Airport clearance obstacle assessment method, device, electronic equipment and storage medium

Abstract

The present application relates to an airport clearance obstacle assessment method, device, electronic device and storage medium, the method comprising: obtaining airport location information, airport environment information, aircraft flight information and obstacle information; obtaining a first airport probability model according to the airport location information and aircraft flight information; obtaining a first terrain model according to the airport environment information and obstacle information; matching the first airport probability model and the first terrain model to obtain an airport clearance obstacle assessment result. The present application improves the accuracy of the generation of the first airport probability model and the first terrain model by introducing airport environment information and aircraft flight information, thereby improving the accuracy of the airport clearance obstacle assessment, and does not require manual processing, thereby improving the efficiency of the airport clearance obstacle assessment.

Description

Technical Field

[0001] The present application relates to the field of aviation safety technology, and in particular to an airport clearance obstacle assessment method, device, electronic equipment and storage medium. Background Art

[0002] Airport clearance refers to an area above the airport, which requires that aircraft must not have ground obstacles to hinder navigation and flight when flying at low altitudes for takeoff and landing. This area is to ensure that the airport can operate safely and efficiently, and is closely related to the terrain and artificial structures inside and outside the site. Airport clearance obstacle assessment includes the calculation of obstacle restriction surfaces such as "Annex 14 Surfaces" and the assessment of the impact of obstacles on aircraft.

[0003] In the current aviation field, the assessment of airport clearance obstacles is generally the responsibility of the designers of the design unit, who search for measurement data, calculate, draw, and finally compile and deliver the document. However, manual data processing has problems such as long cycle, easy errors, and multiple proofreading. Summary of the invention

[0004] Based on this, the purpose of the present application is to provide an airport clearance obstacle assessment method, device, electronic device and storage medium, which can improve the efficiency and accuracy of airport clearance obstacle assessment.

[0005] According to a first aspect of an embodiment of the present application, a method for assessing airport clearance obstacles is provided, comprising the following steps:

[0006] Obtain airport location information, airport environment information, aircraft flight information, and obstacle information;

[0007] Obtaining a first airport probability model according to the airport location information and the aircraft flight information;

[0008] Obtaining a first terrain model according to the airport environment information and obstacle information;

[0009] The first airport probability model and the first terrain model are matched to obtain the airport clearance obstacle assessment result.

[0010] According to a second aspect of an embodiment of the present application, there is provided an airport clearance obstacle assessment device, comprising:

[0011] Obstacle information acquisition module, used to obtain airport location information, airport environment information, aircraft flight information and obstacle information;

[0012] A probability model acquisition module, used for acquiring a first airport probability model according to the airport location information and the aircraft flight information;

[0013] A terrain model acquisition module, used to obtain a first terrain model according to airport environment information and obstacle information;

[0014] The evaluation result acquisition module is used to match the first airport probability model and the first terrain model to obtain the airport clearance obstacle evaluation result.

[0015] According to a third aspect of an embodiment of the present application, there is provided an electronic device, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing any of the above-mentioned airport clearance obstacle assessment methods.

[0016] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the airport clearance obstacle assessment method as described in any one of the above items is implemented.

[0017] The embodiment of the present application obtains airport location information, airport environment information, aircraft flight information and obstacle information; obtains a first airport probability model based on the airport location information and aircraft flight information; obtains a first terrain model based on the airport environment information and obstacle information; matches the first airport probability model with the first terrain model to obtain an airport clearance obstacle assessment result. The present application improves the accuracy of the generation of the first airport probability model and the first terrain model by introducing airport environment information and aircraft flight information, thereby improving the accuracy of the airport clearance obstacle assessment, and does not require manual processing, thereby improving the efficiency of the airport clearance obstacle assessment.

[0018] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application.

