Aircraft optimal re-flight decision determination method and device and aircraft re-flight method and device

Abstract

The invention belongs to the field of flight control, and particularly relates to an aircraft optimal re-flight decision determination method and device and an aircraft re-flight method and device. The optimal re-flight decision determination method comprises the following steps: S1, dividing an airplane re-flight course into a first stage of positive bias of an elevator, a second stage of negative bias of the elevator and a third stage of positive bias of the elevator according to a time sequence; s2, the rudder deflection angle of the first stage, the duration time of the first stage, the rudder deflection angle of the second stage, the duration time of the second stage and the rudder deflection angle of the third stage serve as optimization variables, the minimum leveling advancing distance and the minimum reciprocal of the longitudinal height serve as optimization targets, and the function relation between the optimization targets and the optimization variables is determined; s3, determining an optimal optimization variable combination by using a non-dominated sorting genetic algorithm; and S4, determining a dangerous area and a safe area of aircraft re-flight, and forming a re-flight database. According to the method, the optimal re-flight decision can be quickly made, and the re-flight safety is improved.

Description

Technical Field

[0001] This application belongs to the field of flight control, and particularly relates to a method and device for determining an optimal go-around decision of an aircraft, and a method and device for aircraft go-around. Background Art

[0002] When an aircraft lands on a mobile platform, many external interferences will affect the glide trajectory of the aircraft. When the movement trajectory of the aircraft deviates greatly from the desired glide trajectory, the landing needs to be terminated and a go-around is executed. Statistical results show that a large number of landing accidents are caused by improper go-around decisions. If the go-around decision system can accurately determine the safe go-around boundary in real time, make a go-around decision in a timely manner, and adopt appropriate go-around maneuvers, landing accidents can be avoided.

[0003] Currently, in the traditional go-around decision of an aircraft, the go-around maneuver only uses system thrust and does not deflect the elevator. Some aircraft use a go-around strategy optimized based on numerical simulation, which takes a long time, has low efficiency, and is prone to falling into local optimum during the simulation solution process, resulting in unsatisfactory go-around results. Summary of the Invention

[0004] To solve the above problems, this application provides a method and device for determining an optimal go-around decision of an aircraft, and a method and device for aircraft go-around, so as to improve the go-around success rate.

[0005] The first aspect of this application provides a method for determining an optimal go-around decision of an aircraft, which mainly includes: Step S1: Divide the go-around process of the aircraft into a first stage with positive elevator deflection, a second stage with negative elevator deflection, and a third stage with positive elevator deflection in chronological order; Step S2: Take the elevator deflection angle in the first stage, the duration of the first stage, the elevator deflection angle in the second stage, the duration of the second stage, and the elevator deflection angle in the third stage as optimization variables, and take the minimum of the leveling forward distance and the minimum of the reciprocal of the longitudinal height as optimization objectives, and determine the functional relationship between the optimization objectives and the optimization variables; Step S3: For the given initial position of the aircraft relative to the set point of the mobile platform and the initial velocity of the aircraft at the initial position, given multiple initial combinations of optimization variables, use the non-dominated sorting genetic algorithm to determine the optimal combination of optimization variables; Step S4: For each initial velocity, calculate the flight parameters of the aircraft at each given position under the optimal combination of optimization variables corresponding to the initial velocity and the initial position at different initial positions. When the flight parameters are lower than the set threshold, mark the initial position as a dangerous point, and form a dangerous area corresponding to the initial velocity by combining all dangerous points, and calibrate the non-dangerous area as the safe area of the initial velocity to form a go-around database.

[0006] Preferably, in step S4, the flight parameters at each given position include: The height parameter of the lowest point of the aircraft when it is outside the mobile platform, and the height clearance parameter from the mobile platform when the aircraft is above the mobile platform.

