CN107728163A - Atmospheric Characteristics layer detection method and device - Google Patents
Atmospheric Characteristics layer detection method and device Download PDFInfo
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- CN107728163A CN107728163A CN201710794637.6A CN201710794637A CN107728163A CN 107728163 A CN107728163 A CN 107728163A CN 201710794637 A CN201710794637 A CN 201710794637A CN 107728163 A CN107728163 A CN 107728163A
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- 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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- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
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Abstract
The embodiment of the present invention provides a kind of Atmospheric Characteristics layer detection method and device, is related to detection technique field.Method includes：Obtain Mie scattering polarization lidar signal and meteorological data；Scattering ratio and linear Depolarization Ratio is calculated；Atmospheric Characteristics layer is detected using threshold method；The Atmospheric Characteristics layer detected is classified using empirical value method；Iteration performs above-mentioned steps, judge whether the difference between the classification of the subseries again and the last Atmospheric Characteristics layer and Atmospheric Characteristics layer detected of the Atmospheric Characteristics layer and Atmospheric Characteristics layer detected again is less than given threshold, until the difference between the newest classification of the Atmospheric Characteristics layer and Atmospheric Characteristics layer that are most recently detected and the classification of the last Atmospheric Characteristics layer and Atmospheric Characteristics layer detected is less than given threshold, then the newest classification of Atmospheric Characteristics layer is revised using continuous wavelet analytic approach.Use the Atmospheric Characteristics layer detection method and device, it is possible to increase convenience, accuracy and the integrality of Atmospheric Characteristics layer detection.
Description
Technical field
The present invention relates to detection technique field, in particular to a kind of Atmospheric Characteristics layer detection method and device.
Background technology
Cloud layer and colloidal sol floor in air are very important Atmospheric Characteristics layers.At present, based on atmospheric laser radar pair
The method that Atmospheric Characteristics layer is detected is broadly divided into threshold method and continuous wavelet analytic approach.The principle of threshold method is to utilize actual measurement
Difference between signal and background atmospheric molecule signal identifies Atmospheric Characteristics layer, and threshold method is initially used only static threshold and detects
Cloud layer, including differential interior extrapolation method and Slope Method, they are both needed to carefully adjust threshold value to avoid the interference of noise and colloidal sol floor；
Gradually develop into later using the threshold value with height change while detect cloud layer and colloidal sol floor.Continuous wavelet analytic approach is based on ink
(air is special with the discontinuity point in the high correlation detection signal of laser radar signal profile shape for the waveform of western brother's cap small echo
Sign layer border) obtain Atmospheric Characteristics layer.Further, it is then main to the sorting technique of Atmospheric Characteristics layer based on atmospheric laser radar
For neural network, probabilistic method and empirical value method etc..The principle of neural network is by animal nerve network, passes through adjustment
The relation being connected with each other between internal great deal of nodes, so as to reach the purpose of process signal；The principle of probabilistic method is then based on can be with
The statistical formula that data associate with characteristic layer is provided；Empirical value rule utilizes the parameter that may make up N-dimensional (N=1,2,3) space
Choose empirical threshold value.
Though these methods have obtained considerable progress, Slope Method is only capable of realizing the detection of cloud layer, to further
Cloud classification is realized, other a variety of instruments need to be combined；And though the combination of threshold method and empirical value can realize the inspection of feature simultaneously
Detection and classification, but its hardware index request to laser radar is high, and these algorithms are not suitable in general Mie scattering laser
Radar.For Mie scattering lidar, existing algorithm is based only upon signal profile using threshold method or continuous wavelet analytic approach or dissipated
Penetrate than detecting Atmospheric Characteristics layer.In signal profile, the weak signal at Atmospheric Characteristics layer edge can not be fully detected, simultaneously
More complete Atmospheric Characteristics layer can not be detected merely with scattering ratio.In existing tagsort method, pass through nerve net
Network method and the scheme of probabilistic method progress Atmospheric Characteristics layer detection are realized complex.
The content of the invention
In view of this, the purpose of the embodiment of the present invention is to provide a kind of Atmospheric Characteristics layer detection method and device, to
The potential value of the Mie scattering lidar data with depolarization function is fully excavated, realizes more complete and accurate air
The automatic detection of characteristic layer.
