Airport clearance security situation awareness and management aided decision-making method and system

Abstract

The invention provides an airport clearance security situation awareness and management aided decision-making method and system, and the method comprises the steps: collecting distribution detail data, combining the distribution detail data with patrol data to obtain a clearance patrol database, and removing abnormal values according to the integrity, mathematical expectation and standard deviation; judging whether to generate an obstacle block through clustering according to the data distance of any two obstacles, and determining the range of a buffer area by combining the elevation of the obstacle block with the distance between the center of the obstacle block and the airport reference point, the flight navigation precision, the measurement precision and the elevation of the obstacle block; the final obstacle block information is combined with the clearance reference height map, the clearance limit height map and the electromagnetic height map to generate an obstacle distribution map, the final obstacle block limit height is determined, and an obstacle information list is obtained by combining the elevation output risk assessment result and the obstacle crossing height of the obstacle blocks so as to generate a clearance patrol report. And enabling the inspector to recheck and inspect according to the clearance inspection report to make a decision, and adjusting a data acquisition strategy and an analysis model according to the extracted key data.

Description

Technical Field

[0001] The present invention relates to the technical field of airport operation safety, and in particular to an airport clearance safety situation perception and management auxiliary decision-making method and system. Background Art

[0002] Due to aircraft takeoff and landing and emergency needs, there are strict restrictions on buildings around the airport, mainly including: the impact of construction projects on the airport obstacle restriction surface, visual aids protection area, flight procedures and minimum operating standards, minimum surveillance and guidance altitude, civil aviation radio station (station) site protection and civil airport electromagnetic environment, civil aviation meteorological detection environment, etc. The above restrictions involve multiple civil aviation professions, and the area to be managed involves a 55km range around the airport, which requires a huge workload.

[0003] like Figure 1 As shown in the figure, many scholars have adopted various clearance mathematical models and height limit assessment methods to solve the above problems. Specifically, according to the physical definition of the restriction surface such as Annex 14, OAS surface, simple clearance reference height, etc., the mathematical model of the restriction surface is built, and the mathematical formula and variable constraints of each surface are given. At the same time, the above mathematical model is converted into vector surface shp file, triangulated network elevation TIN file, etc., and imported into mainstream GIS software such as ArcGIS and SuperMap to realize the function of clearance assessment. For example: CN201810154606.9 Airport clearance restriction surface, two-dimensional contour map generation method, building height judgment method and computer storage medium, CN201611029945 Analysis method of the impact of civil airport terrain characteristics on flight limit exceeding events.

[0004] In view of the current status of airport clearance management, by studying the technical standards of clearance areas of major airports, establishing a mathematical model for clearance evaluation, and using high-resolution satellite orthophotos (DOM), high-precision digital elevation models (DEM) and other spatial data as the base map, an airport clearance management system based on a three-dimensional GIS platform has been developed. It realizes clearance obstacle management, clearance calculation, clearance analysis, airport area high-definition image browsing, coordinate conversion / import and export, information query, measurement, chart export and other functions based on "one map", which can improve the efficiency of clearance management, improve the accuracy of clearance calculation, and ensure civil aviation safety.

[0005] Airport clearance management is a highly professional job. In addition to being proficient in the "Technical Standards for Civil Airport Airfields" and the spatial geometric distribution and mathematical relationships of each height-restricted control surface in the airport clearance area, managers also need to master coordinate conversion, elevation interpolation and other skills to accurately plot and calculate accurate clearance information. At the same time, when calculating clearance information, traditional clearance management often requires multiple people to calculate due to the intersection and overlap of restricted surfaces and complex calculations. In addition, obstacle management based on paper drawings lacks intuitiveness and efficiency, which is not conducive to information management such as data integration and updating. At the same time, most existing management processes only consider ICAO-related factors and ignore many other factors that affect flight safety.

[0006] Traditional clearance measurement methods generally use field measurement methods that combine GPS RTK and total stations. This method requires field personnel to reach each obstacle for measurement, which is time-consuming and labor-intensive, and is prone to missing targets. The obstacle measurement method based on UAV oblique photogrammetry combined with field and field work has significantly improved the efficiency of obstacle measurement; remote sensing satellites can use data of different resolutions to carry out remote sensing monitoring of ground object changes in obstacle monitoring areas within a radius of 50km, conduct multiple monitoring in specific periods of time, and produce monitoring base maps; monitoring camera optical equipment can monitor and shoot tower structures and buildings in the core clearance protection area of ​​the airport by building a networking system, and transmit images to the coordinate map model for display, reducing the workload of manual inspections, improving monitoring efficiency, and realizing snapshot evidence collection, which is convenient for timely disposal. For example: CN201911142930.X A method and device for constructing a three-dimensional model of airport clearance based on drone photography, CN202210336515.3 A remote sensing image detection method for building changes in an airport clearance protection area.

[0007] The existing technology currently has the following disadvantages: 1. The relevant research on the restricted altitude of flight procedures is still mainly based on single-point evaluation. There is no mathematical model of the restriction surface for the complete flight procedure. Therefore, the current clearance mathematical model still cannot meet the requirements of actual airport clearance management, has single functions and few interactive operations.

[0008] 2. The digital clearance management technology developed based on the three-dimensional GIS platform is mostly focused on obstacle restriction surfaces, and cannot implement all clearance review contents such as flight procedures, lighting protection, and electromagnetic environment. It is necessary to coordinate all factors and carry out clearance management in a unified manner to avoid omissions.

[0009] 3. Traditional airport clearance obstacle management mostly adopts a one-by-one approach, with a manual closed loop from discovery to processing. For the units in charge of operations and safety, there is a lack of overall perception and auxiliary decision-making platforms. The entire system is not integrated enough, and discovery, evaluation and daily clearance inspections cannot be connected. The current task dispatching and allocation lacks an intelligent task allocation method.