[0007] The second aspect of the present application provides an aircraft optimal go-around decision-making determination device, mainly including: A go-around process division module, configured to divide the aircraft go-around process into a first stage with positive elevator deflection, a second stage with negative elevator deflection, and a third stage with positive elevator deflection in chronological order; An optimization parameter determination module, configured to use the elevator deflection angle in the first stage, the duration of the first stage, the elevator deflection angle in the second stage, the duration of the second stage, and the elevator deflection angle in the third stage as optimization variables, and use the minimum flare advance distance and the minimum reciprocal of the longitudinal height as optimization objectives to determine the functional relationship between the optimization objectives and the optimization variables; A variable optimization module, configured to, for a given initial position of the aircraft relative to the set point of the mobile platform and the initial speed of the aircraft at the initial position, given multiple initial optimization variable combinations, use the non-dominated sorting genetic algorithm to determine the optimal optimization variable combination; A go-around safety area determination module, configured to, for each initial speed, calculate the flight parameters of the aircraft at each given position corresponding to the optimal optimization variable combination of the initial speed and the initial position at different initial positions. When the flight parameters are lower than the set threshold, mark the initial position as a dangerous point, form a dangerous area corresponding to the initial speed by combining all dangerous points, and calibrate the non-dangerous area as the safety area of the initial speed to form a go-around database.

[0008] Preferably, the flight parameters at each given position include: The height parameter of the lowest point of the aircraft when it is outside the mobile platform, and the height clearance parameter from the mobile platform when the aircraft is above the mobile platform.

[0009] The third aspect of the present application provides an aircraft go-around method, using the go-around database constructed by the above-mentioned aircraft optimal go-around decision-making determination method. The aircraft go-around method includes: Step T1, when the horizontal distance between the aircraft and the mobile platform is within a preset range, obtain the real-time speed of the aircraft; Step T2, determine the area where the current position of the aircraft is located when entering the go-around maneuver according to the real-time speed; Step T3, when the area where the current position of the aircraft is located is a safe area, query the corresponding optimization variable combination according to the real-time speed of the aircraft and the current position of the aircraft as the control parameter for the aircraft to go around. When the area where the current position of the aircraft is located is a dangerous area, give a danger prompt.

[0010] Preferably, in step T1, the preset range is 180m - 960m.

[0011] Preferably, step T3 further includes: Step T31: Dynamically display on the on-board display interface the dangerous area, safe area, current position of the aircraft, real-time speed, and the takeoff - go - around trajectory line calculated according to the optimal combination of optimization variables during the aircraft's takeoff - go - around; Step T32: Execute the takeoff - go - around maneuver according to the pilot's takeoff - go - around command.

[0012] In the fourth aspect of the present application, an aircraft takeoff - go - around device is provided, including a takeoff - go - around database constructed by the aircraft optimal takeoff - go - around decision - making method described above. The aircraft takeoff - go - around device further includes: A real - time speed acquisition module, configured to acquire the real - time speed of the aircraft when the horizontal distance between the aircraft and the mobile platform is within the preset range; An area determination module, configured to determine the area where the current position of the aircraft is located when entering the takeoff - go - around maneuver according to the real - time speed; A takeoff - go - around parameter determination module, configured to, when the area where the current position of the aircraft is located is the safe area, query the corresponding combination of optimization variables according to the real - time speed of the aircraft and the current position of the aircraft as the control parameters for the aircraft's takeoff - go - around, and give a danger prompt when the area where the current position of the aircraft is located is the dangerous area.

[0013] Preferably, the preset range is 180m - 960m.

[0014] Preferably, the takeoff - go - around parameter determination module includes: A takeoff - go - around simulation display unit, configured to dynamically display on the on - board display interface the dangerous area, safe area, current position of the aircraft, real - time speed, and the takeoff - go - around trajectory line calculated according to the optimal combination of optimization variables during the aircraft's takeoff - go - around; A takeoff - go - around maneuver unit, configured to execute the takeoff - go - around maneuver according to the pilot's takeoff - go - around command.

[0015] The present application can quickly make an optimal takeoff - go - around decision and improve the safety of takeoff - go - around. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the elevator deflection parameter during the takeoff - go - around process of a preferred embodiment of the aircraft optimal takeoff - go - around decision - making method of the present application.

