Multi-source navigation announcement data model analysis processing display and PIB extraction method

Abstract

The invention discloses a multi-source navigation announcement data model analysis processing display and PIB extraction method, which comprises the following steps: constructing a data identification model containing a navigation announcement standard database, and constructing the navigation announcement standard database according to announcement message types, application ranges and effectiveness levels; obtaining a multi-source navigation announcement data stream, performing structured disassembly on the navigation announcement data stream, and storing the navigation announcement data stream in a navigation announcement standard database according to a hierarchical structure and a standard data format; obtaining all associated data covering the research object from the navigation announcement standard database based on the research object, and forming a navigation announcement data report file of the research object; and extracting point, line and surface data of all associated data of the research object, and visually displaying the point, line and surface data on a GIS geographic map. According to the method, efficient management and query of the navigation announcement data are realized, the navigation announcement data report file of the research object is formed, and information technology support in the aspect of navigation announcement is provided for making a flight plan or flying.

Description

Technical Field

[0001] This invention relates to the field of multi-source information processing and management of NOTAMs (Notifications to Airmen), and particularly to a method for parsing, processing, displaying, and extracting PIBs from a multi-source NOTAM data model. Background Technology

[0002] Notifications to Airmen (NOTAMs) are a crucial element in ensuring flight safety. They are responsible for delivering rapidly changing aeronautical information to pilots and aviation professionals in a timely and accurate manner. The content concerns operational changes, hazardous situations, and airspace shifts that may affect flight safety. Effective management and retrieval of NOTAM information, ensuring the flow of necessary data for flight safety, regularity, and efficiency, is an essential part of pre-flight preparation.

[0003] Currently, the level of airlines' processing and application of NOTAM information in China varies greatly. System providers need to adapt to different levels of source data for various NOTAMs and intelligence, and the message display formats are also diverse. Some systems are still at the stage of filtering NOTAMs by simple attribute matching, which requires a lot of time to obtain all the NOTAM information required by the flight crew. They cannot intuitively see the NOTAMs required for the flight route through a map, and they cannot efficiently extract this NOTAM information and provide it to the crew before the aircraft takes off. Summary of the Invention

[0004] The purpose of this invention is to provide a method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models. This method enables the efficient parsing and processing of NOTAM messages from multiple sources, storing them in a standard NOTAM database according to a hierarchical structure and standard data format. This achieves efficient management and querying of NOTAM data. Based on the research object, the method retrieves all related data covering the research object from the standard NOTAM database and forms a NOTAM data report file for the research object.

[0005] The objective of this invention is achieved through the following technical solution: A method for parsing, processing, displaying, and extracting PIBs from a multi-source NOTAM data model, the method comprising: S1. Construct a data identification model that includes a database of NOTAM standards. The NOTAM standard database is constructed according to the NOTAM message type, scope of application, and validity level. Each NOTAM type includes its corresponding standard data format. S2. Obtain the multi-source NOTAM data stream input data recognition model. The data recognition model performs structured decomposition of the NOTAM data stream and stores it in the NOTAM standard database according to hierarchical structure and standard data format. S3. Select routes, airlines, and / or airports as research objects. Based on the research objects, obtain all related data covering the research objects from the NOTAM standard database and form a NOTAM data report file for the research objects. Extract the point, line, and polygon data of all related data of the research objects and visualize them on a GIS geographic map.

[0006] To better implement this invention, the notification message types include general notifications, snow condition notifications, GRF snow condition notifications, volcanic ash notifications, and airline notifications; the standard data format includes two parts: a general standard part and a personalized standard part. The standard items in the general standard part include notification information and number, effective time, expiration time, effective period, validity, scope of application, plaintext content, altitude range, Q code, and other supplementary information. The plaintext content includes the original plaintext and a plaintext Chinese translation. The personalized standard part customizes the standard items based on the notification message type.

[0007] Preferably, in method S2, the data identification model performs a structured decomposition of the NOTAM data stream according to the NOTAM message type and standard data format, then identifies the sequence number, type identifier, and NOTAM level, and stores them in the NOTAM standard database in a corresponding manner using the addition or replacement method. The type identifier includes new NOTAM, canceled NOTAM, and replacement of original NOTAM. The NOTAM standard database obtains and stores the standard item content in sequence according to the hierarchical structure and standard data format.