[0010] 4. The accuracy of a single airspace sensing device is insufficient and cross-validation cannot be achieved. Although satellite remote sensing and optoelectronic equipment detection technology have been used, the cost of implementing accurate airspace situation awareness in the 55km range around the airport is huge and the feasibility is low. In addition, the different data accuracy requirements in different ranges are not taken into account. Summary of the invention

[0011] The purpose of the technical solution of the present invention is to design a method and system for airport clearance safety situation perception and management decision-making assistance, reduce the clearance management workload of the airport navigation department, combine new remote sensing technology and digital platform to quickly perceive the clearance safety within the 55km clearance protection area around the airport, and provide a reference for corresponding management decisions for airport clearance safety.

[0012] The technical solution of the present invention provides an airport clearance safety situation awareness and management auxiliary decision-making method, comprising the following steps: Obtain the distribution details of topographic features, urban layout information, and various infrastructures, issue inspection tasks based on the distribution details, obtain the inspection data corresponding to the distribution details, and obtain the clearance inspection database based on the distribution situation; Obtain the data integrity of the clearance inspection database, and determine whether the data integrity of the clearance inspection database is less than the preset data integrity. If so, delete the corresponding data once; Continue to obtain the latitude, longitude and / or elevation data set of the same obstacle for the data left after the first deletion, calculate the mathematical expectation and standard deviation, judge the outliers based on the mathematical expectation and standard deviation, and perform a second deletion on the data judged as outliers; The weighted average value is obtained by using different precision data adjustment algorithms, and the weighted average value is used as the obstacle data information. The processed obstacle data is obtained after unifying the standard specifications. The distance between any two obstacle data in the processed obstacle data is calculated. If the preset clustering judgment conditions are met, clustering is performed to obtain the obstacle block. The elevation of the obstacle block is determined according to the highest elevation value corresponding to the obstacle data between any two obstacle data, and the range of the buffer zone is determined according to the obstacle block elevation combined with the distance from the center of the obstacle block to the airport reference point, the flight navigation accuracy, the measurement accuracy and the elevation of the obstacle block. A buffer zone with a size of the buffer zone is generated outward from the periphery of the obstacle block, and the obstacle block and the buffer zone are used as the final obstacle block information to generate a buffer zone overlay map; Combine the final obstacle block information with the clearance reference height map, clearance limit height map and electromagnetic height map to generate an obstacle distribution map, determine the final obstacle block limit height, and output the risk assessment result and obstacle clearance height in combination with the obstacle block elevation; Generate an obstacle information list based on risk assessment results and obstacle clearance height, combine the obstacle information list, risk assessment results, buffer zone overlay map and obstacle distribution map to generate a clearance inspection report, and visualize it; According to the clearance inspection report, inspection and review tasks are issued to review the relevant information of the obstacle blocks and the disposal of the obstacle blocks and conduct inspections. Combined with the clearance reference height map, clearance limit height map and electromagnetic height map, an assessment is conducted to obtain the decision-making and disposal results; Extract key data of decision-making and disposal results, use statistical analysis methods to calculate the probability and severity of the problem, use comparative analysis methods to compare the changes in clearance safety related indicators before and after rectification, and make rationality judgments on the probability, severity and changes based on preset judgment criteria. If it is judged to be reasonable, form a data collection strategy corresponding to the data collection frequency and an analysis model corresponding to data problem feedback and parameter structure adjustment based on the probability, severity and changes.

[0013] Preferably, the formula for determining outliers based on mathematical expectation and standard deviation is as follows:

[0014] in, is any data point in the obstacle information data left after the deletion, μ is the mathematical expectation, is the standard deviation.

[0015] Preferably, the standard specifications of the unified standard specifications include: forcibly converting the spatial coordinate system into the airport engineering coordinate system under the WGS84 ellipsoid, unifying the obstacle height to the 85 elevation benchmark, using the UTC+8 time zone ISO8601 format for the timestamp, and establishing a standard field set including ID, longitude, latitude, elevation, type code, construction year, and material code.

[0016] Preferably, the formula for the preset clustering judgment condition is:

[0017] in, and are any two obstacle data, For distance, is the agglomerative clustering parameter.

[0018] Preferably, the clearance reference altitude map, clearance restriction altitude map and electromagnetic altitude map are generated according to airport clearance restriction standards and relevant regulations and specifications.

[0019] Preferably, the key data include the height of obstacles before and after rectification, location change data, and the types and frequencies of problems encountered during the decision-making execution process.

[0020] The technical solution of the present invention also provides an airport clearance safety situation awareness and management decision-making assistance system, which adopts the above-mentioned airport clearance safety situation awareness and management decision-making assistance method, including: The satellite remote sensing imagery sky perception subsystem is used to obtain data on topographic features, urban layout information, and distribution details of various infrastructures.

[0021] The clearance inspection subsystem is used to issue inspection tasks according to the distribution details data, obtain the inspection data corresponding to the distribution details, obtain the clearance inspection database based on the distribution situation, obtain the data integrity of the clearance inspection database, and determine whether the data integrity of the clearance inspection database is less than the preset data integrity. If so, the corresponding data will be deleted.

[0022] The latitude, longitude and / or elevation data sets of the same obstacle are continuously obtained for the data remaining after the first deletion, and the mathematical expectation and standard deviation are calculated. The outliers are judged according to the mathematical expectation and standard deviation, and the data judged as outliers are deleted for the second time.

[0023] The weighted average value is obtained by using data adjustment algorithms of different accuracies, and the weighted average value is used as the obstacle data information. The processed obstacle data is obtained after unified standards and specifications. The distance between any two obstacle data in the processed obstacle data is calculated. If the preset clustering judgment conditions are met, clustering is performed to obtain the obstacle block.

[0024] The elevation of the obstacle block is determined according to the highest elevation value corresponding to the obstacle data between any two obstacle data. The buffer range is determined according to the obstacle block elevation combined with the distance from the center of the obstacle block to the airport reference point, flight navigation accuracy, measurement accuracy and the elevation of the obstacle block. A buffer with a size of the buffer range is generated outward from the periphery of the obstacle block. The obstacle block and the buffer are used as the final obstacle block information and a buffer overlay map is generated.

