A flight auxiliary decision-making method based on multi-source aviation information priority calculation

Abstract

A flight auxiliary decision-making method based on multi-source aviation information priority calculation, comprising the following steps: step 1, constructing a three-layer aviation information model; step 2, defining a typical flight scene and dividing a standard flight stage; step 3, constructing a structured flight stage-data element information priority matrix and a flight scene-data element information priority matrix; step 4, judging the current flight stage according to real-time data of multi-source aviation information; step 5, identifying the current flight scene according to real-time data of multi-source aviation information and logical rules of the typical flight scene; step 6, calculating the comprehensive priority of information according to the current flight stage and the flight scene; and step 7, generating flight decision information according to the comprehensive priority and controlling the information content and display form of the onboard display. The application controls the information content of air-ground link transmission and onboard device display in the typical scene, generates a flight decision information demand model, and assists the pilot in making flight decisions.

Description

Technical Field

[0001] This invention relates to the field of air traffic management, and in particular to a flight assistance decision-making method based on priority calculation of multi-source aviation information. Background Technology

[0002] The modern aviation industry is undergoing tremendous changes, with autonomy, digitalization, and flexibility being the future development trends. The current control model is centered on air traffic controllers. However, with the continuous growth in air transport demand and the increasing aircraft density within each control area, the workload of controllers in handling handover and coordination has surged, ultimately exceeding their capacity. To adapt to the increasingly busy air transport demands, the International Civil Aviation Organization (ICAO) has proposed the concept of trajectory-based operations, and the European Union Aviation Safety Agency (EASA) plans to transform controlled airspace into free-route airspace by 2030, attempting to shift air traffic control from the traditional controller-centric flight decision-making model to a more flexible autonomous operation model. The core concept of autonomous operation is the delegation of some decision-making power from controllers to pilots, who can independently choose flight routes within free-route airspace.

[0003] Implementing autonomous operation requires access to various air traffic control services, including communication, navigation, surveillance, planning, meteorology, and aeronautical information, to assist pilots in achieving comprehensive situational awareness and collaborative decision-making. Existing systems can provide pilots with some air traffic control services, but because the information comes from independently operating air traffic control systems, they cannot present a comprehensive situation and pose a risk of information overload. Furthermore, due to information silos, most systems lack sufficient integration and filtering of information to highlight relevant content for specific flight scenarios. In some complex flight scenarios, external anomalies or emergencies can affect pilots' reaction speed and perception capabilities. For example, in thunderstorms, adverse external conditions increase pilot stress and workload, leading to a decline in their information retrieval and decision-making abilities. Therefore, filtering key information for specific scenarios and displaying it in a user-friendly manner on a multi-function display based on the flight scenario and flight phase reduces cognitive barriers, supports pilots in performing their tasks, and helps them focus more on flight operations, which is crucial for improving flight efficiency. Summary of the Invention

[0004] Purpose of the invention: The technical problem to be solved by the present invention is to provide a flight assistance decision-making method based on priority calculation of multi-source aviation information, which addresses the shortcomings of the existing technology.

[0005] To address the aforementioned technical problems, this invention discloses a flight assistance decision-making method based on multi-source aeronautical information priority calculation, characterized by comprising the following steps:

[0006] Step 1: Analyze multi-source heterogeneous aviation data and construct a three-layer aviation information model based on data type, data carrier, and data element;

[0007] Step 1-1: Analyze the raw data from different aviation systems, classify them according to the functional type or semantic type of the information, and construct the top layer of the three-layer aviation information model - the data type layer;

[0008] Steps 1-2: Based on the logical or physical source of the information, aviation information is subdivided into data carriers. The data carriers can identify the source entity of the information. The data carriers constitute the middle layer of the three-layer aviation information model - the data carrier layer.

[0009] Steps 1-3: Different data carriers contain data elements with different data structures. A data element can be represented as a specific, quantifiable, and identifiable information item. The data element is the smallest unit of information processing and constitutes the bottom layer of the three-layer information model - the data element layer.