[0008] Preferably, the data recognition model further includes a semantic correction and translation module. The semantic correction and translation module internally constructs a Chinese and foreign language civil aviation knowledge base. The semantic correction and translation module uses the Chinese and foreign language civil aviation knowledge base to perform semantic correction and plaintext translation processing on the NOTAM data stream and stores it in the NOTAM standard database. The standard items of the plaintext original text correspond to the storage of the semantically corrected and untranslated plaintext original text content, and the standard items of the plaintext Chinese translation correspond to the storage of the semantically corrected and translated plaintext Chinese translation content.

[0009] Preferably, in method S3, if the research object is a flight route, then the flight route corresponds to the flight route corresponding to the aircraft, and the flight route includes the take-off and landing airport, the take-off and landing route, and the air route; if the research object is an airline, then the airline includes the flight route data of all aircraft under the airline; if the research object is an airport, then the airport is the flight route data of the airport related to the take-off and landing of the aircraft.

[0010] Preferably, the NOTAM data report file is organized and constructed in sequence according to the NOTAM message type, scope of application, validity, and content.

[0011] Preferably, the points of all associated data of the research object include waypoints and navigation stations, the lines of all associated data of the research object include routes and segments, and the surfaces of all associated data of the research object include buffer zones of points or lines and areas affected by NOTAMs (Notices to Airmen).

[0012] Preferably, the point, line, and area data of all associated data of the research object are extracted and the latitude and longitude, waypoints, matching lines and segments, sector areas, airport area areas, angles, radii, distances, polygons, route information, and VOR navigation station information are identified and visualized on the GIS geographic map according to the built-in standard symbols and early warning configurations.

[0013] Preferably, visual charts are used as auxiliary files for the NOTAM data report file.

[0014] Preferably, the present invention further includes the following method: S4. Screen the standard database of NOTAMs for the research routes, perform attribute filtering and spatial calculations based on flight plans or directions to extract all navigation data that affect and involve flight routes, and visualize and display them on a GIS map or / and generate NOTAM PIB reports corresponding to flight routes.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: (1) This invention can realize the parsing and processing of notification messages from multiple sources of NOTAM data streams through efficient parsing methods, and store them in the NOTAM standard database according to hierarchical structure and standard data format, thereby realizing efficient management and query of NOTAM data; Based on the research object (including routes, airlines and airports), this invention obtains all related data covering the research object from the NOTAM standard database and forms the NOTAM data report file of the research object, providing information technology support for the formulation of flight plans or flight operations in terms of NOTAMs.

[0016] (2) This invention extracts the point, line and surface data of all related data of the research object and visualizes them on the GIS geographic map, which facilitates the accurate and intuitive display of the notification information related to the route and realizes the visualization of the point, line and surface data affected by the navigation notification data on the GIS geographic map. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the method in the embodiment; Figure 3 This is a schematic diagram illustrating the structured breakdown of a specific NOTAM (Notification to Airmen) data as an example. Figure 4 This is a schematic diagram of the semantic correction translation module used in the embodiment; Figure 5 This is a schematic diagram illustrating the construction of a Chinese and foreign language civil aviation knowledge base using the semantic correction translation module in the embodiment. Figure 6 This is a schematic diagram of the semantic correction translation module agent used in the embodiment; Figure 7 This is a schematic diagram illustrating the semantic correction translation module used in the embodiment after translation. Figure 8 This is a schematic diagram illustrating the use of a management system for notification management in this embodiment. Figure 9 This is a schematic diagram illustrating the use of the management system to query announcement data in the embodiment. Figure 10 This is an example diagram of capturing a NOTAM (Notification of Navigation) data report file in the embodiment; Figure 11 This is a schematic diagram illustrating the screening of flight routes and flight paths in method S4 of the embodiment; Figure 12 This is a schematic diagram illustrating the process of filtering flight routes associated with airports and intelligence regions in method S4 of the embodiment. Figure 13 This is a schematic diagram of the flight route association time filtering in method S4 of the embodiment; Figure 14 This is a schematic diagram of the airport filtering and selection based on flight routes in method S4 of the embodiment; Figure 15 This is a schematic diagram of filtering and screening the flight route association information area in method S4 of the embodiment; Figure 16 This is a schematic diagram illustrating the filtering of the upper and lower limits of the flight altitude for the Q item associated with flight routes in method S4 of the embodiment; Figure 17 This is a schematic diagram illustrating the filtering and selection of flight type codes related to flight routes (Q item) in method S4 of the embodiment. Figure 18 This is a schematic diagram illustrating the intersecting and matching filtering of flight route association buffer and Q-item GIS spatial data in method S4 of the embodiment; Figure 19 This is a visualization of the route study information on the GIS map in method S4 of the embodiment. Figure 20 This is a schematic diagram illustrating the principle of obtaining route navigation notice data in method S4 of the embodiment. Detailed Implementation

