Aircraft wake flow real-time monitoring method based on laser radar

Abstract

The invention discloses an aircraft wake flow real-time monitoring method based on laser radars, and the method comprises the steps: collecting the real-time wake flow data in a five-side approaching stage of a front aircraft through a plurality of laser radar devices, and determining the space coordinates and three-dimensional contour of the edge of a wake flow region through an edge detection algorithm; according to the coordinates of the left and right edges and the upper and lower edges of the wake flow area, the front and tail flow areas are displayed in real time; the method comprises the following steps: intercepting a two-dimensional cross section of a front aircraft tail flow area at a rear aircraft real-time flight height, calculating a rolling instability index generated by the two-dimensional cross section area to a rear aircraft wing, determining a wake flow minimum safety interval according to a preset rolling instability index threshold value, and displaying the wake flow minimum safety interval on an air traffic control system radar interface in real time, thereby realizing the purpose that in a five-side approach stage of an aircraft, the flight speed of the aircraft is increased. The front aircraft wake flow area and the rear aircraft wake flow area are displayed in real time, and the minimum safety interval of the front aircraft and the rear aircraft considering the real-time flight height is considered, so that an air traffic controller can clearly know the real-time state and the potential risk of the aircraft wake flow, and the wake flow monitoring accuracy and the flight safety are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of aircraft wake risk analysis, and in particular to a method for monitoring aircraft wake in real time based on a laser radar. BACKGROUND

[0002] The aircraft wake is a strong rotating airflow formed at the wing tip when the aircraft is flying, and has the characteristics of large spatial scale, long duration, and strong rotation. The wake may cause the subsequent aircraft to shake, lose control of the attitude, or even stall, which seriously threatens flight safety. Especially during the five-edge approach of the aircraft, due to the large intensity and slow dissipation of the wake, and the low flight height, speed and thrust of the aircraft being in a critical state, the harmfulness is more significant.

[0003] Currently, the aircraft wake risk monitoring method mainly obtains the height, speed, position and other data of the aircraft through the ADS-B data sent by the aircraft and processed by the ground receiving equipment, and prevents the rear aircraft from entering the wake generated by the front aircraft according to the current static wake separation standard of each airport. With the development of detection technology and prediction algorithm, the aircraft wake risk has been quantitatively evaluated and analyzed. Based on the aircraft wake data detected by the laser radar, a deep learning algorithm is used to identify and predict the aircraft wake, and the aircraft ADS-B data is used to evaluate the wake risk.

[0004] The current air traffic management system deployed by civil aviation air traffic control and airport units in China has realized the core functions of multi-source data information fusion, such as radar, ADS-B, Beidou navigation, and conflict warning of flight path, but has not integrated the real-time monitoring and dynamic alarm display module of the aircraft wake. Air traffic control units still rely on the current static wake separation standard for aircraft operation command. This standard specifies the corresponding wake separation distance for each aircraft combination based on the models of the front and rear aircraft. However, this separation only considers the fixed distance requirement and lacks real-time dynamic monitoring and alarm display of the wake influence.

[0005] Under complex weather conditions, especially in adverse wind environments, the evolution and dissipation process of the wake will be greatly affected, and the deep learning predicted aircraft wake result cannot truly reflect the influence of meteorological parameters on the evolution and dissipation of the wake, which may cause the existing wake monitoring system to issue false alarms in safe conditions, or fail to timely warn in the presence of potential risks, i.e., false negatives, thereby causing the aircraft pilots to misjudge the wake risk. This limitation affects the reliability and accuracy of the wake monitoring system to some extent, especially under complex weather conditions, which may pose a potential threat to flight safety.

[0006] Therefore, the existing wake monitoring technology has the following shortcomings:

[0007] (1) The current wake monitoring method uses a deep learning algorithm model to perform spatiotemporal prediction on the collected aircraft wake to obtain the parameters and evolution of the wake at different positions, and then monitors and evaluates the wake risk. This usually requires accurate labeling of the collected wake data, which puts higher requirements on data processing. At the same time, the generalization ability and interpretability of the algorithm model are limited, which affects the timeliness and accuracy of the wake prediction results, and cannot meet the real-time monitoring requirements of the aircraft wake.

[0008] (2) The existing wake monitoring system uses a fixed circular or fan-shaped projection based on aircraft type classification as the wake area, and uses a pre-set static wake interval standard as the boundary and minimum safety interval of the wake area, so that the range of the wake area and the minimum safety interval cannot be dynamically adjusted in real time according to the real-time sinking trajectory of the wake and the real-time flight height of the following aircraft.