[0010] Step 2: Define typical flight scenarios and divide standard flight phases;

[0011] Step 2-1: Define typical flight scenarios based on operational status and risk sources. Operational status includes normal and abnormal operation, and risk sources include weather impacts and flight conflicts. Design typical flight scenarios such as single-aircraft TBO operation scenario under safe conditions, flight conflict early warning scenario, autonomous rerouting operation scenario under severe weather conditions, and cornering and straightening operation scenario under flexible airspace use. Integrate multi-source contextual information such as weather radar echo intensity, conflict warning codes, air-to-ground data link instructions, and flow control messages, and preset logical judgment conditions for flight scenarios.

[0012] Step 2-2: Based on the BADA (Base of Aircraft Data) standard published by the European Air Traffic Management Organization, the flight phase is divided into takeoff, initial climb, climb, cruise, descent, approach, and landing phases. The boundary conditions of the flight phase are jointly defined by the combined threshold of aircraft pressure altitude, calculated airspeed, and Mach number. The typical scenarios involved in this application are concentrated in the cruise phase. Based on the characteristics of the scenarios, the flight phase is re-divided to add cruise climb and cruise descent phases.

[0013] Step 3: Construct a structured priority matrix for flight phase-data element information and a priority matrix for flight scenario-data element information;

[0014] Step 3-1: Select experts who meet the evaluation qualifications from active pilots, flight instructors and related practitioners. Some newly recruited pilots should be included as members of the expert group to make up for the experience blind spots caused by the long-term fixed behavior patterns of senior pilots.

[0015] Step 3-2: Design a questionnaire on the priority of information elements based on flight scenarios and flight phases. Usually, at least two rounds of questionnaires are designed. The first round of questionnaires is an open-ended survey to form an initial information list for different flight phases in typical scenarios. The second round of questionnaires is a targeted survey, focusing on quantitative scoring of key information and controversial information. The information priority includes at least three levels: high, medium and low.

[0016] Step 3-3: Through multiple rounds of anonymous feedback, a statistical information element importance scale is used to calculate a weighted average of the expert group's group scale, resulting in a structured flight phase-data element information priority matrix and a flight scenario-data element information priority matrix.

[0017] Step 4: Determine the current flight phase based on real-time data from multi-source aviation information;

[0018] Step 4-1: Set a hysteresis judgment time window to prevent frequent switching of flight phases due to short-term fluctuations in flight data;

[0019] Step 4-2: Compare the real-time air pressure altitude, calculated airspeed and Mach number within the time window with the boundary conditions of each flight phase to determine the current flight phase.

[0020] Step 5: Identify the current flight scenario based on real-time data from multi-source aviation information and logical rules for typical flight scenarios;

[0021] Step 5-1: Compare real-time data from multiple sources, such as weather radar echo intensity, conflict alarm codes, and air-to-ground data link commands, with the logical rules of the flight scenario to determine whether a typical flight scenario is activated.

[0022] In step 5-2, the pilot can also make an independent judgment based on the current situation and choose to manually activate the specified typical scenario.

[0023] Step 6: Calculate the overall priority of information based on the current flight phase and flight scenario;

[0024] Step 6-1, change the current flight phase and the current flight scenario Substituting them into the information priority matrix, we can calculate the first... Flight phase priority corresponding to each data element and flight scenario priority ;

[0025] Step 6-2, Set the scene priority weight coefficient The weighted calculation yields the first... The overall priority of each data element is ,in The value is determined by the complexity of the current flight scenario.

[0026] Step 7: Generate a flight decision information requirement model based on the overall priority, control the information content and display format displayed on the airborne display, highlight the information content of data elements with high overall priority by placing them on top, highlighting, or flashing on the airborne display, and fold or hide the information content of data elements with low overall priority. By strengthening the key information for flight decision through visual perception, the flight decision information requirement model is generated, reducing the cognitive load on the pilot.

