CN106772387A - A kind of wind shear recognition methods - Google Patents
A kind of wind shear recognition methods Download PDFInfo
- Publication number
- CN106772387A CN106772387A CN201611186484.9A CN201611186484A CN106772387A CN 106772387 A CN106772387 A CN 106772387A CN 201611186484 A CN201611186484 A CN 201611186484A CN 106772387 A CN106772387 A CN 106772387A
- Authority
- CN
- China
- Prior art keywords
- wind shear
- radial velocity
- velocity data
- data
- recognition methods
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
- G01S13/953—Radar or analogous systems specially adapted for specific applications for meteorological use mounted on aircraft
-
- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The present invention relates to airborne weather radar field, more particularly to a kind of wind shear recognition methods.Recognition methods comprises the following steps：The radial velocity data detected to pre-position are pre-processed, to remove the noise spot and isolated point in radial velocity data；Spectrum width is calculated according to the pretreated radial velocity data, and judges the spectrum width whether more than predetermined value；If it is greater, then illustrating that the precalculated position there may be wind shear, and carry out step 3；If it is lower, explanation does not exist wind shear；Wind shear identification is carried out to pretreated radial velocity data by region-growing method.Wind shear recognition methods of the invention can quickly, accurate, clearly positioning dangerous resultant wind shear region, can on airborne radar can early warning hazardous weather in real time, ensure the flight safety of aircraft.
Description
Technical field
The present invention relates to airborne weather radar field, more particularly to a kind of wind shear recognition methods.
Background technology
Wind shear is one of principal element of threat Flight Safety, and considerable air crash is by low
Cause.Wind shear refers to mutation of the wind speed and direction in the horizontal direction or in vertical direction, produces the weather phenomenon master of wind shear
Have：Clear-air turbulence (heating power bubble, stratocumulus, cumulus), frontal weather (cold front, the warm front), strong convective weather are (many monomers, super
Monomer, squall line, downburst), Gust front near the ground and radiation inversion wind shear etc..Therefore, wind shear has yardstick small, burst
Property it is strong, the features such as intensity is big.
In small mesoscale system, often there is the Convergence and divergence process of wind in slipped region, and strong wind vertical shear promotees
The formation and development of Convective Storms is entered.Therefore, the judgement of wind shear and identification are significant in Severe Convective Weather Forecasting.
Micro-downburst caused by strong vertical wind shear can have a strong impact on the flight safety of aircraft.Entrusted safely according to national transportation
Member can data statistics, the pernicious air crash in the whole world much all causes by weather reason, and wherein most is again and Low level wind
Shear is relevant.Airborne radar weather radar can accurately and rapidly probe gas as the intensity of object, speed and spectrum width number
According to carrying out hazardous weather early warning in real time, guarantee Flight Safety is significant.
The main Types of wind shear have two kinds, and a kind of is the shear that horizontal wind is gone up both horizontally and vertically, another
It is vertical wind shear to plant.Can be established suitable for airborne wind using the approximate energy height transmission function of aircraft in Control in Wind Shear Field
The threshold value of the wind shear danger message of shear detection warning system.Result of calculation shows：For horizontal vertical wind shear, with 30
Rice vertical drop horizontal wind speed as measurement, then for aircraft, its equivalent moderate wind shear threshold value of warning be 2.5~
4.5m·s-1·km-1(criterion that whether there is in this, as wind shear).
But, it is more single in the strength criterion of former wind shear, do not relate to such as meteorological condition, aeroplane performance and
The many factors such as pilot driver technology so that the judgement of final result is not exactly accurate.
The content of the invention
It is an object of the invention to provide a kind of wind shear recognition methods, to solve to exist in existing wind shear recognition methods
At least one technical problem.
The technical scheme is that：
A kind of wind shear recognition methods, comprises the following steps：
Step one, the radial velocity data that pre-position is detected with airborne weather radar are pre-processed, to go
Except noise spot and isolated point in the radial velocity data；
Step 2, spectrum width is calculated according to the pretreated radial velocity data, and judge whether the spectrum width is big
In predetermined value；If it is greater, then illustrating that the precalculated position there may be wind shear, and carry out step 3；If it is lower, explanation
In the absence of wind shear；
Step 3, wind shear identification is carried out to the pretreated radial velocity data by region-growing method.