[0025] According to the clearance inspection report, inspection review tasks are issued to review the relevant information of the obstacle blocks and the disposal of the obstacle blocks and conduct inspections.

[0026] The airport clearance management decision subsystem is used to combine the final obstacle block information with the clearance reference height map, the clearance limit height map and the electromagnetic height map to generate an obstacle distribution map, determine the final obstacle block limit height, and output the risk assessment results and obstacle clearance height in combination with the obstacle block elevation.

[0027] An obstacle information list is generated based on the risk assessment results and obstacle clearance height. The obstacle information list, risk assessment results, buffer zone overlay map and obstacle distribution map are combined to generate a clearance inspection report and visualize it. The review inspection is evaluated in combination with the clearance reference height map, clearance limit height map and electromagnetic height map to obtain the decision-making and disposal results.

[0028] Extract key data of decision-making and disposal results, use statistical analysis methods to calculate the probability and severity of the problem, use comparative analysis methods to compare the changes in clearance safety related indicators before and after rectification, and make rationality judgments on the probability, severity and changes based on preset judgment criteria. If it is judged to be reasonable, form a data collection strategy corresponding to the data collection frequency and an analysis model corresponding to data problem feedback and parameter structure adjustment based on the probability, severity and changes.

[0029] Preferably, the airport clearance safety situation awareness and management decision support system comprises: The satellite remote sensing image clearance perception subsystem includes: a multispectral image sensor, an intelligent recognition and calculation module, a storage medium, and a data transmission module; the clearance inspection subsystem includes: a GPS positioning sensor, a storage medium, and a communication module; the airport clearance management decision-making subsystem includes: a processing and analysis module, a data transmission module, and a storage medium.

[0030] The technical solution of the present invention proposes an airport clearance safety situation awareness and management decision-making auxiliary method and system, which obtains a clearance inspection database by collecting distribution detail data and combining it with inspection data, and removes outliers twice according to completeness, mathematical expectation and standard deviation; determines whether to cluster and generate obstacle blocks by the distance between any two obstacle data, and then determines the buffer range by combining the obstacle block elevation with the distance between the center of the obstacle block and the airport reference point, flight navigation accuracy, measurement accuracy and the elevation of the obstacle block; generates an obstacle distribution map by combining the final obstacle block information with a clearance reference height map, a clearance limit height map and an electromagnetic height map, determines the final obstacle block limit height, outputs a risk assessment result and an obstacle clearance height in combination with the elevation of the obstacle block, obtains an obstacle information list, combines the risk assessment result, the buffer zone overlay map and the obstacle distribution map to generate a clearance inspection report, so that the inspector can make a decision based on the clearance inspection report and the feedback information after the decision, and adjusts the data collection strategy and analysis model. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a structural diagram of an airport clearance safety situation awareness and management decision-making support system in the prior art; Figure 2 A structural function diagram of an airport clearance safety situation awareness and management decision-making support system is provided for an embodiment of the present invention; Figure 3 A flowchart of an airport clearance safety situation awareness and management decision-making assistance method is provided for an embodiment of the present invention; Figure 4 An application structure diagram of an airport clearance safety situation awareness and management auxiliary decision-making system is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0033] like Figure 3 As shown, an embodiment of the present invention provides an airport clearance safety situation awareness and management decision-making assistance method, including the following steps: Step 1: The clearance perception subsystem obtains the topographic features, urban layout information, and distribution details of various infrastructure through satellite remote sensing images. The clearance inspection subsystem issues inspection tasks based on the distribution details data, obtains the inspection data corresponding to the distribution details, and obtains the clearance inspection database in combination with the distribution data. That is, the data sources of the clearance inspection database include high-resolution satellite remote sensing images, airport clearance inspection data, and data reported by other units.

[0034] Among them, the satellite remote sensing image clearance perception subsystem uses advanced image recognition algorithms and artificial intelligence analysis systems to accurately identify various potential obstacles in satellite remote sensing images. It collects a wide range of basic geographic information data, including topographic features, urban layout information, and distribution details of various infrastructures, and stores them as obstacle data in the clearance management area in the clearance inspection subsystem's clearance inspection database. For example, for buildings, it can analyze their height, floor area, and building structure type in detail; for tall communication towers, power poles and other facilities, it can determine their precise coordinates, tower heights, and the spatial distribution of ancillary equipment; for naturally grown tall trees or mountains and other obstacles, it can also accurately measure key data such as their height relative to the airport runway, slope, and distance from the runway centerline.

[0035] The clearance inspection subsystem obtains corresponding data through field exploration and investigation, daily inspection and recording, and stores it in the clearance inspection database in combination with the distribution of the clearance perception subsystem from satellite remote sensing images. For example, the clearance inspection subsystem issues inspection tasks, arranges staff to conduct daily inspections through equipment such as GPS positioning sensors and image acquisition sensors, records detailed information such as the location, type, and scale of various infrastructure and the completion process of the entire inspection task, organizes a professional measurement team, uses total stations, GPS receivers and other measuring instruments, conducts field measurements of the area around the airport, obtains accurate topographic data and uploads it to the clearance inspection database in combination with the distribution situation. The clearance inspection database includes elevation, slope, slope direction, etc.

[0036] Step 2: The clearance inspection subsystem cleans, organizes and converts the data in the clearance inspection database, removes redundant data, erroneous data and incomplete data, and normalizes various types of data according to unified standards to generate processed obstacle data.

[0037] The specific data cleaning process is as follows: First, incomplete data (incomplete data: data completeness < 95%) are directly eliminated; then, the data information of the same obstacle is integrated together through the clustering algorithm. The longitude and latitude or elevation data set of the same obstacle is , where n is the number of data points.

[0038] (1) Calculate the mathematical expectation : ; (2) Calculate variance : ; (3) Calculate the standard deviation : ; (4) Determine outliers: For any data point in the clearance inspection database , if it satisfies:

[0039] but They are considered outliers and need to be cleaned.