Present pre-ferred embodiments provide a kind of Atmospheric Characteristics layer detection method, including：
Obtain Mie scattering polarization lidar signal and meteorological data；
Scattering ratio and linear Depolarization Ratio are calculated according to the Mie scattering polarization lidar signal and meteorological data；
Atmospheric Characteristics layer is detected using threshold method based on the scattering ratio and linear Depolarization Ratio；
Optical characteristics based on air heating power status data and Atmospheric Characteristics layer is big by what is detected using empirical value method
Gas characteristic layer is classified；
Perform again and scattering ratio and linear is calculated according to the Mie scattering polarization lidar signal and meteorological data
The step of Depolarization Ratio is extremely classified the Atmospheric Characteristics layer detected using empirical value method, the Atmospheric Characteristics detected again
The classification results again of layer and Atmospheric Characteristics layer；
Judge the subseries again of the Atmospheric Characteristics layer and Atmospheric Characteristics layer detected again and the last air detected
Whether the difference between the classification of characteristic layer and Atmospheric Characteristics layer is less than given threshold；
If being more than the given threshold, perform according to the Mie scattering polarization lidar signal and meteorological number again
According to scattering ratio and linear Depolarization Ratio is calculated to the step of the Atmospheric Characteristics layer detected is classified using empirical value method, directly
To newest classification and the last Atmospheric Characteristics layer detected and greatly of the Atmospheric Characteristics layer and Atmospheric Characteristics layer being most recently detected
Difference between the classification of gas characteristic layer is less than the given threshold, then revises the Atmospheric Characteristics using continuous wavelet analytic approach
The newest classification of layer.
Alternatively, the Mie scattering polarization lidar signal is expressed as：
Wherein, r is detection range, and C is system constants, and E is pulse energy, and O (r) is geometrical factor, βm(r) it is big qi leel
The backscattering coefficient of son, βp(r) it is the backscattering coefficient of Atmospheric particulates,For big qi leel
The transmitance of son,For the transmitance of Atmospheric particulates, αm(r) it is the extinction coefficient of atmospheric molecule, αp
(r) it is the extinction coefficient of Atmospheric particulates；
The Mie scattering polarization lidar signal is calculated using below equation：
P (r)=P⊥(r)+P||(r)
Wherein, P⊥(r) it is vertical channel, P||(r) it is parallel channels.
Alternatively, the scattering ratio of actual measurement is calculated by below equation：
Wherein, N (r) is molecule number concentration profile, d σRa/dΩπIt is the differential of Rayleigh scattering back scattering cross section；
The scattering ratio of corresponding atmospheric molecule is calculated by below equation：
The scattering ratio uncertainty of corresponding atmospheric molecule is calculated by below equation：
Wherein, A (r) contains other all amounts in scattering ratio；Subscript " m " refers to different variables and corresponds to atmospheric molecule
Amount.
Alternatively, the linear Depolarization Ratio of actual measurement is calculated by below equation：
Wherein, P⊥_o(r) for by the signal of the revised vertical channel of geometrical factor, P||_o(r) it is by geometrical factor
The signal of revised parallel channels；
The linear Depolarization Ratio of corresponding atmospheric molecule is calculated by below equation：
The linear Depolarization Ratio uncertainty of corresponding atmospheric molecule is calculated by below equation：
Alternatively, the step of being detected based on the scattering ratio and linear Depolarization Ratio using threshold method to Atmospheric Characteristics layer
Including：
Using formula τ (r)=Rm(r)+C*σRThe threshold value with height change is calculated in m (r), wherein, Rm(r) it is air
Molecular ratio, σRM (r) is uncertain corresponding to atmospheric molecule ratio, and C is constant；
In the ratio of actual measurement, it will be greater than the threshold value and meet that the part of preparatory condition is determined as Atmospheric Characteristics layer.
Alternatively, the Mie scattering polarization lidar signal comes from by the revised laser radar institute of ambient noise
The initial data of observation；
The meteorological data comes from temperature and humidity data of the global atmosphere again in analysis of data.
Alternatively, the air heating power status data can carry from the global atmosphere temperature of analysis of data, humidity data again
For the foundation of different clouds mutually in height；
The optical characteristics of the Atmospheric Characteristics layer includes linear Depolarization Ratio and backscattering coefficient；
The backscattering coefficient of the Atmospheric Characteristics layer is obtained by Fernald method invertings；
The empirical value is general by the two dimension of linear Depolarization Ratio-backscattering coefficient under different air thermodynamic status
Rate distribution map obtains.