[0018] The present invention will be further described in detail below with reference to embodiments: Example like Figure 1 , Figure 2As shown, a method for parsing, processing, and extracting PIBs from multi-source NOTAM data models is presented. The method includes: S1. Construct a data identification model that includes a database of NOTAM (Notices to Airmen) standards. The NOTAM database is constructed according to the notification message type, scope of application, and validity level. Each notification type includes its corresponding standard data format. Notification message types include general NOTAMs, snow notifications, GRF (Gross Response Notices), volcanic ash notifications, and airline NOTAMs. The standard data format consists of two parts: a general standard section and a custom standard section. The general standard section includes the following standard items: notification information and number (generally corresponding to field A in the NOTAM data, a unique identifier for the NOTAM, in the format of letters / numbers / numbers), effective time (generally corresponding to field B in the NOTAM data, the time when the notification begins to take effect), expiration time (generally corresponding to field C in the NOTAM data, the time when the notification ceases to take effect), effective period, validity, scope of application (generally corresponding to field D in the NOTAM data, the airports, airspaces, etc. involved in the notification), plaintext content (generally corresponding to field E in the NOTAM data, the specific information of the notification), altitude range (generally corresponding to field F in the NOTAM data, the flight altitude layer to which the notification applies), Q code (generally corresponding to field Q in the NOTAM data, including four dimensions: information region, flight rules, facility type, and activity type), and other supplementary information. The plaintext content includes the original plaintext and a plaintext Chinese translation. The custom standard section is based on the notification message type and includes customized standard items.

[0019] S2. The data recognition model receives multi-source NOTAM (Notification of Flights) data streams. It then structurally decomposes the NOTAM data streams and stores them in a hierarchical, standard data format within the NOTAM standard database. The NOTAM data streams originate from third-party sources, air traffic control, airport management, weather stations, volcanic ash monitoring platforms, etc. The data recognition model can directly access the original intelligence data repository (e.g., weather stations, volcanic ash monitoring platforms) and obtain multi-source NOTAM data streams. This embodiment uses a single NOTAM data entry from the NOTAM data stream as an example to convert the NOTAM data into... Figure 3 The standard data format shown includes the following key information in the NOTAM (Notification of Navigation) header: message sending time, message class, sending address, issuance time, message serial number, message type, and affected message serial numbers. Item Q is a set of codes used in NOTAMs to efficiently and unambiguously describe changes in the status of navigational facilities, services, or hazards. Item A is the location of the notification. Item B is the effective date of the notification. Item C is the expiry date. Item D is the effective period. Item E is the body of the notification.

[0020] The data recognition model structurally decomposes the NOTAM data stream according to the NOTAM message type and standard data format (e.g., using regular expression matching for decomposition), obtaining all message lines from the original text after line splitting, and identifying the message header / body, specifically including: a. Matching message header information: b. After finding the message header, the message body begins at the fourth line below it. Extract key information from the message header, such as the message sending time, sequence number, message type, sending address, and issuance time. Regular expressions for identifying message types include those for identifying RQR, RQN, and RQC message types that do not require processing. Identify NOTAM (Notification of Navigation) signs: Identify volcanic ash warning signs: Identify snow warning signs: Identify the logo on the briefcase: ; Identify partial message flags: .

[0021] Identification serial number:

[0022] Identify the affected serial number for the cancellation / replacement report:

[0023] Identify the type of notice: This line contains the following identifiers: New announcement; Cancellation of notice; Replace the original announcement. Identify the announcement's severity level: Identify issuance time: ; Identify dispatch time: The message header information is split into spaces, and the last group is the dispatch time.

[0024] Identifying the sending address includes: 1. Locating a single NOF line: 2. Find the issuance time; 3. The first word remaining after removing the issuance time is SendNOF.

[0025] Identifying forwarding addresses includes: 1. Locating individual NOF lines. 2. Find the issuance date; 3. The first word remaining after removing the issuance date is TransferNOF. Identifying the receiving address includes: 1. Locating the hierarchy line: 2. The receiving address is obtained by removing the level from the level row.

[0026] Identify the various attribute information of a message according to its message type. Specific methods include: Identify option A: The 4-digit number indicates the location where the message originated.

[0027] Identify option B: This refers to the effective time in the format YYMMDDHHMMSS.

[0028] Identify Snow Conditions (Option B):

[0029] Identify option C: The following is the expiration time in YYMMDDHHMMSS format.

[0030] Identify option D: End of D section The content in the middle is a time period. Since there are many formats for effective time periods, this solution lists several matching methods for reference.

[0031] Identify item Q: The precautions include: 1. When the Q-item information area is OIIX, if the number of elements in the Q-line exceeds 8, delete the last two " / " characters; 2. When the Q-item information area is VYYF, if the number of elements in the Q-line exceeds 8, check if there is an element with "M / E". If so, remove the "M / E" character from that element. 3. When the Q item information area is SEFG, if the last element in line Q is "999", then delete that element. Identifying E, F, Q, and G items: The basic principle is the same as above. After parsing, the relevant information can be stored in the database for easy querying and use in subsequent announcements.

[0032] The serial number, type identifier, and notification level are identified and stored in the Notice to Airmen standard database using the addition or replacement method. The type identifier includes new notification, canceled notification, and replacement of original notification. The Notice to Airmen standard database obtains and stores the standard items in the order according to the hierarchical structure and standard data format.

[0033] In some embodiments, the data recognition model further includes a semantic correction and translation module. This module internally constructs a Chinese and foreign language civil aviation knowledge base. Using this knowledge base, the module performs semantic correction and plaintext translation on the NOTAM data stream and stores the corresponding data in the NOTAM standard database. The standard items for the plaintext original text correspond to the semantically corrected but untranslated plaintext original text content, while the standard items for the plaintext Chinese translation correspond to the semantically corrected and translated plaintext Chinese translation content. In this embodiment, the semantic correction and translation module takes the translation of item E in the NOTAM data as an example. Item E, through a systematic and structured description, fully defines the dynamically changing elements in the aviation operating environment, providing flight crews and operational support units with crucial information necessary for risk assessment and decision-making. Its expression is also diverse and has no fixed format; it includes various identification codes, and some international NOTAMs are in foreign languages ​​such as English. Figure 4 As shown, the semantic correction and translation module in this embodiment uses Alibaba's Bailian AI as an example to perform intelligent translation of NOTAM data; Figure 5 As shown, a Chinese and foreign language civil aviation knowledge base (containing relevant industry background knowledge) is built in the semantic correction and translation module. Figure 6 As shown, the semantic correction translation module constructs an agent to perform intelligent translation, and the agent is configured with the following tasks and jobs: 1. Foreign Language Translation: Accurately translate user-inputted foreign language content into Chinese; ensure that the translation results are grammatically and semantically accurate.

[0034] 2. Technical terminology processing: Identify and translate technical terms in the civil aviation field, and use the Chinese meanings from foreign language civil aviation knowledge bases to ensure the accuracy of technical terms.

[0035] 3. Translation of Notices to Airmen: Specializing in texts related to Notices to Airmen, taking into account the specific format and requirements of Notices to Airmen during translation.

[0036] 4. Restrictions: Translation is limited to texts related to civil aviation, particularly NOTAMs (Notifications to Airmen); the translation must use specialized terminology from the knowledge base and its corresponding Chinese meanings; accuracy and professionalism must be maintained, avoiding the introduction of personal opinions or biases; all output must conform to the standard format and requirements of NOTAMs. Figure 7 As shown in the example, this embodiment demonstrates the translation effect of a portion of the NOTAM (Notification to Airmen) data E by the semantic correction translation module.

[0037] The data recognition model of this invention decomposes the NOTAM data stream into a structured form and stores it in a NOTAM standard database according to a hierarchical structure and standard data format; for example... Figure 8 As shown, this embodiment can construct a notification management system for classifying, organizing, and querying navigation notification data streams; such as Figure 9As shown, the navigation notification management system allows for searching and querying of the navigation notification standard database according to its hierarchical structure or specific content.