[0017] Figure 2 It is a schematic diagram of the non - dominated sorting genetic algorithm process.

[0018] Figure 3 It is a schematic diagram of a cluster of takeoff - go - around trajectory curves.

[0019] Figure 4It is a schematic diagram of the go-around safety area and the dangerous area.

[0020] Figure 5 It is a flowchart of the go-around method for the aircraft of this application. Specific implementation manners

[0021] To make the purpose, technical solutions and advantages of the implementation of this application clearer, the technical solutions in the implementation manners of this application will be described in more detail below with reference to the accompanying drawings in the implementation manners of this application. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The described implementation manners are part of the implementation manners of this application, rather than all of the implementation manners. The implementation manners described below by referring to the accompanying drawings are exemplary and are intended to explain this application, and should not be construed as a limitation of this application. Based on the implementation manners in this application, all other implementation manners obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application. The implementation manners of this application will be described in detail below with reference to the accompanying drawings.

[0022] The first aspect of this application provides a method for determining the optimal go-around decision of an aircraft, as Figure 1 shown, mainly including: Step S1: Divide the go-around process of the aircraft into a first stage with the elevator deflected positively, a second stage with the elevator deflected negatively, and a third stage with the elevator deflected positively in chronological order; Step S2: Take the elevator deflection angle in the first stage, the duration of the first stage, the elevator deflection angle in the second stage, the duration of the second stage, and the elevator deflection angle in the third stage as optimization variables, and take the minimum of the flare advance distance and the reciprocal of the longitudinal height as the optimization objectives, and determine the functional relationship between the optimization objectives and the optimization variables; Step S3: For the given initial position of the aircraft relative to the set point of the mobile platform and the initial velocity of the aircraft at the initial position, given multiple initial combinations of optimization variables, use the non-dominated sorting genetic algorithm to determine the optimal combination of optimization variables; Step S4: For each initial velocity, calculate the flight parameters of the aircraft at each given position under the optimal combination of optimization variables corresponding to the initial velocity and the initial position at different initial positions. When the flight parameters are lower than the set threshold, mark the initial position as a dangerous point. The dangerous areas corresponding to the initial velocity are formed by all the dangerous points, and the non-dangerous areas are calibrated as the safety areas of the initial velocity to form a go-around database.

[0023] Traditional go-around decisions do not fully utilize the control performance of the elevator, taking into account the pilot's control difficulty. However, with the development of flight control technology, it has become possible for the aircraft to perform an automatic go-around based on optimal control. Therefore, in step S1 of this application, from the perspective of elevator control, the go-around process of the aircraft is divided into three stages, as Figure 1 shown, the deflection value of the elevator is positive in the first stage, negative in the second stage, and positive in the third stage.

[0024] In step S2, the elevator deflection angle in the first stage, the duration of the first stage, the elevator deflection angle in the second stage, the duration of the second stage, and the elevator deflection angle in the third stage are used as optimization variables. Here, the deflection angle usually refers to the increment of the elevator deflection angle compared to the original trim value, such as the increment of the elevator deflection angle in the first stage compared to the trim value , duration , the increment of the elevator deflection angle in the second stage compared to the trim value , duration , the increment of the elevator deflection angle in the third stage compared to the trim value .

[0025] At the same time, in step S2, the goal of the optimization design of the elevator control during the aircraft go-around is to make the reciprocal of the flare forward distance x and the longitudinal height h the smallest by reasonably setting the above five design parameters, that is: .

[0026] To determine the specific functions between the flare forward distance x, the longitudinal height h and the above five parameters, in step S2, based on the aircraft landing simulation model, when the aircraft's on-board computer receives the go-around command, after a 0.2s system delay, the throttle lever is quickly manipulated to the system thrust to perform the go-around maneuver. Assuming that the mobile platform sails forward along the platform slope direction at a constant speed, the following go-around trajectory equation is constructed with the tail of the mobile platform (the aircraft flies from this tail to above the mobile platform and lands) as the coordinate origin: ; where, is the real-time position of the aircraft relative to the tail of the mobile platform, including the real-time horizontal position and the real-time height, is the initial position of the aircraft when performing the go-around, including the initial horizontal position and the initial height, are respectively the initial value of the aircraft's speed, the disturbance speed, the initial value of the track angle, the disturbance track angle and the interference sinking rate, is the forward speed of the mobile platform along the platform slope direction.