[0027] Assisted decision-making in thunderstorm avoidance scenarios specifically includes:

[0028] Step 1.1: Calculate the information priority of some aeronautical data elements of the aircraft during the cruise phase using multi-source aeronautical information priority calculation;

[0029] Step 1.2: The original priority levels are divided into high, medium and low levels. The expert group comprehensively evaluates the data elements based on the flight stage and flight scenario, samples the statistical results by mean, and obtains the comprehensive priority according to the priority weight coefficient.

[0030] Step 1.3: The airborne system highlights the names of data carriers with higher priority according to the overall priority, and finds the data elements corresponding to the data carriers based on the three-layer aviation information model, and performs flight path planning based on the specific data elements.

[0031] The path planning described in step 1.3 includes path planning that avoids risk areas.

[0032] In a single-aircraft TBO (Trajectory Based Operation) scenario, the planned route and estimated arrival time of waypoints are displayed at the top.

[0033] In flight conflict warning scenarios, the flight paths of the relevant flights are highlighted and signs are set to flash;

[0034] In the autonomous flight rerouting scenario under severe weather conditions, a buffer distance is set, an avoidance zone is generated based on the echo intensity, an offset distance is set, the boundary of the avoidance zone is horizontally extended on one side, the planned flight route is connected to generate a detour path, and the avoidance zone and detour path are displayed at the top according to information priority.

[0035] In the scenario of straightening a bend under flexible use of airspace, a pop-up window displays dynamic airspace information, including the location information of the airspace and temporary routes, as well as their opening and closing times.

[0036] Beneficial effects:

[0037] This invention integrates various types of aviation system information, including planning information, monitoring information, flight intention information, meteorological information, risk information, airspace dynamic information, and operational restriction information. It defines typical flight scenarios covering aviation operational risks and typical abnormal events, constructs an information priority matrix based on expert consensus to calculate comprehensive priorities, controls the information content transmitted via air-to-ground links in typical scenarios, and highlights high-priority information strongly related to flight missions, thereby assisting pilots in flight decision-making. Attached Figure Description

[0038] Figure 1 This is a flowchart of a flight assistance decision-making method based on priority calculation of multi-source aviation information according to the present invention.

[0039] Figure 2 This is an information element priority diagram for an autonomous flight rerouting operation scenario under severe weather conditions, which is an embodiment of the present invention.

[0040] Figure 3 This is a diagram illustrating the negotiation process in an autonomous flight rerouting scenario under severe weather conditions, serving as a real-time example of the present invention. Detailed Implementation

[0041] The following is in conjunction with the appendix Figures 1 to 3 The present invention will be described in further detail below.

[0042] This invention provides a flight assistance decision-making method based on multi-source aeronautical information priority calculation, such as... Figure 1 As shown, it includes the following steps:

[0043] Step 1: Analyze multi-source aviation data and construct a three-layer aviation information model based on data type, data carrier, and data element;

[0044] Step 1-1: Based on the functional or semantic type of information, classify data types and construct the data type layer of the three-layer aviation information model, as shown below:

[0045]

[0046] in, The total number of data types, the first Each data type is denoted as ;

[0047] Data types include: planning information, surveillance information, flight intention information, meteorological information, risk information, airspace dynamic information, and operational restriction information;

[0048] 1-2. Based on the data source and data structure, aviation information is subdivided. Based on the data carriers corresponding to the various subdivided aviation information types, a three-layer aviation information model data carrier layer is constructed, as shown below:

[0049]

[0050] in, For the first Data types The total number of data carriers, its first Each data carrier is recorded as ;

[0051] Various data carriers include: planning data carrier is the planning report; surveillance data carrier includes integrated track, S-mode track data and ADS-B track data; flight intention data carrier is the flight intention; meteorological data carrier includes SIGMET report, SPECI report, TAF, METAR report, radar reflectivity, upper-level wind, avoidance zone, turbulence zone and wake; risk data carrier is risk warning; airspace dynamics carrier includes airspace opening and closing reports and temporary route opening and closing reports; and operational restriction information includes handover agreements and flow restrictions.

