115 results about "Atmospheric temperature" patented technology

The invention relates to the technical field of wetland carbon evaluation, and discloses a wetland carbon flux evaluation and management system based on three-dimensional digital twinning. The system comprises a three-dimensional modeling module, a flux monitoring module, a model optimization module and a twin updating module. The three-dimensional modeling module integrates wetland geographic space coordinates, an ecological parameter set and elevation, vegetation coverage density and soil type layering information, constructs a three-dimensional terrain grid model, and generates a three-dimensional digital twinborn body with a geographic mark; the flux monitoring module is used for collecting data such as atmospheric temperature gradient based on real-time environmental parameters, extracting carbon flux change characteristics through time sequence analysis and outputting a dynamic distribution state value; the model optimization module uses an adaptive evolutionary algorithm to adjust the parameter matching degree, iteratively updates constraint conditions, and generates an optimization parameter set; and the twin updating module recognizes abnormal grid units according to the abnormal grid units, corrects attributes by combining measured data, calibrates a topological relation, and outputs an updated evaluation model.

The invention belongs to the technical field of intelligent agriculture, and discloses a canopy-atmospheric environment information-based soil water content prediction method and system, and the method comprises the steps: setting a canopy and atmospheric environment monitoring unit in a field, and synchronously collecting the canopy temperature, wind speed, relative humidity, and six-dimensional environment parameters of atmospheric temperature, wind speed and relative humidity; the crown temperature difference is calculated after preprocessing; the method comprises the following steps: constructing a training set by utilizing measured data of soil relative water content, constructing a soil water content prediction model by adopting a random forest algorithm, screening and confirming an optimal prediction model through grid search and cross validation, and screening key features by combining an SHAP value; the water demand is automatically calculated according to a pre-established crop whole-growth-period drought stress threshold table and a dynamic irrigation decision formula, and meanwhile, the adaptation of a general model to a regional specific model is realized by constructing an environmental parameter-actually measured water content database and transfer learning, so that the soil water content state is accurately predicted, and the soil quality is improved. And a scientific basis is provided for precise irrigation.

The invention provides an atmospheric temperature and humidity profile repairing method integrating a statistical method and a deep learning technology, belongs to the technical field of meteorological observation, and aims to solve the problem of large-area data missing caused by cloud pollution by taking an FY-4B satellite temperature and humidity profile product as a processing object. Data reconstruction is realized through a three-stage architecture of random cloud mask generation, statistical filling and pre-restoration, and deep learning and fine correction; according to the method, the problem of data truth value missing is solved, meanwhile, the advantages of a statistical method and a deep learning technology are combined, the repair precision in an extreme missing scene is remarkably improved while physical reasonability is guaranteed, and meanwhile the method has the advantages of being few in needed computing resources, high in computing speed and the like.

The invention relates to an airglow layer gravity wave spectrum temperature imaging system and a two-dimensional temperature field point-surface fusion inversion method. The airglow layer gravity wave spectrum temperature imaging system comprises a fine spectrum detection subsystem, a rotation temperature spectrum measurement subsystem and a large-view-field gravity wave imaging subsystem. The three subsystems are respectively provided with three progressively-increased field angles and carry out synchronous detection, a detection area and a detection target are organically cooperated, image and data processing is carried out in the later period, and the fine spectrum detection subsystem and the rotating temperature spectrum measurement subsystem carry out cooperative calibration, so that high-precision inversion of the atmospheric temperature can be realized. And the linear relation between the airglow radiation intensity and the atmospheric temperature is obtained. A small, medium and large field-of-view collaborative observation mode is adopted, and through a point-surface fusion detection method and a data inversion algorithm, a linear relationship between high-accuracy airglow radiation intensity constructed by single-point detection and atmospheric temperature is expanded and fused to an airglow radiation field with a horizontal two-dimensional resolution capability; therefore, the temperature field with the same detection precision and the horizontal two-dimensional resolution capability is obtained.

The invention relates to the technical field of interdiscipline, in particular to a grain depot equipment intelligent operation and maintenance management system based on SAAS, and the system comprises a data collection unit which obtains the atmospheric temperature provided by an external meteorological data interface, and records the preset grain variety physical attributes; the digital twin modeling unit is used for solving a predicted temperature distribution field of the grain pile; the risk quantitative evaluation unit is used for calculating a comprehensive risk state index based on the predicted temperature distribution field and the real-time grain humidity, and judging a risk level according to a preset risk threshold value; the optimization decision-making unit is used for generating an optimal intervention strategy; when the risk level is the security level, maintaining the current intervention strategy; the model self-adaptive correction unit is used for comparing the predicted temperature output by the digital twin modeling unit with the real-time grain temperature acquired by the data acquisition unit and updating a self-adaptive deviation item in the model according to deviation; according to the invention, the reliable foundation of prediction and decision-making of the whole intelligent operation and maintenance management system is ensured.

