Low-altitude airspace performance measurement method and device

Abstract

The embodiment of the invention provides a low-altitude airspace performance measurement method and device. The method comprises the following steps: establishing an airspace performance index system; the method comprises the following steps: extracting an airspace operation data set and an airspace management data set based on an airspace performance index system, defining quality evaluation dimensions, constructing a judgment matrix by adopting a scale method to evaluate the credibility weight of each quality evaluation dimension, calculating the comprehensive credibility weight of each data source under each quality evaluation dimension, and calculating the credibility of each data source; fusing the airspace operation data set and the airspace management data set according to the comprehensive credibility weight, and determining a corresponding multi-source fusion data set; according to the multi-source fusion data set, constructing an airspace dynamic simulation environment, in the simulation environment, calculating airspace capacity performance according to a dynamic capacity calculation model, calculating airspace safety performance according to a conflict detection model, and establishing a service quality comprehensive evaluation index to evaluate airspace efficiency performance. And determining the comprehensive performance of the airspace by integrating the capacity performance, the safety performance and the efficiency performance. The low-altitude airspace management method and device can improve the efficiency of low-altitude airspace management.

Description

Technical Field

[0001] This application relates to the field of data processing, specifically to a method and apparatus for measuring low-altitude airspace performance. Background Technology

[0002] In current airspace management systems, airspace performance calculations and assessments primarily focus on the civil aviation sector, relying on traditional communication and navigation equipment such as ADS-B (Automatic Dependent Surveillance-Broadcast) and VHF (Very High Frequency) communications. However, with the increasing complexity of urban low-altitude environments, existing assessment methods face numerous challenges and shortcomings.

[0003] Urban low-altitude airspace, as an important area for emerging aviation activities, lacks a unified performance evaluation standard. This leads to frequent problems in actual operation, such as uncertainty in communication and navigation performance, ambiguity in safety acceptability, and unclear definition of airspace types. Especially when there are differences in perspective between operators (such as airlines and drone operators) and managers (such as air traffic control departments and government regulatory agencies), how to objectively and comprehensively evaluate airspace performance has become a critical issue that urgently needs to be addressed.

[0004] The shortcomings of existing technologies are mainly reflected in the following aspects: First, the assessment methods are singular, mainly relying on traditional communication and navigation equipment, which is difficult to adapt to the complex and ever-changing environment of urban low-altitude airspace; second, the assessment standards are not uniform, which reduces the comparability and credibility of the assessment results; finally, there is a lack of dynamic assessment mechanisms, which cannot reflect changes in airspace performance in real time and is difficult to meet the actual needs of airspace management.

[0005] Therefore, there is an urgent need to establish a method for measuring low-altitude airspace performance in order to achieve objective, comprehensive, and real-time assessment of airspace performance, provide a scientific and reliable basis for airspace management, and improve the efficiency of low-altitude airspace management. Summary of the Invention

[0006] To address the problems in the prior art, this application provides a method and apparatus for measuring low-altitude airspace performance, which can improve the efficiency of low-altitude airspace management.

[0007] To solve at least one of the above problems, this application provides the following technical solution:

[0008] In a first aspect, this application provides a method for measuring low-altitude airspace performance, including:

[0009] Based on airspace classification requirements, the basic attributes of airspace are determined, the distribution of communication and navigation facilities within the airspace is assessed, and an airspace performance index system is established based on the basic attributes of airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index, and efficiency index.

[0010] Based on the aforementioned airspace performance index system, an airspace operation dataset is extracted from airspace operator data, and an airspace management dataset is extracted from airspace manager data. Quality assessment dimensions are defined, and a scaling method is used to construct a judgment matrix to compare each quality assessment dimension pairwise, determining the credibility weight of each dimension. Local weight calculations are performed on the airspace operation dataset and the airspace management dataset under each quality assessment dimension to determine the comprehensive credibility weight corresponding to each data source. Based on the comprehensive credibility weight, the airspace operation dataset and the airspace management dataset are fused to determine the corresponding multi-source fused dataset.

[0011] Based on the multi-source fusion dataset, a dynamic simulation environment for airspace operation is constructed. According to aircraft performance parameters, airspace structural characteristics, and control rules, a corresponding dynamic capacity calculation model is determined. The dynamic capacity calculation model is used to calculate the capacity of the dynamic simulation environment and determine the corresponding airspace capacity performance. A conflict risk assessment is performed on the dynamic simulation environment based on a defined conflict detection model to determine the corresponding airspace safety performance. A comprehensive service quality evaluation index is established to analyze the service quality of the dynamic simulation environment and determine the corresponding airspace efficiency performance. Finally, the corresponding comprehensive airspace performance is determined based on the airspace capacity performance, airspace safety performance, and airspace efficiency performance.

[0012] Furthermore, the defined quality assessment dimensions include:

[0013] Define the integrity dimension, check the missing data field rate, and perform an integrity assessment based on the missing data field rate.

[0014] Define a timeliness dimension and calculate a timeliness decay coefficient based on the delay between data generation time and evaluation time to conduct timeliness assessment;

[0015] Define a consistency dimension and use cross-source comparison methods to detect outlier data for consistency assessment.

[0016] Define the accuracy dimension and evaluate the accuracy based on the comparison results between quantitative indicators and preset standards.

[0017] Further, the step of calculating local weights for the airspace operation dataset and the airspace management dataset under each of the aforementioned quality assessment dimensions to determine the comprehensive credibility weight corresponding to each data source includes:

[0018] Under each quality assessment dimension, a sub-judgment matrix is ​​constructed for each data source in the airspace operation dataset and the airspace management dataset, and local weights are calculated to determine the corresponding local weights.

[0019] The overall credibility weight corresponding to each data source is determined by summing the credibility weights of each quality assessment dimension with the local weights.

[0020] Furthermore, the step of determining the corresponding dynamic capacity calculation model based on aircraft performance parameters, airspace structural characteristics, and control rules, and then performing capacity calculations on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance includes:

[0021] The aircraft performance parameters are collected and normalized to determine the corresponding normalized parameters. Airspace structure features are extracted to construct a topology graph and determine the corresponding airspace structure parameters. Control rules are analyzed to determine the corresponding constraint parameters. Based on the normalized parameters, the airspace structure parameters, and the constraint parameters, a dynamic capacity calculation model for airspace units is established. The dynamic capacity calculation model is used to quantify the node throughput capacity according to network flow theory.

[0022] Discrete event simulation technology is used to simulate peak-hour capacity bottlenecks based on the dynamic capacity calculation model and traffic data in the dynamic simulation environment, and to determine the corresponding airspace capacity performance.

[0023] Furthermore, the step of assessing the conflict risk of the dynamic simulation environment based on the established conflict detection model and determining the corresponding airspace security performance includes:

[0024] A four-dimensional conflict detection model is constructed, and the probability of potential conflicts occurring in the dynamic simulation environment is calculated based on the four-dimensional conflict detection model.

[0025] A conflict risk assessment algorithm is introduced to conduct differentiated risk level assessments based on the probability of potential conflicts and aircraft type, thereby determining the corresponding airspace safety performance.

[0026] Furthermore, the construction of the four-dimensional conflict detection model includes:

[0027] A grid reference space is constructed based on preset target airspace characteristics and preset aircraft performance characteristics. The grid reference space is used to unify longitude and latitude standards.

[0028] A four-dimensional conflict detection model is constructed based on the grid reference space, altitude transformation matrix, and time synchronization network. The four-dimensional conflict detection model is used to detect conflicts based on the predicted trajectory of the aircraft. The dimensions of the predicted trajectory include longitude, latitude, altitude, and time.

[0029] Further, after determining the corresponding comprehensive airspace performance based on the airspace capacity performance, the airspace security performance, and the airspace efficiency performance, the process includes:

[0030] Based on the performance data of the comprehensive airspace performance, an initial model is trained, and a corresponding performance change trend prediction model is determined.

[0031] Real-time tracking of target airspace operation data; based on the performance change trend prediction model, comprehensive airspace performance prediction for the target airspace is performed to determine whether performance degradation has occurred. If so, an early warning mechanism is activated, and airspace operation strategies are dynamically adjusted.

[0032] Secondly, this application provides a low-altitude airspace performance measurement device, comprising:

[0033] The airspace performance index system determination module is used to determine the basic attributes of airspace according to airspace classification requirements, evaluate the distribution of communication and navigation facilities in airspace, and establish an airspace performance index system based on the basic attributes of airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index.

[0034] The multi-source airspace performance data fusion module is used to extract airspace operation datasets from airspace operator data and airspace management datasets from airspace manager data based on the airspace performance index system. It defines quality assessment dimensions, constructs a judgment matrix using scaling to compare each quality assessment dimension pairwise, determines the credibility weight of each dimension, calculates local weights for the airspace operation dataset and airspace management dataset under each quality assessment dimension, determines the comprehensive credibility weight corresponding to each data source, and fuses the airspace operation dataset and airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset.