Another preferred embodiment of the present invention provides a kind of Atmospheric Characteristics layer detection means, including：
Information acquisition module, for obtaining Mie scattering polarization lidar signal and meteorological data；
Data processing module, for scattering to be calculated according to the Mie scattering polarization lidar signal and meteorological data
Than with linear Depolarization Ratio；
Detection module, for being examined based on the scattering ratio and linear Depolarization Ratio using threshold method to Atmospheric Characteristics layer
Survey；
Sort module, for the optical characteristics based on air heating power status data and Atmospheric Characteristics layer, using empirical value
Method classifies the Atmospheric Characteristics layer detected；
Iteration module, it is calculated for performing again according to the Mie scattering polarization lidar signal and meteorological data
Scattering ratio and linear Depolarization Ratio are detected again to the step of using empirical value method, the Atmospheric Characteristics layer detected is classified
The Atmospheric Characteristics layer and the classification results again of Atmospheric Characteristics layer arrived；
Judge module, for the Atmospheric Characteristics layer and the subseries again of Atmospheric Characteristics layer that judge to detect again and last time
Whether the difference between the classification of the Atmospheric Characteristics layer and Atmospheric Characteristics layer that detect is less than given threshold；
If being more than the given threshold, perform according to the Mie scattering polarization lidar signal and meteorological number again
According to scattering ratio and linear Depolarization Ratio is calculated to the step of the Atmospheric Characteristics layer detected is classified using empirical value method, directly
To newest classification and the last Atmospheric Characteristics layer detected and greatly of the Atmospheric Characteristics layer and Atmospheric Characteristics layer being most recently detected
Difference between the classification of gas characteristic layer is less than the given threshold, then revises the Atmospheric Characteristics using continuous wavelet analytic approach
The newest classification of layer.
Alternatively, described information obtains the Mie scattering polarization lidar signal that module obtains and come from by background
The initial data that the revised laser radar of noise is observed；
Described information obtain the meteorological data that module obtains come from temperature of the global atmosphere again in analysis of data and
Humidity data.
Alternatively, the sort module includes data acquiring unit and data processing unit；
The data acquiring unit is used to obtain air heating power status data and the optical characteristics of Atmospheric Characteristics layer, wherein,
The air heating power status data is from the global atmosphere temperature of analysis of data, humidity data again, it is possible to provide different clouds are mutually in height
Foundation on degree；The optical characteristics of the Atmospheric Characteristics layer includes linear Depolarization Ratio and backscattering coefficient；
The data processing unit is used to obtain the back scattering system of the Atmospheric Characteristics layer by Fernald method invertings
Number, obtained by the dimensional probability distribution figure of linear Depolarization Ratio-backscattering coefficient under different air thermodynamic status described
Empirical value.
Atmospheric Characteristics layer detection method and device provided in an embodiment of the present invention, dexterously utilize scattering ratio and linear depolarization
Than detecting Atmospheric Characteristics layer based on threshold method, scattering ratio and linear Depolarization Ratio can not only be by Atmospheric Characteristics layers on signal profile
The weak signal at edge highlights, and both combinations can be accurately detected more complete Atmospheric Characteristics layer, embodiment party
Just, detection is accurate.
Further, Atmospheric Characteristics layer detection method and device provided in an embodiment of the present invention, with reference to relatively simple warp
Test threshold method and continuous wavelet analytic approach and rational classification is realized to Atmospheric Characteristics layer, continuous wavelet analytic approach can effectively make up
Mie scattering lidar is classified not in the case where that can not calculate Lidar Ratios using empirical value method to characteristic layer
Foot, realizes the detection and classification and the inverting of Extinction Characteristic of Atmospheric Characteristics layer, fully excavates the potential value of data.
Further, Atmospheric Characteristics layer detection method and device provided in an embodiment of the present invention, also have suitable for other
The Mie scattering lidar of depolarization function, the scope of application are wider.
To enable the above objects, features and advantages of the present invention to become apparent, preferred embodiment cited below particularly, and coordinate
Appended accompanying drawing, is described in detail below.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by embodiment it is required use it is attached
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore be not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 is the block diagram for a kind of electronic equipment 10 that present pre-ferred embodiments provide.
Fig. 2 is a kind of flow chart for Atmospheric Characteristics layer detection method that present pre-ferred embodiments provide.
Fig. 3 is the schematic diagram of the sub-step that step S23 shown in Fig. 2 includes in an embodiment.
Fig. 4 is a kind of module frame chart for Atmospheric Characteristics layer detection means 20 that present pre-ferred embodiments provide.
Fig. 5 is the module frame chart of sort module shown in Fig. 4 in an embodiment.
Icon：10- electronic equipments；11- memories；12- processors；13- mixed-media network modules mixed-medias；20- Atmospheric Characteristics layer detection dress
Put；21- information acquisition modules；22- data processing modules；23- detection modules；24- sort modules；241- data acquiring units；
242- data processing units；25- iteration modules；26- judge modules.
Embodiment
Below in conjunction with accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.Generally exist
The component of the embodiment of the present invention described and illustrated in accompanying drawing can be configured to arrange and design with a variety of herein.Cause
This, the detailed description of the embodiments of the invention to providing in the accompanying drawings is not intended to limit claimed invention below
Scope, but it is merely representative of the selected embodiment of the present invention.Based on embodiments of the invention, those skilled in the art are not doing
The every other embodiment obtained on the premise of going out creative work, belongs to the scope of protection of the invention.
It should be noted that：Similar label and letter represents similar terms in following accompanying drawing, therefore, once a certain Xiang Yi
It is defined, then it further need not be defined and explained in subsequent accompanying drawing in individual accompanying drawing.
As shown in figure 1, it is the block diagram for the electronic equipment 10 that present pre-ferred embodiments provide.The embodiment of the present invention
In electronic equipment 10 can be the equipment with data processing function.As shown in figure 1, electronic equipment 10 includes：Memory 11,
Processor 12, mixed-media network modules mixed-media 13 and Atmospheric Characteristics layer detection means 20.
The memory 11, processor 12 and mixed-media network modules mixed-media 13 are directly or indirectly electrically connected between each other, with reality
The transmission or interaction of existing data.For example, these elements can be realized by one or more communication bus or signal wire between each other
It is electrically connected with.Atmospheric Characteristics layer detection means 20 is stored with memory 11, the Atmospheric Characteristics layer detection means 20 is included extremely
A few software function module that can be stored in the form of software or firmware (firmware) in the memory 11, it is described
Processor 12 is stored in software program and module in memory 11 by operation, such as the Atmospheric Characteristics in the embodiment of the present invention
Layer detection means 20, so as to perform various function application and data processing, that is, realizes the Atmospheric Characteristics in the embodiment of the present invention
Layer detection method.
Wherein, the memory 11 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only storage (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only
Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM),
Electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory, EEPROM) etc..
Wherein, memory 11 is used for storage program, and the processor 12 performs described program after execute instruction is received.
The processor 12 is probably a kind of IC chip, has the disposal ability of data.Above-mentioned processor 12
Can be general processor, including central processing unit (Central Processing Unit, CPU), network processing unit
(Network Processor, NP) etc..It can realize or perform each method disclosed in the embodiment of the present invention, step and patrol
Collect block diagram.General processor can be microprocessor or the processor can also be any conventional processor etc..
Mixed-media network modules mixed-media 13 is used for the communication connection established by network between electronic equipment 10 and external communications terminals, realizes
The transmitting-receiving operation of network signal and data.Above-mentioned network signal may include wireless signal or wire signal.
It is appreciated that structure shown in Fig. 1 is only to illustrate, electronic equipment 10 may also include it is more more than shown in Fig. 1 or
Less component, or there is the configuration different from shown in Fig. 1.Each component shown in Fig. 1 can use hardware, software or its
Combination is realized.
The embodiment of the present invention also provides a kind of readable storage medium storing program for executing, and the readable storage medium storing program for executing includes computer program.Institute
State and control electronic equipment 10 where the readable storage medium storing program for executing to perform following Atmospheric Characteristics layer detection during computer program operation
Method.
Referring to Fig. 2, it is a kind of flow chart for Atmospheric Characteristics layer detection method that present pre-ferred embodiments provide.It is described
Method and step defined in the relevant flow of method is applied to electronic equipment 10, can be realized by the processor 12.Below will
Idiographic flow shown in Fig. 2 is described in detail.
Step S21, obtain Mie scattering polarization lidar signal and meteorological data.
Alternatively, the Mie scattering polarization lidar signal is expressed as：
The Mie scattering polarization lidar signal have passed through correcting for ambient noise.
Wherein, r is detection range, and C is system constants, and E is pulse energy, and O (r) is geometrical factor, βm(r) it is big qi leel
The backscattering coefficient of son, βp(r) it is the backscattering coefficient of Atmospheric particulates,For atmospheric molecule
Transmitance,For the transmitance of Atmospheric particulates, αm(r) it is the extinction coefficient of atmospheric molecule, αp(r)
For the extinction coefficient of Atmospheric particulates.
The Mie scattering polarization lidar signal is calculated using below equation：
P (r)=P⊥(r)+P||(r)
Wherein, P⊥(r) it is vertical channel, P||(r) it is parallel channels.
The meteorological data is from the global atmosphere temperature of analysis of data, humidity data again.
Step S22, scattering ratio and linear is calculated according to the Mie scattering polarization lidar signal and meteorological data
Depolarization Ratio.
Wherein, the scattering ratio of actual measurement is calculated by below equation：
Wherein, N (r) is molecule number concentration profile, d σRa/dΩπIt is the differential of Rayleigh scattering back scattering cross section；
The scattering ratio of corresponding atmospheric molecule is calculated by below equation：
The scattering ratio uncertainty of corresponding atmospheric molecule is calculated by below equation：
Wherein, A (r) contains other all amounts in scattering ratio；Subscript " m " refers to different variables and corresponds to atmospheric molecule
Amount.
The linear Depolarization Ratio of actual measurement is calculated by below equation：
Wherein, P⊥_o(r) for by the signal of the revised vertical channel of geometrical factor, P||_o(r) it is by geometrical factor
The signal of revised parallel channels；
The linear Depolarization Ratio of corresponding atmospheric molecule is calculated by below equation：
The linear Depolarization Ratio uncertainty of corresponding atmospheric molecule is calculated by below equation：
Step S23, Atmospheric Characteristics layer is detected using threshold method based on scattering ratio and linear Depolarization Ratio.
Fig. 3 is please referred to, alternatively, step S23 includes step S231 and the sub-steps of step S232 two.
Step S231, using formulaThe threshold value with height change is calculated, its
In, Rm(r) it is atmospheric molecule ratio,To be uncertain corresponding to atmospheric molecule ratio, C is constant.
Step S232, in the ratio of actual measurement, it will be greater than the threshold value and meet that the part of preparatory condition is determined as air
Characteristic layer.
In the ratio profile of observation, the part more than the threshold value is deemed likely to containing Atmospheric Characteristics layer, basic herein
On, in order to avoid being Atmospheric Characteristics layer by noise error detection, thus also need to determine whether to meet preparatory condition.In the present embodiment,
Utilization space filter removes erroneous judgement, if the overlapping possibility between the distribution of desired molecular signal and the signal distributions of actual measurement is more than
During specific threshold value, it is believed that this is characterized as judging and being changed into clear sky by accident.
Step S24, the optical characteristics based on air heating power status data and Atmospheric Characteristics layer, it will be examined using empirical value method
The Atmospheric Characteristics layer classification measured.
For the air thermodynamic status from the global atmosphere temperature of analysis of data, humidity data again, it can provide different clouds
Mutually foundation in height.
The optical characteristics of the Atmospheric Characteristics layer includes linear Depolarization Ratio and backscattering coefficient.
The backscattering coefficient of the Atmospheric Characteristics layer can utilize the inverting of Fernald methods to obtain.
The empirical value is obtained by the dimensional probability distribution figure of linear Depolarization Ratio-backscattering coefficient at different temperatures
Arrive.
Step S25, perform again and scattering is calculated according to the Mie scattering polarization lidar signal and meteorological data
Than, to the step of using empirical value method, the Atmospheric Characteristics layer detected is classified, being detected again with linear Depolarization Ratio
The classification results again of Atmospheric Characteristics layer and Atmospheric Characteristics layer.
Step S26, judge that the subseries again of the Atmospheric Characteristics layer and Atmospheric Characteristics layer detected again detects with last
Whether the difference between the classification of the Atmospheric Characteristics layer and Atmospheric Characteristics layer that arrive is less than given threshold.
Step S27, if being more than the given threshold, perform according to the Mie scattering polarization lidar signal again
Scattering ratio and linear Depolarization Ratio is calculated with meteorological data the Atmospheric Characteristics layer detected is classified to using empirical value method
The step of, until the newest classification for the Atmospheric Characteristics layer and Atmospheric Characteristics layer being most recently detected and the last air detected are special
Difference between sign layer and the classification of Atmospheric Characteristics layer is less than the given threshold, then using described in the revision of continuous wavelet analytic approach
The newest classification of Atmospheric Characteristics layer.
By above-mentioned, the detection method of the Atmospheric Characteristics layer is an iterative process, if the Atmospheric Characteristics layer of detection
Or difference of the feature channel type in newest iteration and last iteration be less than setting threshold value when, step S22~step S24 meetings
Stop performing, circulation terminates.
Through research, sand and dust source region or source area, frequently sand and dust generation is had in spring and winter, and the linear of sand and dust moves back
Partially than can cloud weaker than some linear Depolarization Ratio it is also big, using empirical value to Atmospheric Characteristics layer classification, sand and dust may be made
It is mistaken for ice cloud.And continuous wavelet analytic approach is commonly used to detect the discontinuity point (characteristic layer border) in laser radar signal,
The scattering ratio obtained in the present embodiment based on last time iteration utilizes continuous wavelet analytic approach in the Atmospheric Characteristics layer of detection
Cloud border is found, then further cloud phase is classified using empirical value method, so as to be improved the inspection of Atmospheric Characteristics layer
The accuracy of survey.
On the basis of the above, as shown in figure 4, the embodiments of the invention provide a kind of Atmospheric Characteristics layer detection means 20, institute
Stating Atmospheric Characteristics layer detection means 20 includes information acquisition module 21, data processing module 22, detection module 23, sort module
24th, iteration module 25 and judge module 26.
Wherein, information acquisition module 21 is used to obtain Mie scattering polarization lidar signal and meteorological data.
Because information acquisition module 21 is similar with the realization principle of step S21 in Fig. 2, thus do not illustrate more herein.
Data processing module 22 is scattered for being calculated according to the Mie scattering polarization lidar signal and meteorological data
Penetrate than with linear Depolarization Ratio.
Because data processing module 22 is similar with the realization principle of step S22 in Fig. 2, thus do not illustrate more herein.
Detection module 23 is used to examine Atmospheric Characteristics layer using threshold method based on the scattering ratio and linear Depolarization Ratio
Survey.
Because detection module 23 is similar with the realization principle of step S23 in Fig. 2, thus do not illustrate more herein.
Sort module 24 is used for the optical characteristics based on air heating power status data and Atmospheric Characteristics layer, using empirical value
Method classifies the Atmospheric Characteristics layer detected.
Because sort module 24 is similar with the realization principle of step S24 in Fig. 2, thus do not illustrate more herein.
Iteration module 25 is used to perform again to be calculated according to the Mie scattering polarization lidar signal and meteorological data
To scattering ratio and linear Depolarization Ratio to the step of using empirical value method, the Atmospheric Characteristics layer detected is classified, examined again
The Atmospheric Characteristics layer and the classification results again of Atmospheric Characteristics layer measured.
Because iteration module 25 is similar with the realization principle of step S25 in Fig. 2, thus do not illustrate more herein.
Judge module 26 is used for the subseries again and upper one for judging the Atmospheric Characteristics layer and Atmospheric Characteristics layer detected again
Whether the difference between the classification of the secondary Atmospheric Characteristics layer and Atmospheric Characteristics layer detected is less than given threshold.
If being more than the given threshold, perform according to the Mie scattering polarization lidar signal and meteorological number again
According to scattering ratio and linear Depolarization Ratio is calculated to the step of the Atmospheric Characteristics layer detected is classified using empirical value method, directly
To newest classification and the last Atmospheric Characteristics layer detected and greatly of the Atmospheric Characteristics layer and Atmospheric Characteristics layer being most recently detected
Difference between the classification of gas characteristic layer is less than the given threshold, then revises the Atmospheric Characteristics using continuous wavelet analytic approach
The newest classification of layer.
Because judge module 26 is similar with the realization principle of step S26~step S27 in Fig. 2, thus do not make herein more
Explanation.
Wherein, described information obtains the Mie scattering polarization lidar signal that module 21 obtains and come from by background
The initial data that the revised laser radar of noise is observed.
Described information obtains the meteorological data that module 21 obtains and comes from temperature of the global atmosphere again in analysis of data
And humidity data.
Fig. 5 is please referred to, alternatively, the sort module 24 includes data acquiring unit 241 and data processing unit
242。
The data acquiring unit 241 is used to obtain air heating power status data and the optical characteristics of Atmospheric Characteristics layer, its
In, the air heating power status data is from the global atmosphere temperature of analysis of data, humidity data again, it is possible to provide different clouds mutually exist
Foundation in height；The optical characteristics of the Atmospheric Characteristics layer includes linear Depolarization Ratio and backscattering coefficient.
The data processing unit 242 is used to obtain the back scattering of the Atmospheric Characteristics layer by Fernald method invertings
Coefficient, institute is obtained by the dimensional probability distribution figure of linear Depolarization Ratio-backscattering coefficient under different air thermodynamic status
State empirical value.
Atmospheric Characteristics layer detection method and device in the embodiment of the present invention, are sufficiently used Mie scattering polarization laser thunder
The limited detection amount reached detects more complete and accurate Atmospheric Characteristics layer, simple to the sorting technique of Atmospheric Characteristics layer and have
Effect, can realize the detection and classification and the inverting of Extinction Characteristic of Atmospheric Characteristics layer simultaneously, fully excavate the potential of data
Value, it is also largely effective in sand and dust source region or the source area detection method.