[0009] (3) ADS-B data cannot reflect the influence of meteorological parameters on wake evolution and dissipation, which may cause false positives and false negatives in the wake monitoring system, and thus cause air traffic controllers to misjudge the wake risk, affecting the reliability and accuracy of wake monitoring.

[0010] Therefore, a laser radar-based real-time monitoring method for aircraft wake is proposed to solve the above problems. SUMMARY

[0011] To solve the above problems, the purpose of the present application is to provide a laser radar-based real-time monitoring method for aircraft wake, which realizes real-time monitoring of the wake area of the preceding aircraft and the minimum safety interval between the preceding and following aircraft after the preceding aircraft cuts into the five-edge heading path during the last five-edge approach phase, so that air traffic controllers can clearly understand the real-time state and potential risk of the aircraft wake, improving the accuracy of wake monitoring and the safety of flight. The technical solution is as follows:

[0012] A laser radar-based real-time monitoring method for aircraft wake, comprising the following steps:

[0013] Step S1, synchronize the clocks and spatial coordinate systems of the multiple laser radar devices on the five-edge approach path with the air traffic control system; during the five-edge approach phase of the preceding aircraft, use the multiple laser radar devices to collect real-time data of the preceding aircraft, including wake data and wind field data; preprocess the wake data, including data calibration and background wind field removal;

[0014] Step S2, using the pre-processed wake data, determining the wake region edge by edge detection algorithm, and obtaining the spatial coordinates of the wake region edge, determining the three-dimensional profile of the wake region of the front aircraft; according to the spatial coordinates of the left and right edges and the upper and lower edges of the wake region, the width data and the height data of the wake region are calculated, and the width data and the height data of the wake region are superimposed on the radar interface of the air traffic control system, and the wake region of the front aircraft is displayed in real time;

[0015] Step S3, collecting real-time flight height data and real-time flight speed data of the rear aircraft, and intercepting the two-dimensional section of the three-dimensional profile of the front aircraft wake region under the real-time flight height plane of the rear aircraft; according to the model and aerodynamic parameters of the front aircraft and the rear aircraft, the real-time flight speed data of the rear aircraft and the pre-processed wake data of the front aircraft, the roll moment of the two-dimensional section region on the rear aircraft wing is calculated, and the corresponding roll instability index is calculated using the roll moment; according to the preset roll instability index safety threshold, the dangerous region range of the front aircraft wake under the real-time flight height of the rear aircraft is determined; according to the dangerous region range of the front aircraft wake under the real-time flight height of the rear aircraft, the minimum safety interval between the front aircraft and the rear aircraft is obtained, and is displayed in real time on the radar interface of the air traffic control system.

[0016] Further, the step S1 of synchronizing the plurality of laser radar devices on the five-edge approach path with the clock and the spatial coordinate system of the air traffic control system comprises the following steps:

[0017] Synchronize the plurality of laser radar devices with the clock of the air traffic control system through the network time protocol NTP or GPS;

[0018] Synchronize the plurality of laser radar devices with the spatial coordinate system of the air traffic control system through the coordinate conversion matrix.

[0019] Further, the pre-processing of the wake data in step S1 comprises the following steps:

[0020] Firstly, the original data collected by the laser radar is calibrated by the calibration parameter, and the formula is: ; Wherein, is the calibrated original data, is the original data collected by the laser radar, is the calibration coefficient, is the calibration offset;

[0021] Then, using the calibrated original data, the local mean of the wind field data in the wake data is removed to highlight the dynamic characteristics of the wake, and the formula is: ; ; Wherein, tail flow data after removing background wind field, tail flow data after calibration, is the background wind speed at the current time, is the background wind speed at the current time, is the wind field data sequence after calibration, is an index variable, is the sampling window size of the filter.

[0022] Further, the step S2 of determining the edge of the wake region by the edge detection algorithm comprises the following steps:

[0023] According to the Doppler effect principle, the preprocessed wake data is converted into a local airflow velocity distribution, and a signal intensity distribution map of the wake region is constructed;

[0024] In the signal intensity distribution map of the wake region, the gradient value of each pixel point is calculated by a gradient operator , and a gradient map is generated, and the calculation formula of the gradient value is: ; wherein, represents the wake signal intensity of each pixel point in the signal intensity distribution map, and respectively represent the change rate of the signal intensity in the horizontal direction and the vertical direction;

[0025] Set a gradient threshold, and determine the region boundary with a gradient value higher than the threshold as the edge of the wake region.