[0040] The remaining available data are then adjusted using different precision data algorithms to obtain a weighted average, which is ultimately used as the obstacle data information.

[0041] Data adjustment algorithms with different precision: Assume there are n measurements with different precisions , for each measurement value, its measurement accuracy is . Weight coefficient It is a value that measures the reliability of each measurement value. The weight coefficient is inversely proportional to the square of the measurement accuracy. The calculation formula is:

[0042] in is a constant, (Depending on the civil aviation airport clearance data accuracy requirement of 0.01m). The weighted average value X is the average value of each measurement value with its weight as the weight, and the calculation formula is: .

[0043] Unified standards and specifications: (1) Spatial coordinate system: forced conversion to the airport engineering coordinate system under the WGS84 ellipsoid (projection parameters: central longitude = runway center axis longitude); (2) Data format: The obstacle height is unified as 85 elevation benchmark, and the timestamp uses the ISO8601 format of UTC+8 time zone; (3) Attribute structure: establish a standard field set (ID, longitude, latitude, elevation, type code, construction year, material code); Perform cluster analysis on the processed obstacle data, assuming that the obstacle set is ,in Represents the coordinates of the i-th obstacle and elevation , for any two obstacles and , through the Euclidean distance formula Calculate the distance between them and set the agglomerative clustering parameters to ,like , then and The obstacle blocks are regarded as clusters, and their elevation is calculated according to the elevation of the highest point in the range. , the elevation information of the obstacle block for: .

[0044] After completing the cluster analysis, a buffer zone is generated for each obstacle block. The buffer zone range is d meters expanded outward from the obstacle block range. The buffer zone is regarded as part of the obstacle block, and the elevation information is consistent with the obstacle block, so as to obtain the final obstacle block information.

[0045] ( , where H is the elevation of the obstacle block, D is the distance from the center of the obstacle block to the airport reference point, A is the flight navigation accuracy, and B is the measurement accuracy, all in meters).

[0046] Step 3: Input the final obstacle block information into the clearance assessment module of the airport clearance management decision subsystem with the clearance reference height map, clearance limit height map and electromagnetic height map, determine its limit height according to the location and coverage of the obstacle block, and give the corresponding risk assessment result and obstacle clearance height according to the elevation information of the obstacle block.

[0047] Among them, the risk assessment level is divided into six levels, the first level is low risk, and the sixth level is high risk. The first-level risk classification standard is that the obstacle elevation is lower than the limit height of the electromagnetic height map, the clearance reference height map and the clearance limit height map. At this time, the risk assessment level is no risk; the second-level risk classification standard is that the obstacle elevation is lower than the limit height of the clearance reference height map and the clearance limit height map, and higher than the limit height of the electromagnetic height map. The risk assessment level is medium risk and electromagnetic environment warning; the third-level risk classification standard is that the obstacle elevation is lower than the limit height of the electromagnetic height map and the clearance limit height map, and higher than the limit height of the clearance reference height map. The risk assessment level is medium risk and electromagnetic environment warning. The levels are medium risk and clearance warning; the fourth-level risk level division standard is that the obstacle elevation is lower than the limit height of the clearance limit height map, and higher than the limit height of the electromagnetic height map and the clearance reference height map, and the risk assessment level is high risk, electromagnetic and clearance warning; the fifth-level risk level division standard is that the obstacle elevation is lower than the limit height of the electromagnetic height map, and higher than the limit height of the clearance reference height map and the clearance limit height map, and the risk assessment level is medium-high risk and clearance warning; the sixth-level risk level division standard is that the obstacle elevation is higher than the limit height of the electromagnetic height map, the clearance reference height map and the clearance limit height map, and the risk assessment level is ultra-high risk and prohibited.

[0048] Each map in the clearance assessment module is generated according to the airport clearance restriction standards and relevant regulations and specifications, and specifies the corresponding height restrictions for each location within the airport clearance assessment range to adapt to the clearance requirements of the specific airport.

[0049]

[0050] Based on the risk assessment results and obstacle clearance height, an obstacle information list in a specified format (such as Excel table, CSV file) is generated, and the data visualization tool (Tableau) is used to generate corresponding analysis charts for the spatial analysis results (such as buffer overlay map, obstacle distribution map), risk assessment results (obstacle risk assessment situation), etc., and finally generate a detailed, accurate and forward-looking clearance inspection report, which includes a detailed obstacle list, risk assessment results and corresponding analysis charts.

[0051] The airport clearance situation display and analysis module and the obstacle management decision analysis module obtain clearance inspection reports for visual display, which can be retrieved and viewed by users at any time. The clearance inspection report is submitted to the airport clearance management decision subsystem, which issues inspection review tasks through the clearance inspection subsystem to review the relevant information of the obstacle block, and after the corresponding obstacle block is disposed of, it can also issue inspection tasks to verify the disposal of the obstacle block. Inspectors can receive and execute inspection tasks through the clearance inspection subsystem, use the GPS positioning sensor and image acquisition sensor therein to record the inspection trajectory and collect obstacle data and upload it, and use the evaluation algorithm in its calculation module that is consistent with the clearance evaluation module of the airport clearance management decision subsystem to realize location-based height limit calculation and auxiliary measurement, providing all-round support and data interaction for inspectors in clearance inspection work.

[0052] After the decision and disposal measures are implemented, the inspectors will feedback the detailed decision and disposal results, including the actual situation during the implementation process, the problems encountered and the solutions, the final rectification effect and other information to the feedback information database of the airport clearance management decision subsystem in accordance with the prescribed data feedback format and process.

[0053] The airport clearance management decision subsystem extracts key data from the decision-making results, such as the height and position change data of obstacles before and after rectification, and the types and frequencies of problems encountered during the decision-making process. Statistical analysis methods are used to calculate the probability and severity of the problem; comparative analysis methods are used to compare the changes in clearance safety-related indicators before and after rectification. Afterwards, based on the extracted and analyzed data, it is determined whether the various parameters of the system (such as data collection frequency and threshold setting) are reasonable. Finally, based on the judgment results, various parameters are adjusted, and the data collection frequency of certain areas is increased or decreased according to actual needs to form a data collection strategy; based on new data and problem feedback, the parameters or structure of the model are adjusted to form an analysis model.

[0054] For example, if multiple feedbacks reveal that untimely data collection in a certain area leads to delayed problem handling, then it is judged that the frequency of data collection needs to be increased; if it is found that certain risk assessment thresholds are set too high or too low, resulting in inaccurate risk judgment, then the thresholds need to be adjusted.

[0055] Intelligent algorithms are used to optimize and improve the system's parameters, data collection strategies, analysis models, etc., thereby continuously improving the accuracy, efficiency and adaptability of the entire airport clearance safety management system to better respond to the increasingly complex and changing airport clearance safety challenges.

[0056] For example, large-scale urban construction and development is underway around a certain international airport. At the same time, there are some natural terrain and existing infrastructure around the airport, which requires comprehensive situational awareness and management decisions for the airport's airspace safety.

[0057] First, obtain detailed basic geographic information data of the area where the airport is located and a certain range around it, including terrain contour data, urban road network, existing building distribution and other information. At the same time, regular monitoring of the airport clearance management area is carried out through high-resolution satellite remote sensing images. For example, in the latest satellite remote sensing image analysis, it was identified that there was a newly planned residential area about 3 kilometers away from the extension line of one end of the airport runway, and some of the buildings had already started construction. The image showed that the preliminary estimate of the building height may be close to the clearance limit height; about 1.5 kilometers to the side of the runway, some trees were found to have obvious signs of growth, and the height was increased compared with the previous one. Use professional software to analyze and collect detailed data of these newly built buildings and growing trees, including the precise coordinates of the buildings, the preliminary estimated height, the area occupied, the location coordinates of the trees, the height range and other obstacle data.

[0058] Assuming that 1,000 pieces of obstacle information data are initially collected, after the data enters the database, it is first cleaned, sorted and converted, and all types of data are first normalized according to unified standards.

[0059] Unified standards and specifications: (1) Spatial coordinate system: forced conversion to the airport engineering coordinate system under the WGS84 ellipsoid (projection parameters: central longitude = runway center axis longitude); (2) Data format: The obstacle height is unified as 85 elevation benchmark, and the timestamp uses the ISO8601 format of UTC+8 time zone; (3) Attribute structure: Establish a standard field set (ID, longitude, latitude, elevation, type code, construction year, material code).

[0060] After checking, it was found that 30 data were less than 95% complete, such as lack of key elevation or type information, and these 30 data were directly removed. Taking a residential building as an example, the relevant multi-source data was integrated through the clustering algorithm, and the mathematical expectation μ and variance σ^2 of its longitude, latitude and elevation information were calculated. Assuming that the calculated elevation mean μ is 20 meters and the standard deviation σ is 2 meters, if there is data showing that the elevation of the residential building is 28 meters, it exceeds the range of [18, 22] and is determined to be an outlier for cleaning. The remaining available data is then used to obtain a weighted average using different precision data adjustment algorithms, and finally the weighted average is used as the data information of the obstacle and recorded in the database.

[0061] Perform cluster analysis on the processed obstacle data. There are multiple street light poles near the airport runway. With one of the street light poles as the center, there are 3 street light poles within a 2-meter range. They are considered as a whole. The highest of these street light poles is 5 meters, so the elevation of the obstacle block is determined to be 5 meters. The distance between this obstacle block and the airport benchmark is D = 3000 meters, the flight navigation accuracy is A = 0.5 meters, the measurement accuracy is B = 0.2 meters, and the calculated buffer range is d = 5 2 ÷3000 +√(0.5 2 + 0.2 2 )≈0.54 m, the buffer zone is considered as part of the obstacle block, and its elevation information is consistent with that of the obstacle block.

[0062] Input these obstacle block information into the clearance assessment module. For a certain obstacle block, determine its restricted height according to its location and coverage. Assume that the restricted height of the clearance reference height map at its location is 10 meters, the restricted height of the clearance restricted height map is 12 meters, and the restricted height of the electromagnetic height map is 8 meters. The elevation of this obstacle block is 9 meters, and its risk assessment level is level 2. The remaining obstacle blocks are calculated in the same way.

[0063] After calculation, if the height of some buildings near the runway extension line in the newly built residential area is built according to the plan, it will exceed the airport clearance limit height map by about 5 meters; and although the growing trees have not yet exceeded the clearance limit, according to their growth rate, it is expected that they may affect clearance safety in the next 6 months. Based on these analysis results, a clearance inspection report is generated, which lists in detail the building number, location, current height, expected height, impact level on clearance safety, and location, current height, and expected impact time of the trees in the newly built residential area, and is equipped with intuitive charts to show the relative position relationship between the buildings and trees and the airport runway and the comparison of clearance restriction areas.

[0064] The clearance assessment report is submitted to the airport clearance management decision-making subsystem, and the inspection and obstacle disposal tasks are transmitted to the airport clearance management decision-making subsystem. The airport clearance management decision-making subsystem automatically formulates a work plan and path. After completing the inspection and disposal tasks, the clearance inspection subsystem will feed back the processing results to the airport clearance management decision-making subsystem. Including the modified architectural design drawings and construction progress reports submitted by the construction unit, the comparison photos of trees before and after pruning, and height measurement data submitted by the greening department. Based on this feedback information, the system optimizes the frequency of data collection, for example, increasing the frequency of satellite remote sensing image monitoring of the area from once a month to once every half a month, and adjusting some parameters in the data processing model, such as the correction coefficient of building height estimation, so that airport clearance safety issues can be discovered and handled more accurately and timely in the future.

[0065] like Figure 2 and Figure 4 As shown, an embodiment of the present invention further provides an airport clearance safety situation awareness and management decision-making assistance system, which adopts an airport clearance safety situation awareness and management decision-making assistance method as described above, including: The satellite remote sensing image clearance perception subsystem includes sensors, storage media, intelligent recognition and calculation modules, and data transmission modules. It is mainly responsible for receiving and processing multi-source satellite data, accurately extracting information on super-high buildings and obstacles within the airport clearance protection area, and marking key areas of concern, providing basic data support for airport clearance management.

[0066] Among them, the sensor is equipped with a multispectral image sensor, which can receive and analyze data signals from Gaojing stereo satellite, GF7 stereo satellite, Ziyuan-3 stereo satellite and 0.5-meter resolution monolithic satellite, ensuring accurate collection of satellite image data of different bands and resolutions. The storage medium has a built-in large-capacity and high-speed solid-state hard drive (SSD) to store massive amounts of satellite raw data, intermediate data in the processing process, and the final generated DSM (digital surface model), DEM (digital elevation model) data, etc. The storage capacity can be set according to the estimated amount of airport clearance monitoring data and long-term storage requirements, such as 5TB or larger capacity, to meet the storage requirements of long-term and multi-batch satellite data. The intelligent recognition and computing module adopts an architecture in which a high-performance graphics processing unit (GPU) and a central processing unit (CPU) work together. The GPU is good at handling large-scale parallel computing tasks, such as fast processing and analysis of satellite images, including image stitching, feature extraction, etc.; the CPU is responsible for overall data scheduling, control logic and communication with other systems. The intelligent recognition and calculation module has powerful floating-point computing capabilities and can efficiently process high-precision geospatial data calculations to meet the calculation needs of screening out airport buildings and obstacles based on the airport runway in the three-dimensional environment of satellite data. At the same time, through the intelligent recognition algorithm, the monitoring area is regularly inspected, the changes in the map are analyzed, and the data information of the airport's buildings and obstacles is updated to provide more real and accurate data for subsequent decision-making. The data transmission module has a high-speed network communication interface, such as a Gigabit Ethernet port or a fiber optic interface, which is used to transmit data with a satellite data receiving station or a data center to ensure timely acquisition of the latest satellite image data, and can upload the processed data to the core server or other related systems of the airport clearance management to achieve data sharing and interaction.

[0067] The clearance inspection subsystem includes GPS positioning sensor, image acquisition sensor, storage medium, computing module and communication module.

[0068] Functional Overview: It mainly realizes the functions of dispatching and receiving inspection tasks, recording inspection trajectories, collecting and uploading obstacle data, calculating positioning height limits and auxiliary measurements, etc., providing all-round support and data interaction for inspectors in clearance inspections.

[0069] sensor: GPS positioning sensor: Accurately obtain the real-time location information of patrol personnel and patrol vehicles with a positioning accuracy within a few meters, providing basic data support for patrol trajectory recording, task planning and dispatching, and location-based height limit calculation.

[0070] Image acquisition sensor: An integrated high-resolution camera is used by inspectors to take photos of obstacles, changes in construction area patterns, and other on-site conditions. The camera pixel should meet the requirements of clearly recording on-site details, such as 12 million pixels or higher.

[0071] Storage media: Use a portable large-capacity storage device, such as a pluggable high-speed memory card (such as an SDXC card with a capacity of up to 256GB or more) combined with an internal small-capacity solid-state hard drive. The memory card is used to temporarily store photos, videos, and text information taken during the inspection process. After the inspection is completed or when network conditions are available, the data is uploaded to the internal solid-state hard drive for centralized storage and organization. The internal solid-state hard drive is used to store system software, map data, historical inspection records, and other related configuration information to ensure stable operation of the system and long-term preservation of data.

[0072] Computing module: Based on low-power, high-performance mobile processors, it has a multi-core architecture and can handle multiple tasks simultaneously, such as task reception and processing, data upload and download, height limit calculation, and map data loading and display. The computing module runs a special patrol task management software to realize the reception and execution of task dispatch, the recording and display of patrol trajectories, and the preliminary processing and analysis of obstacle data.

[0073] Communication module: supports multiple wireless communication methods, including 4G / 5G mobile communication network module, which is used to interact with the background server in real time, receive inspection tasks, upload inspection results and field data; it also has a Bluetooth module, which can be connected to the inspectors' mobile devices (such as mobile phones and tablets) over short distances to facilitate data transmission and device configuration; it is also equipped with a Wi-Fi module. In areas with available Wi-Fi networks, Wi-Fi can be used for data transmission to reduce data traffic costs and increase transmission speeds.

[0074] The airport clearance management decision subsystem includes storage media, processing and analysis modules, and data transmission modules.

[0075] Functional Overview: Mainly serving as the core hub of the entire airport clearance management system, it integrates the data of satellite remote sensing image clearance perception and clearance patrol system, and conducts situation display, obstacle management decision-making, patrol management analysis, clearance assessment and other tasks, providing comprehensive and accurate decision-making support for airport clearance management.

[0076] Storage media: Equipped with enterprise-level large-capacity storage arrays, using redundant disk array (RAID) technology, such as RAID5 or RAID 6, to ensure data reliability and security. The storage capacity is designed according to the long-term data storage needs of airport clearance management, and can reach tens of TB or even larger, which is used to store massive data such as airport digital models, surrounding 3D terrain data, clearance 3D restriction data, satellite remote sensing analysis data, clearance inspection data, and various event databases.

[0077] Processing and analysis module: It uses high-performance server-level processors with multi-core, high frequency, and large cache, and can quickly process complex data analysis and computing tasks. The processing and analysis module runs the airport clearance situation awareness and management decision-making software platform, which integrates core functional components such as data fusion algorithm, clearance assessment algorithm, statistical analysis algorithm, and visualization rendering engine. Through the data fusion algorithm, multi-dimensional data fusion with different accuracy requirements within the 55km range of the airport is realized, such as fusing satellite remote sensing data, patrol data, airport design data, etc.; the clearance assessment algorithm is used to evaluate the airport clearance status and provide reference results based on relevant laws and regulations and standards, taking into account various clearance restriction factors; the clearance situation data is analyzed in real time with the help of statistical analysis algorithms to provide data support for decision-making; the clearance situation, obstacle block information and clearance patrol situation are displayed on the desktop or large screen through the visualization rendering engine to achieve intuitive and clear visualization effects; key data is extracted from the feedback information generated after the execution of the clearance patrol report, and the probability and severity of the problem are calculated using statistical analysis methods. The changes in clearance safety-related indicators before and after rectification are compared using comparative analysis methods, and the probability, severity and changes are judged rationally according to the preset judgment criteria, and the various system parameters, data collection strategies, analysis models, etc. are optimized and improved.

[0078] Data transmission module: It has high-speed network interfaces, including multiple Gigabit Ethernet ports or 10 Gigabit Ethernet ports, which are used for data interaction and sharing with other systems within the airport (such as air traffic control system, airport operation management system, etc.). At the same time, it connects to the satellite remote sensing image clearance perception module and the clearance inspection system module to achieve data aggregation and distribution, and build a complete airport clearance management network system.

[0079] The technical effects of the embodiments of the present invention are as follows: 1. Comprehensively consider the factors affecting clearance assessment, and develop an airport clearance rapid assessment algorithm based on the requirements of clearance review such as obstacle restriction surfaces, flight procedures and operating standards, visual aid protection areas, radar minimum guidance altitudes, electromagnetic environment of civil aviation radio stations, and meteorological detection environment to achieve a comprehensive clearance assessment.

[0080] 2. Integrate multi-source data modules such as flight procedures, lighting protection, and electromagnetic environment in the 3D GIS platform, establish unified data standards and interfaces, and realize data interconnection. For example, convert flight procedure data into a format that can be visualized and analyzed in the GIS platform, and conduct collaborative analysis with obstacle restriction surface data.

[0081] 3. Develop an intelligent clearance management platform to integrate all aspects of clearance obstacle discovery, evaluation, and processing. Use IoT technology to achieve real-time connection with various monitoring devices and automatically receive and process monitoring data. Establish an intelligent task allocation system based on big data analysis and artificial intelligence algorithms to automatically assign tasks to the most appropriate staff or department based on factors such as the type, urgency, personnel skills, and workload of clearance management tasks. At the same time, the platform provides an overall clearance situation awareness function, which displays the real-time status, historical change trends, and potential risk points of airport clearance through a visual interface, providing strong support for decision-making.

[0082] 4. Research multi-sensor fusion technology, fuse the data of various air clearance sensing devices such as satellite remote sensing, optoelectronic equipment, radar, etc., improve the accuracy and reliability of air clearance monitoring through data fusion algorithms, and achieve cross-validation. For example, the large-scale monitoring capability of satellite remote sensing and the high-precision local monitoring capability of optoelectronic equipment are combined to conduct hierarchical monitoring of different areas around the airport. At the same time, research monitoring schemes that set different data accuracy requirements according to the needs of different ranges around the airport, use high-precision monitoring equipment in key areas (such as near the runway), and appropriately reduce the monitoring accuracy requirements in areas far away from the runway to reduce costs. At the same time, explore new low-cost, high-precision air clearance monitoring technologies, such as distributed monitoring technology based on drone clusters, to improve the feasibility and economy of air clearance situational awareness.

[0083] 5. With the help of three-dimensional GIS, satellite remote sensing and intelligent algorithms, this study embedded the management procedures and calculation methods of civil aviation professional norms and standards, and improved the level of airport clearance management through digital means; at the same time, by providing urban planning management departments and civil aviation authorities with the system, urban planning management and airport clearance protection can be better connected, effectively improving the efficiency of building clearance height limit approval, and promoting the comprehensive balance and development of civil aviation operation safety control and urban construction.

[0084] 6. Make full use of the advantages of remote sensing satellite images in coverage and spatial resolution to achieve a detailed survey of super-high buildings and obstacles around the airport, providing a clearer goal for the airport to conduct field inspections of obstacles, effectively avoiding the waste of manpower and material resources, and improving work efficiency. And through the key area identification algorithm, provide path optimization and task distribution for clearance inspectors. The implementation of this project provides strong technical support for the civil aviation department to fully grasp the information of super-high buildings around the airport and formulate corresponding prevention and control measures. From the actual use point of view, the airport clearance management system has strong practicality and broad application prospects.

[0085] 7. At the same time, the construction of this system will provide a carrier for the access of hardware such as low-altitude radars and multi-array cameras at future airports to achieve real-time monitoring and processing of airspace.

Claims

1. An airport clearance safety situation awareness and management decision-making assistance method, characterized in that: The following steps are involved: Obtain the distribution details of topographic features, urban layout information, and various infrastructures, issue inspection tasks based on the distribution details, obtain the inspection data corresponding to the distribution details, and obtain the clearance inspection database based on the distribution situation; Obtain the data integrity of the clearance inspection database, and determine whether the data integrity of the clearance inspection database is less than the preset data integrity. If so, delete the corresponding data once; Continue to obtain the latitude, longitude and / or elevation data set of the same obstacle for the data left after the first deletion, calculate the mathematical expectation and standard deviation, judge the outliers based on the mathematical expectation and standard deviation, and perform a second deletion on the data judged as outliers; The weighted average value is obtained by using different precision data adjustment algorithms, and the weighted average value is used as the obstacle data information. The processed obstacle data is obtained after unifying the standard specifications. The distance between any two obstacle data in the processed obstacle data is calculated. If the preset clustering judgment conditions are met, clustering is performed to obtain the obstacle block. The elevation of the obstacle block is determined according to the highest elevation value corresponding to the obstacle data between any two obstacle data, and the range of the buffer zone is determined according to the obstacle block elevation combined with the distance from the center of the obstacle block to the airport reference point, the flight navigation accuracy, the measurement accuracy and the elevation of the obstacle block. A buffer zone with a size of the buffer zone is generated outward from the periphery of the obstacle block, and the obstacle block and the buffer zone are used as the final obstacle block information to generate a buffer zone overlay map; Combine the final obstacle block information with the clearance reference height map, clearance limit height map and electromagnetic height map to generate an obstacle distribution map, determine the final obstacle block limit height, and output the risk assessment result and obstacle clearance height in combination with the obstacle block elevation; Generate an obstacle information list based on risk assessment results and obstacle clearance height, combine the obstacle information list, risk assessment results, buffer zone overlay map and obstacle distribution map to generate a clearance inspection report, and visualize it; According to the clearance inspection report, inspection and review tasks are issued to review the relevant information of the obstacle blocks and the disposal of the obstacle blocks and conduct inspections. Combined with the clearance reference height map, clearance limit height map and electromagnetic height map, an assessment is conducted to obtain the decision-making and disposal results; Extract key data of decision-making and disposal results, use statistical analysis methods to calculate the probability and severity of the problem, use comparative analysis methods to compare the changes in clearance safety related indicators before and after rectification, and make rationality judgments on the probability, severity and changes based on preset judgment criteria. If it is judged to be reasonable, form a data collection strategy corresponding to the data collection frequency and an analysis model corresponding to data problem feedback and parameter structure adjustment based on the probability, severity and changes.

2. The airport clearance safety situation awareness and management decision-making support method according to claim 1, characterized in that: The formula for judging outliers based on mathematical expectation and standard deviation is as follows: in, is any data point in the obstacle information data left after the deletion, μ is the mathematical expectation, is the standard deviation.

3. The airport clearance safety situation awareness and management decision-making support method according to claim 1, characterized in that: The standard specifications of the unified standard specifications include: forcibly converting the spatial coordinate system into the airport engineering coordinate system under the WGS84 ellipsoid, unifying the obstacle height to the 85 elevation benchmark, using the UTC+8 time zone ISO8601 format for the timestamp, and establishing a standard field set including ID, longitude, latitude, elevation, type code, construction year, and material code.

4. The airport clearance safety situation awareness and management decision-making support method according to claim 1, characterized in that: The formula for the preset clustering judgment condition is: in, and are any two obstacle data, For distance, is the agglomerative clustering parameter.

5. The airport clearance safety situation awareness and management decision-making support method according to claim 1, characterized in that: The clearance reference altitude map, clearance restriction altitude map and electromagnetic altitude map are generated according to the airport clearance restriction standards and relevant regulations and specifications.

6. The airport clearance safety situation awareness and management decision-making support method according to claim 1, characterized in that: The key data include the height and position change data of obstacles before and after rectification, and the types and frequency of problems encountered during the decision-making execution process.

7. An airport clearance safety situation awareness and management decision-making support system, using an airport clearance safety situation awareness and management decision-making support method as claimed in claim 1, comprising: Satellite remote sensing imagery clear space perception subsystem, used to obtain topographic features, urban layout information, and distribution details of various infrastructures; The clearance inspection subsystem is used to issue inspection tasks according to the distribution details data, obtain the inspection data corresponding to the distribution details, obtain the clearance inspection database in combination with the distribution situation, obtain the data integrity of the clearance inspection database, and determine whether the data integrity of the clearance inspection database is less than the preset data integrity. If so, the corresponding data will be deleted once; the longitude and latitude and / or elevation data sets of the same obstacle will continue to be obtained for the data left after the deletion, and the mathematical expectation and standard deviation will be calculated. The outliers will be determined based on the mathematical expectation and standard deviation, and the data determined as outliers will be deleted twice; the weighted average value is obtained by using different precision data adjustment algorithms, and the weighted average value is used as the obstacle data information, and the data is processed after unified standards and specifications. After obstacle data is processed, the distance between any two obstacle data in the obstacle data is calculated. If the preset clustering judgment condition is met, clustering is performed to obtain an obstacle block; the elevation of the obstacle block is determined according to the highest elevation value corresponding to the obstacle data between any two obstacle data, and the buffer range is determined according to the obstacle block elevation combined with the distance from the center of the obstacle block to the airport reference point, flight navigation accuracy, measurement accuracy and the elevation of the obstacle block. A buffer zone with a size of the buffer range is generated outward from the outside of the obstacle block, and the obstacle block and the buffer zone are used as the final obstacle block information and a buffer zone overlay map is generated; according to the clearance inspection report, an inspection review task is issued to review the relevant information of the obstacle block and the disposal of the obstacle block and conduct an inspection; The airport clearance management decision subsystem is used to combine the final obstacle block information with the clearance reference height map, the clearance limit height map and the electromagnetic height map to generate an obstacle distribution map, determine the final obstacle block limit height, and output the risk assessment results and obstacle clearance height in combination with the elevation of the obstacle block; generate an obstacle information list based on the risk assessment results and obstacle clearance height, combine the obstacle information list, risk assessment results, buffer zone overlay map and obstacle distribution map to generate a clearance inspection report, and visualize it; review the inspection and evaluate it in combination with the clearance reference height map, the clearance limit height map and the electromagnetic height map to obtain the decision-making and disposal results; extract the key data of the decision-making and disposal results, use statistical analysis methods to calculate the probability and severity of the problem, use comparative analysis methods to compare the changes in clearance safety-related indicators before and after rectification, and make a reasonable judgment on the probability, severity and changes based on the preset judgment criteria. If it is judged to be reasonable, a data collection strategy corresponding to the data collection frequency and an analysis model corresponding to data problem feedback and parameter structure adjustment are formed based on the probability, severity and changes.

8. The airport clearance safety situation awareness and management decision-making support system according to claim 7, characterized in that: The airport clearance safety situation awareness and management auxiliary decision-making includes: The satellite remote sensing image clear space perception subsystem includes: a multispectral image sensor, an intelligent recognition and calculation module, a storage medium, and a data transmission module; The clearance inspection subsystem includes: GPS positioning sensor, storage medium and communication module; The airport clearance management decision subsystem includes: processing and analysis module, data transmission module and storage medium.

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