[0038] S3. Select flight routes, airlines, and / or airports as research objects. If the research object is a flight route, the flight route corresponds to the flight path of the aircraft, including the take-off and landing airports, take-off and landing routes, and air routes. If the research object is an airline, the airline includes flight route data for all aircraft under the airline's fleet. If the research object is an airport, the airport includes flight route data for airports related to aircraft take-off and landing. Based on the research object, retrieve all relevant data covering the research object from the NOTAM standard database and form a NOTAM data report file for the research object. The NOTAM data report file is organized and constructed in the following order: NOTAM message type, scope of application, validity, and content. Figure 10 As shown in the example, this embodiment extracts a portion of the pages from the NOTAM data report file for demonstration purposes. Point, line, and polygon data of all associated data of the research object are extracted and visualized on a GIS geographic map. Preferably, the points of all associated data of the research object include waypoints and navigation stations; the lines of all associated data of the research object include routes and segments; and the polygons of all associated data of the research object include buffer zones of points or lines and NOTAM influence areas. The point, line, and polygon data of all associated data of the research object are extracted and latitude and longitude, waypoints, matching lines and segments, sector areas, airport area areas, angles, radii, distances, polygons, route information, and VOR navigation station information are visualized on the GIS geographic map according to built-in standard symbols (e.g., dedicated symbols used by navigation stations) and warning configurations (e.g., using red lines for line data warnings). Figure 11 As shown. Visual charts are obtained as auxiliary files for the Notice to Airmen (NOAAM) data report. Taking NOAAM message E in the NOAAM data stream as an example, the GIS spatial features are broken down and parsed, including lines, line buffers, polygons formed by waypoints, circles, sectors, flight segments, polygons, waypoints, navigation beacons, and other geographic features.

[0039] 1. Identify latitude and longitude: .

[0040] 2. Identify and match the standard line: .

[0041] 3. Identify segment E: .

[0042] 4. Identify the radius and unit attribute of item E: .

[0043] 5. Identify sectors: .

[0044] 6. Recognition angle: .

[0045] 7. Recognition radius: .

[0046] 8. Recognition distance: .

[0047] 9. Recognize polygons: .

[0048] 10. Identify VOR navigation console: .

[0049] 11. Identify the serial number: .

[0050] 12. Airport identification: .

[0051] 13. Identify the entire flight route information: .

[0052] 14. Identify key waypoints: @"AKVOR|AMVOR|ANVOR|EDVOR|FAVOR|GEVOR|GIVOR|IGVOR|ILVOR|INVOR|IVORA|IVORY|JIVOR|KAVOR|LEV OR|LIVOR|LUVOR|MAVOR|MIVOR|MOVOR|OLVOR|ORVOR|OSVOR|OVORA|PEVOR|POVOR|RIVOR|SIVOR|UVORA|UV ORI|VAVOR|VORAG|VORAX|VORDA|VOREG|VORET|VOREX|VORHE|VORIN|VORON|VORVI|15DME|ADMEC|ADMEG|A DMER|ADMES|ADMEX|DME12|EDMEK|IDMEN|IDMES|IDMET|NODME|ODMEL|ODMEN|ODMET|RADME|ZUDME|ENDBY" 15. Identify route closures: .

[0053] S4. Screen the NOTAM standard database for the research route, perform attribute filtering and spatial calculations based on the flight plan or direction to extract all navigation data affecting and related to the flight route, and visualize and / or generate a NOTAM PIB report corresponding to the flight route on a GIS map; specifically: based on the flight plan or direction, perform attribute filtering and spatial calculations based on the previously analyzed and processed NOTAM database to extract all navigation data affecting and related to the flight, and visualize and generate a PIB report on a GIS map. In some embodiments, such as Figures 11-20 As shown, this embodiment uses a specific flight route as a study route to screen flight routes and flight paths (see...). Figure 11 ); Obtain route data, including data on routes passing through airports and intelligence regions (such as...). Figure 12 As shown, the process involves filtering by airport and intelligence region associated with flight routes. Figure 13 As shown, perform airport filtering for flight routes, such as... Figure 13 As shown, perform airport filtering for flight routes, such as... Figure 14 As shown, perform airport filtering for flight routes; such as Figures 15-18 As shown, the process involves sequentially filtering the associated intelligence area, filtering the upper and lower limits of the associated Q-item flight altitude, filtering the associated Q-item flight type code, and filtering the associated buffer and Q-item GIS spatial data through intersection matching. This process yields all NOTAM data that affect and involve flight routes. The NOTAM data corresponding to the research routes is then visualized on the NOTAM GIS map.