[0035] The airspace comprehensive performance determination module is used to construct a dynamic simulation environment of airspace operation status based on the multi-source fusion dataset, determine the corresponding dynamic capacity calculation model based on aircraft performance parameters, airspace structural characteristics, and control rules, perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance, conduct conflict risk assessment on the dynamic simulation environment based on a set conflict detection model to determine the corresponding airspace safety performance, establish a comprehensive service quality evaluation index to analyze the service quality of the dynamic simulation environment to determine the corresponding airspace efficiency performance, and determine the corresponding airspace comprehensive performance based on the airspace capacity performance, the airspace safety performance, and the airspace efficiency performance.

[0036] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the low-altitude airspace performance measurement method.

[0037] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the low-altitude airspace performance measurement method described above.

[0038] Fifthly, this application provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the low-altitude airspace performance measurement method.

[0039] As can be seen from the above technical solution, this application provides a method and apparatus for measuring low-altitude airspace performance. It establishes an airspace performance index system; extracts airspace operation datasets and airspace management datasets based on the airspace performance index system; defines quality assessment dimensions; constructs a judgment matrix using a scaling method to evaluate the credibility weights of each quality assessment dimension; calculates the comprehensive credibility weights of each data source under each quality assessment dimension; merges the airspace operation dataset and airspace management dataset according to the comprehensive credibility weights to determine the corresponding multi-source fused dataset; constructs a dynamic airspace simulation environment based on the multi-source fused dataset; calculates airspace capacity performance based on a dynamic capacity calculation model and airspace safety performance based on a conflict detection model in the simulation environment; establishes a comprehensive service quality evaluation index to evaluate airspace efficiency performance; and determines the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance, thereby improving the efficiency of low-altitude airspace management. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is one of the flowcharts illustrating the low-altitude airspace performance measurement method in the embodiments of this application;

[0042] Figure 2 This is a structural diagram of the low-altitude airspace performance measurement device in the embodiments of this application;

[0043] Figure 3 This is a schematic diagram of the structure of the electronic device in the embodiments of this application.

[0044] Figure label:

[0045] Electronic device 9600, central processing unit 9100, memory 9140, communication module 9110, input unit 9120, audio processor 9130, display 9160, power supply 9170, buffer memory 9141, application / function storage unit 9142, data storage unit 9143, driver storage unit 9144, antenna 9111, speaker 9131, microphone 9132. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0048] Given that urban low-altitude airspace, as an important area for emerging aviation activities, lacks a unified performance evaluation standard, problems frequently arise in actual operations, including uncertainty in communication and navigation performance, ambiguity in safety acceptability, and unclear definition of airspace types. Especially when there are differences in perspective between operators (such as airlines and drone operators) and managers (such as air traffic control departments and government regulatory agencies), how to objectively and comprehensively evaluate airspace performance has become a critical issue that urgently needs to be addressed. This application provides a method and apparatus for measuring low-altitude airspace performance. It establishes an airspace performance index system; extracts airspace operation datasets and airspace management datasets based on this system; defines quality assessment dimensions; constructs a judgment matrix using a scaling method to evaluate the credibility weights of each quality assessment dimension; calculates the comprehensive credibility weights of each data source under each quality assessment dimension; and fuses the airspace operation dataset and airspace management dataset according to the comprehensive credibility weights to determine the corresponding multi-source fused dataset. Based on the multi-source fused dataset, it constructs a dynamic airspace simulation environment. In this simulation environment, it calculates airspace capacity performance using a dynamic capacity calculation model, calculates airspace safety performance using a conflict detection model, establishes a comprehensive service quality evaluation index to evaluate airspace efficiency performance, and determines the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance. This improves the efficiency of low-altitude airspace management.

[0049] To improve the efficiency of low-altitude airspace management, this application provides an embodiment of a low-altitude airspace performance measurement method, see [link to embodiment]. Figure 1 The low-altitude airspace performance measurement method specifically includes the following:

[0050] Step S101: Determine the basic attributes of the airspace according to the airspace classification requirements, evaluate the distribution of communication and navigation facilities in the airspace, and establish an airspace performance index system based on the basic attributes of the airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index.

[0051] Optionally, in this embodiment, the purpose of this step is to construct an airspace performance index system to provide a solid foundation and precise guidance for subsequent airspace operation and management.

[0052] Optionally, in this embodiment, the national airspace classification requirements cover a variety of key characteristics of airspace to ensure the reasonable division and effective management of airspace. For example, based on factors such as flight altitude, flight rules, and aircraft type, airspace is divided into different categories, such as Class A, Class B, and Class C. Class A airspace is generally suitable for high-altitude flights, requiring strict flight rules and altitude control; Class B airspace mainly targets busy airspace around airports, requiring precise navigation and communication support; Class C airspace is suitable for airport terminal areas, requiring refined management of takeoffs and landings. Based on these classification requirements, the specific purpose and operating environment of each airspace can be clearly defined. For example, in urban low-altitude environments, Class C or Class D airspace is mainly involved. These airspaces need to meet the special needs of urban low-altitude flights, such as drone delivery and urban air traffic. The process of determining the basic attributes of airspace is to combine the national airspace classification requirements with the specific urban low-altitude environment to clarify the operating environment and usage requirements of the airspace.

[0053] Specifically, the basic attributes of airspace, determined based on national airspace classification requirements, include the type of aircraft operating there, minimum equipment requirements, and meteorological conditions.

[0054] The type of aircraft operating is a crucial component of basic airspace attributes. In urban low-altitude environments, aircraft types include small drones, helicopters, and light aircraft. Different types of aircraft have significantly different performance parameters and operational requirements. Determining the type of aircraft operating helps clarify airspace usage needs and performance indicators. For example, if an airspace is primarily used for small drone delivery, then the airspace's capacity indicators need to consider drone flight density and route planning; safety indicators need to focus on drone obstacle avoidance capabilities and communication link stability; and efficiency indicators need to consider drone flight speed and mission completion time.

[0055] Minimum equipment requirements refer to the equipment that an aircraft must possess to operate within a specific airspace. This equipment typically includes communication equipment, navigation equipment, and surveillance equipment. Determining minimum equipment requirements helps assess the distribution and performance of airspace communication and navigation facilities. If an aircraft is equipped with advanced communication and navigation equipment, then the airspace's communication and navigation facilities must have corresponding support capabilities, such as sufficient communication bandwidth and navigation signal coverage.

[0056] Meteorological conditions are a crucial factor affecting airspace performance. Different airspaces have different meteorological requirements. For example, high-altitude flight has relatively lenient requirements, focusing primarily on large-scale weather systems; while low-altitude urban flight has more stringent requirements, needing to consider local meteorological conditions such as wind speed, wind direction, visibility, and precipitation. Determining meteorological requirements helps assess airspace operational safety and efficiency. For instance, in urban low-altitude environments, unfavorable meteorological conditions, such as low visibility or excessively high wind speeds, can threaten aircraft flight safety and reduce airspace operational efficiency. Therefore, determining meteorological requirements is a vital step in ensuring safe airspace operation.

[0057] Optionally, in this embodiment, the distribution of communication and navigation facilities in the airspace is assessed, including ground surveillance equipment, communication equipment, and navigation equipment.

[0058] Ground surveillance equipment is a crucial component of airspace communication and navigation facilities, primarily including radar, ADS-B ground stations, and multipoint positioning systems. These devices monitor the position and status of aircraft within the airspace in real time, providing controllers with accurate airspace operational information. Assessing the distribution of ground surveillance equipment requires considering its coverage, detection accuracy, and reliability. For example, radar typically has a large coverage area but limited detection capability against low-altitude targets; ADS-B ground stations, on the other hand, have strong detection capabilities against low-altitude targets but relatively smaller coverage areas. Therefore, in urban low-altitude environments, a diverse range of ground surveillance equipment needs to be strategically deployed to achieve comprehensive airspace coverage and accurate monitoring.

[0059] Communication equipment is another crucial component of airspace communication and navigation facilities, primarily including Very High Frequency (VHF) communication equipment, satellite communication equipment, and data link communication equipment. These devices enable real-time communication between aircraft and ground control, ensuring flight safety and operational efficiency. Assessing the distribution of communication equipment requires considering its communication range, quality, and service capabilities. For example, VHF communication equipment typically has a line-of-sight range but offers high communication quality; satellite communication equipment has a wider range but suffers from greater latency. Therefore, in urban low-altitude environments, communication equipment must be rationally selected and deployed based on the specific needs of the airspace to ensure reliable and real-time communication.