[0019] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a flow chart of an airport clearance obstacle assessment method provided in one embodiment of the present application;

[0021] Figure 2 A structural block diagram of an airport clearance obstacle assessment device provided in one embodiment of the present application;

[0022] Figure 3 A schematic block diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0024] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0025] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0026] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0027] In addition, in the description of this application, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0028] In order to better understand the design scheme of the present application, it is explained below in conjunction with specific application scenarios.

[0029] The airport clearance obstacle assessment method of the embodiment of the present application can be executed by an airport clearance obstacle assessment device, and the airport clearance obstacle assessment device can be implemented by software and / or hardware. The airport clearance obstacle assessment device can be composed of two or more physical entities, or it can be composed of one physical entity. The hardware pointed to by the airport clearance obstacle assessment device essentially refers to computer equipment. For example, the airport clearance obstacle assessment device can be a computer, a mobile phone, a tablet or other smart device.

[0030] In order to better understand the design scheme of the present application, the following first introduces the airport clearance obstacle assessment method of the related art.

[0031] In the current aviation field, the assessment of airport clearance obstacles is generally the responsibility of the designers of the design unit, who search for measurement data, calculate, draw pictures, and finally compile and deliver the documents. Manual data processing has problems such as long cycle, easy errors, and multiple proofreading.

[0032] There are some auxiliary tools available, usually in the form of PC clients, which input various parameters such as the latitude and longitude of obstacles, types, etc. to generate various obstacle restriction surfaces. However, such tools are limited to the reference level, because the data source is single and the static model is used, which cannot be adapted to the actual situation, resulting in large errors and low accuracy in the final evaluation results.

[0033] To this end, an embodiment of the present application proposes an airport clearance obstacle assessment method.

[0034] See also Figure 1 , Figure 1 A flowchart of an airport clearance obstacle assessment method provided in one embodiment of the present application, the method includes the following steps:

[0035] S10: Acquire airport location information, airport environment information, aircraft flight information, and obstacle information.

[0036] The airport location information includes, but is not limited to, the location information of the airport area, the location information of the airport runway area, the length, width and grade of the airport runway, the height of the runway reference point and the longitude and latitude of the runway center point. The airport environment information includes, but is not limited to, the topographic data near or around the airport. The aircraft flight information includes, but is not limited to, the wind speed data, temperature data, and the flight path of the aircraft above or around the airport. The obstacle information includes, but is not limited to, the name of the obstacle, the type of obstacle, the altitude of the obstacle, the longitude and latitude of the obstacle, the magnetic direction and distance of the obstacle relative to the airport, etc.

[0037] In the embodiment of the present application, the airport location information and airport environment information can be obtained from the Aeronautical Information Publication (AIP), and updated airport location information and airport environment information can be obtained from the navigation notice of the civil aviation telegram according to the navigation notice compilation and issuance specifications and navigation notice code selection specifications, obstacle information can be obtained from the obstacle database, and aircraft flight information can be obtained from the ground automatic receiving device. Among them, the ground automatic receiving device receives the aviation flight information sent by the aircraft, and the ground automatic receiving device includes but is not limited to the ADS-B receiving device and some receiving devices based on the ground-to-air data link protocol.

[0038] S20: Obtain a first airport probability model according to the airport location information and aircraft flight information.

[0039] The first airport probability model includes several clearance obstacle limitation surfaces, including conical surface, inner horizontal surface, inner approach surface, approach surface, transition surface, inner transition surface, missed approach surface and take-off climb surface.

[0040] In the embodiment of the present application, the first airport probability model can be directly generated according to the airport location information. In this case, the first airport probability model is a static model. The first airport probability model can also be generated according to the airport location information and the aircraft flight information. In this case, the first airport probability model is a dynamic model.

[0041] S30: Obtain a first terrain model according to the airport environment information and obstacle information.

[0042] The first terrain model is a three-dimensional space model obtained by fitting the obstacle and the terrain within the range where the obstacle is located.