[0026] Further, the step S3 of calculating the roll moment generated by the two-dimensional cross-sectional region of the front aircraft and the rear aircraft on the rear aircraft wing according to the model and aerodynamic parameters of the front aircraft and the rear aircraft, the real-time flight speed data of the rear aircraft and the preprocessed wake data of the front aircraft comprises the following steps:

[0027] The vortex panel line method is used to calculate the change amount of the lift of each wing projection chord line of the rear aircraft due to the induced velocity of the wake, and the calculation formula is as follows: ; wherein, is the wake vortex circulation at the wing, is the change amount of the lift of each wing projection chord line due to the induced velocity of the wake, y is the wing spanwise coordinate, s y is the chord length of the wing at y , is the vertical induced velocity at y , C is the wing span, ​​for air density, for real-time flight speed of the rear aircraft, d is a differential symbol;

[0028] According to the lift change amount of each wing projection chord line caused by the wake induced velocity, the roll moment of the wake on the wing of the rear aircraft is calculated, and the calculation formula is as follows: ; wherein M L is the roll moment of the wake on the wing of the rear aircraft.

[0029] Further, it further comprises:

[0030] According to the historical data set of the wake dissipation time, the average wake dissipation time of different aircraft types under different headwind speeds is calculated, and is displayed in the radar interface of the air traffic control system; meanwhile, the wake dissipation time of the current front aircraft wake event is determined according to the wake intensity in the preprocessed wake data and the average intensity of the background wind field, and the aircraft type, the wake dissipation time and the real-time headwind speed of the current front aircraft wake event are added to the historical data set.

[0031] Further, the wake dissipation time of the current front aircraft wake event is determined according to the wake intensity in the preprocessed wake data and the average intensity of the background wind field, comprising the following steps:

[0032] The wake intensity of the preprocessed wake data is compared with the average intensity of the background wind field, when the wake intensity in the preprocessed wake data exceeds the average intensity of the background wind field, it is determined that this is the occurrence time of the wake of the current front aircraft wake event; after the wake undergoes a decay process, when the wake intensity is lower than the average intensity of the background wind field, it is determined that this is the end time of the wake of the current front aircraft wake event; the time interval between the occurrence time and the end time of the front aircraft wake is the wake dissipation time of the current front aircraft wake event.

[0033] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0034] The present application collects real-time wake data in the five-edge approach stage of the front aircraft through the laser radar equipment, determines the spatial coordinates and three-dimensional profile of the wake area edge combining the edge detection algorithm, and displays the wake area of the front aircraft in real time according to the coordinates of the left and right edges and the upper and lower edges of the wake area; intercepts the two-dimensional section of the three-dimensional profile of the wake area under the real-time flight height plane of the rear aircraft, calculates the roll instability index of the two-dimensional section area on the wing of the rear aircraft according to the front and rear aircraft types and aerodynamic parameters, real-time flight speed data of the rear aircraft and real-time wake data of the front aircraft, determines the minimum safety interval of the wake according to the preset roll instability index safety threshold, and displays it in real time on the radar interface of the air traffic control system, so that the real-time monitoring of the wake area of the front aircraft and the minimum safety interval between the front and rear aircrafts in the five-edge approach stage of the aircraft is realized, and the air traffic controller can clearly understand the real-time state and potential risk of the aircraft wake, and the accuracy of the wake monitoring and the safety of the flight are improved.

[0035] According to the historical data set of the wake dissipation time, the present application calculates the mean value of the wake dissipation time of different aircraft types under different headwind speeds, and displays it in the radar interface of the air traffic control system; compares the wake intensity of the collected wake data with the average intensity of the background wind field, determines the wake dissipation time of the current front aircraft wake event, and adds it to the historical data set of the wake dissipation time, so as to provide the air traffic controller with the reference of the wake dissipation time considering the headwind speed, and improve the reliability of the wake monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 It is the schematic diagram of the overall process of the present method.

[0037] Figure 2 It is the test downslide interface diagram of the air traffic control system.

[0038] Figure 3 It is the mean value of the wake dissipation time prompt interface diagram.

[0039] Figure 4 It is the radar interface diagram of the air traffic control system when the distance between the front and rear aircrafts is greater than the wake interval standard.

[0040] Figure 5 It is the radar interface diagram of the air traffic control system when the distance between the front and rear aircrafts is less than the wake interval standard.

[0041] Figure 6 It is the radar interface diagram of the air traffic control system when the distance between the front and rear aircrafts is less than the wake interval standard. DETAILED DESCRIPTION

[0042] The technical solutions in the present application will be described clearly and completely in combination with the drawings in the present application, so as to have a further understanding of the concept of the present application, the solved technical problems, the technical features constituting the technical solutions and the brought technical effects.

[0043] The approach phase refers to the flight phase of an aircraft after descending from the en route phase to the initial approach positioning point (IAF). It is divided into three segments: initial approach, intermediate approach, and final approach. The fifth approach refers to the process by which the aircraft, under the guidance of air traffic controllers, enters the final approach segment, completes the heading alignment with the runway direction, and descends for landing. This plan applies to the fifth approach phase during the approach and landing process.