The invention provides an overhead atmospheric temperature measuring device and method. The measuring device comprises at least one temperature probe and a temperature measuring circuit. The temperature probe adopts a patch type four-wire platinum resistor temperature sensor, spaceflight white paint is coated on the surface of the temperature probe and a nearby cable, and the temperature probe is arranged on the outer surface of the high-altitude balloon; the temperature measurement circuit adopts a four-wire system constant current source temperature measurement circuit and comprises a power conversion circuit, a constant current source circuit, a filter circuit and an instrument amplification circuit.

The invention belongs to the technical field of atmosphere data detection, and particularly discloses a helicopter distributed three-axis atmosphere data measuring device which comprises a left three-axis atmosphere measuring assembly and a right three-axis atmosphere measuring assembly which are installed on the two sides of a nose and are the same in structure. Each airspeed tube consists of a rotary airspeed tube and an electronic component; the rotary airspeed tube and the electronic component are electrically connected through the fuselage skin opening; the rotating airspeed tubes are mounted outside skins on two sides of the machine head and used for sensing total pressure, static pressure, local attack angle and local sideslip angle of the synthetic gas flow in real time; the electronic component is arranged in the machine head skin and used for collecting the total pressure, the static pressure, the local attack angle, the local sideslip angle and the atmospheric temperature of the synthetic gas flow, conducting parameter calculation and outputting atmospheric parameters. According to the invention, the problem that a centralized atmosphere data system, a distributed atmosphere data system and a three-axis atmosphere data system have different restrictions on the use of a helicopter at present is solved.

The invention relates to the technical field of atmospheric remote sensing, in particular to an all-weather temperature and humidity inversion method based on a laser radar, which comprises the following steps: S1, acquiring laser radar data of related wavelengths required by water vapor and temperature inversion, and preprocessing the laser radar data; s2, carrying out noise filtering processing on the laser radar data preprocessed in the step S1; and S3, performing inversion processing on the laser radar data subjected to noise filtering processing in the step S2 by using a temperature and humidity inversion formula and substituting the calibration parameters so as to obtain an atmospheric temperature profile # imgabs0 # and an atmospheric humidity profile # imgabs1 #. Through self-adaptive filtering treatment, signal smoothness is ensured, abundant high-altitude information is reserved, the temperature and humidity detection distance is increased, all-weather detection of the temperature and humidity is ensured, the temperature and humidity inversion precision can be effectively improved, in addition, the method can adapt to the complex atmospheric environment, the data reliability is high, and the method is suitable for popularization and application. And all-weather and long-term temperature and humidity data inversion is further effectively supported.

The invention discloses a method for inverting a cloud condensation nucleus number concentration profile based on a laser radar and a neural network. The method comprises the following steps: collecting multi-wavelength laser radar data including a backscattering coefficient vertical profile, an extinction coefficient vertical profile, a laser radar ratio and a depolarization ratio; the method comprises the following steps: acquiring an atmospheric temperature profile and a water vapor mixing ratio profile which are in time-space synchronization with multi-wavelength laser radar data, performing grid alignment on a vertical height, and constructing a multi-channel input feature set for each preset target supersaturation ratio; and constructing a convolutional neural network profile inversion model, taking the multi-channel input feature set as input and the cloud condensation nucleus number concentration profile data as output, training the model, and obtaining the trained convolutional neural network profile inversion model. According to the method, the limitation of continuous, high-precision and high-temporal-spatial-resolution detection of CCN number concentration vertical distribution is overcome, and key data support is provided for the fields of weather forecast, climate models, artificial influence weather and the like.

The invention provides an atmospheric temperature and humidity profile inversion method, device and equipment, a medium and a program product, and relates to the technical field of atmospheric remote sensing, and the method comprises the steps: collecting the brightness temperature data of the atmosphere, the cloud feature data of the atmosphere and the ground temperature, humidity and pressure data; inputting the brightness temperature data, the cloud feature data and the ground temperature, humidity and pressure data into a meteorological profile inversion model to obtain an atmospheric temperature and humidity profile output by the meteorological profile inversion model; wherein the meteorological profile inversion model comprises a multi-modal feature extraction layer, a double-flow collaborative network layer and a physical-data hybrid constraint layer. According to the method, cloud feature data and ground temperature, humidity and pressure data are introduced into atmosphere temperature and humidity profile inversion of the microwave radiometer, and an artificial intelligence algorithm is introduced to realize multi-modal feature fusion and automatically adapt to different weather conditions, so that the inversion precision of the atmosphere temperature and humidity profile is improved.