[0027] Figure 1After the five optimization variables in are determined, that is, after the rudder deflection angle is determined, the disturbance velocity and the disturbance track angle

[0028] in the go-around trajectory equation will have solutions in the time domain and become known, and then the real-time position of the aircraft relative to the tail of the moving platform can be calculated. The above constructs the functional relationship between the five optimization variables and the two optimization objectives. Further, constraints on the aircraft rudder deflection angle are added. For example, the elevator deflection is limited to .

[0029] After that, in step S3, the non-dominated sorting genetic algorithm NSGA is used to solve the optimization variable combination composed of the above 5 optimization parameters. Here, the second-generation non-dominated sorting genetic algorithm NSGA-II is used. As Figure 2 shown, first, a parent population with an individual number of N is randomly generated , and the parent population generates an offspring population with the same individual number N through selection, recombination, and mutation . The parent population and the offspring population are combined into a new population, and then fast non-dominated sorting is performed. In the figure, - are different non-dominated rank sets. For the sets , with higher non-dominated ranks, they directly enter the new parent population , and the sets , , with lower non-dominated ranks are eliminated. Because there is still space in the new population, the set is sorted by crowding degree, and the individuals with higher crowding degree are added to the population until the individual number of the population is guaranteed to be N, and the individuals with lower crowding degree are also eliminated. The new parent population will generate an offspring population through selection, recombination, and mutation, and the above process is repeated until the iteration times are met.

[0030] Step S3 uses the fast non-dominated sorting algorithm to reduce the computational complexity, introduces the elite strategy, which is beneficial to maintaining the excellent individuals in the parent generation, expands the sampling space, and at the same time introduces the crowding degree and the crowding degree comparison operator to ensure the diversity of the population.

[0031] In addition, it can be seen from the go-around trajectory equation that the parameters affecting the go-around trajectory also include the initial position and initial velocity of the aircraft. Here, the initial position includes the horizontal distance and altitude relative to the coordinate origin, and the initial velocity includes the horizontal velocity and sink rate relative to the coordinate origin. That is to say, the optimal go-around trajectories under different initial positions and different initial velocities are different. Therefore, in step S3, for each given set of initial positions and initial velocities, an optimal combination of optimization variables will be obtained, and this optimal combination of optimization variables corresponds to a go-around trajectory line, as Figure 3 shown.

[0032] Step S4 is used to determine whether each go-around trajectory meets the safety conditions. Here, multiple given positions on the go-around trajectory are selected as reference points to determine whether the flight parameters at these reference points meet the conditions. For example, in some alternative embodiments, in step S4, the flight parameters at each given position include: the altitude parameter of the lowest point when the aircraft is outside the mobile platform, and the altitude clearance parameter from the mobile platform when the aircraft is above the mobile platform. If the altitude parameter of the lowest point when the aircraft is outside the mobile platform is lower than the set threshold, or the altitude clearance parameter from the mobile platform is lower than the set threshold, it indicates that there is a go-around risk for this go-around trajectory.

[0033] Specifically, it is required that when the aircraft flies over the tail of the mobile platform, there is at least a 3m altitude clearance between the bottom of the aircraft and the surface of the mobile platform; when the aircraft is above the mobile platform and the sink rate is zero, there is at least a 3m altitude clearance between the bottom of the aircraft and the surface of the mobile platform; define the 5m horizontal line below the surface of the mobile platform as the lowest reference line, and the lowest point of the aircraft's go-around trajectory should be higher than this reference line.