[0044] like Figure 1 The diagram shown illustrates the overall process of this method. This method designs a real-time aircraft wake turbulence monitoring approach suitable for air traffic automation management systems. It is used to monitor the wake turbulence region of the preceding aircraft and the minimum safe separation between aircraft during the five-way approach phase. Specifically, it includes:

[0045] Step S1: Synchronize the clock and spatial coordinate system of multiple lidar devices along the five-sided approach path with the air traffic control system; during the five-sided approach phase of the leading aircraft, use multiple lidar devices to collect raw data from the leading aircraft in real time, including wake data and wind field data; preprocess the wake data, including data calibration and background wind field removal, specifically including the following steps:

[0046] Step S11: Synchronize the clock and spatial coordinate systems of multiple Doppler lidar devices on the five-sided approach path with the air traffic control system;

[0047] To ensure that the data from all LiDAR devices are consistent with the air traffic control system's time standard, time synchronization is performed. Typically, all LiDAR devices are synchronized with the air traffic control system's clock to ensure the data is correctly arranged in time. The synchronization formula is as follows: ; in, It is the synchronized timestamp. It is the timestamp of the lidar device. It is the time offset, which is usually calculated through Network Time Protocol (NTP) or GPS time synchronization.

[0048] Step S12: Next, spatial synchronization is performed to ensure that the spatial coordinate systems of different sensors or radars are consistent.

[0049] Each detection unit data of the Doppler lidar includes range (r), i.e., the distance from the lidar to the target voxel; azimuth (θ), i.e., the horizontal scanning angle; and elevation (θ). ), that is, the vertical angle; radial velocity (V r (i.e., detecting the velocity of the target along the radar beam direction);

[0050] The data collected by the lidar equipment is in polar coordinates (r, θ, ...). ) is expressed, and the Cartesian coordinate system (X, Y, Z) is defined, and the formula is as follows: ; ; ; Wherein, the positive direction of the X axis is the flight direction of the aircraft; the Y axis is the lateral direction, that is, parallel to the ground and perpendicular to the X axis direction, which can represent the lateral wake width, and the Z axis is the direction perpendicular to the ground, vertically upward, which can represent the wake height; according to the coordinates of the left and right edges and the upper and lower edges of the wake, the polar coordinates are converted to Cartesian coordinates, and the actual spatial height (Z axis) and actual width (Y axis) of the wake can be obtained;

[0051] Based on the Cartesian coordinate system (X, Y, Z), the spatial coordinates of all laser radar devices and air traffic control systems are synchronized through the coordinate conversion matrix; assuming that the data coordinates collected by the laser radar device are (y radar , z radar ), and the air traffic control system coordinate system is (y system , z system ), the expression of the space synchronization of the two is: ; Wherein, is the coordinate transformation matrix.

[0052] Step S13, starting at the five-edge 25km of the aircraft, when intercepting the glide path, the raw data of the preceding aircraft obtained by the multiple Doppler laser radar devices arranged on the five-edge approach path of the aircraft are used for real-time detection, the raw data including wake data (velocity field, position, etc. of the wake) and wind field data, and the wake data is preprocessed: first, the raw data collected by the laser radar is calibrated by the calibration parameters, and the formula is: ; Wherein, is the calibrated raw data, is the raw data collected by the laser radar, is the calibration coefficient, is the calibration offset;

[0053] Then, using the calibrated raw data, the local mean of the wind field data is removed in the wake data to highlight the dynamic characteristics of the wake, and the formula is: ; ; Wherein, is the wake data after removing the background wind field, is the calibrated wake data, is the background wind speed at the current moment, is the background wind speed at the moment, is the calibrated wind field data sequence, for example may be represented as the 8-point atmospheric wind field data collected, is represented as the atmospheric wind field data collected at 8 o'clock 2 seconds, and so on. is an index variable, is the sampling window size of the filter.

[0054] In the radar interface of the air traffic control system, the real-time flight positions of the front aircraft and the rear aircraft are displayed in real time, and the icons of the front aircraft and the rear aircraft are represented by a green circular ring and a yellow circular ring respectively.

[0055] The method realizes real-time monitoring of the aircraft wake based on the wake data collected by the laser radar in the five-edge approach stage of the aircraft, reduces the wake data transmission time, and improves the real-time performance and accuracy of the wake monitoring.