This invention discloses a method and system for predicting the structural response of historical buildings under atmospheric temperature fields. The method includes: acquiring atmospheric temperature field information, structural temperature field information, and structural response information over a past period; using the atmospheric temperature field information, structural temperature field information, and structural temperature field information and structural response information as training sets, respectively, to establish and train an atmospheric temperature prediction model for structural temperature and a structural temperature prediction model for structural response based on artificial intelligence algorithms; predicting future structural temperature field information based on future atmospheric temperature field information and historical structural temperature field information using the atmospheric temperature prediction model for structural temperature; and predicting the future structural response information of the historical building structure over a future period based on future structural temperature field information and historical structural response information using the structural temperature prediction model for structural response. This invention improves the accuracy and precision of predicting the structural response of historical buildings as atmospheric temperature changes, and has a wide range of applications.

The present invention relates to an airglow layer gravity wave spectral temperature imaging system and a two-dimensional temperature field point-surface fusion inversion method, comprising a fine spectrum detection subsystem, a rotational temperature spectrum measurement subsystem, and a large-field-of-view gravity wave imaging subsystem. The three subsystems are each provided with three increasing field-of-view angles and perform synchronous detection. The detection area and the detection target are organically coordinated. Later, through image and data processing, the fine spectrum detection subsystem and the rotational temperature spectrum measurement subsystem are collaboratively calibrated to achieve high-precision inversion of atmospheric temperature and obtain a linear relationship between airglow radiation intensity and atmospheric temperature. Using small, medium, and large field-of-view collaborative observation modes, and through a point-surface fusion detection method and a data inversion algorithm, the highly accurate linear relationship between airglow radiation intensity and atmospheric temperature constructed by single-point detection is expanded and fused to an airglow radiation field with horizontal two-dimensional resolution, thereby obtaining a temperature field with the same horizontal two-dimensional resolution of detection accuracy.

The invention discloses a miniature automatic weather station and a temperature measurement optimization control method and system. The temperature measurement performance of the miniature weather station is improved through global comprehensive optimization in the aspects of a system structure, circuit layout and a data algorithm. The system structure is improved, the structural design of the double-layer vertical-wall hollow cylindrical radiation-proof cover retains the advantage of compact structure of the miniature automatic weather station, and meanwhile, a conventional horizontal natural ventilation radiation-proof cover in a louver blade overlapping form is changed into the double-layer vertical-wall hollow cylindrical radiation-proof cover; sampling airflow is changed from horizontal natural ventilation airflow to vertical active air exhaust sampling. According to real-time meteorological environment data, a sampling air pump is driven and controlled in a segmented mode to operate, the solar radiation intensity, the atmospheric wind speed and the atmospheric temperature are used as control variables to determine the operation speed and the sampling flow of the sampling air pump, and a working mode, a circulation control variable and a working time sequence are selected. And in the aspect of a data processing algorithm, a multi-source data fusion calibration method is adopted to improve the accuracy of temperature measurement data.

The invention discloses a temperature monitoring and control method in a large-volume concrete pouring process of a fan foundation, which belongs to the technical field of fan foundation construction and comprises the following steps: S10, arranging temperature measuring points in the foundation: arranging at least two temperature measuring points along the radial direction of the foundation; s20, test element installation: arranging a first test element for monitoring the atmospheric temperature on the outer side of the foundation; correspondingly installing a second test element at each temperature measurement point in the foundation; s30, constructing a temperature change model; and S40, inputting real-time monitoring data of each monitoring point in the pouring process into the temperature change model, wherein the temperature change model gives an implementation regulation and control scheme. According to the method, the temperature change of mass concrete in the pouring process can be monitored in real time, an accurate regulation and control scheme is given, real-time and accurate monitoring and regulation and control can be achieved, and the construction quality requirement of a wind power foundation is met.

The present invention discloses a temperature prediction system for measuring atmospheric physical structure. The system comprises a space-based module that periodically collects space-based atmospheric data from the airspace below and records the collection time; several ground-based modules that obtain several copies of ground-based atmospheric data from the airspace above; several image acquisition modules that obtain characteristic images of the airspace above; a processing module that, based on the collection time of the space-based atmospheric data, obtains the ground-based atmospheric data with the closest collection time from the corresponding copies of ground-based data; obtains cloud data and atmospheric analysis data based on the collection time of the space-based atmospheric data; obtains the corresponding atmospheric temperature profile based on the atmospheric analysis data; and several prediction modules that are used to obtain correction data; and obtains temperature data at several preset heights based on the correction data.

The disclosure relates to a control device. The control device includes an acquisition unit configured to acquire an infrared image including at least part of surroundings of the moving object, and an estimation unit configured to estimate an imaginary horizontal axis based on an atmospheric temperature distribution shown by the infrared image.