[0034] It should be noted that traditional safe go-around only uses the net height at the tail of the mobile platform as the standard to measure go-around safety, and the consideration of go-around safety is not comprehensive. When the aircraft performs a go-around operation when it is close to the mobile platform, although the height requirement is met at the tail of the mobile platform, at this time, the sink rate of the aircraft may not be zero and the height continues to decrease, resulting in the relative height between the aircraft and the mobile platform not meeting the requirements of the matching movement. During the go-around process, it is even possible that part of the structure of the aircraft hits the mobile platform, with a relatively high go-around risk. At the same time, when the aircraft performs a go-around operation when it is far from the mobile platform, although the height distance from the mobile platform can meet the requirements, the lowest point of the aircraft's go-around trajectory is relatively close to the sea level, presenting a risk of falling into the sea. During the actual descent process, define the 5m horizontal line below the surface of the mobile platform as the lowest reference line, and require that the lowest point of the aircraft's go-around trajectory should not be lower than this reference line.

[0035] For each given initial speed of the aircraft, according to the above safety go-around criteria, a go-around boundary dataset is obtained from the go-around trajectory dataset. The go-around boundary is the boundary composed of the track critical points. The area below the go-around boundary is the go-around risk area, and the area above the go-around boundary is the go-around safety area, as Figure 4 shown. It can be understood that during the gliding process of the aircraft, the go-around boundary is not fixed, but a dynamic curve that changes with the initial speed of the aircraft (including the real-time horizontal speed and the real-time sinking rate). Similarly, the go-around risk area is also changing in real time. Therefore, through a large number of simulation calculations, a go-around boundary database corresponding to different speeds and sinking rates is established and stored in the on-board computer for go-around decision-making.

[0036] In the second aspect of the present application, an aircraft optimal go-around decision-making determination device mainly includes: A go-around process division module for dividing the aircraft go-around process into a first stage with the elevator deflected forward, a second stage with the elevator deflected backward, and a third stage with the elevator deflected forward in chronological order; An optimization parameter determination module for taking the elevator deflection angle in the first stage, the duration of the first stage, the elevator deflection angle in the second stage, the duration of the second stage, and the elevator deflection angle in the third stage as optimization variables, and taking the minimum of the leveling forward distance and the reciprocal of the longitudinal height as optimization objectives to determine the functional relationship between the optimization objectives and the optimization variables; A variable optimization module for, for a given initial position of the aircraft relative to the set point of the mobile platform and the initial speed of the aircraft at the initial position, giving multiple initial combinations of optimization variables and using the non-dominated sorting genetic algorithm to determine the optimal combination of optimization variables; A go-around safety area determination module for, for each initial speed, calculating the flight parameters of the aircraft at each given position under the optimal combination of optimization variables corresponding to the initial speed and the initial position at different initial positions. When the flight parameters are lower than the set threshold, marking the initial position as a dangerous point, forming a dangerous area corresponding to the initial speed by combining all dangerous points, and calibrating the non-dangerous area as the safety area of the initial speed to form a go-around database.

[0037] In some alternative embodiments, the flight parameters at each given position include: The height parameter of the lowest point when the aircraft is outside the mobile platform, and the height clearance parameter from the mobile platform when the aircraft is above the mobile platform.

[0038] In the third aspect of the present application, an aircraft go-around method uses the go-around database constructed by the above-mentioned aircraft optimal go-around decision-making determination method. The aircraft go-around method includes: Step T1, when the horizontal distance between the aircraft and the mobile platform is within a preset range, obtain the real-time speed of the aircraft; Step T2. Determine the area where the current position of the aircraft is located when entering the go-around maneuver according to the real-time speed; Step T3. When the area where the current position of the aircraft is located is a safe area, query the corresponding optimized variable combination according to the real-time speed of the aircraft and the current position of the aircraft as the control parameter for the aircraft to go around. When the area where the current position of the aircraft is located is a dangerous area, give a danger prompt.