[0043] In the embodiment of the present application, obstacle information input by a user can be received, and the obstacle information can be searched and matched in the obstacle database to determine whether the obstacle information is historical obstacle information. If so, the created terrain model is called. If not, a terrain model is generated according to the obstacle information. A first terrain model is generated according to the terrain model and the airport environment information.

[0044] S40: Matching the first airport probability model and the first terrain model to obtain an airport clearance obstacle assessment result.

[0045] In the embodiment of the present application, whether the obstacle passes the airport clearance assessment is determined by evaluating whether the obstacle limitation surface in the first airport probability model intersects or overlaps with the first terrain model. Specifically, if the first terrain model penetrates the first airport probability model above due to its abrupt shape, it is determined that the obstacle does not pass the airport clearance assessment. If the first terrain model does not penetrate the first airport probability model above, it is determined that the obstacle passes the airport clearance assessment.

[0046] By using the embodiment of the present application, by acquiring airport location information, airport environment information, aircraft flight information and obstacle information;

[0047] According to the airport location information and the aircraft flight information, a first airport probability model is obtained; according to the airport environment information and the obstacle information, a first terrain model is obtained; the first airport probability model and the first terrain model are matched to obtain the airport clearance obstacle assessment result. This application improves the accuracy of the first airport probability model and the first terrain model by introducing the airport environment information and the aircraft flight information, thereby improving the accuracy of the airport clearance obstacle assessment, and does not require manual processing, thereby improving the efficiency of the airport clearance obstacle assessment.

[0048] In an optional embodiment, the aircraft flight information includes wind speed data, temperature data, and a number of flight procedures. Step S20 includes steps S21 to S22, which are specifically as follows:

[0049] S21: Generate an airport probability model based on the airport location information.

[0050] Among them, an airport probability model generation tool can be used to generate a corresponding airport probability model from the airport location information.

[0051] S22: Optimizing the airport probability model according to the wind speed data, the temperature data and a number of flight procedures, the first airport probability model.

[0052] Among them, the flight procedure is a series of maneuvering flights carried out in sequence as specified for aircraft operations, including flight routes, altitudes and maneuvering areas. Specifically, the flight procedure includes several flight paths.

[0053] In the embodiment of the present application, the trajectory of the aircraft is more susceptible to the influence of aerodynamics when the attitude is adjusted. When the aircraft is turning, that is, when the aircraft is making a curved motion, the adjustment of its attitude will introduce additional changes in maneuverability, thereby increasing the instability of the trajectory. In this process, the influence of temperature and wind is more prominent, and the curved path becomes more unreliable than the straight path. Therefore, the influence of wind speed and temperature on each flight path in the flight program is considered, and the airport probability model is optimized according to the flight path to obtain the first airport probability model.

[0054] Based on wind speed data, temperature data and several flight procedures, the accuracy of generating the first airport probability model can be improved.

[0055] In an optional embodiment, step S22 includes steps S221 to S225, which are specifically as follows:

[0056] S221: Traverse each flight path, determine the first angle between the current flight path and the next flight path of the current flight path and the first ratio of the length of the current flight path to the sum of the lengths of all flight paths; based on the first angle and the first ratio, determine the weight ratio of the curved path corresponding to the current flight path, until the weight ratio of the curved path corresponding to each flight path is determined.

[0057] In the embodiment of the present application, the expression of the curve path weight ratio is as follows:

[0058]

[0059] Among them, x represents the weight ratio of the curve path, a represents the first angle, and b represents the first ratio.

[0060] S222: Traverse each flight path, divide the current flight path into an initial segment, a middle segment and a final segment, determine the second angle between the initial segment and the final segment, and the second ratio of the middle segment to the total length of all flight paths; determine the average curve path weight ratio corresponding to the current flight path based on the second angle and the second ratio, until the average curve path weight ratio corresponding to each flight path is determined.

[0061] In the embodiment of the present application, the expression of the average curve path weight ratio is as follows:

[0062] y=B*ln(A / 15) / Π

[0063] Among them, y represents the average curve path weight ratio, A represents the second angle, and B represents the second ratio.