[0052] Steps 1-3: Different data carriers contain data items with different data structures. These data items together constitute the data element layer in the three-layer information model, as shown below:

[0053]

[0054] in, For the first Data carriers The total number of data elements, its first Each data element is denoted as ;

[0055] The correspondence between data carriers and data items is as follows: The plan carrier includes data elements such as plan ID, message type, message status, 24-bit address code, flight number, secondary code, departure airport, destination airport, aircraft type, wake turbulence, cruising altitude, cruising speed, departure procedure, and arrival procedure. The integrated track carrier includes data elements such as flight number, fused timestamp, secondary code, 24-bit address code, longitude, latitude, altitude, track angle, ground speed, roll angle, track angular velocity, barometric altitude change rate, and heading. The flight intent carrier includes 24-bit address code, altitude intent, and speed. Data elements include: intention, radar reflectivity carrier (including serial number, radar reflectivity contour lines, duration, effective time, observation time, start time, and end time); upper-level wind carrier (including transmission time, start time, end time, and altitude layer grid points); SIGMET carrier (including ID, serial number, type, message area, transmission center, flight information region code, flight information region, start time, end time, weather type, trend, direction of movement, speed of movement, top altitude, bottom altitude, and severity); SPEC. The I-type carrier includes data elements such as ID, serial number, type, transmission time, airport, wind direction, wind speed, visibility, runway visual range, weather phenomena, temperature, dew point temperature, cloud conditions, and QNH. The TAF carrier includes data elements such as ID, serial number, type, transmission time, start time, end time, airport, wind direction, wind speed, visibility, runway visual range, weather phenomena, temperature, dew point temperature, cloud conditions, and QNH. The METAR carrier includes data elements such as ID, serial number, type, transmission time, airport, wind direction, wind speed, visibility, runway visual range, weather phenomena, temperature, dew point temperature, cloud conditions, and QNH. Data elements include point temperature, cloud conditions, QNH, etc.; risk alarm carriers include alarm type, alarm level, alarm flight number, etc.; airspace opening and closing reporting carriers include message ID, sending time, start time, end time, airspace structure sequence, airspace status, etc.; temporary route opening and closing reporting carriers include message ID, sending time, start time, end time, temporary route structure sequence, temporary route status, etc.; flow restriction carriers include message ID, sending time, start time, end time, flow control point code, description information, etc.

[0056] Step 2: Divide the standard flight phases and define several typical flight scenarios;

[0057] Step 2-1 divides the flight phase into the climb phase, cruise phase, cruise climb phase, cruise descent phase, and descent phase, as shown below:

[0058]

[0059] in, The total number of flight phases, the first Each flight phase is recorded as ;

[0060] Step 2-2: Design flight scenarios. Based on factors such as aircraft performance, weather impacts, airspace conditions, air traffic control decisions, and operational efficiency, design typical flight scenarios including single-aircraft TBO operation under safe conditions, flight conflict early warning scenario, autonomous rerouting operation under severe weather conditions, and cornering and straightening operation under flexible airspace utilization. A flight scene recorded The set of flight scenarios is represented as ,in, This represents the total number of flight scenarios.

[0061] Step 3: Construct a structured priority matrix for flight phase-data element information and a priority matrix for flight scenario-data element information;

[0062] Step 3-1: Collect priority scoring tables from different experts for different data elements at different stages, and construct a flight stage priority mapping table, as shown below:

[0063]

[0064] in, For the total number of experts, the first An expert's record He assigned priority scores to all data elements at different flight phases, recorded as follows: , It was this expert who was the first The element in the first... The priority settings for each flight phase are as follows: information priority has three levels: low, medium, and high, represented by 2, 1, and 0 respectively. ;

[0065] Step 3-2: Average the priority scores of all experts to obtain the information priority table of data elements under different flight phases, as shown below:

[0066] .

[0067] Step 3-3: Collect priority scoring tables from different experts for different data elements in different flight scenarios, and construct a flight scenario priority mapping table, as shown below:

[0068]

[0069] in, For the total number of experts, the first An expert's record He assigned priority scores to all data elements in different flight scenarios, which were recorded in a table. , It was this expert who was the first The element in the first... The priority settings for each flight phase.