[0039] As Figure 5 shown, after the aircraft moves to the specified position, it is considered to enter the "go-around decision area". In some alternative embodiments, in step T1, the preset range is 180m - 960m. That is to say, the area with a horizontal distance of 180m - 960m from the tail of the mobile platform is defined as the "go-around decision area". When the aircraft enters this area, the on-board go-around decision-making system starts to work. The aircraft radar real-time tracks the horizontal distance and longitudinal height of the aircraft from the tail of the mobile platform, and filters out the platform motion parameters through the platform motion compensation system, and then transmits them to the go-around decision-making system. On the other hand, the real-time speed and sink rate of the aircraft are measured by on-board equipment. According to the real-time speed and sink rate measured by the on-board equipment, the corresponding go-around boundary in the database is found, and then it is judged whether the aircraft is in a safe area or a dangerous area. If it is in a safe area, the go-around maneuver can be further performed according to the go-around instruction. If it is in a dangerous area, a danger prompt is given. For example, some other more aggressive control strategies can be executed.

[0040] In some alternative embodiments, step T3 further includes: Step T31. Dynamically display the dangerous area, safe area, current position of the aircraft, real-time speed and the go-around trajectory line calculated according to the optimal optimized variable combination on the on-board display interface; Step T32. Execute the go-around maneuver according to the pilot's go-around instruction.

[0041] This embodiment is mainly for manned aircraft. An auxiliary interface as Figure 4 shown is given on the in-aircraft display interface to assist the pilot in more clearly judging the current position of the aircraft relative to the mobile platform and the go-around trajectory line for executing the go-around strategy, so as to make a final decision.

[0042] In the fourth aspect of the present application, an aircraft go-around device includes a go-around database constructed by the above-mentioned aircraft optimal go-around decision-making method. The aircraft go-around device further includes: A real-time speed acquisition module, configured to acquire the real-time speed of the aircraft when the horizontal distance between the aircraft and the mobile platform is within the preset range; An area determination module, configured to determine the area where the current position of the aircraft is located when entering the go-around maneuver according to the real-time speed; A go-around parameter determination module, configured to, when the area where the current position of the aircraft is located is a safe area, query a corresponding optimized variable combination according to the real-time speed of the aircraft and the current position of the aircraft, and use it as the control parameter for the aircraft to go around. When the area where the current position of the aircraft is located is a dangerous area, a danger prompt is given.

[0043] In some alternative embodiments, the preset range is 180m - 960m.

[0044] In some alternative embodiments, the go-around parameter determination module includes: A go-around simulation display unit, configured to dynamically display on the on-board display interface the dangerous area, safe area, current position of the aircraft, real-time speed, and go-around trajectory line calculated according to the optimal optimized variable combination during the go-around of the aircraft; A go-around operation unit, configured to perform go-around operations according to the pilot's go-around command.

[0045] As mentioned above, the above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed in the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for determining an optimal go-around decision for an aircraft, characterized in that: include: Step S1, dividing the aircraft's go-around process into a first stage of positive elevator deflection, a second stage of negative elevator deflection, and a third stage of positive elevator deflection in chronological order; Step S2, taking the rudder deflection angle of the first stage, the duration of the first stage, the rudder deflection angle of the second stage, the duration of the second stage and the rudder deflection angle of the third stage as optimization variables, taking the minimum leveling forward distance and the minimum reciprocal of the longitudinal height as optimization targets, and determining the functional relationship between the optimization target and the optimization variables; Step S3: for a given initial position of the aircraft relative to a set point of the mobile platform and an initial speed of the aircraft at the initial position, a plurality of initial optimization variable combinations are given, and an optimal optimization variable combination is determined using a non-dominated sorting genetic algorithm; Step S4: for each initial speed, the flight parameters of the aircraft at each given position under the optimal combination of optimization variables corresponding to the initial speed and the initial position are calculated at different initial positions; when the flight parameters are lower than a set threshold, the initial position is marked as a danger point; a danger area corresponding to the initial speed is formed by combining all danger points; a non-danger area is marked as a safe area for the initial speed, and a go-around database is formed.

2. The method for determining the optimal missed approach decision of an aircraft according to claim 1, characterized in that: In step S4, the flight parameters at each given position include: The height parameter of the lowest point when the aircraft is outside the mobile platform, and the height clearance parameter of the aircraft from the mobile platform when the aircraft is above the mobile platform.