Optionally, include in the step 3：
Step 3.1, to step 2 in the radial velocity data carry out extremely straight Coordinate Conversion；
Two-dimentional radial velocity data after step 3.2, conversion are stored in two-dimensional array DATA；
Step 3.3, construction one RESULT two-dimensional array, wherein, be worth for 0 when represent initialization, be worth for 1 when represent identification
Slipped region afterwards, be worth for 255 when represent identification after non-slipped region；
Step 3.4, one SEED seed stack of construction, deposit seed point；
Step 3.5, set initial seed point M (x0,y0) it is the radial direction wind speed of radar center, and the radial direction wind speed is always
0；
Step 3.6, by the initial seed point M (x0,y0) as the central point of two-dimensional array DATA, by the central point
Difference comparsion is carried out with the data point in its 4 neighborhoods, the difference of acquisition is compared with equivalent moderate wind shear threshold value of warning
Compared with；If it is greater, then RESULT two-dimensional array intermediate values are set to 1；If it is lower, RESULT two-dimensional array intermediate values are set to 255；
Step 3.7, using 4 neighborhood points in step 3.6 as new seed point, clicked through with 4 neighborhoods around respective
Row contrast, is judged；
Step 3.8, repeat step 3.7, complete in the two-dimensional array DATA comparison a little.
Optionally, in the step one, be the radial velocity data are carried out using P-M PDE models it is pre-
Treatment.
Invention effect：
Wind shear recognition methods of the invention can quickly, accurate, clearly positioning dangerous resultant wind shear region, Neng Gou
On airborne radar can early warning hazardous weather in real time, ensure the flight safety of aircraft.Wind shear recognition methods of the invention, in gas
As in the pretreatment of radar radial velocity base data, the interference pulsed between removal storehouse, reject isolated point and scarce measuring point and retain pass
The slipped region of key, effectively preserves small wind shear area data message；In addition, joint is combined using radial velocity and spectrum width data
Judge synthesis wind shear position, the wind shear region that can not be recognized only in accordance with radial velocity data can be made up, improve wind shear
The precision of identification；Further, the synthesis wind shear of radial velocity is quickly recognized using region-growing method, than traditional radial direction and is cut
More can intuitively reflect position and the degree of danger of wind shear to shear, and improve wind shear recognition speed.
Brief description of the drawings
Fig. 1 is the flow chart of region-growing method in wind shear recognition methods of the present invention.
Specific embodiment
To make the purpose, technical scheme and advantage of present invention implementation clearer, below in conjunction with the embodiment of the present invention
Accompanying drawing, the technical scheme in the embodiment of the present invention is further described in more detail.In the accompanying drawings, identical from start to finish or class
As label represent same or similar element or the element with same or like function.Described embodiment is the present invention
A part of embodiment, rather than whole embodiments.Embodiment below with reference to Description of Drawings is exemplary, it is intended to used
It is of the invention in explaining, and be not considered as limiting the invention.Based on the embodiment in the present invention, ordinary skill people
The every other embodiment that member is obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.Under
Face is described in detail with reference to accompanying drawing to embodiments of the invention.
In the description of the invention, it is to be understood that term " " center ", " longitudinal direction ", " transverse direction ", "front", "rear",
The orientation or position relationship of the instruction such as "left", "right", " vertical ", " level ", " top ", " bottom ", " interior ", " outward " are based on accompanying drawing institute
The orientation or position relationship for showing, are for only for ease of the description present invention and simplify description, rather than the dress for indicating or implying meaning
Put or element with specific orientation, with specific azimuth configuration and operation, therefore it is not intended that must be protected to the present invention
The limitation of scope.
1 pair of wind shear recognition methods of the present invention below in conjunction with the accompanying drawings is described in further details.
The invention provides a kind of wind shear recognition methods, comprise the following steps：
Step one, the radial velocity data that pre-position is detected with airborne weather radar are pre-processed, to go
Except noise spot and isolated point in radial velocity data.