[0070] Step 4: Determine the current flight phase based on real-time data from multi-source aviation information;

[0071] Step 4-1, set the hysteresis time window length to seconds, set height threshold to Record the cruising altitude as ;

[0072] Step 4-2, denote the set of altitude data elements in the integrated track carrier corresponding to the surveillance information as [the set of data elements]. Let the current time be denoted as From the previous time window to the current time Within the range, the difference in height ;

[0073] Step 4-3, if the current height satisfies And the height difference satisfies If the conditions are met, then the current flight phase is the climb phase; if the current altitude meets the conditions... And the height difference satisfies If the conditions are met, the current flight phase is the cruise phase. And the height difference satisfies If the conditions are met, the current flight phase is the cruise climb phase. And the height difference satisfies If the conditions are met, the current flight phase is the cruise descent phase. And the height difference satisfies If the conditions are met, then the current flight phase is the descent phase.

[0074] Step 5: Identify the current flight scenario based on real-time data from multi-source aviation information and logical rules for typical flight scenarios;

[0075] Step 5-1: Set the logical judgment conditions for typical flight scenarios, and determine whether to activate the scenario based on real-time data and the logical rules of the flight scenario;

[0076] Step 5-2: The pilot assesses the current situation and inputs the current flight scenario into the onboard equipment.

[0077] Step 5-3, record the input flight scenario as the first... A flight scene, recorded .

[0078] Step 6: Calculate the comprehensive priority of information based on the current flight phase and flight scenario to generate a pilot information requirement model;

[0079] Step 6-1, record the current flight phase as Substituting into the flight phase priority matrix, let... ,get Information priority matrix of data elements .

[0080] Step 6-2, let the first... The data elements are ,Will Substituting into the flight phase information priority matrix, we obtain the first... During the first flight phase, the... The flight phase priority of each data element is ;

[0081] Step 6-3, substitute into the flight scenario priority matrix, and set... Get the current flight scenario The information priority matrix of all data elements is as follows .

[0082] Step 6-4, Substituting the flight scenario information priority matrix, we obtain the first... In the first flight scenario, the... The flight scenario priority of each data element is ;

[0083] Step 6-5: Take the smaller of the flight phase priority and the flight scenario priority as the first priority. Data elements Overall priority: Create an information needs model from the pilot's perspective to assist pilots in making flight decisions.

[0084] Step 7: Generate a flight decision information requirement model based on the overall priority and control the information display format of the airborne display.

[0085] Step 7-1: Set priority display style thresholds according to the scene, and record the current flight scene. Priority display style threshold ;

[0086] Step 7-2: Compare the first Data elements Overall priority and display style threshold Data elements with a comprehensive priority higher than the display style threshold are highlighted on the airborne display by means of pinning, highlighting, or flashing. Data elements with a comprehensive priority lower than the display style threshold are folded or hidden. By enhancing key information for flight decision-making through visual perception, a flight decision information demand model is generated, reducing the cognitive load on the pilot.

[0087] This method integrates seven categories of basic information: ground-based planning information, surveillance information, flight intention information, meteorological information, risk information, airspace dynamic information, and operational restriction information. Based on expert flight experience, it constructs an information priority function, calculates information priorities based on flight phase and flight scenario, and filters information for specific scenarios and flight phases according to the comprehensive priority. The method highlights aviation information related to the flight scenario and the current flight phase on a multi-function display, assisting pilots in obtaining key information for timely decision-making.

[0088] In this embodiment, as Figure 2 The curve represents the priority mapping of some aeronautical data elements. A flight-aided decision-making method based on multi-source aeronautical information priority calculation is used to obtain the comprehensive priority of the data elements. Figure 3 A negotiation process diagram for autonomous flight rerouting operations in severe weather is created, highlighting detour routes for hazardous weather based on comprehensive priority, and an information demand model from the pilot's perspective is established. Figure 2 This represents the information priority of certain aviation data elements during the cruise phase of an aircraft in a thunderstorm avoidance operation scenario. The vertical axis represents the aviation data element item, and the horizontal axis represents the priority level. The original priority levels are divided into high, medium, and low levels, represented by values ​​of 0, 1, and 2. Experts comprehensively evaluate the priority of data elements based on the priority of the flight phase and flight scenario, and the statistical results are averaged to obtain the comprehensive priority, which is a floating-point number from 0 to 2. The smaller the number, the higher the priority of the data element. Figure 2 It can be seen that in the scenario of flying around thunderstorms, radar reflectivity map and avoidance zone information have a high priority. The airborne system will highlight the weather and avoidance zone information according to the information priority. Figure 3 a) The irregular polygonal color blocks in the background represent meteorological cloud maps of thunderstorms. The areas within the white dashed boxes indicate higher thunderstorm intensity. The areas within the white dotted boxes are avoidance zones. The white airplane icon indicates the current location of the aircraft. The dashed circles represent the 50km and 100km flight paths centered on the aircraft. The solid lines represent the aircraft's planned flight path. Figure 3 a) It can be seen that the aircraft's planned flight path crossed the center of the thunderstorm, indicating that the aircraft would be affected by thunderstorm weather during its subsequent flight path. Figure 3In section b), the white dashed box at the bottom displays three detour options (A, B, and C) automatically generated by the airborne equipment. The thick, dark dashed lines in the white dashed box at the top represent the detour paths corresponding to the three options, assisting pilots in planning detour routes during thunderstorms. After the pilot selects detour path A, the information is sent to the ground system for negotiation. Figure 3 c) Display ground feedback information, agreeing to the change of the rerouting route provided by the crew, and then the crew completes the subsequent flight along the rerouting route. Figure 3 The white dashed box in d) shows the modified detour route. This result indicates that the method of the present invention can construct an information priority function based on expert flight experience. By calculating information priorities based on flight phases and flight scenarios, an information demand model from the pilot's perspective is created to assist pilots in making flight decisions. Furthermore, the information filtering strategy created by experts with rich flight experience can better guide novice pilots in processing information, reducing the workload of information processing for pilots.

[0089] This invention provides a flight assistance decision-making method based on priority calculation of multi-source aviation information. Many methods and approaches exist for implementing this technical solution; the above description is merely a preferred embodiment of the invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention. All components not explicitly stated in this embodiment can be implemented using existing technologies.

Claims

1. A flight assistance decision-making method based on priority calculation of multi-source aeronautical information, characterized in that, Includes the following steps: Step 1: Analyze multi-source heterogeneous aeronautical data to construct a three-layer aeronautical information model based on data type, data carrier, and data element; Step 2: Define typical flight scenarios and divide standard flight phases; Step 3: Construct a structured priority matrix for flight phase-data element information and a priority matrix for flight scenario-data element information; Step 4: Determine the current flight phase based on real-time data from multi-source aviation information; Step 5: Identify the current flight scenario based on real-time data from multi-source aviation information and logical rules for typical flight scenarios; Step 6: Calculate the overall priority of information based on the current flight phase and flight scenario; Step 7: Generate flight decision information based on comprehensive priority, control the information content and display format displayed on the airborne display, and generate a flight decision information demand model to further assist flight operations.

2. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, In step 1, the specific process of constructing the three-layer aviation information model is as follows: Step 1-1: Analyze the raw data from different aviation systems, classify them according to the functional type or semantic type of the information, and construct the top layer of the three-layer aviation information model - the data type layer; Steps 1-2: Based on the logical or physical source of the information, aviation information is subdivided into data carriers. The data carriers can identify the source entity of the information. The data carriers constitute the middle layer of the three-layer aviation information model - the data carrier layer. Steps 1-3: Different data carriers contain data elements with different data structures. A data element can be represented as a specific, quantifiable, and identifiable information item. The data element is the smallest unit of information processing and constitutes the bottom layer of the three-layer information model - the data element layer.

3. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, The typical scenarios and flight phases in step 2 are defined as follows: Step 2-1: Define typical flight scenarios based on the operating status and risk sources. The operating status includes normal and abnormal operation, and the risk sources include weather impact and flight conflict. Design single-aircraft TBO operation scenarios under safe conditions, flight conflict early warning scenarios, autonomous rerouting operation scenarios under severe weather, and cornering and straightening operation scenarios under flexible airspace use. Integrate multi-source contextual information including weather radar echo intensity, conflict warning codes, air-to-ground data link instructions, and flow control messages, and preset logical judgment conditions for flight scenarios. Step 2-2: Based on the BADA standard issued by the European Air Traffic Management Organization, the flight phase is divided into takeoff, initial climb, climb, cruise, descent, approach and landing phases. The boundary conditions of the flight phase are defined by a combination of aircraft pressure altitude, calculated airspeed and Mach number thresholds.

4. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, Step 3, the process of constructing the structured flight phase-data element information priority matrix and the flight scenario-data element information priority matrix includes: Step 3-1: Select experts who meet the evaluation criteria; Step 3-2: Design a questionnaire on the priority of information elements based on flight scenarios and flight phases. Design at least two rounds of questionnaires. The first round of questionnaires is an open-ended survey to form an initial information list for different flight phases in typical scenarios. The second round of questionnaires is a targeted survey, focusing on quantitative scoring of key information and controversial information. The information priority should include at least three levels: high, medium and low. Step 3-3: Through multiple rounds of anonymous feedback, a statistical information element importance scale is used to calculate a weighted average of the expert group's group scale, resulting in a structured flight phase-data element information priority matrix and a flight scenario-data element information priority matrix.

5. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, Step 4, the process of determining the current flight phase based on real-time data from multi-source aviation information, is as follows: Step 4-1: Set the hysteresis detection time window; Step 4-2: Compare the real-time air pressure altitude, calculated airspeed and Mach number within the time window with the boundary conditions of each flight phase to determine the current flight phase.

6. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, In step 5, the process of identifying the current flight scenario is as follows: Compare real-time data from multiple sources with the logical rules of the flight scenario to determine whether a typical flight scenario is activated; Alternatively, the pilot may make an independent judgment based on the current situation and choose to manually activate a designated typical scenario.

7. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, In step 6, the method for calculating the comprehensive priority of the information is as follows: Step 6-1, change the current flight phase and the current flight scenario Substituting them into the information priority matrix, we can calculate the first... Flight phase priority corresponding to each data element and flight scenario priority ; Step 6-2, Set the scene priority weight coefficient The weighted calculation yields the first... The overall priority of each data element is ,in The value is determined by the complexity of the current flight scenario.

8. The flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 1, characterized in that, In step 7, for data elements with a comprehensive priority higher than the first threshold, the information content is highlighted on the airborne display in a manner including pinning, highlighting, or flashing. For data elements with a comprehensive priority lower than the second threshold, the information content is folded or hidden. By enhancing key information for flight decision-making through visual perception, the cognitive load on the pilot is reduced.

9. A flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 8, characterized in that, Assisted decision-making in thunderstorm avoidance scenarios specifically includes: Step 1.1: Calculate the information priority of some aeronautical data elements of the aircraft during the cruise phase using multi-source aeronautical information priority calculation; Step 1.2: The original priority levels are divided into high, medium and low levels. The expert group comprehensively evaluates the data elements based on the flight stage and flight scenario, samples the statistical results by mean, and obtains the comprehensive priority according to the priority weight coefficient. Step 1.3: The airborne system highlights the names of data carriers with higher priority according to the overall priority, and finds the data elements corresponding to the data carriers based on the three-layer aviation information model, and performs flight path planning based on the specific data elements.

10. A flight assistance decision-making method based on multi-source aeronautical information priority calculation according to claim 9, characterized in that, The path planning described in step 1.3 includes path planning to avoid risk areas: setting a buffer distance, generating an avoidance area based on the intensity of weather radar echoes, setting a safety offset distance, horizontally expanding the boundary of the avoidance area on one side, connecting the planned flight routes to generate a detour path, and displaying the avoidance area and detour path at the top according to information priority.

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