3. An optimal go-around decision determination device for an aircraft, characterized in that: include: A missed approach process division module is used to divide the aircraft's missed approach process into a first stage of positive elevator deflection, a second stage of negative elevator deflection and a third stage of positive elevator deflection in chronological order; an optimization parameter determination module, for taking the rudder deflection angle of the first stage, the duration of the first stage, the rudder deflection angle of the second stage, the duration of the second stage and the rudder deflection angle of the third stage as optimization variables, taking the minimum leveling forward distance and the minimum reciprocal of the longitudinal height as optimization targets, and determining the functional relationship between the optimization targets and the optimization variables; a variable optimization module, for determining an optimal optimization variable combination using a non-dominated sorting genetic algorithm given a plurality of initial optimization variable combinations for a given initial position of the aircraft relative to a set point of the mobile platform and an initial speed of the aircraft at the initial position; The missed approach safety area determination module is used to calculate, for each initial speed, at different initial positions, the flight parameters of the aircraft at each given position under the optimal optimization variable combination corresponding to the initial speed and the initial position; when the flight parameter is lower than a set threshold, the initial position is marked as a dangerous point, and the dangerous area corresponding to the initial speed is formed by combining all dangerous points, and the non-dangerous area is marked as the safe area of ​​the initial speed to form a missed approach database.

4. The aircraft optimal go-around decision determination device according to claim 3, characterized in that: The flight parameters at each given location include: The height parameter of the lowest point when the aircraft is outside the mobile platform, and the height clearance parameter of the aircraft from the mobile platform when the aircraft is above the mobile platform.

5. A method for an aircraft go-around, characterized in that: A go-around database constructed using the aircraft optimal go-around decision determination method according to any one of claims 1 to 2, wherein the aircraft go-around method comprises: Step T1: when the horizontal distance between the aircraft and the mobile platform is within a preset range, obtain the real-time speed of the aircraft; Step T2, determining the area where the current position of the aircraft is located when entering the missed approach maneuver according to the real-time speed; Step T3: When the area where the aircraft's current position is located is a safe area, the optimization variable combination corresponding to the aircraft's real-time speed and the aircraft's current position query is used as the aircraft's go-around control parameter; when the area where the aircraft's current position is located is a dangerous area, a danger warning is given.

6. The aircraft go-around method according to claim 5, characterized in that: In step T1, the preset range is 180m-960m.

7. The aircraft go-around method according to claim 5, characterized in that: Step T3 further comprises: Step T31, dynamically displaying the dangerous area, safe area, current position, real-time speed and the missed approach trajectory calculated according to the best combination of optimized variables for the aircraft's missed approach on the onboard display interface; Step T32: Execute a go-around maneuver according to the pilot's go-around instruction.

8. An aircraft go-around device, characterized in that: A go-around database constructed by the aircraft optimal go-around decision determination method according to any one of claims 1 to 2, wherein the aircraft go-around device further comprises: A real-time speed acquisition module is used to acquire the real-time speed of the aircraft when the horizontal distance between the aircraft and the mobile platform is within a preset range; An area determination module, used to determine the area where the current position of the aircraft is located when entering a missed approach maneuver according to the real-time speed; The module for determining the parameters for the missed approach is used to determine the optimal variable combination corresponding to the real-time speed of the aircraft and the current position of the aircraft as the control parameters for the missed approach of the aircraft when the area where the current position of the aircraft is located is a safe area, and to give a danger prompt when the area where the current position of the aircraft is located is a dangerous area.

9. The aircraft go-around device according to claim 8, characterized in that: The preset range is 180m-960m.

10. The aircraft go-around device according to claim 8, characterized in that: The go-around parameter determination module includes: A missed approach simulation display unit is used to dynamically display the dangerous area, safe area, current position, real-time speed and missed approach trajectory calculated according to the best combination of optimized variables on the onboard display interface; The go-around control unit is used to execute the go-around maneuver according to the pilot's go-around instruction.

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