Specifically, data prediction is carried out using P-M PDE models in step one, so as to reach denoising fidelity
Effect, has reached the effect of denoising fidelity；Processing method is as follows：
Set up the following denoising fidelity model (1) based on P-M partial differential equation：
In relational expression (1), u is on the coordinate position and the function of time in two-dimensional radar polar coordinate system, i.e. radial direction speed
Angle value, x, y represents data point coordinates respectively along radar radially and tangentially；U changes with the time into Nonlinear Diffusion；Div is represented
Divergence operator, ▽ u represent the gradient of u, and | ▽ u | refer to the mould of gradient, and g (| ▽ u |) is the diffusion coefficient of gradient fields, for controlling thunder
Up to data with the diffusion velocity of gradient, typically have：
Based on above-mentioned property, P-M provides following diffusion coefficient function：
In relational expression (3), k is edge threshold, and this parameters relationship to denoising and edge keep this balance journey to contradiction
Degree.Therefore, in gradient larger part, i.e. shear region, k values choose smaller value as far as possible, prevent slipped region to be smoothed；Gradient compared with
Small place, i.e., non-shear region or noise spot (isolated point), k values choose higher value as far as possible, and noise spot is fallen by diffusion smoothing.
(4) formula as follows is obtained using difference scheme numerical solution to relational expression (1)：
Wherein, the div operators of relational expression (1) are discrete turns to diffusion data point and along its radar radially and tangentially adjacent 4
The weight gradient mean value of individual data point, the weight gradient on 4 data point directions is respectively：
Simultaneous relational expression (3), (4), (5), the P-M denoising equations for obtaining discretization are：
The primary condition be given using relational expression (6) formula and (1) formula, is iterated solution.T in relational expression (6) is table
Show iterations.Find out that iterations is too low from formula, denoising effect is not obvious, the too high easily smooth slipped region of iterations
Data value.Therefore, the iterations that the present invention chooses is t=50, can reach ideal denoising fidelity effect.
Step 2, spectrum width is calculated according to pretreated radial velocity data, and judge spectrum width whether more than predetermined value；
If it is greater, then explanation precalculated position there may be wind shear, and carry out step 3；If it is lower, explanation does not exist wind shear.
After to the pretreatment of radar radial velocity base data, in order to improve the precision of wind shear identification, also need to increase
Weather radar spectrum width base data carries out joint judgement.Weather radar spectrum width is defined as：
In relational expression (7),It is represented to the average radial velocity of radar sampling pulse echo signal in set a distance storehouse, Vri
The radial velocity of each sampling pulse echo-signal in set a distance storehouse is represented to, N represents radar pulse sampled signal in range bin
Sum.
By relational expression (7), what spectrum width reflected is the doppler velocity mark of radar pulse sampled signal in range bin
It is accurate poor.Therefore, should be noted at following 2 points when choosing spectrum width data as wind shear criterion：
1) the spectrum width data at the low elevation angle, is analyzed.This is because the end speed of raindrop vertical drop is pressed from both sides with the radial direction at the low elevation angle
Angle is very big, so can be ignored by whereabouts end speed radial component, the doppler velocity very little for causing, so as to reduce to spectrum width number
According to interference.
2), close and far spectrum width data is not analyzed.This is because distant location radar effectively irradiates
It is sufficiently bulky, many particles for deviateing doppler velocity average value may be included in this volume, cause spectrum width to become big, produce larger
Error.
After some of the above interference is excluded, it is possible to use spectrum width data information comes subsidiary discriminant wind shear position.It is general next
Say, spectrum width data are considered as the position and there may be wind shear area up to more than 4m/s, and the corresponding speed data in the position is entered
Row signature identification, so as to make up the simple defect that wind shear is recognized by radial velocity data.
Step 3, wind shear identification is carried out to pretreated radial velocity data by region-growing method.
Specifically, the middle region-growing method of step 3 comprises the following steps：
Step 3.1, to step 2 in the radial velocity data carry out extremely straight Coordinate Conversion.
Two-dimentional radial velocity data after step 3.2, conversion are stored in two-dimensional array DATA.
Step 3.3, one RESULT two-dimensional array of construction (are called：As a result two-dimensional array), wherein, be worth for 0 when represent just
Beginningization (representing does not carry out contrast identification), be worth for 1 when represent identification after slipped region, be worth for 255 when represent identification after it is non-
Slipped region.
Step 3.4, one SEED seed stack of construction, deposit seed point；Stack was empty, follow-up newly-increased seed point in the past.
Step 3.5, set initial seed point M (x0,y0) it is the radial direction wind speed of radar center, and the radial direction wind speed is always
0。
Step 3.6, by the initial seed point M (x0,y0) as the central point of two-dimensional array DATA, by the central point
Difference comparsion is carried out with the data point in its 4 neighborhoods, the difference and equivalent moderate wind shear threshold value of warning (i.e. background that will be obtained
2.5~4.5ms of equivalent moderate wind shear threshold value of warning in technology-1·km-1) be compared；If it is greater, then RESULT
Two-dimensional array intermediate value is set to 1 (having wind shear between the two points)；If it is lower, RESULT two-dimensional array intermediate values are set to 255
(i.e. either with or without wind shear).