[0056] Step S2, using the preprocessed wake data, determining the edge of the wake area by an edge detection algorithm, and obtaining the spatial coordinates of the edge of the wake area, determining the three-dimensional contour of the wake area of the front aircraft; according to the spatial coordinates of the left and right edges and the upper and lower edges of the wake area, the width data and the height data of the wake area are calculated, and the width data and the height data of the wake area are superimposed on the radar interface of the air traffic control system, the wake area of the front aircraft is displayed in real time, which specifically includes the following steps:

[0057] Step S21, according to the Doppler effect principle, the preprocessed wake data is converted into local airflow velocity distribution, and a signal intensity distribution map of the wake area is constructed, and the basic formula is: ; wherein, is the local airflow velocity, is the Doppler shift detected by the laser radar, is the wavelength of the laser.

[0058] Step S22, after obtaining the two-dimensional distribution map of the wake area, an edge detection algorithm is used to extract the edge of the wake area, and the three-dimensional contour of the wake area of the front aircraft is determined:

[0059] In the constructed signal intensity distribution map of the wake area, the gradient value of each pixel point is calculated by a gradient operator , and a gradient map is generated, and the calculation formula of the gradient value is: ; wherein, represents the wake signal intensity of each pixel point in the signal intensity distribution map, and These represent the rates of change of the signal strength in the horizontal and vertical directions, respectively.

[0060] Based on the gradient value of each pixel, a wake region gradient map is obtained. By setting an appropriate gradient threshold, the boundary of the region with a gradient value higher than the threshold in the wake region gradient map is determined as the edge of the wake region, and the spatial coordinates of the edge of the wake region are obtained to determine the three-dimensional contour of the wake region of the front machine.

[0061] Step S23: Calculate the width and height data of the wake region based on the spatial coordinates of the left and right edges and the top and bottom edges of the wake region, and overlay the width and height data of the wake region onto the air traffic control system radar interface to display the wake region of the preceding aircraft in real time.

[0062] Step S231: Using the coordinates of the left and right edges of the acquired wake region in the Y-axis direction, calculate the width data of the wake region of the front aircraft. Wake region width data The calculation formula is: ; in, and These are the coordinates of the right and left edges of the wake region along the Y-axis, respectively.

[0063] The wake region width data is overlaid on the air traffic control system radar interface to display the wake region range of the preceding aircraft in real time, and the edge outline of the wake region is marked with a solid yellow line.

[0064] Step S232: Using the obtained coordinates of the upper and lower edges of the wake region in the Z-axis direction, calculate the wake region height data of the preceding aircraft. Wake region height data The calculation formula is: ; in, and These are the coordinates of the upper and lower edges of the wake region along the Z-axis, respectively.

[0065] The wake region height data is overlaid on the air traffic control system's side-view glide slope interface to display the wake region range of the preceding aircraft in real time; for example... Figure 2 As shown, in the side-view glide slope interface, the aircraft icon is represented by a circle, displaying the current profile position of the aircraft during the five-sided approach landing, its relative position to the standard 3° glide slope, and its relative position to the runway threshold. Next to each aircraft's icon, a label displays information such as the current aircraft's flight number, aircraft type, and flight altitude.

[0066] The air traffic control system superimposes the contour of the wake on the real-time radar image on the radar interface to intuitively show the spatial distribution of the wake, thereby helping the controller to better monitor the safety separation and adjust the operation, and improving the safety of flight.

[0067] Step S3, collecting real-time flight height data and real-time flight speed data of the rear aircraft, intercepting a two-dimensional section of the three-dimensional contour of the wake area of the front aircraft under the real-time flight height plane of the rear aircraft; calculating the roll moment generated by the two-dimensional section area on the wings of the rear aircraft according to the model and aerodynamic parameters of the front and rear aircrafts, the real-time flight speed data of the rear aircraft and the preprocessed wake data of the front aircraft, and calculating the corresponding roll instability index using the roll moment; determining the dangerous area range of the wake of the front aircraft at the real-time flight height of the rear aircraft according to the preset roll instability index safety threshold; obtaining the minimum safety separation between the front and rear aircrafts according to the dangerous area range of the wake of the front aircraft at the real-time flight height of the rear aircraft, and displaying it in real time on the radar interface of the air traffic control system, specifically including the following steps:

[0068] Step S31, obtaining the real-time flight height data of the rear aircraft according to the ADS-B data and the radar control device API interface, and intercepting a two-dimensional section of the three-dimensional contour of the wake area of the front aircraft under the real-time flight height of the rear aircraft as the wake area of the front aircraft at the real-time flight height of the rear aircraft.

[0069] Step S32, obtaining the model category (J, B, C, etc.), aerodynamic parameters (wing area, wing span, etc.) of the front and rear aircrafts and the real-time flight speed data of the rear aircraft from the air traffic control software; calculating the key parameters such as circulation of the wake according to the preprocessed wake data collected by the laser radar of the front aircraft.

[0070] Step S33, calculating the roll moment generated by the wake area of the front aircraft at the real-time flight height of the rear aircraft on the wings of the rear aircraft according to the model and aerodynamic parameters of the front and rear aircrafts, the real-time flight speed data of the rear aircraft and the preprocessed wake data of the front aircraft, including:

[0071] Calculating the vertical induced velocity field V of the wake area of the front aircraft at the real-time flight height plane of the rear aircraft, abstracting the wake of the front aircraft as a point vortex system, setting the left and right wake vortex core coordinates of the aircraft wake as (y1, z1) and (y2, z2), and calculating the induced velocity of any point (y, z) in the YOZ coordinate system in the real-time flight height plane of the rear aircraft V (y, z), the formula is as follows: ; Where, is the circulation at the point (y, z), is the vortex core radius;

[0072] The change in lift caused by wake-induced velocity along the projected chord of each wing of the rear fuselage is calculated using the vortex plate method. The calculation formula is as follows: ; in, This refers to the amount of wake vortex annulus at the wing. The change in lift caused by the wake-induced velocity along each wing projection chord. y For wing spanwise coordinates, s ( y ) for the wing in y chord length at the point, for y Vertical induced velocity at that location C For wingspan, air density, This refers to the real-time flight speed of the aircraft behind it. d The differential symbol;

[0073] Based on the change in lift caused by the wake-induced velocity along each wing projection chord, the rolling moment generated by the wake on the rear wing is calculated using the following formula: ; Among them, M L This refers to the rolling torque generated by the wake on the rear wing of the aircraft.

[0074] Step S34: Calculate the corresponding instability index using the roll moment generated on the wing of the rear aircraft by the wake region of the preceding aircraft at the real-time flight altitude of the following aircraft. E The calculation formula is: ; in, This refers to the area of ​​the rear fuselage wing;

[0075] Instability Index E As an indicator for determining wake hazard areas, the roll instability index safety threshold can be set based on the common aircraft types at the airport. H The roll instability index of the preceding aircraft in the wake region at the real-time flight altitude of the following aircraft. E > H The area is identified as a wake hazard zone. In this embodiment, the roll instability index safety threshold is... H Set to 0.05.

[0076] Step S35, the distance between the farthest end of the wake hazard area close to the rear aircraft direction (X-axis negative direction) and the front aircraft tail end on the X-axis is taken as the minimum safety interval between the front aircraft and the rear aircraft; on the radar interface of the air traffic control system, the coordinates of the center of the front aircraft icon (green circle) on the X-axis and the coordinates of the farthest end of the wake hazard area range close to the rear aircraft direction on the X-axis are connected by a red thick solid line, and the distance between the two coordinates is marked in red font, with the unit accurate to 0.1 km, for example, "WAR4.7KM", indicating that the minimum safety interval between the front aircraft wake and the rear aircraft is 4.7KM;

[0077] Real-time monitoring of the minimum safety interval between the front and rear aircrafts is realized on the radar interface of the air traffic control system according to the real-time sinking track of the wake and the real-time flight height of the rear aircraft, the accuracy of wake monitoring is improved, and the air traffic controller can accurately know the potential risk of the wake, thereby improving the safety of flight.

[0078] Step S4, according to the historical data set of wake dissipation time, the mean value of wake dissipation time of different aircraft types under different headwind speeds is calculated and displayed in the radar interface of the air traffic control system; at the same time, the wake dissipation time of the current front aircraft wake event is determined according to the wake intensity in the preprocessed wake data and the average intensity of the background wind field, and the aircraft type, wake dissipation time and real-time headwind speed of the current front aircraft wake event are added to the historical data set, as follows:

[0079] By comparing the preprocessed wake signal with the average signal of the background wind field , the occurrence and end time of the wake are determined, so as to calculate the wake dissipation time of the current front aircraft wake event, and the aircraft type, wake dissipation time and real-time headwind speed of the current front aircraft wake event are added to the historical data set;

[0080] The processed background wind field data signal is taken as the basis for determining the occurrence time of the wake When the wake signal collected by the laser radar exceeds the average signal of the background wind field , it is considered that the wake begins to appear, and the corresponding time is recorded, and the determination formula is: ; Wherein, t represents the time;

[0081] The determination of the end time of the wake When the wake signal undergoes a decay process and its intensity decreases below the average signal of the background wind field , it is considered that the wake ends, and the time is recorded, and the determination formula is: ;

[0082] According to the determination criteria of the appearance and end time of the wake, the wake dissipation time is defined The time interval of the wake signal from the appearance time to the end time : ;

[0083] According to the historical data set of the wake dissipation time, the mean value of the wake dissipation time of different aircraft types under different headwind speeds is calculated. For the same aircraft type under the same headwind condition, the th wake dissipation time is recorded as , and the mean value of the wake dissipation time of the same aircraft type under the same headwind speed is . The calculation formula is: ; Among them, is the total number of wake events of the same aircraft type under the same headwind speed, is the wake dissipation time of the th wake event.

[0084] As shown in Figure 3 , the mean value of the wake dissipation time (Decay Time Mean Value) of different aircraft types and different headwind speeds is displayed in the form of a table in the air traffic control system. Different wake level aircraft types refer to the standards of RECAT-CN, and the mean value of the dissipation time of B, M and C level aircraft is displayed to provide key wake dynamic monitoring data for the air traffic management system, so that the controller can intuitively understand the dissipation characteristics of the wake of various aircraft types under different weather conditions, thereby more accurately evaluating the influence of the wake on the following aircraft, reasonably adjusting the interval between aircraft, improving the safety and control allocation ability of control command, and improving the reliability of wake monitoring.

[0085] Step S5, wake warning display on the air traffic control system radar interface:

[0086] Determine the front and rear aircraft wake interval standard according to the front and rear aircraft types and the RECAT-CN radar wake interval standard. The RECAT-CN radar wake interval standard is shown in Table 1:

[0087] Table 1 RECAT-CN radar wake interval standard .

[0088] In the air traffic control system radar interface (top view), the aircraft information placard of the front and rear aircraft is displayed beside the icons of the front and rear aircraft, and the runway number, flight number, aircraft type, current flight height and ground speed and other information are displayed in black font.

[0089] When the aircraft behind cuts into the fifth approach and intercepts the glide path, the aircraft type and wake separation standard of the aircraft in front and behind are displayed below the aircraft information label of the aircraft behind, for example, "B < M 9.3KM". "B < M" means that the aircraft in front is a type B and the aircraft behind is a type M. "9.3KM" means that the current RECAT-CN radar wake separation standard between the aircraft in front and the aircraft behind is the RECAT-CN radar wake separation standard when the aircraft in front is a type B aircraft and the aircraft behind is a type M aircraft.

[0090] like Figure 4 As shown, when the distance between the center of the front aircraft icon (green ring) and the rear aircraft icon (yellow ring) is greater than the RECAT-CN radar wake separation standard between the currently operating front and rear aircraft, "B < M 9.3KM" will be displayed in yellow font;

[0091] like Figure 5 As shown, when the distance between the center of the front aircraft icon (green ring) and the rear aircraft icon (yellow ring) is less than the RECAT-CN radar wake separation standard between the currently operating front and rear aircraft, "B < M 9.3KM" will be displayed with a yellow box.

[0092] like Figure 6 As shown, when the center of the aircraft icon (yellow circle) enters the wake turbulence area of ​​the aircraft in front, a yellow box is added to the display of "B < M 9.3KM". Below "B < M 9.3KM", a bold red "IN WAKE" is displayed and flashes as a warning. This allows controllers to quickly determine whether the safe distance between the aircraft in front and behind meets the standard based on the intuitive display on the air traffic control system radar interface, ensuring flight safety and improving the efficiency of air traffic control.

[0093] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for real-time monitoring of aircraft wake based on lidar, characterized in that, The method comprises the following steps: Step S1, synchronizing the multiple laser radar devices on the five-edge approach path with the clock and spatial coordinate system of the air traffic control system; during the five-edge approach phase of the preceding aircraft, the multiple laser radar devices are used to collect real-time raw data of the preceding aircraft, and the raw data comprises wake data and wind field data; The wake data is preprocessed, including data calibration and background wind field removal; Step S2, using the preprocessed wake data, the edge detection algorithm is used to determine the edge of the wake area and obtain the spatial coordinates of the edge of the wake area, and the three-dimensional profile of the wake area of the preceding aircraft is determined; according to the spatial coordinates of the left and right edges and the upper and lower edges of the wake area, the width data and the height data of the wake area are calculated, and the width data and the height data of the wake area are superimposed on the radar interface of the air traffic control system, and the wake area of the preceding aircraft is displayed in real time; Step S3, collecting real-time flight height data and real-time flight speed data of the following aircraft, and intercepting the two-dimensional section of the three-dimensional profile of the wake area of the preceding aircraft under the real-time flight height plane of the following aircraft; according to the model and aerodynamic parameters of the preceding aircraft and the following aircraft, the real-time flight speed data of the following aircraft and the preprocessed wake data of the preceding aircraft, the roll moment of the two-dimensional section area on the wing of the following aircraft is calculated, and the corresponding roll instability index is calculated using the roll moment; according to the pre-set roll instability index safety threshold, the dangerous area range of the wake of the preceding aircraft at the real-time flight height of the following aircraft is determined; the minimum safety interval between the preceding aircraft and the following aircraft is obtained according to the dangerous area range of the wake of the preceding aircraft at the real-time flight height of the following aircraft, and is displayed in real time on the radar interface of the air traffic control system.

2. A laser radar based aircraft wake real-time monitoring method according to claim 1, characterized in that, In step S1, the multiple laser radar devices on the five-edge approach path are synchronized with the clock and spatial coordinate system of the air traffic control system, comprising the following steps: Synchronize the multiple laser radar devices with the clock of the air traffic control system through the network time protocol NTP or GPS; Synchronize the multiple laser radar devices with the spatial coordinate system of the air traffic control system through the coordinate conversion matrix.

3. A laser radar based aircraft wake real-time monitoring method according to claim 1, wherein, The preprocessing of the wake data in step S1 comprises the following steps: First, the original data collected by the laser radar is calibrated by the calibration parameters, and the formula is: ； wherein, is the calibrated raw data, is the raw data collected by the lidar, is the calibration coefficient, is the calibration offset; Then, using the calibrated original data, the local mean of the wind field data in the wake data is removed to highlight the dynamic characteristics of the wake, and the formula is: ； ； wherein, is the wake data after removing the background wind field, is the calibrated wake data, is the background wind speed at the current time, is the background wind speed at the current time, is the background wind speed at the current time, is the sequence of calibrated wind field data, is an index variable, is the sample window size of the filter.

4. A laser radar based aircraft wake real-time monitoring method according to claim 1, wherein, In step S2, the edge detection algorithm is used to determine the edge of the wake area, comprising the following steps: According to the Doppler effect principle, the preprocessed wake data is converted into a local airflow velocity distribution, and a signal intensity distribution map of the wake area is constructed; In the signal intensity distribution map of the wake region, the gradient value of each pixel point is calculated by a gradient operator , and a gradient map is generated, and the calculation formula of the gradient value is: ； wherein, represents the wake signal intensity of each pixel point in the signal intensity distribution map, and respectively represent the rate of change of the signal intensity in the horizontal direction and the vertical direction; Set a gradient threshold, and determine the region boundary with a gradient value higher than the threshold as the edge of the wake area.

5. A laser radar based aircraft wake real-time monitoring method according to claim 1, wherein, In step S3, according to the model and aerodynamic parameters of the preceding aircraft and the following aircraft, the real-time flight speed data of the following aircraft and the preprocessed wake data of the preceding aircraft, the roll moment of the two-dimensional section area on the wing of the following aircraft is calculated, comprising the following steps: The vortex plate line method is used to calculate the lift change of each wing projection chord line caused by the wake induced velocity, and the calculation formula is as follows: ； wherein, is the wake vortex circulation at the wing, is the change in lift of each wing due to wake induced velocity, y is the spanwise coordinate of the wing, s y is the chord length of the wing at y is the vertical induced velocity at y C is the wing span, is the air density, is the real-time flight speed of the aft wing, d is the differential symbol;​​​ According to the lift change of each wing projection chord line caused by the wake induced velocity, the roll moment of the wake on the wing of the following aircraft is calculated, and the calculation formula is as follows: ； where M L is the roll moment generated by the wake on the wing of the following aircraft.

6. A laser radar based aircraft wake real-time monitoring method according to claim 1, wherein, Further comprising: According to the historical data set of wake dissipation time, the mean values of wake dissipation time of different aircraft models under different headwind speeds are calculated and displayed in the radar interface of the air traffic control system; meanwhile, the wake dissipation time of the current preceding aircraft wake event is determined according to the wake intensity in the preprocessed wake data and the average intensity of the background wind field, and the aircraft model of the current preceding aircraft wake event, the wake dissipation time and the real-time headwind speed are added to the historical data set.

7. A laser radar based aircraft wake real-time monitoring method according to claim 6, characterized in that, The determination of the wake dissipation time of the current preceding aircraft wake event according to the wake intensity in the preprocessed wake data and the average intensity of the background wind field comprises the following steps: The wake intensity in the preprocessed wake data is compared with the average intensity of the background wind field, when the wake intensity in the preprocessed wake data exceeds the average intensity of the background wind field, it is determined that this is the appearance time of the wake of the current preceding aircraft wake event; after the wake undergoes a certain decay process, when the wake intensity is lower than the average intensity of the background wind field, it is determined that this is the end time of the wake of the current preceding aircraft wake event; the time interval between the appearance time and the end time of the wake of the preceding aircraft is the wake dissipation time of the current preceding aircraft wake event.

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