[0060] Navigation equipment is the third crucial component of airspace communication and navigation facilities, primarily including the Global Positioning System (GPS), Inertial Navigation Systems (INS), and Ground-Based Augmentation Systems (GBAS). These devices provide aircraft with accurate navigation information, ensuring they fly along predetermined routes within the airspace. Assessing the distribution of navigation equipment requires considering its navigation accuracy, coverage, and service capabilities. For example, GPS offers high navigation accuracy but is significantly affected by satellite signal obstruction; INS has relatively lower accuracy but is less susceptible to external signal interference. Therefore, in urban low-altitude environments, it is necessary to combine the advantages of multiple navigation devices and rationally deploy navigation facilities to improve navigation accuracy and reliability.

[0061] Optionally, in this embodiment, after determining the basic airspace attributes and the distribution of communication and navigation facilities within the airspace, we establish an airspace performance index system framework, including capacity index, safety index, and efficiency index.

[0062] Capacity metrics are crucial indicators for measuring the number and flow of aircraft an airspace can accommodate. In urban low-altitude environments, establishing capacity metrics requires considering factors such as the airspace's structural characteristics, operational rules, and aircraft performance. For example, an airspace's capacity may be limited by factors like the number of flight routes, flight altitudes, and aircraft spacing. Establishing capacity metrics helps assess the airspace's operational efficiency and management capabilities. For instance, low airspace capacity may lead to increased aircraft waiting times and reduced operational efficiency; conversely, high capacity requires greater control and technical support to ensure safe airspace operation.

[0063] Safety indicators are crucial metrics for measuring airspace operational safety. In urban low-altitude environments, establishing safety indicators requires considering factors such as aircraft obstacle avoidance capabilities, communication link stability, and surveillance equipment reliability. For example, safety indicators may include minimum safe distances between aircraft, tolerance for communication interruptions, and the coverage area of ​​surveillance equipment. Establishing safety indicators helps assess the operational risks and safety levels of airspace. For instance, low safety indicators in an airspace may increase the risk of collisions between aircraft, reducing operational safety; conversely, high safety indicators require greater technical support and management measures to ensure safe airspace operation.

[0064] Efficiency indicators are crucial metrics for measuring airspace operational efficiency. In urban low-altitude environments, establishing efficiency indicators requires considering factors such as aircraft flight speed, mission completion time, and airspace utilization. For example, efficiency indicators may include average aircraft flight speed, mission completion rate, and airspace utilization. Establishing efficiency indicators helps assess airspace operational efficiency and management capabilities. For instance, low efficiency indicators may lead to increased mission completion time for aircraft, reducing airspace operational efficiency; conversely, high efficiency indicators require greater technical support and management measures to ensure efficient airspace operation.

[0065] Once the aforementioned indicator system framework is established, it is possible to comprehensively evaluate airspace performance indicators such as capacity, safety, and efficiency, achieving an objective quantitative assessment of airspace performance. This quantitative assessment provides a scientific basis for airspace management and helps in formulating reasonable airspace management strategies and operational rules. The implementation of step S101 provides the basic data and evaluation framework for subsequent multi-source data fusion and comprehensive airspace performance measurement.

[0066] Step S102: Based on the airspace performance index system, extract the airspace operation dataset from the airspace operator data and the airspace management dataset from the airspace manager data. Define quality assessment dimensions, construct a judgment matrix using the scaling method to compare the quality assessment dimensions pairwise, determine the credibility weight of each quality assessment dimension, calculate the local weights of the airspace operation dataset and the airspace management dataset under each quality assessment dimension, determine the comprehensive credibility weight corresponding to each data source, and fuse the airspace operation dataset and the airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset.

[0067] Optionally, in this embodiment, in order to address the problem that the conflict of multiple source data caused by the difference in perspectives between operators and managers makes it impossible to achieve low-altitude airspace performance measurement, this step performs credibility assessment and conflict resolution on the multi-source data to obtain multi-source fused data, laying a data foundation for subsequent low-altitude airspace performance measurement.

[0068] Optionally, in this embodiment, after the “spatial performance index system” in step S101 is constructed, a unified quantitative standard is provided for the multi-source data (operator data, manager data) in this step, ensuring that data from different sources can be mapped to the same evaluation dimension (capacity, security, efficiency).

[0069] Specifically, a data acquisition system is used to extract the airspace operation dataset required for the "airspace performance indicator system" from airspace operator data. For operator data, the focus is on efficiency indicators, such as communication performance indicators (data link quality, communication latency, etc.), location reporting quality (location accuracy, update frequency, etc.), and timeliness prediction. From airspace manager data, the airspace management dataset required for the "airspace performance indicator system" is extracted. For manager data, the focus is on safety indicators, mainly including surveillance and perception capability assessment (equipment coverage, detection accuracy, etc.), unknown target identification capability, and anomaly handling capability.

[0070] After extracting data on the "airspace performance index system" from the data of operators and managers respectively, the credibility of these data was assessed.

[0071] Optionally, in this embodiment, multiple dimensions for data quality assessment are first defined, including data accuracy, completeness, timeliness, and consistency. These dimensions are used to assess the credibility of data from different sources. Among them:

[0072] Data accuracy refers to how closely the value of data approximates the true value. For example, the accuracy of a location report can be measured by its deviation from a known location.

[0073] Data integrity refers to the completeness of data, i.e., whether any data is missing. For example, does communication performance data include all the necessary parameters?

[0074] Data timeliness refers to the frequency and timeliness of data updates. For example, does the update frequency of location reports meet the requirements of airspace management?

[0075] Data consistency refers to the consistency of data across different sources and at different points in time. For example, whether different surveillance devices report the position of the same aircraft consistently.

[0076] Based on the four dimensions mentioned above, a scaling method is used to compare each quality assessment dimension pairwise, constructing a judgment matrix. The scaling method is a commonly used multi-criteria decision-making method that quantifies the importance of each dimension to construct a judgment matrix. Assume four quality assessment dimensions are defined: accuracy, completeness, timeliness, and consistency. Through data analysis, the relative importance of each dimension is determined. For example, accuracy is 1.5 times more important than completeness, completeness is 1.2 times more important than timeliness, and timeliness is 1.3 times more important than consistency. Based on these relative importances, a judgment matrix is ​​constructed. Using the eigenvalue method, the largest eigenvalue of the judgment matrix and its corresponding eigenvector are calculated, and the eigenvector is normalized to obtain the credibility weights of each dimension. These weights reflect the importance of each dimension in data quality assessment.

[0077] Example: Suppose that in low-altitude airspace, the weights of the four dimensions are: completeness (w1 = 0.2), timeliness (w2 = 0.25), consistency (w3 = 0.25), and accuracy (w4 = 0.3).

[0078] Next, for each data source extracted from the airspace operations dataset and the airspace management dataset, a sub-judgment matrix is ​​constructed under each evaluation dimension, and its local weight under that dimension is calculated. The local weight calculation quantifies the performance of each data source in each dimension to obtain the local weight of each data source.

[0079] Example: Suppose a data source for the airspace operations dataset has a performance rating of 0.8 in the accuracy dimension, 0.7 in the completeness dimension, 0.9 in the timeliness dimension, and 0.85 in the consistency dimension.

[0080] The calculation of the overall credibility weight is to quantify the overall credibility of each data source after comprehensively considering all quality assessment dimensions.

[0081] Example: Calculate the overall credibility weight based on the credibility weights of each dimension and the local weights corresponding to the data sources in the airspace operations dataset for each dimension:

[0082] W 运营 =0.8×0.3+0.7×0.2+0.9×0.25+0.85×0.25=0.8125

[0083] Similarly, calculate the overall credibility weight of each data source in the airspace management dataset.

[0084] Optionally, in this embodiment, after calculating the comprehensive credibility weight of each data source in the airspace operation dataset and the airspace management dataset, the multi-source data is integrated based on credibility. This process involves the handling of conflicting data.

[0085] Specifically, for multi-source data belonging to the same indicator (such as airspace capacity) in the airspace operations dataset and the airspace management dataset, the summation is performed according to the confidence weight:

[0086]

[0087] A time decay factor is introduced to increase the weight of long-term stable data sources (such as fixed radar) and decrease the weight of sudden abnormal data (such as temporary interference).

[0088] Furthermore, to address the inconsistency between multi-source data in the airspace operations dataset and the airspace management dataset, conflict resolution strategies are constructed. These conflict resolution strategies include, but are not limited to:

[0089] 1. Adaptive Strategy: For conflicting efficiency metrics, prioritize the use of operator data; for conflicting safety metrics, prioritize the use of manager data.