Step 3.7, using 4 neighborhood points in step 3.6 as new seed point, clicked through with 4 neighborhoods around respective
Row contrast, is judged.
Step 3.8, repeat step 3.7, complete in the two-dimensional array DATA comparison a little, so as to obtain wind shear
Distribution.
It should be noted that especially as shown in figure 1, region-growing method is based on by the two-dimentional footpath after extremely straight Coordinate Conversion
To speed data, it is first determined initial seed point simultaneously sets wind shear threshold value thresholding.Seed point compares with the vertex neighborhood of surrounding four, when
Neighborhood point is invalid value or when exceeding decision threshold or reaching two-dimensional array border, then stop growing.Otherwise, neighborhood point extension
It is new seed point.It should be noted that often complete a neighborhood point comparing, then need to delete current seed point (herein by the point
Value puts 1 or 255), prevents from repeating to travel through.
Wind shear recognition methods of the invention can quickly, accurate, clearly positioning dangerous resultant wind shear region, Neng Gou
On airborne radar can early warning hazardous weather in real time, ensure the flight safety of aircraft.Wind shear recognition methods of the invention, in gas
As in the pretreatment of radar radial velocity base data, the interference pulsed between removal storehouse, reject isolated point and scarce measuring point and retain pass
The slipped region of key, effectively preserves small wind shear area data message；In addition, joint is combined using radial velocity and spectrum width data
Judge synthesis wind shear position, the wind shear region that can not be recognized only in accordance with radial velocity data can be made up, improve wind shear
The precision of identification；Further, the synthesis wind shear of radial velocity is quickly recognized using region-growing method, than traditional radial direction and is cut
More can intuitively reflect position and the degree of danger of wind shear to shear, and improve wind shear recognition speed.
When the wind shear recognition methods of present invention hair is used, wind shear danger classes threshold data storehouse can be first set up, used
Judge in the dangerous alarm grade of follow-up wind shear；Base data file is parsed and read again, can parse different-format definition
Airborne radar weather radar radial velocity and spectrum width base data；Further, by parsing the different base datas of acquisition
Specifeca tion speeification and observation data in file；Above-mentioned parsing data are finally based on, are given birth to using region using C Plus Plus establishment
The synthesis wind shear Fast Recognition Algorithm of regular way, and it is packaged into DLL dynamic bases.The dynamic base is available for other application programs dynamically to add
Carry.
The above, specific embodiment only of the invention, but protection scope of the present invention is not limited thereto, and it is any
Those familiar with the art the invention discloses technical scope in, the change or replacement that can be readily occurred in, all should
It is included within the scope of the present invention.Therefore, protection scope of the present invention should be with the scope of the claims
It is accurate.
Claims (3)
1. a kind of wind shear recognition methods, it is characterised in that comprise the following steps：
Step one, the radial velocity data detected to pre-position are pre-processed, to remove the radial velocity data
In noise spot and isolated point；
Step 2, spectrum width is calculated according to the pretreated radial velocity data, and judge the spectrum width whether more than pre-
Definite value；If it is greater, then illustrating that the precalculated position there may be wind shear, and carry out step 3；If it is lower, explanation is not deposited
In wind shear；
Step 3, wind shear identification is carried out to the pretreated radial velocity data by region-growing method.
2. wind shear recognition methods according to claim 1, it is characterised in that include in the step 3：
Step 3.1, to step 2 in the radial velocity data carry out extremely straight Coordinate Conversion；
Two-dimentional radial velocity data after step 3.2, conversion are stored in two-dimensional array DATA；
Step 3.3, construction one RESULT two-dimensional array, wherein, be worth for 0 when represent initialization, be worth for 1 when represent recognize after
Slipped region, be worth for 255 when represent identification after non-slipped region；
Step 3.4, one SEED seed stack of construction, deposit seed point；
Step 3.5, to set initial seed point be the radial direction wind speed of radar center, and the radial direction wind speed is always 0；
Step 3.6, using the initial seed point as two-dimensional array DATA central point, by the central point and its 4 neighborhoods
Interior data point carries out difference comparsion, and the difference of acquisition is compared with equivalent moderate wind shear threshold value of warning；If it does,
Then RESULT two-dimensional arrays intermediate value is set to 1；If it is lower, RESULT two-dimensional array intermediate values are set to 255；
Step 3.7, using 4 neighborhood points in step 3.6 as new seed point, with it is respective around 4 neighborhood points carry out it is right
Than being judged；
Step 3.8, repeat step 3.7, complete in the two-dimensional array DATA comparison a little.