In several embodiments that the embodiment of the present invention is provided, it should be understood that disclosed apparatus and method, also may be used
To realize by another way.Apparatus and method embodiment described above is only schematical, for example, in accompanying drawing
Flow chart and block diagram show the device of multiple embodiments according to the present invention, the possibility of method and computer program product is realized
Architectural framework, function and operation.At this point, each square frame in flow chart or block diagram can represent module, a program
A part for section or code, a part for the module, program segment or code include one or more and are used to realize defined patrol
Collect the executable instruction of function.It should also be noted that at some as the function of in the implementation replaced, being marked in square frame
Can be with different from the order marked in accompanying drawing generation.For example, two continuous square frames can essentially be held substantially in parallel
OK, they can also be performed in the opposite order sometimes, and this is depending on involved function.It is also noted that block diagram and/or
The combination of each square frame and block diagram in flow chart and/or the square frame in flow chart, function or dynamic as defined in performing can be used
The special hardware based system made is realized, or can be realized with the combination of specialized hardware and computer instruction.
In addition, each functional module in each embodiment of the present invention can integrate to form an independent portion
Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized in the form of software function module and is used as independent production marketing or in use, can be with
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
The part to be contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, including some instructions are causing a computer equipment (can be
People's computer, electronic equipment 10, or network equipment etc.) perform all or part of step of each embodiment methods described of the present invention
Suddenly.And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), deposit at random
Access to memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.
It should be noted that herein, term " comprising ", "comprising" or its any other variant are intended to the bag of nonexcludability
Contain, so that process, method, article or equipment including a series of elements not only include those key elements, but also including
The other element being not expressly set out, or also include for this process, method, article or the intrinsic key element of equipment.
In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including the key element
Process, method, other identical element also be present in article or equipment.
The alternative embodiment of the present invention is the foregoing is only, is not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.Within the spirit and principles of the invention, that is made any repaiies
Change, equivalent substitution, improvement etc., should be included in the scope of the protection.
Claims (10)
- A kind of 1. Atmospheric Characteristics layer detection method, it is characterised in that including：Obtain Mie scattering polarization lidar signal and meteorological data；Scattering ratio and linear Depolarization Ratio are calculated according to the Mie scattering polarization lidar signal and meteorological data；Atmospheric Characteristics layer is detected using threshold method based on the scattering ratio and linear Depolarization Ratio；Optical characteristics based on air heating power status data and Atmospheric Characteristics layer, it is using empirical value method that the air detected is special Levy layer classification；Perform again and scattering ratio and linear depolarization are calculated according to the Mie scattering polarization lidar signal and meteorological data Than to the step of using empirical value method, the Atmospheric Characteristics layer detected is classified, the Atmospheric Characteristics layer that is detected again with The classification results again of Atmospheric Characteristics layer；Judge the subseries again of the Atmospheric Characteristics layer and Atmospheric Characteristics layer detected again and the last Atmospheric Characteristics detected Whether the difference between layer and the classification of Atmospheric Characteristics layer is less than given threshold；If being more than the given threshold, perform according to the Mie scattering polarization lidar signal and meteorological data meter again Calculation obtains scattering ratio and linear Depolarization Ratio to the step of the Atmospheric Characteristics layer detected is classified using empirical value method, up to most The newest classification of the Atmospheric Characteristics layer and Atmospheric Characteristics layer that newly detect and the last Atmospheric Characteristics layer detected and air are special The difference levied between the classification of layer is less than the given threshold, then revises the Atmospheric Characteristics layer using continuous wavelet analytic approach Newest classification.
- 2. according to the method for claim 1, it is characterised in that the Mie scattering polarization lidar signal is expressed as：Wherein, r is detection range, and C is system constants, and E is pulse energy, and O (r) is geometrical factor, βm(r) it is atmospheric molecule Backscattering coefficient, βp(r) it is the backscattering coefficient of Atmospheric particulates,For the saturating of atmospheric molecule Cross rate,For the transmitance of Atmospheric particulates, αm(r) it is the extinction coefficient of atmospheric molecule, αp(r) it is big The extinction coefficient of aerated particle thing；The Mie scattering polarization lidar signal is calculated using below equation：P (r)=P⊥(r)+P||(r)Wherein, P⊥(r) it is vertical channel, P||(r) it is parallel channels.
- 3. according to the method for claim 2, it is characterised in that the scattering ratio of actual measurement is calculated by below equation：Wherein, N (r) is molecule number concentration profile, d σRa/dΩπIt is the differential of Rayleigh scattering back scattering cross section；The scattering ratio of corresponding atmospheric molecule is calculated by below equation：The scattering ratio uncertainty of corresponding atmospheric molecule is calculated by below equation：Wherein, A (r) contains other all amounts in scattering ratio；Subscript " m " refers to the amount that different variables correspond to atmospheric molecule.