[0090] 2. Time Priority: Select the data version with the latest timestamp;

[0091] 3. Majority voting: When ≥3 independent data sources agree, the majority result is adopted;

[0092] 4. Prioritize credibility: Adopt data with high overall credibility;

[0093] 5. When a strategy cannot be chosen, a manual review process is triggered, and arbitration is conducted by combining historical data or third-party verification equipment.

[0094] Based on the aforementioned multi-source data fusion and conflict resolution strategies using comprehensive credibility weights, we ultimately obtain fused multi-source data. The comprehensive credibility weight calculation method can evaluate data quality and credibility in real time. This dynamic evaluation mechanism can promptly identify data quality issues, ensuring the real-time nature and reliability of airspace performance evaluation. This multi-source data fusion method considers not only the data source but also the data quality, which helps optimize airspace management strategies and improve airspace operational efficiency and security.

[0095] Step S103: Based on the multi-source fusion dataset, construct a dynamic simulation environment of airspace operation status. Based on aircraft performance parameters, airspace structural characteristics, and control rules, determine the corresponding dynamic capacity calculation model. Perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance. Perform conflict risk assessment on the dynamic simulation environment based on the set conflict detection model to determine the corresponding airspace safety performance. Establish a comprehensive service quality evaluation index to perform service quality analysis on the dynamic simulation environment to determine the corresponding airspace efficiency performance. Determine the corresponding comprehensive airspace performance based on the airspace capacity performance, the airspace safety performance, and the airspace efficiency performance.

[0096] Based on the performance index system framework constructed in step S101, step S102 extracts data related to airspace performance evaluation from the data of operators and managers respectively, and realizes multi-source fusion to obtain multi-source fused data based on data credibility evaluation and conflict resolution mechanism.

[0097] Optionally, in this embodiment, a comprehensive airspace performance measurement is conducted. This is achieved through a combination of digital measurement and actual flight measurement. Digital measurement uses multi-source fusion data to measure and evaluate the target airspace's performance, obtaining its capacity, efficiency, and safety performance. Actual flight measurement involves deploying calibration equipment and conducting measurements using standardized flight procedures, paying particular attention to the impact of different weather conditions and time periods on airspace performance. The accuracy of the digital evaluation method is verified by comparing the results of digital and actual measurements.

[0098] Optionally, in this embodiment, digital measurement first constructs a dynamic simulation environment of airspace operational status. The dynamic simulation environment is a virtual airspace operational environment used to simulate the operational status of aircraft within the airspace. By constructing a dynamic simulation environment, airspace performance can be quantitatively evaluated, potential problems in airspace operations can be predicted, and airspace management strategies can be optimized. The multi-source fusion dataset obtained in step S102 is input into the simulation environment. This data includes aircraft communication performance, position reporting, surveillance and perception capabilities, and unknown target identification capabilities, providing basic data support for the simulation.

[0099] Optionally, in this embodiment, after constructing the simulation environment, the target airspace performance of the simulation environment is evaluated using a dynamic capacity calculation model, a conflict detection model, and a comprehensive service quality evaluation index, respectively.

[0100] Specifically, the dynamic capacity calculation model is used to evaluate the capacity performance of airspace, that is, the number of aircraft and traffic that airspace can accommodate. This model considers factors such as the airspace's structural characteristics, operational rules, aircraft performance parameters, and meteorological conditions.

[0101] Specifically, the conflict risk assessment model is used to evaluate the safety performance of airspace, that is, the probability of conflict between aircraft within the airspace. This model considers factors such as aircraft flight paths, speeds, and position reporting accuracy. Parameters of the model, such as minimum safe distance and conflict warning time, are set according to the specific conditions of the airspace. These parameters can be adjusted according to actual needs to simulate different operational scenarios.

[0102] Specifically, the Service Quality Comprehensive Evaluation Index (SQCI) is used to assess the efficiency and performance of airspace, namely its operational efficiency and service quality. This index considers factors such as aircraft flight speed, mission completion time, and airspace utilization. Parameters for the index, such as average flight speed, mission completion rate, and airspace utilization, are set according to the specific conditions of the airspace. These parameters can be adjusted according to actual needs to simulate different operational scenarios.

[0103] Optionally, in this embodiment, the overall performance of the airspace is determined based on the evaluation results of capacity performance, safety performance, and efficiency performance. The overall performance indicators reflect the overall operational status of the airspace, providing a comprehensive evaluation result for airspace management. Through comprehensive performance evaluation, the operational status of the airspace can be fully assessed, and its performance in terms of capacity, safety, and efficiency can be understood.

[0104] This step involves constructing a dynamic simulation environment and establishing a dynamic capacity calculation model, a conflict risk assessment model, and a comprehensive service quality evaluation index. This allows for a comprehensive evaluation of airspace performance indicators such as capacity, safety, and efficiency, achieving a unified quantitative assessment of airspace performance. Through this comprehensive performance evaluation, potential problems in airspace operation can be identified, such as insufficient capacity, high safety risks, and low efficiency. Subsequent optimization of airspace structure, safety strategies, and operational efficiency can further improve the overall operational efficiency and safety of the airspace.

[0105] This example demonstrates how this embodiment constructs a standard framework for airspace performance evaluation, collects corresponding datasets from operators and managers based on the required data, performs multi-source data fusion based on data credibility, and generates a simulation environment based on the multi-source fused data to achieve digital airspace performance evaluation.

[0106] As described above, the low-altitude airspace performance measurement method provided in this application can improve the efficiency of low-altitude airspace management by establishing an airspace performance index system; extracting airspace operation datasets and airspace management datasets based on the airspace performance index system; defining quality assessment dimensions; constructing a judgment matrix using a scaling method to evaluate the credibility weights of each quality assessment dimension; calculating the comprehensive credibility weights of each data source under each quality assessment dimension; fusing the airspace operation dataset and airspace management dataset according to the comprehensive credibility weights; constructing a dynamic airspace simulation environment based on the multi-source fusion dataset; calculating airspace capacity performance based on a dynamic capacity calculation model and airspace safety performance based on a conflict detection model in the simulation environment; establishing a comprehensive service quality evaluation index to evaluate airspace efficiency performance; and determining the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance.

[0107] In one embodiment of the low-altitude airspace performance measurement method of this application, see [link to relevant documentation]. Figure 2 It can also specifically include the following:

[0108] Step S201: Define the integrity dimension, check the missing data field rate, and perform an integrity assessment based on the missing data field rate;

[0109] Step S202: Define the timeliness dimension and calculate the timeliness decay coefficient based on the delay between the data generation time and the evaluation time to conduct timeliness evaluation;

[0110] Step S203: Define the consistency dimension and perform consistency assessment by detecting outlier data through cross-source comparison;

[0111] Step S204: Define the accuracy dimension and evaluate the accuracy based on the comparison results between the quantitative indicators and the preset standards.

[0112] Optionally, in this embodiment, integrity refers to the completeness of the data, i.e., whether the data is missing. In airspace management, integrity assessment mainly focuses on whether the data contains all the necessary information.

[0113] The method for integrity assessment involves defining data integrity rules based on business needs. For example, it might stipulate that each location report must include fields such as timestamp, latitude / longitude, and altitude. Data validation tools are then used to verify whether the data meets these integrity rules. These tools check the location report data to ensure that each record contains the timestamp, latitude / longitude, and altitude fields. If a record is found to be missing the altitude field, that record is considered incomplete.

[0114] Integrity metrics: Define integrity assessment metrics, such as integrity percentage.

[0115] Completeness percentage = (Number of complete records / Total number of records) × 100%.

[0116] Optionally, in this embodiment, timeliness refers to the frequency and timeliness of data updates. In airspace management, timeliness assessment mainly focuses on whether the data can reflect the operational status of the airspace in a timely manner.

[0117] The method for assessing timeliness involves calculating the frequency of data updates, specifically the number of times data is updated per unit of time. The timestamps of the data are also checked to ensure its timeliness. For example, checking whether the timestamps of location report data fall within the specified time frame.

[0118] Define timeliness assessment metrics, such as the percentage of timeliness decay.

[0119] Timeliness percentage = (Number of records within the specified time range / Total number of records) × 100%.

[0120] Optionally, in this embodiment, consistency refers to the consistency of data across different sources and at different points in time. In airspace management, consistency assessment primarily focuses on whether the measurement results of the same target from different data sources are consistent.

[0121] The consistency assessment method involves comparing data from different sources to check their consistency. For example, comparing radar data and ADS-B data to see if their position reports for the same aircraft are consistent. A reasonable deviation threshold is set; if the deviation is less than the threshold, the data is considered consistent; otherwise, the data is considered inconsistent.

[0122] Preferably, for time series data, time series analysis is performed on data of the same target at different time points to check its consistency. The proportion of inconsistent data in the time series is calculated; the lower the proportion, the higher the data consistency.