3. wind shear recognition methods according to claim 1, it is characterised in that in the step one, is inclined using P-M
Differential Equation Model is pre-processed to the radial velocity data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611186484.9A CN106772387B (en) | 2016-12-21 | 2016-12-21 | A kind of wind shear recognition methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611186484.9A CN106772387B (en) | 2016-12-21 | 2016-12-21 | A kind of wind shear recognition methods |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106772387A true CN106772387A (en) | 2017-05-31 |
| CN106772387B CN106772387B (en) | 2019-06-14 |
Family
ID=58894031
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611186484.9A Active CN106772387B (en) | 2016-12-21 | 2016-12-21 | A kind of wind shear recognition methods |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106772387B (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108254750A (en) * | 2017-11-24 | 2018-07-06 | 南京信息工程大学 | A kind of downburst intelligent recognition method for early warning based on Radar Data |
| CN108896995A (en) * | 2018-08-03 | 2018-11-27 | 中国航空工业集团公司雷华电子技术研究所 | A kind of airborne weather radar thunderstorm recognition methods |
| CN109521429A (en) * | 2018-11-14 | 2019-03-26 | 王啸华 | Boundary layer wind speed lattice point zoning method for calculating |
| CN109583593A (en) * | 2018-10-31 | 2019-04-05 | 安徽四创电子股份有限公司 | A kind of low-level wind shear recognition methods based on automatic weather station |
| CN110441776A (en) * | 2019-07-02 | 2019-11-12 | 中国航空工业集团公司雷华电子技术研究所 | A kind of middle-size and small-size airborne platform weather radar wind shear detection and display methods |
| CN110531359A (en) * | 2019-07-02 | 2019-12-03 | 中国航空工业集团公司雷华电子技术研究所 | A kind of design method of airborne weather radar wind shear detection |
| CN111624607A (en) * | 2020-06-12 | 2020-09-04 | 上海眼控科技股份有限公司 | Low-altitude wind shear area acquisition method, device, equipment and storage medium |
| CN111929687A (en) * | 2020-08-25 | 2020-11-13 | 中国气象局武汉暴雨研究所 | Automatic recognition algorithm for tornado vortex characteristics |
| CN115937007A (en) * | 2022-03-04 | 2023-04-07 | 中科三清科技有限公司 | Wind shear identification method and device, electronic equipment and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3724379B2 (en) * | 2001-03-14 | 2005-12-07 | 三菱電機株式会社 | Wind shear detector |
| CN102565771A (en) * | 2010-12-14 | 2012-07-11 | 中国航天科工集团第二研究院二十三所 | Single station wind profile radar-based wind shear identification and tracking method |
| CN105607063A (en) * | 2016-01-05 | 2016-05-25 | 北京无线电测量研究所 | Detection method and system for low-altitude wind shear at airport |
-
2016
- 2016-12-21 CN CN201611186484.9A patent/CN106772387B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3724379B2 (en) * | 2001-03-14 | 2005-12-07 | 三菱電機株式会社 | Wind shear detector |
| CN102565771A (en) * | 2010-12-14 | 2012-07-11 | 中国航天科工集团第二研究院二十三所 | Single station wind profile radar-based wind shear identification and tracking method |
| CN105607063A (en) * | 2016-01-05 | 2016-05-25 | 北京无线电测量研究所 | Detection method and system for low-altitude wind shear at airport |
Non-Patent Citations (2)
| Title |
|---|
| 方贤德 等: "区域生长法在多普勒天气雷达速度场分析中的应用", 《南京大学学报（自然科学）》 * |
| 王芬 等: "新一代多普勒天气雷达CINRAD/CD谱宽资料分析应用初探", 《沙漠与绿洲气象》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108254750A (en) * | 2017-11-24 | 2018-07-06 | 南京信息工程大学 | A kind of downburst intelligent recognition method for early warning based on Radar Data |
| CN108254750B (en) * | 2017-11-24 | 2021-07-30 | 南京信息工程大学 | Down-blast intelligent identification early warning method based on radar data |
| CN108896995A (en) * | 2018-08-03 | 2018-11-27 | 中国航空工业集团公司雷华电子技术研究所 | A kind of airborne weather radar thunderstorm recognition methods |
| CN109583593A (en) * | 2018-10-31 | 2019-04-05 | 安徽四创电子股份有限公司 | A kind of low-level wind shear recognition methods based on automatic weather station |
| CN109583593B (en) * | 2018-10-31 | 2020-11-13 | 安徽四创电子股份有限公司 | Low-altitude wind shear identification method based on automatic meteorological station |