- 4. according to the method for claim 2, it is characterised in that the linear Depolarization Ratio of actual measurement is calculated by below equation Arrive：Wherein, P⊥_o(r) for by the signal of the revised vertical channel of geometrical factor, P||_o(r) it is to be corrected by geometrical factor The signal of parallel channels afterwards；The linear Depolarization Ratio of corresponding atmospheric molecule is calculated by below equation：The linear Depolarization Ratio uncertainty of corresponding atmospheric molecule is calculated by below equation：
- 5. the method according to claim 3 or 4, it is characterised in that threshold is used based on the scattering ratio and linear Depolarization Ratio The step of value method detects to Atmospheric Characteristics layer includes：Using formulaThe threshold value with height change is calculated, wherein, Rm (r) it is atmospheric molecule ratio,To be uncertain corresponding to atmospheric molecule ratio, C is constant；In the ratio of actual measurement, it will be greater than the threshold value and meet that the part of preparatory condition is determined as Atmospheric Characteristics layer.
- 6. according to the method for claim 1, it is characterised in that the Mie scattering polarization lidar signal come from by The initial data that the revised laser radar of ambient noise is observed；The meteorological data comes from temperature and humidity data of the global atmosphere again in analysis of data.
- 7. according to the method for claim 1, it is characterised in that the air heating power status data is divided again from global atmosphere The temperature of analysis data, humidity data, it is possible to provide the foundation of different clouds mutually in height；The optical characteristics of the Atmospheric Characteristics layer includes linear Depolarization Ratio and backscattering coefficient；The backscattering coefficient of the Atmospheric Characteristics layer is obtained by Fernald method invertings；The Two-dimensional Probabilistic point that the empirical value passes through linear Depolarization Ratio-backscattering coefficient under different air thermodynamic status Butut obtains.
- A kind of 8. Atmospheric Characteristics layer detection means, it is characterised in that including：Information acquisition module, for obtaining Mie scattering polarization lidar signal and meteorological data；Data processing module, for according to the Mie scattering polarization lidar signal and meteorological data be calculated scattering ratio and Linear Depolarization Ratio；Detection module, for being detected based on the scattering ratio and linear Depolarization Ratio using threshold method to Atmospheric Characteristics layer；Sort module, will using empirical value method for the optical characteristics based on air heating power status data and Atmospheric Characteristics layer The Atmospheric Characteristics layer classification detected；Iteration module, scattering is calculated according to the Mie scattering polarization lidar signal and meteorological data for performing again Than, to the step of using empirical value method, the Atmospheric Characteristics layer detected is classified, being detected again with linear Depolarization Ratio The classification results again of Atmospheric Characteristics layer and Atmospheric Characteristics layer；Judge module, Atmospheric Characteristics layer and the subseries again of Atmospheric Characteristics layer for judging to detect again detect with last Whether the difference between the classification of the Atmospheric Characteristics layer and Atmospheric Characteristics layer that arrive is less than given threshold；If being more than the given threshold, perform according to the Mie scattering polarization lidar signal and meteorological data meter again Calculation obtains scattering ratio and linear Depolarization Ratio to the step of the Atmospheric Characteristics layer detected is classified using empirical value method, up to most The newest classification of the Atmospheric Characteristics layer and Atmospheric Characteristics layer that newly detect and the last Atmospheric Characteristics layer detected and air are special The difference levied between the classification of layer is less than the given threshold, then revises the Atmospheric Characteristics layer using continuous wavelet analytic approach Newest classification.
- 9. Atmospheric Characteristics layer detection means according to claim 8, it is characterised in that described information obtains what module obtained The Mie scattering polarization lidar signal comes from the initial data observed by the revised laser radar of ambient noise；Described information obtains the meteorological data that module obtains and comes from temperature and humidity of the global atmosphere again in analysis of data Data.
- 10. Atmospheric Characteristics layer detection means according to claim 8, it is characterised in that the sort module includes data Obtaining unit and data processing unit；The data acquiring unit is used to obtain air heating power status data and the optical characteristics of Atmospheric Characteristics layer, wherein, it is described Air heating power status data is from the global atmosphere temperature of analysis of data, humidity data again, it is possible to provide different clouds are mutually in height Foundation；The optical characteristics of the Atmospheric Characteristics layer includes linear Depolarization Ratio and backscattering coefficient；The data processing unit is used to obtain the backscattering coefficient of the Atmospheric Characteristics layer by Fernald method invertings, leads to The dimensional probability distribution figure for the linear Depolarization Ratio-backscattering coefficient crossed under different air thermodynamic status obtains the experience threshold Value.
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