[0123] Example: Perform time series analysis on the position report data of an aircraft at different time points to check whether its position changes are consistent with its flight trajectory.

[0124] Optionally, in this embodiment, accuracy refers to how close the data value is to the true value. In airspace management, accuracy assessment mainly focuses on whether the data truly reflects the aircraft's status and the airspace's operational status.

[0125] The accuracy assessment method involves selecting known, accurate data as a benchmark, such as high-precision GPS data or calibrated radar data. The data to be evaluated is compared with the benchmark data, and the deviation is calculated. For example, for location report data, the deviation from high-precision GPS data is calculated. A reasonable deviation threshold is then set. If the deviation is less than the threshold, the data is considered accurate; otherwise, the data is inaccurate.

[0126] Through step S202, this embodiment obtains four dimensions for data credibility evaluation. By comprehensively evaluating and applying the data credibility based on these four dimensions, high-credibility data is used to measure low-altitude airspace performance, laying a solid data foundation for the accuracy of the measurement results.

[0127] In one embodiment of the low-altitude airspace performance measurement method of this application, see [link to relevant documentation]. Figure 3 It can also specifically include the following:

[0128] Step S301: Under each quality assessment dimension, construct a sub-judgment matrix for each data source in the airspace operation dataset and the airspace management dataset, calculate local weights, and determine the corresponding local weights;

[0129] Step S302: Perform a comprehensive weighted summation of the credibility weights of each quality assessment dimension and the local weights to determine the comprehensive credibility weights corresponding to each data source.

[0130] Optionally, in this embodiment, for each data source extracted from the airspace operation dataset and the airspace management dataset, a sub-judgment matrix is ​​constructed under each evaluation dimension, and its local weight under that dimension is calculated. The local weight calculation quantifies the performance of each data source in each dimension to obtain the local weight of each data source.

[0131] Example: Suppose a data source for the airspace operations dataset has a performance rating of 0.8 in the accuracy dimension, 0.7 in the completeness dimension, 0.9 in the timeliness dimension, and 0.85 in the consistency dimension.

[0132] The calculation of the overall credibility weight is to quantify the overall credibility of each data source after comprehensively considering all quality assessment dimensions.

[0133] Example: Calculate the overall credibility weight based on the credibility weights of each dimension and the local weights corresponding to the data sources in the airspace operations dataset for each dimension:

[0134] Woperation = 0.8 × 0.3 + 0.7 × 0.2 + 0.9 × 0.25 + 0.85 × 0.25 = 0.8125

[0135] Similarly, calculate the overall credibility weight of each data source in the airspace management dataset.

[0136] Through step S302, this embodiment realizes the calculation of the comprehensive credibility weight of each data source in the airspace operation dataset and airspace management dataset, laying the data foundation for subsequent multi-source data fusion.

[0137] In one embodiment of the low-altitude airspace performance measurement method of this application, it may further include the following:

[0138] Step S401: Collect aircraft performance parameters and normalize them, determine the corresponding normalized parameters, extract airspace structure features to construct a topology graph, determine the corresponding airspace structure parameters, analyze control rules, determine the corresponding constraint parameters, and establish a dynamic capacity calculation model for airspace units based on the normalized parameters, the airspace structure parameters, and the constraint parameters. The dynamic capacity calculation model is used to quantify the node throughput capacity based on network flow theory.

[0139] Step S402: Using discrete event simulation technology, simulate peak-hour capacity bottlenecks based on the dynamic capacity calculation model and traffic data in the dynamic simulation environment, and determine the corresponding airspace capacity performance.

[0140] Optionally, in this embodiment, performance parameters are collected from the aircraft's flight management system, communication equipment, and navigation equipment. These parameters include flight speed, rate of climb, rate of descent, fuel consumption rate, and maximum range. Since the performance parameters of different aircraft vary significantly, these parameters need to be normalized for easier subsequent calculations and comparisons. Through normalization, normalized values ​​for each aircraft's performance parameters are obtained. These normalized values ​​serve as the basis for subsequent calculations.

[0141] Optionally, in this embodiment, the structural characteristics of the airspace are analyzed, including flight path distribution, flight altitude layers, and airspace boundaries. These characteristics reflect the airspace's operating environment and management requirements. Based on the extracted airspace structural characteristics, a topological graph of the airspace is constructed. The topological graph represents the airspace structure in the form of nodes and edges, where nodes represent key locations (such as airports and waypoints), and edges represent flight paths or routes. Through the topological graph, airspace structural parameters are determined, such as the distance between nodes and the capacity of flight paths. These parameters provide basic data for the dynamic capacity calculation model of airspace units.

[0142] Optionally, in this embodiment, control rules are parsed from airspace management rules and aircraft operation rules. These rules include flight interval requirements, communication requirements, weather condition restrictions, etc. Based on the parsed control rules, constraining parameters for airspace operation are determined, such as minimum safe intervals and communication coverage. These parameters provide constraints for the dynamic capacity calculation model of airspace units.

[0143] Optionally, in this embodiment, a dynamic capacity calculation model for airspace units is established based on normalized parameters, airspace structure parameters, and constraint parameters. This model is based on network flow theory and is used to quantify the throughput capacity of nodes. Network flow theory is a mathematical theory used to analyze and optimize traffic allocation in networks. In airspace capacity calculation, nodes represent airspace units, edges represent flight routes or paths, and traffic represents aircraft traffic. Through network flow theory, the throughput capacity of each node is calculated, i.e., the aircraft traffic that each airspace unit can accommodate. Throughput capacity is jointly influenced by aircraft performance, airspace structure, and control rules.

[0144] The dynamic capacity calculation model employs discrete event simulation technology to model airspace operational status. Based on kinematic equations (BADA model), it simulates aircraft dynamic behavior according to normalized aircraft performance parameters, while considering the speed-altitude profiles and acceleration / deceleration characteristics of different aircraft types. A spatiotemporal network diagram is constructed based on airspace structure parameters, and simulations are performed during peak airspace operation periods to assess route capacity bottlenecks. Capacity constraints are applied based on air traffic control rules, generating a visualized dynamic capacity limitation heatmap for each airspace region. The capacity heatmap is automatically updated when air traffic control rules change (e.g., by reducing separation standards).

[0145] Through step S402, this embodiment successfully evaluates the capacity performance of the target airspace using a dynamic capacity calculation model. The capacity performance evaluation results can support airspace management decisions, help managers formulate reasonable management strategies and operating rules, and ensure the safe operation and efficient management of the airspace.

[0146] In one embodiment of the low-altitude airspace performance measurement method of this application, it may further include the following:

[0147] Step S501: Construct a four-dimensional conflict detection model, and calculate the probability of potential conflicts occurring in the dynamic simulation environment based on the four-dimensional conflict detection model;

[0148] Step S502: Introduce a conflict risk assessment algorithm to conduct differentiated risk level assessments based on the probability of potential conflicts and aircraft type, and determine the corresponding airspace safety performance.

[0149] Optionally, in this embodiment, the four-dimensional conflict detection model is an algorithm used to detect potential conflicts in the airspace. This model considers not only the three-dimensional spatial position of aircraft (longitude, latitude, and altitude) but also introduces a time dimension, thus enabling more accurate prediction of potential conflicts between aircraft. In a dynamic simulation environment, information such as the aircraft's flight path, speed, and acceleration is updated in real time, and the four-dimensional conflict detection model uses this information to calculate the probability of potential conflicts occurring.

[0150] Specifically, the model predicts the spatial relationship between aircraft in the future by calculating their relative positions and speeds. If the distance between two aircraft at a future moment is less than a preset safe distance threshold, it is considered a potential conflict. The model then calculates the probability of the potential conflict by analyzing factors such as the aircraft's flight paths, speed changes, and position reporting errors. For example, if two aircraft have similar flight paths but different speeds, the model calculates the probability of them meeting within a specific time window.

[0151] Optionally, in this embodiment, the conflict risk assessment algorithm performs differentiated risk level assessments based on the conflict probability and aircraft type to determine the specific risk level of each potential conflict. Different types of aircraft (such as small drones, helicopters, light aircraft, etc.) have different flight characteristics and safety requirements. For example, small drones have slower flight speeds but may be more numerous; helicopters fly at lower altitudes but have greater payload capacity.

[0152] Based on the type of aircraft and the probability of potential conflict, the risk level is divided into three levels: low, medium, and high. For example, for small drones, even if the probability of potential conflict is high, the risk level may be rated as medium due to their slow flight speed; while for helicopters, due to their low flight altitude and large payload capacity, even if the probability of potential conflict is low, the risk level may be rated as high.

[0153] Through step S502, this embodiment successfully achieves risk calculation based on the conflict detection model and conflict risk assessment algorithm, assesses the safety performance of airspace, and enables airspace managers to handle potential conflicts more efficiently and optimize airspace management strategies.

[0154] In one embodiment of the low-altitude airspace performance measurement method of this application, it may further include the following:

[0155] Step S601: Construct a grid reference space based on preset target airspace characteristics and preset aircraft performance characteristics. The grid reference space is used to unify longitude and latitude standards.

[0156] Step S602: Construct a four-dimensional conflict detection model based on the grid reference space, altitude transformation matrix, and time synchronization network. The four-dimensional conflict detection model is used to perform conflict detection based on the aircraft's predicted trajectory. The dimensions of the aircraft's predicted trajectory include longitude, latitude, altitude, and time.

[0157] The construction process of the four-dimensional conflict detection model.

[0158] Optionally, in this embodiment, the grid reference space is a virtual three-dimensional space used to unify the longitude, latitude, and altitude standards within the airspace. By constructing the grid reference space, the operational data of all aircraft within the airspace can be unified into a standard coordinate system.

[0159] Specifically, target airspace characteristics include the airspace's range, type, and operational rules. For example, urban low-altitude airspace may have specific altitude ranges (such as below 100 meters) and specific operational rules (such as drone delivery rules).

[0160] Aircraft performance characteristics include flight speed, altitude, communication capabilities, and navigation capabilities. For example, a small drone might have a flight speed of 10-20 meters per second, a flight altitude below 100 meters, and a communication link coverage range of 5 kilometers.

[0161] Based on the target airspace's extent and the aircraft's performance characteristics, the airspace is divided into multiple three-dimensional grids. Each grid has a fixed range of longitude, latitude, and altitude. For example, urban low-altitude airspace can be divided into 100m × 100m × 10m grids. Using this grid-based reference space, all aircraft operational data are unified into a standardized coordinate system, facilitating subsequent conflict detection and performance evaluation.

[0162] Optionally, in this embodiment, the four-dimensional conflict detection model is a model used to detect potential conflicts between aircraft. This model considers not only the three-dimensional spatial position of the aircraft (longitude, latitude, and altitude), but also the time dimension, i.e., the predicted trajectory of the aircraft.

[0163] Based on the grid reference space constructed in step S601, an altitude transformation matrix and a time synchronization network are defined. The altitude transformation matrix is ​​used to convert the aircraft's altitude data into a unified altitude standard; the time synchronization network is used to ensure that the time data of all aircraft are synchronized. On this basis, a four-dimensional conflict detection model is constructed.

[0164] When receiving UAV trajectory data from multi-source fusion data, a trajectory simulation algorithm is used to obtain the predicted trajectory of the aircraft. The predicted trajectory includes four dimensions: longitude, latitude, altitude, and time. The four-dimensional conflict detection model calculates the spatial distance and time interval between aircraft using geometric methods to determine whether a conflict exists; it also calculates the probability of conflict between aircraft using probabilistic methods.

[0165] Through step S602, this embodiment successfully predicted the potential conflict and conflict probability of the target airspace by constructing a four-dimensional conflict detection model, laying the foundation for subsequent evaluation of the target airspace security performance.

[0166] In one embodiment of the low-altitude airspace performance measurement method of this application, it may further include the following:

[0167] Step S701: Train an initial model based on the performance data of the comprehensive airspace performance, and determine the corresponding performance change trend prediction model;

[0168] Step S702: Track the target airspace operation data in real time, perform comprehensive airspace performance prediction on the target airspace based on the performance change trend prediction model, determine whether performance degradation has occurred, and if so, activate the early warning mechanism and dynamically adjust the airspace operation strategy.

[0169] Optionally, in this embodiment, a dynamic performance monitoring mechanism is established to track airspace performance changes in real time. Monitoring content includes changes in equipment performance (such as equipment failure, performance degradation, etc.), environmental influencing factors (such as weather changes, electromagnetic interference, etc.), and changes in operating status (such as traffic flow changes, event occurrences, etc.). A data-driven approach is adopted, using historical data analysis to establish a performance change trend prediction model. When performance degradation is detected, an early warning mechanism is promptly activated, and corresponding management measures are taken. Simultaneously, through continuous data accumulation, the evaluation model is continuously optimized to improve the accuracy of the evaluation.

[0170] Specifically, based on comprehensive airspace performance data (capacity performance, safety performance, and efficiency performance), features related to changes in airspace performance are selected. These include meteorological conditions, airspace type, aircraft traffic, and equipment performance. Correlation analysis and other methods are used to identify features that significantly impact changes in airspace performance. Machine learning algorithms are then used to train the selected features and comprehensive airspace performance data. The resulting performance change trend prediction model can predict the changing trend of comprehensive airspace performance based on real-time data.

[0171] Real-time tracking of operational data in the target airspace, including aircraft flight data, communication data, and surveillance data. This data is collected in real-time through ground monitoring and communication equipment and preprocessed to ensure its timeliness and accuracy. The real-time operational data is then input into a performance trend prediction model, which predicts the overall performance of the target airspace based on the input data. The prediction results include trends in airspace capacity performance, safety performance, and efficiency performance.

[0172] Based on the forecast results, determine whether the overall airspace performance has declined. Set a threshold for performance decline; for example, consider a decline in airspace performance to have occurred when the predicted overall performance index falls below a certain set value. If a decline in airspace performance is determined, activate the early warning mechanism. The early warning mechanism may include sending alert messages to controllers and displaying warning signals in the airspace management system to remind controllers to take timely measures.

[0173] Real-time tracking and performance prediction enable early detection of airspace performance degradation trends, facilitating timely activation of early warning mechanisms. This allows airspace managers to take preventative measures in advance, avoiding potential safety risks and operational efficiency issues.

[0174] Through step S702, this embodiment successfully provides decision support based on a performance change trend prediction model, making airspace managers' decisions more scientific and reasonable.

[0175] To improve the efficiency of low-altitude airspace management, this application provides an embodiment of a low-altitude airspace performance measurement device for implementing all or part of the aforementioned low-altitude airspace performance measurement method. See [link to embodiment]. Figure 2 The low-altitude airspace performance measurement device specifically includes the following components:

[0176] The airspace performance index system determination module 10 is used to determine the basic attributes of airspace according to airspace classification requirements, evaluate the distribution of communication and navigation facilities in airspace, and establish an airspace performance index system based on the basic attributes of airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index.

[0177] The multi-source airspace performance data fusion module 20 is used to extract airspace operation datasets from airspace operator data and airspace management datasets from airspace manager data based on the airspace performance index system. It defines quality assessment dimensions, constructs a judgment matrix using scaling to compare each quality assessment dimension pairwise, determines the credibility weight of each quality assessment dimension, calculates local weights for the airspace operation dataset and the airspace management dataset under each quality assessment dimension, determines the comprehensive credibility weight corresponding to each data source, and fuses the airspace operation dataset and the airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset.

[0178] The airspace comprehensive performance determination module 30 is used to construct a dynamic simulation environment of airspace operation status based on the multi-source fusion dataset, determine the corresponding dynamic capacity calculation model based on aircraft performance parameters, airspace structural characteristics and control rules, perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance, conduct conflict risk assessment on the dynamic simulation environment based on the set conflict detection model to determine the corresponding airspace safety performance, establish a comprehensive service quality evaluation index to conduct service quality analysis on the dynamic simulation environment to determine the corresponding airspace efficiency performance, and determine the corresponding airspace comprehensive performance based on the airspace capacity performance, the airspace safety performance and the airspace efficiency performance.

[0179] As described above, the low-altitude airspace performance measurement device provided in this application embodiment can improve the efficiency of low-altitude airspace management by establishing an airspace performance index system; extracting airspace operation datasets and airspace management datasets based on the airspace performance index system; defining quality assessment dimensions; constructing a judgment matrix using a scaling method to evaluate the credibility weight of each quality assessment dimension; calculating the comprehensive credibility weight of each data source under each quality assessment dimension; fusing the airspace operation dataset and airspace management dataset according to the comprehensive credibility weight; constructing a dynamic airspace simulation environment based on the multi-source fusion dataset; calculating airspace capacity performance based on a dynamic capacity calculation model and airspace safety performance based on a conflict detection model in the simulation environment; establishing a comprehensive service quality evaluation index to evaluate airspace efficiency performance; and determining the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance.

[0180] From a hardware perspective, in order to improve the efficiency of low-altitude airspace management, this application provides an embodiment of an electronic device for implementing all or part of the aforementioned low-altitude airspace performance measurement method. The electronic device specifically includes the following components:

[0181] The system comprises a processor, memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to realize information transmission between the low-altitude airspace performance measurement method and core business systems, user terminals, and related databases and other related devices; the logic controller can be a desktop computer, tablet computer, or mobile terminal, etc., and this embodiment is not limited to these. In this embodiment, the logic controller can be implemented with reference to the embodiments of the low-altitude airspace performance measurement method in the present embodiment, and the contents of the embodiments of the low-altitude airspace performance measurement method are incorporated herein, and repeated details will not be described again.

