above embodiments.

[0079] The above has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification are only preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. Large UAV communication system, characterized by: It includes data collection module, resource classification module, hierarchical model construction and application module and resource analysis module, among which: The data collection module collects communication resource data and current environment data; The resource classification module classifies the communication resource data using a hierarchical clustering algorithm to generate a hierarchical resource list, wherein the hierarchical resource list includes different types of resources; The hierarchical structure model construction and application module constructs a hierarchical structure model based on the current environment data and the hierarchical resource list using the hierarchical analysis method; and calculates weights of different types of resources in the hierarchical resource list based on the constructed hierarchical structure model. The hierarchical structure model construction and application module includes a hierarchical structure model construction unit. The hierarchical structure model construction unit constructs the hierarchical structure model based on the current environment data and the hierarchical resource list using the hierarchical analysis method, specifically including: Obtain current environmental data and use machine learning methods to identify the factors that have the greatest impact on communication effectiveness; quantify each identified key factor and convert it into a value between 0 and 1, where quantification methods include but are not limited to linear mapping, nonlinear functions, and discrete classification; Based on the quantified key environmental factors and the hierarchical resource list, a hierarchical model is established, wherein the hierarchical model includes a top layer, a middle layer and a bottom layer, wherein the top layer is the overall goal, the middle layer uses the quantified key environmental factors as the influencing factors, and the bottom layer uses the resource categories in the hierarchical resource list; The resource analysis module analyzes different types of resources in the hierarchical resource list in descending order of weight according to the weights of different types of resources, obtains analysis results of different types of resources, and performs weighted summation of the analysis results of different types of resources according to the weights to obtain an overall score, which is output to the front end. The calculation of the weights of different types of resources in the hierarchical resource list specifically includes: Each pair of environmental factors in the middle layer of the hierarchical model is compared pairwise to construct the judgment matrix A, and the weight vector W_env of the environmental factors is obtained. The relative importance of resource categories is evaluated to obtain the weight matrix B of each resource category relative to each environmental factor. According to B*W_env, the final weight vector of the resource category is calculated.

2. The large-scale UAV communication system according to claim 1, characterized in that: The data collection module collects communication resource data and current environment data, wherein the communication resource data includes but is not limited to hardware resources, software resources, spectrum resources and data link resources; the current environment data includes but is not limited to electromagnetic environment, meteorological conditions and geographical location.

3. The large-scale UAV communication system according to claim 1, characterized in that: The resource classification module classifies the communication resource data using a hierarchical clustering algorithm to generate a structured resource list. The hierarchical clustering algorithm specifically includes: For each type of communication resource data, key features are extracted and the extracted features are normalized to form an N-dimensional feature vector, where the total number of resource items in the communication resource data; Calculate the distance between any two types of communication resource data based on the N-dimensional feature vector of each type of communication resource data, and construct an N×N similarity matrix, where the distance calculation includes but is not limited to Euclidean distance and Manhattan distance; Each type of communication resource data is considered as a separate cluster, and according to the similarity matrix, the two clusters with the highest similarity are found, the two clusters are merged, and the similarity matrix is updated. This step is repeated until the preset number of clusters is reached to generate the clustering result; A hierarchical tree is constructed based on the clustering results, where each node represents a communication resource category and the leaf nodes are specific resource items in the communication resource category; A descriptive label is assigned to each non-leaf node in the hierarchical tree. The label is determined based on the common characteristics of the resource items in the category, and the tree structure is converted into a hierarchical resource list. The hierarchical resource list includes resource categories and specific resource items.

4. The large-scale UAV communication system according to claim 1, characterized in that: The hierarchical model construction and application module includes a hierarchical model application unit, which calculates the weights of different types of resources in the hierarchical resource list according to the constructed hierarchical model, specifically including: Each pair of environmental factors in the middle layer of the hierarchical model is compared pairwise to construct a judgment matrix A, and the comparison is made using a 1-9 scale, where 1 represents equal importance and 9 represents the most important; Use the eigenvalue method to calculate the maximum eigenvalue λmax of the judgment matrix A and the corresponding eigenvector W, normalize the eigenvector W, and obtain the weight vector W_env of the environmental factors; Calculate the consistency index CI = (λmax-n) / (n-1), where n is the number of environmental factors. Calculate the consistency ratio CR = CI / RI, where RI is the random consistency index. If CR < 0.1, it is judged to have acceptable consistency, and the relative importance of resource categories is evaluated to obtain the weight matrix B of each resource category relative to each environmental factor; otherwise, reconstruct the judgment matrix A; According to the different types of resources in the hierarchical resource list, the comprehensive contribution of the top layer in the hierarchical structure model is calculated as the final weight vector W_end of the resource category.

5. The large-scale UAV communication system according to claim 1, characterized in that: The resource analysis module includes a primary analysis unit, which performs resource analysis on the hierarchical resource list in descending order of weight according to the weights of different types of resources, and obtains analysis results of different types of resources, specifically including: Sort the final weight vector W_end of the resource categories calculated by the hierarchical model application unit in descending order, and create a resource type index list corresponding to the weight; Based on the sorted weights, determine the priority of the hierarchical resource list for resource analysis, and prepare corresponding analysis methods and evaluation indicators for each resource type.

6. The large-scale UAV communication system according to claim 1, characterized in that: The resource analysis module includes a secondary analysis unit, which standardizes the evaluation indicators of each resource type calculated in the primary analysis unit; for each resource type, the standardized analysis result is multiplied by the corresponding weight to obtain an overall score for reflecting the performance of the entire communication system, and the overall score is output to the front end.

7. A resource classification method for a large-scale unmanned aerial vehicle communication system using any one of claims 1 to 6, characterized in that: The method comprises the following steps: S1. Collect communication resource data and current environment data; S2. Classify the communication resource data using a hierarchical clustering algorithm to generate a hierarchical resource list, wherein the hierarchical resource list includes different types of resources; S3. Based on the current environmental data and the hierarchical resource list, use the hierarchical analysis method to build a hierarchical structure model; based on the built hierarchical structure model, calculate the weights of different types of resources in the hierarchical resource list; S4. According to the weights of different types of resources, in descending order of weight, perform resource analysis on different types of resources in the hierarchical resource list to obtain analysis results of different types of resources. According to the weights, perform weighted summation on the analysis results of different types of resources to obtain an overall score, which is then output to the front end.

8. A UAV of a large UAV communication system, comprising a processor and a memory storing a computer program, characterized in that: When the processor executes the computer program, the drone communication system according to any one of claims 1 to 6 is implemented.

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