| CN109521429A (en) * | 2018-11-14 | 2019-03-26 | 王啸华 | Boundary layer wind speed lattice point zoning method for calculating |
| CN110441776A (en) * | 2019-07-02 | 2019-11-12 | 中国航空工业集团公司雷华电子技术研究所 | A kind of middle-size and small-size airborne platform weather radar wind shear detection and display methods |
| CN110531359A (en) * | 2019-07-02 | 2019-12-03 | 中国航空工业集团公司雷华电子技术研究所 | A kind of design method of airborne weather radar wind shear detection |
| CN111624607A (en) * | 2020-06-12 | 2020-09-04 | 上海眼控科技股份有限公司 | Low-altitude wind shear area acquisition method, device, equipment and storage medium |
| CN111929687A (en) * | 2020-08-25 | 2020-11-13 | 中国气象局武汉暴雨研究所 | Automatic recognition algorithm for tornado vortex characteristics |
| CN111929687B (en) * | 2020-08-25 | 2023-11-21 | 中国气象局武汉暴雨研究所 | Automatic recognition algorithm for characteristics of tornado vortex |
| CN115937007A (en) * | 2022-03-04 | 2023-04-07 | 中科三清科技有限公司 | Wind shear identification method and device, electronic equipment and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106772387B (en) | 2019-06-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106772387A (en) | A kind of wind shear recognition methods | |
| CN102508219B (en) | Turbulent current target detection method of wind profiler radar | |
| CN108387885B (en) | Aircraft wake characteristic parameter inversion method under clear sky condition based on laser radar detection | |
| CN103903481B (en) | The threshold value and envelope curve design method of a kind of ground proximity warning system | |
| CN104931949B (en) | Wind turbine clutter background is got off the plane object detection method under radar scanning pattern | |
| CN113673181A (en) | Intelligent airport area wind shear identification method based on multi-source wind field data | |
| CN104597430B (en) | Low-altitude wind shear three-dimensional backscattering wave simulation method for airborne meteorological radar | |
| CN113868971B (en) | Airport area three-dimensional refined wind field reconstruction method based on numerical simulation model and historical wind field characteristics | |
| CN103745441A (en) | Method of filtering airborne LiDAR (Light Detection and Ranging) point cloud | |
| CN104714225B (en) | Dynamic programming tracking-before-detection method based on generalized likelihood ratios | |
| CN104240251A (en) | Multi-scale point cloud noise detection method based on density analysis | |
| CN105869212B (en) | A kind of ice shape simplification method | |
| CN105093215A (en) | Doppler information based method for tracking low-altitude low-speed small target through radar | |
| CN104574303A (en) | Airborne LiDAR point cloud ground filtering method based on spatial clustering | |
| CN104597449B (en) | A kind of airborne many scanning weather radar target vertical contour reconstruction methods | |
| Li et al. | Numerical simulation study of the effect of buildings and complex terrain on the low-level winds at an airport in typhoon situation | |
| CN109188382A (en) | A kind of target identification method based on millimetre-wave radar | |
| CN107479065A (en) | A kind of three-dimensional structure of forest gap method for measurement based on laser radar | |
| CN104008403B (en) | A kind of SVM（Vector machine）The multi-targets recognition decision method of pattern | |
| CN106600107A (en) | Spacecraft collision risk assessment method | |
| CN106019286A (en) | Multi-scanning multi-pulse-repetition-frequency full-airspace meteorological target detection method for airborne weather radar | |
| CN108459323A (en) | Strong convergence field identification based on Doppler radar data and speed correction method | |
| CN202433521U (en) | Wind profile radar turbulence target detection processing plate | |
| Schwarz et al. | A full-scale rotor-wake investigation of a free-flying helicopter in ground effect using BOS and PIV | |
| Zuo et al. | Identification of convective and stratiform clouds based on the improved DBSCAN clustering algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |