CN112965084A - Airport wind field characteristic detection method, device and equipment based on laser radar - Google Patents
Airport wind field characteristic detection method, device and equipment based on laser radar Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/95—Lidar systems specially adapted for specific applications for meteorological use
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- G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
- G01P5/00—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft
- G01P5/26—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft by measuring the direct influence of the streaming fluid on the properties of a detecting optical wave
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Abstract
The application relates to a method, a device and equipment for detecting airport wind field characteristics based on laser radar, wherein the method comprises the following steps: scanning strategy configuration is carried out on the laser radar deployed at a preset position of an airport according to a set configuration strategy; obtaining Doppler radial velocity information obtained by volume scanning of the laser radar, and obtaining a three-dimensional wind field in a scanning volume through inversion; extracting wind field data below 600 meters from the three-dimensional wind field, and calculating according to the wind field data below 600 meters to obtain corresponding F factor values; extracting radial wind speed data of 35.3-degree altitude angle in Doppler radial speed information, and calculating by partial Fourier decomposition algorithm to obtain the kinetic energy intensity of turbulence at different heights; and extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information, and calculating by a Doppler frequency spectrum method to obtain the turbulent flow dissipation rate of each radial distance of the wind field. According to the scheme, the effect of stronger comprehensive detection performance of the wind field is achieved.
Description
Technical Field
The application relates to the technical field of aviation meteorological guarantee, in particular to a method, a device and equipment for detecting airport wind field characteristics based on a laser radar.
Background
Low altitude wind shear and turbulence are internationally recognized wind field phenomena that severely impact flight safety. Low altitude wind shear generally refers to the variation of the wind vector (wind direction, wind speed) over horizontal and/or vertical distances below 600 meters height near the ground; turbulence is caused by the sharp and irregular flow of air, manifested as temporal and spatial irregularities in wind speed, superimposed by the continuous distribution of vortices of various dimensions. Because wind shear and turbulence have the characteristics of high intensity, difficult prediction and the like, the safety of the airplane in the takeoff phase and the landing phase is seriously damaged. Currently, the technologies for wind shear and turbulence detection mainly include anemometers, meteorological radars, wind profile radars, and lidar, where lidar is considered to be a wind field detection system with superior clear air conditions.
There are various scanning strategies for wind shear and turbulence detection using lidar, mainly including PPI (Plan Position Indicator), RHI (Range Height Indicator), DBS (Doppler Beam swing), staring, GPScan (Glide Path Scan), and the like. However, in the process of implementing the present invention, the inventor finds that the conventional lidar scanning strategy still has the technical problem of poor comprehensive detection performance of the wind field.
Disclosure of Invention
In view of the above, it is necessary to provide a lidar-based airport wind field feature detection method with a strong wind field comprehensive detection performance, a lidar-based airport wind field feature detection apparatus, a computer device and a computer-readable storage medium.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
on one hand, the embodiment of the invention provides a method for detecting airport wind field characteristics based on laser radar, which comprises the following steps:
scanning strategy configuration is carried out on the laser radar deployed at a preset position of an airport according to a set configuration strategy;
obtaining Doppler radial velocity information obtained by volume scanning of the laser radar, and obtaining a three-dimensional wind field in a scanning volume through inversion;
extracting wind field data below 600 meters from the three-dimensional wind field, and calculating according to the wind field data below 600 meters to obtain corresponding F factor values;
extracting radial wind speed data of 35.3-degree altitude angle in Doppler radial speed information, and calculating by partial Fourier decomposition algorithm to obtain the kinetic energy intensity of turbulence at different heights;
and extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information, and calculating by a Doppler frequency spectrum method to obtain the turbulent flow dissipation rate of each radial distance of the wind field.
On the other hand, still provide an airport wind field characteristic detection device based on laser radar, include:
the configuration processing module is used for carrying out scanning strategy configuration on the laser radar deployed at a preset position of the airport according to a set configuration strategy;
the wind field inversion module is used for carrying out volume scanning according to the laser radar to obtain Doppler radial velocity information and carrying out inversion to obtain a three-dimensional wind field in a scanning volume;
the factor calculation module is used for extracting wind field data below 600 meters from the three-dimensional wind field and calculating to obtain a corresponding F factor value according to the wind field data below 600 meters;
the kinetic energy calculation module is used for extracting radial wind speed data of a 35.3-degree altitude angle in the Doppler radial speed information and calculating the kinetic energy intensity of turbulence at different heights through a partial Fourier decomposition algorithm;
and the turbulence calculation module is used for extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information and calculating the turbulence dissipation rate of each radial distance of the wind field through a Doppler frequency spectrum method.
In still another aspect, a computer device is further provided, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the above method for detecting wind field characteristics of an airport based on lidar when executing the computer program.
In still another aspect, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, implements the steps of the above-mentioned lidar-based airport wind field characteristic detection method.
One of the above technical solutions has the following advantages and beneficial effects:
according to the airport wind field characteristic detection method, device and equipment based on the laser radar, after the laser radar deployed to a preset position of an airport is configured according to a scanning strategy, the laser radar carries out volume scanning to obtain a radial speed for inverting a three-dimensional wind field in a scanning volume, then wind field data below 600 meters are extracted to be used for calculating a corresponding F factor value, radial wind speed data of 35.3-degree altitude angles are extracted, the kinetic energy intensity of turbulent flow at different heights is calculated through a partial Fourier decomposition algorithm, finally Doppler frequency spectrum data of each altitude angle is extracted, and the turbulent flow dissipation rate of each radial distance of the wind field is calculated through a Doppler frequency spectrum method. Therefore, a multipurpose wind lidar volume scanning strategy under the clear sky condition is formed, the space coverage, the space-time resolution and the robustness can be effectively considered, the key detection on the aircraft glidepath area can be realized, the accurate sensing on the near-field turbulence intensity can also be realized, the accurate detection and inversion can also be realized on the three-dimensional wind field, and the effect of stronger comprehensive detection performance of the wind field is achieved.
Drawings
FIG. 1 is a schematic flow chart of a method for detecting airport wind field characteristics based on lidar in one embodiment;
FIG. 2 is a schematic diagram of a scanning strategy for a lidar in one embodiment;
FIG. 3 is a schematic diagram of an improved VPP wind field inversion algorithm analysis unit in one embodiment;
FIG. 4 is a schematic illustration of an aircraft glidepath area according to one embodiment;
FIG. 5 is a schematic illustration of a 35.3 elevation scan in one embodiment;
FIG. 6 is a diagram of a Doppler spectrum of a lidar in one embodiment;
FIG. 7 is a schematic block diagram of an airport wind field feature detection device based on lidar in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. It will be understood that when an element is referred to as being "connected" to another element, it can be directly connected to the other element and integrated therewith or intervening elements may be present, i.e., indirectly connected to the other element.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
In various scanning strategies of detecting wind shear and turbulence by adopting a laser radar, the PPI scanning mode is that the height angle of a laser beam is fixed, and uniform scanning is carried out in the azimuth, and based on the scanning mode, under the assumption that wind fields at the same height are consistent, wind profile information (including wind speed and wind direction) in a scanning area can be inverted through Fourier series expansion; when the height angle is 35.3 degrees, the turbulence kinetic energy intensity can be quickly acquired by using a partial Fourier decomposition algorithm; meanwhile, turbulence characteristic parameters can be inverted through a radial velocity and azimuth structure function.
The RHI scanning mode is that the azimuth angle of a laser beam is fixed, and the elevation angle is scanned up and down uniformly. The scanning mode can accurately detect the radial wind field information of a plurality of altitude angles, and is usually used when the speed change in the vertical direction is large, such as the detection of aircraft wake flow. Based on the method, various parameters of the turbulence are calculated by fitting a radial velocity structure function and the Von Kalman spectrum. However, the detection coverage range of the method is small, only the wind field information of a certain direction can be detected, and the three-dimensional wind field cannot be sensed.
The DBS scanning mode is that laser beams are rapidly scanned in a plurality of directions with fixed altitude angles and azimuth angles, is similar to the PPI scanning mode, and can rapidly invert wind field profile information with different heights by using the scanning mode under the assumption that a wind field with the same altitude is uniform. Based on the mode, the information such as wind speed, wind direction and turbulence kinetic energy intensity can be solved by establishing a radial pulsation velocity equation. However, this method uses only a small amount of measurement information at azimuth angles and is susceptible to measurement errors at certain angles.
The staring scanning mode is a detection mode that the elevation angle and the azimuth angle of a laser beam are fixed, based on the mode, the turbulent flow dissipation rate is calculated through a Doppler frequency spectrum method and a radial velocity structure function method, but because the mode can only obtain the radial velocity in one direction, a three-dimensional wind field structure cannot be inverted, the detection range is small, and a large-range wind field cannot be perceived.
The GPScan scanning mode proposed by Chan et al, hong kong astronomical observatory, which employs cooperative variation of elevation and azimuth to scan a laser radar beam along a descending channel of an airplane, has a wind shear detection rate of 90% when a GLYGA algorithm is applied to the scanning mode. However, in the processing process, the laser radar radial wind speed is used as the head wind of the airplane, and the precondition is reasonable only when the laser radar is deployed near the landing point (or the flying point) of the airplane.
In summary, the existing various scanning methods are set based on some specific wind field characteristic acquisition requirements, cannot simultaneously realize inversion of large-scale three-dimensional wind fields, turbulence intensity, glide slope wind field characteristics and the like, and the comprehensive detection performance of the wind field is poor, so that a laser radar volume scanning method which considers space coverage, space-time resolution and robustness is urgently needed to be provided to obtain strong comprehensive detection performance of the wind field.
In order to solve the technical problem of poor comprehensive detection performance of a wind field in the traditional laser radar scanning strategy, the embodiment of the invention provides the following technical scheme:
referring to fig. 1, in an embodiment, the present invention provides a method for detecting airport wind field characteristics based on lidar, which includes the following steps S12 to S20:
and S12, scanning strategy configuration is carried out on the laser radar deployed at the preset position of the airport according to the set configuration strategy.
It will be appreciated that the lidar used for detection of airport wind field features should be deployed in the vicinity of the aircraft landing point, i.e. at what is referred to as the aforementioned airport predetermined location, such that the effective detection range R of the lidar ismaxThe airplane glidepath can completely cover all areas of the airplane glidepath, the deployment number of the laser radars can be one or more, and different laser radars can be selectively deployed according to the scale of different airports. The set configuration strategy refers to a scanning method set according to input data required by detection and calculation according to parameters such as a scanning mode, a scanning period number, a scanning height, a radar rotation angular velocity, a scanning sector and the like required by the laser radar when the laser radar scans the space volume of an airport airspace, and is used for configuring the scanning strategy of the laser radar so that the laser radar executes corresponding scanning operation according to the configured scanning strategy.
And S14, obtaining the three-dimensional wind field in the scanning volume by inversion according to Doppler radial velocity information obtained by volume scanning of the laser radar.
It can be understood that the laser radar performs volume scanning operation on the airport airspace and can output corresponding Doppler radial velocity information, wherein the radial velocity refers to the radial wind speed information of the scanned airspace. Doppler radial velocity information scanned and output by the laser radar is utilized, and data are converted into a coordinate system used for measuring a wind field, so that a three-dimensional wind field in a scanning volume when the laser radar scans an airport airspace can be obtained in an inversion mode. The three-dimensional wind field can contain wind speed data of the wind field in three dimensions, such as radial speed of different altitude angles in the wind field, horizontal tangential speed, vertical speed of a plane normal to the radial speed and the horizontal tangential speed, and the like.
And S16, extracting wind field data below 600 meters from the three-dimensional wind field, and calculating according to the wind field data below 600 meters to obtain corresponding F factor values.
It is understood that low altitude wind shear generally refers to the change in wind vector (wind direction, wind speed) over horizontal and/or vertical distances below 600 meters of near-ground height. Therefore, after the three-dimensional wind field is obtained by inversion, wind field data of 600 meters or less, for example, wind speed data of head wind, crosswind, vertical wind, and the like in the aircraft glidepath area of 600 meters or less, can be extracted from the three-dimensional wind field. And calculating to obtain a corresponding F factor value in the current wind field detection according to the calculation mode of the F factor in the field by using the wind field data.
And S18, extracting radial wind speed data of 35.3-degree altitude angles in the Doppler radial speed information, and calculating by a partial Fourier decomposition algorithm to obtain the kinetic energy intensity of turbulence at different altitudes.
It can be understood that radial wind speed data of 35.3 ° elevation angle can be extracted from doppler radial speed information obtained by volume scanning of the laser radar, wherein a partial fourier decomposition algorithm is a data processing algorithm existing in the art, and the extracted radial wind speed data of the specific elevation angle is solved on PPI scanning by using the algorithm, so that the kinetic energy intensity of turbulence at different heights can be calculated. The heights of different points in the airspace for volume scanning can be obtained by converting the radial distance and the elevation angle of the laser radar.
And S20, extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information, and calculating the turbulence dissipation rate of each radial distance of the wind field by a Doppler frequency spectrum method.
It is understood that the obtained doppler radial velocity information may include data of the lidar in a plurality of scanning cycles at each elevation angle, so that the doppler spectrum data at each elevation angle may be directly extracted from the obtained doppler radial velocity information, and then the doppler spectrum algorithm is used to calculate the turbulent dissipation rate at each radial distance accordingly.
According to the airport wind field characteristic detection method based on the laser radar, after the laser radar deployed to a preset position of an airport is configured according to a scanning strategy, the laser radar performs volume scanning to obtain a radial velocity to invert and scan a three-dimensional wind field in a volume, then wind field data below 600 meters are extracted to be used for calculating corresponding F factor values, radial wind velocity data of 35.3-degree altitude angles are extracted, kinetic energy intensities of turbulent flows at different heights are calculated through a partial Fourier decomposition algorithm, finally Doppler frequency spectrum data of all altitude angles are extracted, and turbulent flow dissipation rates of all radial distances of the wind field are calculated through a Doppler frequency spectrum method. Therefore, a multipurpose wind lidar volume scanning strategy under the clear sky condition is formed, the space coverage, the space-time resolution and the robustness can be effectively considered, the key detection on the aircraft glidepath area can be realized, the accurate sensing on the near-field turbulence intensity can also be realized, the accurate detection and inversion can also be realized on the three-dimensional wind field, and the effect of stronger comprehensive detection performance of the wind field is achieved.
Referring to fig. 2, in an embodiment, the step S12 may include the following steps:
determining an airport preset position for laser radar deployment; the vertical distance between the preset position of the airport and the runway is any distance value between 100m and 200m, and no obstacle is shielded between the laser radar and the lower slideway of the airplane;
establishing a Cartesian coordinate system (x, y, z) and a spherical coordinate system (phi, theta, r) by taking a laser radar as an origin; wherein x represents the distance from the laser radar in the direction perpendicular to the runway on the horizontal plane, y represents the distance from the laser radar in the direction parallel to the runway, z represents the distance from the laser radar in the vertical direction, phi represents the altitude angle, theta represents the azimuth angle, and r represents the radial distance to the laser radar; in FIG. 2, L denotes a lidar (hereinafter, the lidar of the corresponding figure is denoted by the letter L for the same reason), (φ)l,θm,rn) Indicating the altitude, azimuth and radial distance of a point in the spherical coordinates.
Setting a laser radar to alternately perform volume scanning in a PPI scanning mode with different altitude angles; the different elevation angles are arranged in accordance with phi 1,3,8,15,25,35.3,45, 90.
Specifically, before detecting the wind field characteristics required by the airport airspace, the laser radar is deployed on the landing point of the airplaneShort, perpendicular distance d from runwayTThe optimal selection is 100-200 m, so that no obstacle is shielded between the laser radar and the airplane lower slideway, and the effective detection distance R of the laser radar is ensuredmaxCan completely cover all areas of the aircraft glidepath. Among the different elevation angles of the arrangement, four elevation angles of 1,3, …,35.3, …,90 are the specific elevation angles of the scanning, and the rest of the elevation angles can be arranged according to 1,3,8,15,25,35.3,45, 90. If the specific area needs to be subjected to key scanning, encryption configuration can be carried out, and the difference delta phi between 2 adjacent elevation angles is less than 10 degrees. The 90-degree altitude can be selected according to the actual needs of different airport environments to reserve (can be used as a vertical wind speed reference), and the maximum altitude can be selected according to the actual altitude requirement and R of a measured airspacemaxAnd (the height angle of 45 degrees can meet the requirement of airspace detection below 600 meters). Through the steps, the deployment and scanning mode configuration of the laser radar can be completed quickly.
In an embodiment, regarding the substep of setting the laser radar to perform the volume scanning alternately by using PPI scans with different elevation angles in step S12, optionally, the setting process may be implemented specifically by the following processing steps:
setting a complete PPI scanning mode or a sector PPI scanning mode at each altitude angle of the laser radar to obtain Doppler radial velocity information of each altitude angle;
the rotation angular velocity and the scanning sector size of the laser radar are set to be adjustable along with the concerned detection space area respectively.
It should be noted that the above complete PPI scanning mode or sector PPI scanning mode is an existing PPI scanning strategy in the art, and the detailed explanation of the two scanning modes can be understood by referring to the same principle of PPI scanning technology in the art, and will not be described again in this embodiment. The detection space region concerned means a space region which needs to be mainly detected and designated by monitoring personnel according to the actual airspace environment of an airport, the entrance situation of an airplane and the like. The scanning control information such as different scanning modes, rotation angular velocities, scanning sectors and the like can be transmitted to the laser radar in real time or at regular time, so that the laser radar performs corresponding volume scanning according to the newly configured scanning control information.
Through the steps, the scanning mode configuration of the laser radar can be more accurate and flexible, and the scanning requirements under different working condition requirements can be met.
Referring to fig. 2 and 3, in an embodiment, the step S14 may include the following steps:
selecting an analysis volume unit in a scanning space of the laser radar, and determining the inversion speed of each point in the analysis volume unit;
wherein the analysis volume unit has a height angle span of
Span of azimuth angle of
And a radial distance span of
The analysis volume units are all equal in speed;
wherein phi islHeight angle, theta, representing a central point within the analysis volume unitmRepresenting the azimuth of a central point in the analysis volume, rnThe radial distance of a central point in the analysis volume unit is represented, delta phi, delta theta and delta r respectively represent the height angle, the azimuth angle and the radial resolution of the laser radar, and I, J and K respectively represent the number of the height angle, the azimuth angle and the radial resolution unit in the analysis volume unit;
converting the inversion speed of any point into a Cartesian coordinate system to obtain a three-dimensional wind field; the three-dimensional wind field is as follows:
wherein u, v and w represent the velocity components of the x-axis, y-axis and z-axis, respectively, in a Cartesian coordinate system, and ulmnRepresenting the radial velocity, v, of a central point within the analysis volume unitlmnPresentation of analytical volume sheetsHorizontal tangential velocity of centre point in element, wlmnRepresents ulmnAnd vlmnVertical velocity normal to the plane.
It will be appreciated that in the scanning space of the lidar, the analysis volume unit a may be selected according to the above stepslmnIn the analysis volume unit, phi can be usedi、θjAnd rkRespectively representing the elevation angle, azimuth angle and radial distance of any point within the analysis volume unit. Velocity of the center point in the analysis volume unit is (u)lmn,vlmn,wlmn)。
Assuming all velocities in the analysis volume are equal, the radial velocity at any point in the analysis volume is equal
Wind speed projection F on the wind field of the central pointijkTherefore u islmn、vlmnAnd wlmnThe expression of (c) can be expressed as:
Fijk＝ulmn(cosφlcosφicos(θm-θj)+sinφlsinφi)-vlmncosφisin(θm-θj)
+wlmn(cosφlsinφi-sinφlcosφicos(θm-θj))
inverting the velocity (u) of any pointlmn,vlmn,wlmn) The velocity (u, v, w) is obtained by conversion to a cartesian coordinate system, so that the corresponding three-dimensional wind field can be represented as shown in the foregoing steps. In fig. 3, AS represents an azimuth span, RS represents a radial distance span, and ES represents an elevation span.
Through the processing steps, the inversion of the three-dimensional wind field can be quickly and accurately realized.
In one embodiment, regarding step S16 described above, the following processing steps may be included:
if the included angle between the connecting line between the laser radar and the landing point of the airplane and the runway is less than 30 degrees, the head-on wind speed in the airplane glide slope is the radial speed of the altitude angle of 3 degrees on the azimuth angle;
extracting the vertical wind speed in the aircraft glidepath according to the three-dimensional wind field;
calculating to obtain an F factor value according to the head-on wind speed and the vertical wind speed; the F factor value is calculated by the following formula:
wherein, VhRepresenting head-on wind speed, w vertical wind speed, g gravitational acceleration, VaRepresenting the aircraft approach speed.
It can be understood that when the connection line between the laser radar and the landing point of the aircraft is formed, and the included angle Θ between the runways is smaller than 30 °, the radial speed of the 3 ° altitude angle at the azimuth angle of the runways can be directly selected as the head-on wind speed of the aircraft, and the corresponding vertical wind speed, that is, the vertical wind speed in the glidepath of the aircraft can be directly obtained from the corresponding wind speed data in the three-dimensional wind field inverted in the above steps. And calculating the corresponding F factor value by using the head-on wind speed and the vertical wind speed through the calculation formula of the F factor value.
Through the steps, when the included angle between the connecting line and the runway is less than 30 degrees, the corresponding F factor value can be obtained through calculation.
Referring to fig. 4, in an embodiment, the step S16 may alternatively include the following steps:
if the included angle between the connecting line between the laser radar and the aircraft landing point and the runway is more than 30 degrees, extracting wind field data in a spatial range of 30m in the radial direction by taking the aircraft glideslope as an axis at an azimuth angle of 3 degrees from the three-dimensional wind field;
synthesizing the head-on wind speed and the vertical wind speed in the aircraft glideslope according to the extracted wind field data;
calculating to obtain an F factor value according to the head-on wind speed and the vertical wind speed; the F factor value is calculated by the following formula:
wherein, VhRepresenting head-on wind speed, w representing vertical wind speed, g being gravitational acceleration, VaThe approach speed of the airplane.
It can be understood that when the connection line between the laser radar and the landing point of the airplane is connected and the included angle theta between the runways of the airplane is larger than 30 degrees, the wind field data in the area of the airplane glidepath is screened out according to the extracted three-dimensional wind field data, namely the three-dimensional wind field data in the space range of 30m nearby is selected by taking the airplane glidepath with the altitude angle of 3 degrees on the azimuth angle of the runway as an axis. Synthesizing the head-on wind speed V of the head-on wind in the aircraft glideslope again according to the extracted three-dimensional wind field datahVecos (pi · 3/180) -wsin (pi · 3/180), crosswind VcThe values of the F-factors are finally calculated using the data obtained above.
Through the steps, when the included angle between the connecting line and the runway is larger than 30 degrees, the corresponding F factor value can be obtained through calculation.
Referring to fig. 5, in an embodiment, the step S18 may include the following steps:
extraction ofRadial wind speed data in a plurality of scanning periods on the 35.3-degree elevation angle is calculated, and the average value of the radial speed of each point of the corresponding wind field in a plurality of periods is calculated<Vr>；
Calculating to obtain the pulsation radial velocity of each point of the corresponding wind field according to the radial velocity of each point and the corresponding average value;
calculating the kinetic energy intensity of the turbulence on the whole PPI scanning according to the pulse radial velocity; the intensity of the kinetic energy of the turbulent flow is calculated by the following formula:
wherein phi represents an altitude angle, V'rRepresenting the pulsatile radial velocity and theta the azimuth angle.
Specifically, in the analysis volume unit, radial wind speed data in a plurality of scanning periods at an altitude angle of 35.3 degrees are extracted, and the average value of the radial speed of each point in the analysis volume unit in a plurality of periods is calculated<Vr>Then calculating the pulsating radial velocity V 'of each point'r＝Vr-<Vr>And then calculating the kinetic energy intensity (TKE) of the turbulent flow on the whole PPI, wherein the corresponding height of each point is known by h ═ rsin phi:
wherein u ', v ' and w ' represent three pulsating velocity components of the three-dimensional wind field, respectively. Through the steps, the kinetic energy intensity of the high-efficiency failure turbulence can be calculated and obtained.
Referring to fig. 6, in an embodiment, the step S20 may include the following steps:
extracting Doppler frequency spectrum data in a plurality of scanning periods at each altitude angle, and calculating the average value of the Doppler frequency spectrum of each point of the corresponding wind field in the plurality of periods;
calculating to obtain radial velocity variance and turbulence outer scale according to the average value in a plurality of periods;
calculating to obtain the turbulent flow dissipation rate according to the radial velocity variance and the turbulent flow outer scale; the turbulent dissipation ratio is calculated by the following formula:
wherein σVRepresenting the square of the radial velocity variance, LV representing the turbulence outer scale, CKDenotes the Kolmogorov constant, CK≈2。
It can be understood that, in this embodiment, the doppler spectrum data in a plurality of scanning periods at each altitude angle is extracted, and the average value of the doppler spectrum of each point in the plurality of scanning periods is calculated
The turbulent dissipation ratio at each radial velocity is calculated by the doppler spectrum method.
Specifically, the following relationship is given:
wherein the content of the first and second substances,
which represents the doppler spectrum of the light beam,
indicating the spectral broadening caused by turbulence,
indicating the spectral broadening caused by wind shear,
representing the spectral width of a uniform wind field,<E>indicating an observation error.
Wherein
Representing radial wind shear;
where λ denotes the laser wavelength, σMfRepresenting the power spectral width, σ, of the ideal transmitted signalWThe width of the window function is represented,
representing the variance of the sampling frequency.
In fig. 6, a represents spectral broadening due to turbulence, b represents spectral broadening due to wind shear, c represents spectral broadening due to a uniform wind field, and d represents observation noise.
Under the premise of knowing the intrinsic parameter characteristics of the laser radar and not considering observation errors, the corresponding parameters can be calculated
And radial velocity variance
Establishing
And turbulent outer dimension LVBy numerical calculation to obtain the turbulence outer dimension LV：
Where δ r represents the radial distance resolution. Finally, the turbulent dissipation ratio can be calculated as shown in the above step. By the above processing steps, the required turbulent dissipation factor epsilon is efficiently and accurately obtained.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps of fig. 1 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
Referring to fig. 7, in another aspect, an airport wind field feature detection apparatus 100 based on lidar is further provided, which includes a configuration processing module 13, a wind field inversion module 15, a factor calculation module 17, a kinetic energy calculation module 19, and a turbulence calculation module 21. The configuration processing module 13 is used for configuring the scanning strategy of the laser radar deployed at a predetermined position of the airport according to the set configuration strategy. The wind field inversion module 15 is configured to perform inversion to obtain a three-dimensional wind field in a scanning volume according to doppler radial velocity information obtained by performing volume scanning on the laser radar. The factor calculation module 17 is configured to extract wind field data of less than 600 meters from the three-dimensional wind field, and calculate a corresponding F factor value according to the wind field data of less than 600 meters. The kinetic energy calculating module 19 is configured to extract radial wind speed data of a 35.3 ° altitude angle in the doppler radial velocity information, and calculate kinetic energy intensities of turbulence at different altitudes through a partial fourier decomposition algorithm. The turbulence calculation module 21 is configured to extract doppler spectrum data of each altitude angle in the doppler radial velocity information, and calculate a turbulence dissipation rate at each radial distance of the wind field by using a doppler spectrum method.
According to the airport wind field characteristic detection device 100 based on the laser radar, after the laser radar deployed to a preset position of an airport is configured according to a scanning strategy according to needs through cooperation of all modules, the laser radar performs volume scanning to obtain a radial velocity to invert a three-dimensional wind field in a scanning volume, then wind field data below 600 meters are extracted to be used for calculating a corresponding F factor value, radial wind speed data of 35.3-degree altitude angles are extracted, kinetic energy intensities of turbulent flows at different heights are calculated through a partial Fourier decomposition algorithm, finally Doppler frequency spectrum data of all altitude angles are extracted, and turbulent flow dissipation rates of all radial distances of the wind field are calculated through a Doppler frequency spectrum method. Therefore, a multipurpose wind lidar volume scanning strategy under the clear sky condition is formed, the space coverage, the space-time resolution and the robustness can be effectively considered, the key detection on the aircraft glidepath area can be realized, the accurate sensing on the near-field turbulence intensity can also be realized, the accurate detection and inversion can also be realized on the three-dimensional wind field, and the effect of stronger comprehensive detection performance of the wind field is achieved.
In one embodiment, the configuration processing module 13 may be specifically configured to determine an airport location for lidar deployment; the vertical distance between the preset position of the airport and the runway is any distance value between 100m and 200m, no obstacle is shielded between the laser radar and the airplane glide slope, and a Cartesian coordinate system (x, y, z) and a spherical coordinate system (phi, theta, r) are established by taking the laser radar as an origin; wherein x represents the distance from the laser radar in the direction perpendicular to the runway, y represents the distance from the laser radar in the direction parallel to the runway, z represents the distance from the laser radar in the vertical direction, phi represents the altitude angle, theta represents the azimuth angle, r represents the radial distance from the laser radar, and the method is used for setting the volume scanning of the laser radar by alternately adopting PPI scanning modes with different altitude angles; the different elevation angles are arranged in accordance with phi 1,3,8,15,25,35.3,45, 90.
In an embodiment, the configuration processing module 13 is configured to set that the laser radar performs volume scanning by alternately adopting PPI scanning modes of different elevation angles, and specifically may be configured to set that the laser radar obtains doppler radial velocity information of each elevation angle by adopting a complete PPI scanning mode or a sector PPI scanning mode at each elevation angle; and the rotation angular speed and the scanning sector size for setting the laser radar are respectively adjustable along with the concerned detection space area.
In one embodiment, the wind field inversion module 15 may be specifically configured to select an analysis volume unit in a scanning space of a laser radar, and determine an inversion speed of each point in the analysis volume unit;
wherein the analysis volume unit has a height angle span of
Span of azimuth angle of
And a radial distance span of
The analysis volume units are all equal in speed;
wherein phi islHeight angle, theta, representing a central point within the analysis volume unitmRepresenting the azimuth of a central point in the analysis volume, rnThe radial distance of a central point in the analysis volume unit is represented, delta phi, delta theta and delta r respectively represent the height angle, the azimuth angle and the radial resolution of the laser radar, and I, J and K respectively represent the number of the height angle, the azimuth angle and the radial resolution unit in the analysis volume unit;
the inversion speed of any point is converted into a Cartesian coordinate system to obtain a three-dimensional wind field; the three-dimensional wind field is as follows:
wherein u, v and w represent the velocity components of the x-axis, y-axis and z-axis, respectively, in a Cartesian coordinate system, and ulmnRepresenting the radial velocity, v, of a central point within the analysis volume unitlmnRepresenting the horizontal tangential velocity, w, of a central point in the analysis volume unitlmnRepresents ulmnAnd vlmnVertical velocity normal to the plane.
In one embodiment, the factor calculating module 17 may be specifically configured to determine that the head-on wind speed in the aircraft glideslope is a radial speed of a 3 ° altitude angle in the azimuth angle when an included angle between a connection line between the laser radar and the aircraft landing point and the runway is less than 30 °; the vertical wind speed in the airplane glidepath is extracted according to the three-dimensional wind field; the system is also used for calculating to obtain an F factor value according to the head-on wind speed and the vertical wind speed; the F factor value is calculated by the following formula:
wherein, VhRepresenting head-on wind speed, w vertical wind speed, g gravitational acceleration, VaRepresenting the aircraft approach speed.
In one embodiment, the factor calculating module 17 may be further configured to implement the following functions: the included angle between a connecting line between the laser radar and the landing point of the airplane and the runway is more than 30 degrees, and wind field data of which the azimuth angle is 3 degrees and the spatial range is 30m in the radial direction by taking the airplane glide slope as an axis are extracted from the three-dimensional wind field; synthesizing the head-on wind speed and the vertical wind speed in the aircraft glideslope according to the extracted wind field data; calculating to obtain an F factor value according to the head-on wind speed and the vertical wind speed; the F factor value is calculated by the following formula:
wherein, VhRepresenting head-on wind speed, w representing vertical wind speed, g being gravitational acceleration, VaThe approach speed of the airplane.
In an embodiment, the kinetic energy calculating module 19 may be specifically configured to implement the following functions: extracting radial wind speed data in a plurality of scanning periods at an altitude angle of 35.3 degrees, and calculating the average value of the radial speed of each point of the corresponding wind field in a plurality of periods<Vr>(ii) a Calculating to obtain the pulsation radial velocity of each point of the corresponding wind field according to the radial velocity of each point and the corresponding average value; according to the pulsating radial velocityCalculating the kinetic energy intensity of the turbulence on each PPI scanning; the intensity of the kinetic energy of the turbulent flow is calculated by the following formula:
wherein phi represents an altitude angle, V'rRepresenting the pulsatile radial velocity and theta the azimuth angle.
In one embodiment, the turbulence calculation module 21 may be specifically configured to implement the following functions: extracting Doppler frequency spectrum data in a plurality of scanning periods at each altitude angle, and calculating the average value of the Doppler frequency spectrum of each point of the corresponding wind field in the plurality of periods; calculating to obtain radial velocity variance and turbulence outer scale according to the average value in a plurality of periods; calculating to obtain the turbulent flow dissipation rate according to the radial velocity variance and the turbulent flow outer scale; the turbulent dissipation ratio is calculated by the following formula:
wherein σVExpressing the square of the radial velocity variance, LVDenotes the outer dimension of the turbulence, CKDenotes the Kolmogorov constant, CK≈2。
For specific limitations of the apparatus 100 for detecting wind field characteristics of an airport based on lidar, reference may be made to the corresponding limitations of the method for detecting wind field characteristics of an airport based on lidar, and details are not repeated here. The modules in the lidar based airport wind farm characteristic detection apparatus 100 may be implemented in whole or in part by software, hardware, and combinations thereof. The modules may be embedded in a hardware form or a device independent of a specific data processing function, or may be stored in a memory of the device in a software form, so that a processor may invoke and execute operations corresponding to the modules, where the device may be, but is not limited to, a monitoring terminal of a control system of a radar station, a control device, or a personal computer.
In still another aspect, a computer device is provided, which includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the following steps: scanning strategy configuration is carried out on the laser radar deployed at a preset position of an airport according to a set configuration strategy; obtaining Doppler radial velocity information obtained by volume scanning of the laser radar, and obtaining a three-dimensional wind field in a scanning volume through inversion; extracting wind field data below 600 meters from the three-dimensional wind field, and calculating according to the wind field data below 600 meters to obtain corresponding F factor values; extracting radial wind speed data of 35.3-degree altitude angle in Doppler radial speed information, and calculating by partial Fourier decomposition algorithm to obtain the kinetic energy intensity of turbulence at different heights; and extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information, and calculating by a Doppler frequency spectrum method to obtain the turbulent flow dissipation rate of each radial distance of the wind field.
In one embodiment, the processor when executing the computer program may further implement the additional steps or sub-steps of the above-mentioned lidar-based airport wind field characteristic detection method in various embodiments.
In yet another aspect, there is also provided a computer readable storage medium having a computer program stored thereon, the computer program when executed by a processor implementing the steps of: scanning strategy configuration is carried out on the laser radar deployed at a preset position of an airport according to a set configuration strategy; obtaining Doppler radial velocity information obtained by volume scanning of the laser radar, and obtaining a three-dimensional wind field in a scanning volume through inversion; extracting wind field data below 600 meters from the three-dimensional wind field, and calculating according to the wind field data below 600 meters to obtain corresponding F factor values; extracting radial wind speed data of 35.3-degree altitude angle in Doppler radial speed information, and calculating by partial Fourier decomposition algorithm to obtain the kinetic energy intensity of turbulence at different heights; and extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information, and calculating by a Doppler frequency spectrum method to obtain the turbulent flow dissipation rate of each radial distance of the wind field.
In one embodiment, the computer program, when executed by the processor, may further implement the additional steps or sub-steps of the above-described lidar-based airport wind farm feature detection method in various embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link DRAM (Synchlink) DRAM (SLDRAM), Rambus DRAM (RDRAM), and interface DRAM (DRDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the spirit of the present application, and all of them fall within the scope of the present application. Therefore, the protection scope of the present patent should be subject to the appended claims.
Claims (10)
1. A method for detecting airport wind field characteristics based on laser radar is characterized by comprising the following steps:
scanning strategy configuration is carried out on the laser radar deployed at a preset position of an airport according to a set configuration strategy;
according to Doppler radial velocity information obtained by volume scanning of the laser radar, a three-dimensional wind field in a scanning volume is obtained through inversion;
extracting wind field data below 600 meters from the three-dimensional wind field, and calculating according to the wind field data below 600 meters to obtain corresponding F factor values;
extracting radial wind speed data of a 35.3-degree altitude angle in the Doppler radial speed information, and calculating by a partial Fourier decomposition algorithm to obtain the kinetic energy intensity of turbulence at different heights;
and extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information, and calculating by a Doppler frequency spectrum method to obtain the turbulent flow dissipation rate of each radial distance of the wind field.
2. The method for detecting the wind field characteristics of the airport based on the lidar according to claim 1, wherein the step of configuring the scanning strategy of the lidar deployed at the preset position of the airport according to the set configuration strategy comprises:
determining the airport predetermined locations for the lidar deployment; the vertical distance between the preset position of the airport and the runway is any distance value between 100m and 200m, and no obstacle is shielded between the laser radar and the lower slideway of the airplane;
establishing a Cartesian coordinate system (x, y, z) and a spherical coordinate system (phi, theta, r) by taking the laser radar as an origin; wherein x represents the distance from the laser radar in a direction perpendicular to the horizontal plane and parallel to the runway, y represents the distance from the laser radar in a direction parallel to the runway, z represents the distance from the laser radar in a vertical direction, phi represents an elevation angle, theta represents an azimuth angle, and r represents a radial distance to the laser radar;
setting the laser radar to alternately perform volume scanning in PPI scanning modes with different elevation angles; the different elevation angles are arranged in accordance with phi 1,3,8,15,25,35.3,45, 90.
3. The method for detecting airport wind field features based on lidar according to claim 2, wherein the step of setting the lidar to scan the volume alternately by PPI scanning at different elevation angles comprises:
setting the laser radar to adopt a complete PPI scanning mode or a sector PPI scanning mode at each altitude angle to obtain the Doppler radial velocity information of each altitude angle;
the rotation angular velocity and the scanning sector size of the laser radar are set to be adjustable along with the concerned detection space area respectively.
4. The method for detecting airport wind field features based on lidar according to claim 2 or 3, wherein the step of obtaining a three-dimensional wind field in a scanning volume by inversion according to Doppler radial velocity information obtained by volume scanning of the lidar comprises:
selecting an analysis volume unit in a scanning space of the laser radar, and determining the inversion speed of each point in the analysis volume unit;
wherein the analysis volume unit has a height angle span of
Span of azimuth angle of
And a radial distance span of
All velocities within the analysis volume unit are equal;
wherein phi islAn elevation angle, theta, representing a central point within the analysis volume unitmRepresenting the azimuth of a central point in said analysis volume, rnRepresents the radial distance, delta phi, of a central point within said analysis volume unit,δ θ and δ r respectively represent the altitude angle, azimuth angle and radial resolution of the lidar, and I, J and K respectively represent the number of altitude angle, azimuth angle and radial resolution units in the analysis volume unit;
converting the inversion speed of any point into the Cartesian coordinate system to obtain the three-dimensional wind field; the three-dimensional wind field is as follows:
wherein u, v and w represent velocity components of x, y and z axes, respectively, in the Cartesian coordinate system, and ulmnRepresenting the radial velocity, v, of a central point within said analysis volume unitlmnRepresenting the horizontal tangential velocity of a centre point within said analysis volume element, wlmn representing ulmnAnd vlmnVertical velocity normal to the plane.
5. The method for detecting airport wind field features based on lidar according to claim 1, wherein the step of extracting wind field data of less than 600 meters from the three-dimensional wind field and calculating corresponding F factor values according to the wind field data of less than 600 meters comprises:
if the included angle between the connecting line between the laser radar and the aircraft landing point and the runway is less than 30 degrees, the head-on wind speed in the aircraft glideslope is the radial speed of the altitude angle of 3 degrees on the azimuth angle;
extracting the vertical wind speed in the aircraft glideslope according to the three-dimensional wind field;
calculating to obtain the F factor value according to the head-on wind speed and the vertical wind speed; the F factor value is calculated by the following formula:
wherein, VhRepresenting the head-on wind speed, w representing the droopDirect wind speed, g represents gravitational acceleration, VaRepresenting the aircraft approach speed.
6. The method for detecting airport wind field features based on lidar according to claim 1, wherein the step of extracting wind field data of less than 600 meters from the three-dimensional wind field and calculating corresponding F factor values according to the wind field data of less than 600 meters comprises:
if the included angle between the connecting line between the laser radar and the aircraft landing point and the runway is more than 30 degrees, extracting wind field data in a space range of 30m in the radial direction by taking the aircraft glideslope as an axis at an azimuth angle of 3 degrees from the three-dimensional wind field;
synthesizing the head-on wind speed and the vertical wind speed in the aircraft glideslope according to the extracted wind field data;
calculating to obtain the F factor value according to the head-on wind speed and the vertical wind speed; the F factor value is calculated by the following formula:
wherein, VhRepresenting the head-on wind speed, w representing the vertical wind speed, g being the acceleration of gravity, VaThe approach speed of the airplane.
7. The method for detecting airport wind field features based on lidar according to claim 1, wherein the step of extracting radial wind speed data of 35.3 ° altitude angle in the doppler radial velocity information and calculating the kinetic energy intensity of turbulence at different altitudes by partial fourier decomposition algorithm comprises:
extracting the radial wind speed data in a plurality of scanning periods at an altitude angle of 35.3 degrees, and calculating the average value < V > of the radial speed of each point of the corresponding wind field in a plurality of periodsr>；
Calculating to obtain the pulsating radial velocity of each point of the corresponding wind field according to the radial velocity of each point and the corresponding average value;
calculating the kinetic energy intensity of the turbulent flow on the whole PPI scanning according to the pulse radial velocity; the kinetic energy intensity of the turbulent flow is calculated by the following formula:
wherein phi represents an altitude angle, V'rRepresents the pulsatile radial velocity and theta represents the azimuth angle.
8. The method for detecting the wind field characteristics of the airport based on the laser radar according to any one of the claims 1, 5, 6 and 7, characterized in that the step of extracting Doppler spectrum data of each altitude angle in the Doppler radial velocity information and calculating the turbulent dissipation rate of each radial distance of the wind field by using a Doppler spectrum method comprises the following steps:
extracting the Doppler frequency spectrum data in a plurality of scanning periods at each altitude angle, and calculating the average value of the Doppler frequency spectrum of each point of the corresponding wind field in the plurality of periods;
calculating to obtain radial velocity variance and turbulence outer dimension according to the average value in a plurality of periods;
calculating to obtain the turbulent dissipation rate according to the radial velocity variance and the turbulent outer scale; the turbulent dissipation ratio is calculated by the following formula:
wherein σVRepresents the square of the radial velocity variance, LVDenotes the outer dimension of the turbulence, CKDenotes the Kolmogorov constant, CK≈2。
9. An airport wind field characteristic detection device based on laser radar, characterized by that includes:
the configuration processing module is used for carrying out scanning strategy configuration on the laser radar deployed at a preset position of the airport according to a set configuration strategy;
the wind field inversion module is used for carrying out inversion according to Doppler radial velocity information obtained by volume scanning of the laser radar to obtain a three-dimensional wind field in a scanning volume;
the factor calculation module is used for extracting wind field data below 600 meters from the three-dimensional wind field and calculating to obtain a corresponding F factor value according to the wind field data below 600 meters;
the kinetic energy calculation module is used for extracting radial wind speed data of a 35.3-degree altitude angle in the Doppler radial speed information and calculating the kinetic energy intensity of turbulence at different heights through a partial Fourier decomposition algorithm;
and the turbulence calculation module is used for extracting Doppler frequency spectrum data of each altitude angle in the Doppler radial velocity information and calculating the turbulence dissipation rate of each radial distance of the wind field by a Doppler frequency spectrum method.
10. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program performs the steps of the lidar based airport wind field characteristic detection method of any of claims 1 to 8.
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| CN115060457B (en) * | 2022-08-18 | 2022-11-08 | 珠海翔翼航空技术有限公司 | Method, system and equipment for detecting atmospheric vortex dissipation rate based on aircraft bump |
| CN115508580A (en) * | 2022-11-16 | 2022-12-23 | 中国海洋大学 | Airport runway virtual air rod construction method based on laser remote sensing technology |
| CN115508580B (en) * | 2022-11-16 | 2023-03-24 | 中国海洋大学 | Airport runway virtual air rod construction method based on laser remote sensing technology |
| CN117420569A (en) * | 2023-12-19 | 2024-01-19 | 南京牧镭激光科技股份有限公司 | Inversion method of non-uniform wind field based on Doppler laser wind finding radar |
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