[0064] S223: If the curve path weight ratio is greater than the corresponding average curve path weight ratio, calculate the standard deviation of the average curve path weight ratio.

[0065] In an embodiment of the present application, after obtaining the average curve path weight ratio corresponding to each flight path, the standard deviation calculation formula can be used to calculate the standard deviation corresponding to all flight paths.

[0066] S224: Determine the impact factor of wind speed data and temperature data on each flight path.

[0067] In the embodiment of the present application, wind and temperature will have different effects on the aircraft depending on the flight path, forming three types of events: favorable events, unfavorable events, and no-effect events. Among them, the influencing factors include a first influencing factor, a second influencing factor, and a third influencing factor. The first influencing factor is used to indicate a favorable event, that is, the wind speed and temperature are favorable to the flight path, the second influencing factor is used to indicate an unfavorable event, that is, the wind speed and temperature are not favorable to the flight path, and the third influencing factor is used to indicate a no-effect event, that is, the wind speed and temperature do not affect the flight path.

[0068] S225: Optimize the airport probability model according to the standard deviation and the influencing factor to obtain the first airport probability model.

[0069] In an embodiment of the present application, the standard deviation and the influencing factor determine the model parameters in the airport probability model. According to the standard deviation and the influencing factor, the model parameters in the airport probability model are optimized to obtain a first airport probability model.

[0070] According to wind speed data, temperature data and several flight procedures, the first airport probability model can be automatically and quickly obtained.

[0071] In an optional embodiment, step S225 includes steps S2251 to S2252, which are specifically as follows:

[0072] S2251: If the influencing factor is the first influencing factor, multiply the standard deviation by the preset weight to obtain a first product result; subtract the standard deviation from the product result to obtain a first weight; according to the first weight, iterate the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function in the airport probability model until the number of iterations meets the first preset number to obtain a first airport probability model; wherein the first influencing factor is used to indicate that the wind speed and temperature are favorable to the flight path.

[0073] In the embodiment of the present application, the expression of the first weight is as follows:

[0074] P1=P(1-K)

[0075] Among them, P1 represents the first weight, P represents the preset weight, and K represents the standard deviation.

[0076] S2252: If the influencing factor is the second influencing factor, multiply the standard deviation by the preset weight to obtain a first product result; add the standard deviation and the product result to obtain a second weight; according to the second weight, iterate the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function in the airport probability model until the number of iterations meets the first preset number to obtain a first airport probability model; wherein the second influencing factor is used to indicate that the wind speed and temperature are not favorable for the flight path.

[0077] In the embodiment of the present application, the expression of the second weight is as follows:

[0078] P2=P(1+K)

[0079] Wherein, P2 represents the second weight.

[0080] Since the accuracy optimization of the airport probability model depends on the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function, optimizing the first parameter and the second parameter according to the first weight and the second weight can improve the accuracy of generating the first airport probability model.

[0081] In an optional embodiment, the airport environment information includes GIS data and magnetic variation data, and step S30 includes steps S31 to S32, which are specifically as follows:

[0082] S31: Generate a terrain model based on obstacle information.

[0083] Among them, a terrain model generation tool can be used to generate a corresponding terrain model from obstacle information.

[0084] S32: Optimize the terrain model according to the GIS data and the magnetic variation data to obtain a first terrain model.

[0085] Magnetic variation is the angle between magnetic north and true north. Magnetic variation varies from place to place and changes over time. Changes in magnetic variation can affect navigation accuracy and pose potential risks to flight safety.

[0086] In the embodiment of the present application, the terrain model is optimized through GIS data and magnetic variation data, thereby improving the accuracy of generating the first terrain model.

[0087] In an optional embodiment, step S32 includes step S321, which is specifically as follows:

[0088] S321: According to the GIS data, the third parameter of the GIS modification function in the terrain model is iterated in a loop, and according to the magnetic variation data, the fourth parameter of the magnetic variation modification function in the terrain model is iterated in a loop until the number of iterations meets the second preset number, so as to obtain the first terrain model.