[0182] It is understood that the user terminal may include smartphones, tablet computers, network set-top boxes, portable computers, desktop computers, personal digital assistants (PDAs), in-vehicle devices, smart wearable devices, etc. Among these, the smart wearable devices may include smart glasses, smartwatches, smart bracelets, etc.

[0183] In practical applications, some aspects of the low-altitude airspace performance measurement method can be executed on the electronic device side as described above, or all operations can be completed in the client device. The choice can be made based on the processing power of the client device and the limitations of the user's usage scenario. This application does not impose any limitations on this. If all operations are completed in the client device, the client device may further include a processor.

[0184] The aforementioned client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission. The server may include a server on the task scheduling center side; in other implementation scenarios, it may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, a server cluster consisting of multiple servers, or a distributed server structure.

[0185] Figure 3 This is a schematic block diagram illustrating the system configuration of the electronic device 9600 according to an embodiment of this application. Figure 3 As shown, the electronic device 9600 may include a central processing unit 9100 and a memory 9140; the memory 9140 is coupled to the central processing unit 9100. It is worth noting that... Figure 3 This is an example; other types of structures can also be used to supplement or replace this structure to achieve telecommunications functions or other functions.

[0186] In one embodiment, the low-altitude airspace performance measurement method function can be integrated into the central processing unit 9100. The central processing unit 9100 can be configured to perform the following control:

[0187] Step S101: Determine the basic attributes of the airspace according to the airspace classification requirements, evaluate the distribution of communication and navigation facilities in the airspace, and establish an airspace performance index system based on the basic attributes of the airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index.

[0188] Step S102: Based on the airspace performance index system, extract the airspace operation dataset from the airspace operator data and the airspace management dataset from the airspace manager data. Define quality assessment dimensions, construct a judgment matrix using the scaling method to compare the quality assessment dimensions pairwise, determine the credibility weight of each quality assessment dimension, calculate the local weights of the airspace operation dataset and the airspace management dataset under each quality assessment dimension, determine the comprehensive credibility weight corresponding to each data source, and fuse the airspace operation dataset and the airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset.

[0189] Step S103: Based on the multi-source fusion dataset, construct a dynamic simulation environment of airspace operation status. Based on aircraft performance parameters, airspace structural characteristics, and control rules, determine the corresponding dynamic capacity calculation model. Perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance. Perform conflict risk assessment on the dynamic simulation environment based on the set conflict detection model to determine the corresponding airspace safety performance. Establish a comprehensive service quality evaluation index to perform service quality analysis on the dynamic simulation environment to determine the corresponding airspace efficiency performance. Determine the corresponding comprehensive airspace performance based on the airspace capacity performance, the airspace safety performance, and the airspace efficiency performance.

[0190] As described above, the electronic device provided in this application establishes an airspace performance index system; extracts airspace operation datasets and airspace management datasets based on the airspace performance index system, defines quality assessment dimensions, constructs a judgment matrix using a scaling method to evaluate the credibility weights of each quality assessment dimension, calculates the comprehensive credibility weights of each data source under each quality assessment dimension, merges the airspace operation dataset and airspace management dataset according to the comprehensive credibility weights, and determines the corresponding multi-source fused dataset; based on the multi-source fused dataset, constructs an airspace dynamic simulation environment, calculates airspace capacity performance based on a dynamic capacity calculation model, calculates airspace safety performance based on a conflict detection model, establishes a comprehensive service quality evaluation index to evaluate airspace efficiency performance, and determines the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance, thereby improving the efficiency of low-altitude airspace management.

[0191] In another embodiment, the low-altitude airspace performance measurement method can be configured separately from the central processing unit 9100. For example, the low-altitude airspace performance measurement method can be configured as a chip connected to the central processing unit 9100, and the function of the low-altitude airspace performance measurement method can be implemented through the control of the central processing unit.

[0192] like Figure 3 As shown, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily need to include these components. Figure 3 All components shown; in addition, the electronic device 9600 may also include Figure 3 For components not shown, please refer to existing technologies.

[0193] like Figure 3 As shown, the central processing unit 9100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device, which receives inputs and controls the operation of various components of the electronic device 9600.

[0194] The memory 9140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 9100 may execute the program stored in the memory 9140 to perform information storage or processing, etc.

[0195] Input unit 9120 provides input to central processing unit 9100. Input unit 9120 may be, for example, a keypad or touch input device. Power supply 9170 provides power to electronic device 9600. Display 9160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0196] The memory 9140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 9140 can also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142 for storing application programs and function programs or processes for executing the operation of the electronic device 9600 via the central processing unit 9100.

[0197] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0198] The communication module 9110 is a transmitter / receiver that sends and receives signals via the antenna 9111. The communication module 9110 is coupled to the central processing unit 9100 to provide input signals and receive output signals, which is the same as in a conventional mobile communication terminal.

[0199] Based on different communication technologies, multiple communication modules 9110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby realizing typical telecommunications functions. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. Furthermore, the audio processor 9130 is also coupled to a central processing unit 9100, enabling on-device recording via the microphone 9132 and on-device playback of stored sound via the speaker 9131.

[0200] Embodiments of this application also provide a computer-readable storage medium capable of implementing all steps of the low-altitude airspace performance measurement method with a server or client as the execution subject in the above embodiments. The computer-readable storage medium stores a computer program that, when executed by a processor, implements all steps of the low-altitude airspace performance measurement method with a server or client as the execution subject in the above embodiments. For example, when the processor executes the computer program, it implements the following steps:

[0201] Step S101: Determine the basic attributes of the airspace according to the airspace classification requirements, evaluate the distribution of communication and navigation facilities in the airspace, and establish an airspace performance index system based on the basic attributes of the airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index.

[0202] Step S102: Based on the airspace performance index system, extract the airspace operation dataset from the airspace operator data and the airspace management dataset from the airspace manager data. Define quality assessment dimensions, construct a judgment matrix using the scaling method to compare the quality assessment dimensions pairwise, determine the credibility weight of each quality assessment dimension, calculate the local weights of the airspace operation dataset and the airspace management dataset under each quality assessment dimension, determine the comprehensive credibility weight corresponding to each data source, and fuse the airspace operation dataset and the airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset.

[0203] Step S103: Based on the multi-source fusion dataset, construct a dynamic simulation environment of airspace operation status. Based on aircraft performance parameters, airspace structural characteristics, and control rules, determine the corresponding dynamic capacity calculation model. Perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance. Perform conflict risk assessment on the dynamic simulation environment based on the set conflict detection model to determine the corresponding airspace safety performance. Establish a comprehensive service quality evaluation index to perform service quality analysis on the dynamic simulation environment to determine the corresponding airspace efficiency performance. Determine the corresponding comprehensive airspace performance based on the airspace capacity performance, the airspace safety performance, and the airspace efficiency performance.

[0204] As described above, the computer-readable storage medium provided in this application establishes an airspace performance index system; extracts airspace operation datasets and airspace management datasets based on the airspace performance index system, defines quality assessment dimensions, constructs a judgment matrix using a scaling method to evaluate the credibility weights of each quality assessment dimension, calculates the comprehensive credibility weights of each data source under each quality assessment dimension, merges the airspace operation dataset and airspace management dataset according to the comprehensive credibility weights, and determines the corresponding multi-source fused dataset; based on the multi-source fused dataset, constructs an airspace dynamic simulation environment, calculates airspace capacity performance based on a dynamic capacity calculation model, calculates airspace safety performance based on a conflict detection model, establishes a comprehensive service quality evaluation index to evaluate airspace efficiency performance, and determines the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance, thereby improving the efficiency of low-altitude airspace management.

[0205] Embodiments of this application also provide a computer program product capable of implementing all steps of the low-altitude airspace performance measurement method with the execution subject being a server or client in the above embodiments. When executed by a processor, this computer program / instruction implements the steps of the low-altitude airspace performance measurement method. For example, the computer program / instruction implements the following steps:

[0206] Step S101: Determine the basic attributes of the airspace according to the airspace classification requirements, evaluate the distribution of communication and navigation facilities in the airspace, and establish an airspace performance index system based on the basic attributes of the airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index.

[0207] Step S102: Based on the airspace performance index system, extract the airspace operation dataset from the airspace operator data and the airspace management dataset from the airspace manager data. Define quality assessment dimensions, construct a judgment matrix using the scaling method to compare the quality assessment dimensions pairwise, determine the credibility weight of each quality assessment dimension, calculate the local weights of the airspace operation dataset and the airspace management dataset under each quality assessment dimension, determine the comprehensive credibility weight corresponding to each data source, and fuse the airspace operation dataset and the airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset.

[0208] Step S103: Based on the multi-source fusion dataset, construct a dynamic simulation environment of airspace operation status. Based on aircraft performance parameters, airspace structural characteristics, and control rules, determine the corresponding dynamic capacity calculation model. Perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance. Perform conflict risk assessment on the dynamic simulation environment based on the set conflict detection model to determine the corresponding airspace safety performance. Establish a comprehensive service quality evaluation index to perform service quality analysis on the dynamic simulation environment to determine the corresponding airspace efficiency performance. Determine the corresponding comprehensive airspace performance based on the airspace capacity performance, the airspace safety performance, and the airspace efficiency performance.

[0209] As described above, the computer program product provided in this application establishes an airspace performance index system; extracts airspace operation datasets and airspace management datasets based on the airspace performance index system, defines quality assessment dimensions, constructs a judgment matrix using a scaling method to evaluate the credibility weights of each quality assessment dimension, calculates the comprehensive credibility weights of each data source under each quality assessment dimension, merges the airspace operation dataset and airspace management dataset according to the comprehensive credibility weights, and determines the corresponding multi-source fused dataset; based on the multi-source fused dataset, constructs an airspace dynamic simulation environment, calculates airspace capacity performance based on a dynamic capacity calculation model, calculates airspace safety performance based on a conflict detection model, establishes a comprehensive service quality evaluation index to evaluate airspace efficiency performance, and determines the comprehensive airspace performance by combining capacity performance, safety performance, and efficiency performance, thereby improving the efficiency of low-altitude airspace management.

[0210] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0211] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0212] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0213] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0214] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for measuring low-altitude airspace performance, characterized in that, The method includes: Based on airspace classification requirements, the basic attributes of airspace are determined, the distribution of communication and navigation facilities within the airspace is assessed, and an airspace performance index system is established based on the basic attributes of airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index, and efficiency index. Based on the aforementioned airspace performance index system, an airspace operation dataset is extracted from airspace operator data, and an airspace management dataset is extracted from airspace manager data. Quality assessment dimensions are defined, and a scaling method is used to construct a judgment matrix to compare each quality assessment dimension pairwise, determining the credibility weight of each dimension. Local weight calculations are performed on the airspace operation dataset and the airspace management dataset under each quality assessment dimension to determine the comprehensive credibility weight corresponding to each data source. Based on the comprehensive credibility weight, the airspace operation dataset and the airspace management dataset are fused to determine the corresponding multi-source fused dataset. Based on the multi-source fusion dataset, a dynamic simulation environment for airspace operation is constructed. According to aircraft performance parameters, airspace structural characteristics, and control rules, a corresponding dynamic capacity calculation model is determined. The dynamic capacity calculation model is used to calculate the capacity of the dynamic simulation environment and determine the corresponding airspace capacity performance. A conflict risk assessment is performed on the dynamic simulation environment based on a defined conflict detection model to determine the corresponding airspace safety performance. A comprehensive service quality evaluation index is established to analyze the service quality of the dynamic simulation environment and determine the corresponding airspace efficiency performance. Finally, the corresponding comprehensive airspace performance is determined based on the airspace capacity performance, airspace safety performance, and airspace efficiency performance.

2. The method for measuring low-altitude airspace performance according to claim 1, characterized in that, The defined dimensions for quality assessment include: Define the integrity dimension, check the missing data field rate, and perform an integrity assessment based on the missing data field rate. Define a timeliness dimension and calculate a timeliness decay coefficient based on the delay between data generation time and evaluation time to conduct timeliness assessment; Define a consistency dimension and use cross-source comparison methods to detect outlier data for consistency assessment. Define the accuracy dimension and evaluate the accuracy based on the comparison results between quantitative indicators and preset standards.

3. The method for measuring low-altitude airspace performance according to claim 1, characterized in that, The step of calculating local weights for the airspace operation dataset and the airspace management dataset under each of the aforementioned quality assessment dimensions to determine the comprehensive credibility weight corresponding to each data source includes: Under each quality assessment dimension, a sub-judgment matrix is ​​constructed for each data source in the airspace operation dataset and the airspace management dataset, and local weights are calculated to determine the corresponding local weights. The overall credibility weight corresponding to each data source is determined by summing the credibility weights of each quality assessment dimension with the local weights.

4. The method for measuring low-altitude airspace performance according to claim 1, characterized in that, The process involves determining a corresponding dynamic capacity calculation model based on aircraft performance parameters, airspace structure characteristics, and control rules; performing capacity calculations on the dynamic simulation environment based on the dynamic capacity calculation model; and determining the corresponding airspace capacity performance, including: The aircraft performance parameters are collected and normalized to determine the corresponding normalized parameters. Airspace structure features are extracted to construct a topology graph and determine the corresponding airspace structure parameters. Control rules are analyzed to determine the corresponding constraint parameters. Based on the normalized parameters, the airspace structure parameters, and the constraint parameters, a dynamic capacity calculation model for airspace units is established. The dynamic capacity calculation model is used to quantify the node throughput capacity according to network flow theory. Discrete event simulation technology is used to simulate peak-hour capacity bottlenecks based on the dynamic capacity calculation model and traffic data in the dynamic simulation environment, and to determine the corresponding airspace capacity performance.

5. The method for measuring low-altitude airspace performance according to claim 1, characterized in that, The step of conducting a conflict risk assessment of the dynamic simulation environment based on a predefined conflict detection model to determine the corresponding airspace security performance includes: A four-dimensional conflict detection model is constructed, and the probability of potential conflicts occurring in the dynamic simulation environment is calculated based on the four-dimensional conflict detection model. A conflict risk assessment algorithm is introduced to conduct differentiated risk level assessments based on the probability of potential conflicts and aircraft type, thereby determining the corresponding airspace safety performance.

6. The method for measuring low-altitude airspace performance according to claim 5, characterized in that, The construction of the four-dimensional conflict detection model includes: A grid reference space is constructed based on preset target airspace characteristics and preset aircraft performance characteristics. The grid reference space is used to unify longitude and latitude standards. A four-dimensional conflict detection model is constructed based on the grid reference space, altitude transformation matrix, and time synchronization network. The four-dimensional conflict detection model is used to detect conflicts based on the predicted trajectory of the aircraft. The dimensions of the predicted trajectory include longitude, latitude, altitude, and time.

7. The method for measuring low-altitude airspace performance according to claim 1, characterized in that, After determining the corresponding comprehensive airspace performance based on the airspace capacity performance, the airspace security performance, and the airspace efficiency performance, the process includes: Based on the performance data of the comprehensive airspace performance, an initial model is trained, and a corresponding performance change trend prediction model is determined. Real-time tracking of target airspace operation data; based on the performance change trend prediction model, comprehensive airspace performance prediction for the target airspace is performed to determine whether performance degradation has occurred. If so, an early warning mechanism is activated, and airspace operation strategies are dynamically adjusted.

8. A low-altitude airspace performance measurement device, characterized in that, The device includes: The airspace performance index system determination module is used to determine the basic attributes of airspace according to airspace classification requirements, evaluate the distribution of communication and navigation facilities in airspace, and establish an airspace performance index system based on the basic attributes of airspace and the distribution of communication and navigation facilities. The airspace performance index system includes capacity index, safety index and efficiency index. The multi-source airspace performance data fusion module is used to extract airspace operation datasets from airspace operator data and airspace management datasets from airspace manager data based on the airspace performance index system. It defines quality assessment dimensions, constructs a judgment matrix using scaling to compare each quality assessment dimension pairwise, determines the credibility weight of each dimension, calculates local weights for the airspace operation dataset and airspace management dataset under each quality assessment dimension, determines the comprehensive credibility weight corresponding to each data source, and fuses the airspace operation dataset and airspace management dataset according to the comprehensive credibility weight to determine the corresponding multi-source fused dataset. The airspace comprehensive performance determination module is used to construct a dynamic simulation environment of airspace operation status based on the multi-source fusion dataset, determine the corresponding dynamic capacity calculation model based on aircraft performance parameters, airspace structural characteristics, and control rules, perform capacity calculation on the dynamic simulation environment based on the dynamic capacity calculation model to determine the corresponding airspace capacity performance, conduct conflict risk assessment on the dynamic simulation environment based on a set conflict detection model to determine the corresponding airspace safety performance, establish a comprehensive service quality evaluation index to analyze the service quality of the dynamic simulation environment to determine the corresponding airspace efficiency performance, and determine the corresponding airspace comprehensive performance based on the airspace capacity performance, the airspace safety performance, and the airspace efficiency performance.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the low-altitude airspace performance measurement method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the low-altitude airspace performance measurement method according to any one of claims 1 to 7.

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