[0054] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models, characterized in that: The methods include: S1. Construct a data identification model that includes a database of NOTAM standards. The NOTAM standard database is constructed according to the NOTAM message type, scope of application, and validity level. Each NOTAM type includes its corresponding standard data format. S2. Obtain the multi-source NOTAM data stream input data recognition model. The data recognition model performs structured decomposition of the NOTAM data stream and stores it in the NOTAM standard database according to hierarchical structure and standard data format. S3. Select routes, airlines, and / or airports as research objects. Based on the research objects, obtain all related data covering the research objects from the NOTAM standard database and form a NOTAM data report file for the research objects. Extract the point, line, and polygon data of all related data of the research objects and visualize them on a GIS geographic map.

2. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1, characterized in that: The notification message types include general notifications, snow condition notifications, GRF snow condition notifications, volcanic ash notifications, and airline notifications; the standard data format includes two parts: a general standard part and a personalized standard part. The standard items in the general standard part include notification information and number, effective time, expiration time, effective period, validity, scope of application, plaintext content, altitude range, Q code, and other supplementary information. The plaintext content includes the original plaintext and a plaintext Chinese translation. The personalized standard part customizes the standard items based on the notification message type.

3. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1, characterized in that: In method S2, the data identification model decomposes the NOTAM data stream into a structured form according to the NOTAM message type and standard data format. Then, it identifies the sequence number, type identifier, and NOTAM level, and stores them in the NOTAM standard database in the corresponding manner by adding or replacing. The type identifier includes new NOTAM, canceled NOTAM, and replacement of original NOTAM. The NOTAM standard database obtains and stores the standard items in the order of hierarchical structure and standard data format.

4. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1 or 2, characterized in that: The data recognition model also includes a semantic correction and translation module. The semantic correction and translation module has a Chinese and foreign language civil aviation knowledge base built inside. The semantic correction and translation module uses the Chinese and foreign language civil aviation knowledge base to perform semantic correction and plaintext translation on the NOTAM data stream and stores it in the NOTAM standard database. The standard items of the plaintext original text correspond to the storage of the semantically corrected and untranslated plaintext original text content, and the standard items of the plaintext Chinese translation correspond to the storage of the semantically corrected and translated plaintext Chinese translation content.

5. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1, characterized in that: In method S3, if the research object is a flight route, then the flight route corresponds to the flight route of the aircraft, and the flight route includes the take-off and landing airport, the take-off and landing route, and the air route; if the research object is an airline, then the airline includes the flight route data of all aircraft under the airline; if the research object is an airport, then the airport is the flight route data of the airport related to the take-off and landing of the aircraft.

6. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1, characterized in that: The NOTAM data report file is organized and constructed in the following order: NOTAM message type, scope of application, validity, and content.

7. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1, characterized in that: The points of all associated data of the research object include waypoints and navigation stations; the lines of all associated data of the research object include routes and segments; and the surfaces of all associated data of the research object include buffer zones of points or lines and areas affected by NOTAMs (Notices to Airmen).

8. A method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1 or 7, characterized in that: Extract point, line, and area data of all related data of the research object and identify latitude and longitude, waypoints, matching lines and segments, sector areas, airport area areas, angles, radii, distances, polygons, route information, and VOR navigation station information. Then, visualize the data on the GIS geographic map according to the built-in standard symbols and early warning configurations.

9. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 8, characterized in that: Obtain visual charts as supplementary files for the NOTAM data report.

10. The method for parsing, processing, displaying, and extracting PIBs from multi-source NOTAM data models according to claim 1, characterized in that: It also includes the following methods: S4. Screen the standard database of NOTAMs for the research routes, perform attribute filtering and spatial calculations based on flight plans or directions to extract all navigation data that affect and involve flight routes, and visualize and display them on a GIS map or / and generate NOTAM PIB reports corresponding to flight routes.

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