[0089] In an embodiment of the present application, since the accuracy optimization of the terrain model depends on the third parameter of the GIS modification function and the fourth parameter of the magnetic variation modification function, the accuracy of generating the first terrain model can be improved by optimizing the third parameter and the fourth parameter according to the GIS data and the magnetic variation data.

[0090] In an optional embodiment, step S40 includes steps S41 to S42, which are specifically as follows:

[0091] S41: Obtaining clearance curve coordinates according to the first airport probability model; and obtaining terrain curve coordinates according to the first terrain model.

[0092] Among them, the clearance curve coordinates refer to the coordinates of points on each obstacle limitation surface. The terrain curve coordinates refer to the coordinates of points on the obstacle.

[0093] S42: Determine whether there is interference between the terrain curve coordinates and the clearance curve coordinates; if there is interference, determine that the obstacle has not passed the airport clearance assessment; if there is no interference, determine that the obstacle has passed the airport clearance assessment.

[0094] In the embodiment of the present application, the distance between the terrain curve coordinates and the clearance curve coordinates can be calculated. If the distance is greater than or equal to a preset threshold, it is determined that the terrain curve coordinates and the clearance curve coordinates interfere with each other, and the obstacle fails the airport clearance assessment. If the distance is less than the preset threshold, it is determined that the terrain curve coordinates and the clearance curve coordinates do not interfere with each other, and the obstacle passes the airport clearance assessment.

[0095] By comparing the coordinates of the terrain curve with the coordinates of the clearance curve, the airport clearance obstacle assessment results can be obtained automatically and quickly.

[0096] The present application also provides a device embodiment that can be used to execute the contents of the airport clearance obstacle assessment method in the embodiment of the present application. For details not disclosed in the device embodiment of the present application, please refer to the contents of the airport clearance obstacle assessment method in the embodiment of the present application.

[0097] See also Figure 2 , which shows a schematic diagram of the structure of an airport clearance obstacle assessment device provided by an embodiment of the present application. The airport clearance obstacle assessment device 5 provided by the embodiment of the present application includes:

[0098] The obstacle information acquisition module 51 is used to acquire airport location information, airport environment information, aircraft flight information and obstacle information;

[0099] The probability model obtaining module 52 is used to obtain a first airport probability model according to the airport location information and the aircraft flight information;

[0100] A terrain model obtaining module 53, used to obtain a first terrain model according to the airport environment information and obstacle information;

[0101] The evaluation result obtaining module 54 is used to match the first airport probability model and the first terrain model to obtain the airport clearance obstacle evaluation result.

[0102] Optional, probability model acquisition module, including:

[0103] A probability model generating unit, used for generating an airport probability model according to the airport location information;

[0104] The probability model optimization unit is used to optimize the airport probability model according to the wind speed data, the temperature data and a plurality of flight programs to obtain a first airport probability model.

[0105] Optional, probabilistic model optimization unit, including:

[0106] A curve path weight ratio determination unit is used to traverse each flight path, determine a first angle between a current flight path and a flight path next to the current flight path, and a first ratio between the length of the current flight path and the sum of the lengths of all flight paths; determine the curve path weight ratio corresponding to the current flight path according to the first angle and the first ratio, until the curve path weight ratio corresponding to each flight path is determined;

[0107] The average curve path weight ratio determination unit is used to traverse each flight path, divide the current flight path into an initial path segment, a middle path segment and a final path segment, determine a second angle between the initial path segment and the final path segment and a second ratio between the middle path segment and the sum of the lengths of all flight paths; determine the average curve path weight ratio corresponding to the current flight path according to the second angle and the second ratio, until the average curve path weight ratio corresponding to each flight path is determined;

[0108] A standard deviation calculation unit, for calculating the standard deviation of the average curve path weight ratio if the curve path weight ratio is greater than the corresponding average curve path weight ratio;

[0109] An influence factor determination unit, used to determine the influence factor of wind speed data and temperature data on each flight path;

[0110] The first airport probability model obtaining unit is used to optimize the airport probability model according to the standard deviation and the influencing factor to obtain the first airport probability model.

[0111] Optionally, the first airport probability model obtaining unit includes:

[0112] The first loop iteration unit is used for, if the influencing factor is the first influencing factor, multiplying the standard deviation by the preset weight to obtain a first product result; subtracting the standard deviation from the product result to obtain a first weight; and iterating the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function in the airport probability model according to the first weight until the number of iterations meets the first preset number, thereby obtaining a first airport probability model; wherein the first influencing factor is used to indicate that the wind speed and temperature are favorable to the flight path;

[0113] The second loop iteration unit is used to, if the influencing factor is the second influencing factor, multiply the standard deviation by the preset weight to obtain a first product result; add the standard deviation and the product result to obtain a second weight; and according to the second weight, iterate the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function in the airport probability model until the number of iterations meets the first preset number of times to obtain a first airport probability model; wherein the second influencing factor is used to indicate that the wind speed and temperature are not favorable for the flight path.

[0114] Optional, terrain model acquisition module, including:

[0115] A terrain model generating unit, used for generating a terrain model according to obstacle information;

[0116] The first terrain model obtaining unit is used to optimize the terrain model according to the GIS data and the magnetic variation data to obtain the first terrain model.

[0117] Optionally, the first terrain model obtaining unit includes:

[0118] The third loop iteration unit is used to loop iterate the third parameter of the GIS modification function in the terrain model according to the GIS data, and to loop iterate the fourth parameter of the magnetic variation modification function in the terrain model according to the magnetic variation data, until the number of iterations meets the second preset number, so as to obtain the first terrain model.

[0119] Optional, evaluation result acquisition module, including:

[0120] The curve coordinate obtaining unit is used to obtain the clearance curve coordinates according to the first airport probability model; and obtain the terrain curve coordinates according to the first terrain model;

[0121] The coordinate interference judgment unit is used to judge whether there is interference between the terrain curve coordinates and the clearance curve coordinates; if there is interference, it is determined that the obstacle has not passed the airport clearance assessment; if there is no interference, it is determined that the obstacle has passed the airport clearance assessment.

[0122] By using the embodiment of the present application, the airport location information, airport environment information, aircraft flight information and obstacle information are obtained; the first airport probability model is obtained according to the airport location information and aircraft flight information; the first terrain model is obtained according to the airport environment information and obstacle information; the first airport probability model and the first terrain model are matched to obtain the airport clearance obstacle assessment result. The present application improves the accuracy of the generation of the first airport probability model and the first terrain model by introducing the airport environment information and aircraft flight information, thereby improving the accuracy of the airport clearance obstacle assessment, and does not require manual processing, thereby improving the efficiency of the airport clearance obstacle assessment.

[0123] The present application also provides a device embodiment that can be used to execute the contents of the airport clearance obstacle assessment method in the embodiment of the present application. For details not disclosed in the device embodiment of the present application, please refer to the contents of the airport clearance obstacle assessment method in the embodiment of the present application.

[0124] See also Figure 3 The present application also provides an electronic device 300, which may be a computer, a mobile phone, a tablet computer, an airport clearance obstacle assessment device, etc. In an exemplary embodiment of the present application, the electronic device 300 is an airport clearance obstacle assessment device, and the airport clearance obstacle assessment device includes: at least one processor 301, at least one memory 302, at least one display, at least one network interface 303, a user interface 304, and at least one communication bus 305.

[0125] The user interface 304 is mainly used to provide an input interface for the user and obtain data input by the user. Optionally, the user interface may also include a standard wired interface or a wireless interface.

[0126] The network interface 303 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0127] The communication bus 305 is used to realize the connection and communication between these components.

[0128] Among them, the processor 301 may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Optionally, the processor can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor can integrate one or more combinations of central processing unit (Central Processing Unit, CPU), image processor (Graphics Processing Unit, GPU) and modem. Among them, the CPU mainly processes the operating system, user interface and application program, etc.; the GPU is responsible for rendering and drawing the content to be displayed by the display layer; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor, but implemented by a single chip.

[0129] Among them, the memory 302 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory includes a non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory may also be optionally at least one storage device located away from the aforementioned processor. As Figure 3 As shown, the memory as a computer storage medium may include an operating system, a network communication module, a user interface module, and an operating application program.

[0130] The processor can be used to call the application of the airport clearance obstacle assessment method stored in the memory, and specifically execute the steps of the airport clearance obstacle assessment method in the above-mentioned embodiment. The specific execution process can be referred to the specific description shown in the embodiment, which will not be repeated here.

[0131] The present application also provides a computer-readable storage medium on which a computer program is stored, and the instructions are suitable for being loaded by a processor and executing the steps of the airport clearance obstacle assessment method of the above-mentioned embodiment. The specific execution process can refer to the specific description shown in the embodiment, which will not be repeated here. The device where the storage medium is located can be a personal computer, a laptop computer, a smart phone, a tablet computer and other electronic devices.

[0132] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial description of the method embodiments. The device embodiments described above are merely schematic, wherein the components described as separate parts may or may not be physically separated, and the parts displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0133] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0134] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the function selected in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 function selected in a box or multiple boxes.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 steps for the function selected in a box or multiple boxes.

[0136] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0137] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0138] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0139] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0140] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for assessing airport clearance obstacles, characterized in that: The steps include: Obtain airport location information, airport environment information, aircraft flight information, and obstacle information; A first airport probability model is obtained according to the airport location information and the aircraft flight information; wherein the aircraft flight information includes wind speed data, temperature data and a number of flight programs; each of the flight programs includes a number of flight paths; an airport probability model is generated according to the airport location information; each of the flight paths is traversed to determine a first angle between a current flight path and a flight path next to the current flight path and a first ratio between the length of the current flight path and the sum of the lengths of all flight paths; a weight proportion of the curved path corresponding to the current flight path is determined according to the first angle and the first ratio, until a weight proportion of the curved path corresponding to each of the flight paths is determined; each of the flight paths is traversed to divide the current flight path into an initial segment, an intermediate segment and a final segment, and a ratio between the initial segment and the final segment is determined. a second angle of the segments and a second ratio of the length of the middle segment of the path to the sum of the lengths of all flight paths; according to the second angle and the second ratio, determining the average curve path weight ratio corresponding to the current flight path, until the average curve path weight ratio corresponding to each flight path is determined; if the curve path weight ratio is greater than the corresponding average curve path weight ratio, calculating the standard deviation of the average curve path weight ratio; determining the influence factor of the wind speed data and the temperature data on each flight path; according to the standard deviation and the influence factor, optimizing the airport probability model to obtain the first airport probability model; the first airport probability model includes a plurality of clearance obstacle limitation surfaces; the clearance obstacle limitation surfaces include a conical surface, an inner horizontal surface, an inner approach surface, an approach surface, a transition surface, an inner transition surface, a missed approach surface and a take-off climb surface; Obtaining a first terrain model according to the airport environment information and the obstacle information; The first airport probability model and the first terrain model are matched to obtain an airport clearance obstacle assessment result.

2. The airport clearance obstacle assessment method according to claim 1, characterized in that: The step of optimizing the airport probability model according to the standard deviation and the influencing factor, the first airport probability model, comprises: If the influencing factor is the first influencing factor, multiply the standard deviation by a preset weight to obtain a first product result; subtract the standard deviation from the product result to obtain a first weight; according to the first weight, iterate the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function in the airport probability model until the number of iterations meets the first preset number, and obtain the first airport probability model; wherein the first influencing factor is used to indicate that the wind speed and temperature are favorable to the flight path; If the influencing factor is a second influencing factor, multiply the standard deviation by a preset weight to obtain a first product result; add the standard deviation to the product result to obtain a second weight; according to the second weight, iterate the first parameter in the wind speed correction modifier function and the second parameter in the temperature correction modifier function in the airport probability model until the number of iterations meets the first preset number to obtain a first airport probability model; wherein the second influencing factor is used to indicate that the wind speed and temperature are not favorable for the flight path.

3. The airport clearance obstacle assessment method according to claim 1, characterized in that: The airport environment information includes GIS data and magnetic variation data; The step of obtaining a first terrain model according to the airport environment information and the obstacle information comprises: generating a terrain model according to the obstacle information; The terrain model is optimized according to the GIS data and the magnetic variation data to obtain a first terrain model.

4. The airport clearance obstacle assessment method according to claim 3, characterized in that: The step of optimizing the terrain model according to the GIS data and the magnetic variation data to obtain a first terrain model comprises: According to the GIS data, the third parameter of the GIS modification function in the terrain model is iterated in a loop, and according to the magnetic variation data, the fourth parameter of the magnetic variation modification function in the terrain model is iterated in a loop until the number of iterations meets the second preset number, so as to obtain the first terrain model.

5. The airport clearance obstacle assessment method according to any one of claims 1 to 4, characterized in that: The step of matching the first airport probability model and the first terrain model to obtain an airport clearance obstacle assessment result includes: According to the first airport probability model, obtaining clearance curve coordinates; according to the first terrain model, obtaining terrain curve coordinates; It is determined whether the terrain curve coordinates and the clearance curve coordinates interfere with each other; if there is interference, it is determined that the obstacle has not passed the airport clearance assessment; if there is no interference, it is determined that the obstacle has passed the airport clearance assessment.

6. An airport clearance obstacle assessment device, characterized in that: include: Obstacle information acquisition module, used to obtain airport location information, airport environment information, aircraft flight information and obstacle information; A probability model acquisition module is used to obtain a first airport probability model according to the airport location information and the aircraft flight information; wherein the aircraft flight information includes wind speed data, temperature data and a plurality of flight programs; each of the flight programs includes a plurality of flight paths; an airport probability model is generated according to the airport location information; each of the flight paths is traversed to determine a first angle between a current flight path and a flight path next to the current flight path and a first ratio of the length of the current flight path to the sum of the lengths of all flight paths; according to the first angle and the first ratio, a weight proportion of a curved path corresponding to the current flight path is determined until a weight proportion of a curved path corresponding to each of the flight paths is determined; Traverse each of the flight paths, divide the current flight path into an initial segment, an intermediate segment and a final segment, determine a second angle between the initial segment and the final segment and a second ratio of the intermediate segment to the total length of all flight paths; determine the average curve path weight ratio corresponding to the current flight path according to the second angle and the second ratio, until the average curve path weight ratio corresponding to each of the flight paths is determined; if the curve path weight ratio is greater than the corresponding average curve path weight ratio, calculate the standard deviation of the average curve path weight ratio; determine the influence factor of the wind speed data and the temperature data on each of the flight paths; optimize the airport probability model according to the standard deviation and the influence factor to obtain the first airport probability model; the first airport probability model includes a plurality of clearance obstacle limitation surfaces; the clearance obstacle limitation surfaces include a conical surface, an inner horizontal surface, an inner approach surface, an approach surface, a transition surface, an inner transition surface, a missed approach surface and a take-off climb surface; A terrain model acquisition module, used to obtain a first terrain model according to the airport environment information and the obstacle information; The evaluation result acquisition module is used to match the first airport probability model and the first terrain model to obtain an airport clearance obstacle evaluation result.

7. An electronic device, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the airport clearance obstacle assessment method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the airport clearance obstacle assessment method according to any one of claims 1 to 5 is implemented.

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