The invention relates to a forest steppe combustible moisture content detection method, and relates to the field of combustible moisture content detection.The forest steppe combustible moisture content detection method comprises the steps that a combustible sample to be detected is weighed and then put into a container, and the container is put into a high-low temperature test box; setting the temperature and humidity of a high-low temperature test box and the wind speed of an airflow generator; acquiring atmospheric humidity, atmospheric temperature and wind speed for recording weather elements; adding quantitative water into the container, and recording the volume of the added water and the hygrometer value of the combustible; dividing the collected data set into a training set, a verification set and a test set; calculating input parameters by using a neural network, and adjusting the input parameters to receive atmospheric temperature, humidity, wind speed and combustible humidity parameters as input; a training set is used for training a model, hyper-parameters of the model are adjusted through a verification set, an optimization algorithm is utilized, network weight is updated, an error between a predicted value and the actual moisture content is minimized, and the problem that the moisture content of the combustible is not accurately measured is solved.

1. The name of the design product: Raman and Mie scattering temperature and humidity aerosol lidar. 2. The use of the design product: for high spatial and temporal resolution vertical distribution measurement of atmospheric temperature, humidity and aerosol. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.

The present invention discloses a tropospheric atmospheric temperature and humidity profile inversion method based on a multi-objective genetic algorithm, and specifically relates to the technical field of computer systems based on a multi-objective genetic algorithm. The method specifically comprises the following steps: S1, first constructing an objective function, setting reasonable constraints such as temperature and humidity lapse rates, so that the errors between the calculated values ​​and the measured values ​​of the simulated brightness temperatures of the water vapor channel and the oxygen channel are minimized; in this embodiment, it is specifically explained that the objective function uses temperature and humidity data variables collected in the troposphere to represent the target form of the temperature and humidity profile; the temperature and humidity lapse rates are such that in the troposphere, the temperature and humidity decrease with increasing altitude; compared with the traditional tropospheric atmospheric temperature and humidity profile inversion method, the present invention adopts a multi-objective genetic NSGA2 algorithm, establishes an inversion model of the tropospheric atmospheric temperature and humidity profile through the NSGA2 algorithm, and improves the inversion accuracy of the tropospheric atmospheric temperature and humidity profile.

The invention discloses a stationary satellite surface emissivity collaborative inversion method based on background field reconstruction, and belongs to the technical field of satellite remote sensing information processing, and the method comprises the steps: constructing a background field of surface temperature and atmospheric temperature space structure collaborative constraint, employing a three-dimensional variational assimilation cost function to assimilate the actually measured surface temperature of a surface meteorological observation station, and calculating the surface emissivity of a stationary satellite. The obtained surface temperature analysis field is used as a surface temperature initial guess field for inverting surface emissivity by a one-bit variation inversion cost function; generating a ground surface emissivity background field by using the ground surface emissivity in the ground surface element historical data set, and constructing a ground surface item background error covariance matrix capable of representing a coupling relationship between the ground surface emissivity and the ground surface temperature based on the ground surface element historical data set so as to construct a one-dimensional variation inversion cost function; and the inversion of the surface emissivity can be realized by combining the satellite observation brightness temperature of the clear sky observation pixel observed by the infrared window area channel of the stationary orbit radiation imager, so that the inversion level of the surface emissivity is improved.

The present invention provides an all-weather assimilation method and device for a satellite microwave temperature and humidity sounder based on the inversion of cloud area temperature and humidity profiles. The method includes the following steps: obtaining satellite data, conventional observation data, and forecast field data; outputting the satellite data determined to be non-clear sky, and inversely obtaining the atmospheric temperature and humidity profiles based on the observed brightness temperature; converting the atmospheric temperature and humidity profiles into the prebufr format in the form of radiosonde data to obtain the non-clear sky area profile information in the prebufr format; performing bias correction on the satellite data determined to be clear sky to obtain the corrected microwave brightness temperature data for the clear sky area; performing quality control on the corrected microwave brightness temperature data for the clear sky area to eliminate the observation data with low quality; putting the non-clear sky area profile information converted into the prebufr format and the microwave brightness temperature data for the clear sky area into the WRFDA assimilation system for data assimilation, and outputting the assimilated analysis field. The present invention can improve the precipitation forecast effect of numerical models.

The invention discloses a hyperspectral target height inversion method and device based on a radiation transfer model, and belongs to the field of remote sensing data analysis. The method comprises the following steps: acquiring a corresponding relation between atmospheric height and atmospheric temperature in the weather based on atmospheric data, and establishing a relation equation between target surface temperature and atmospheric temperature to determine the corresponding relation between atmospheric height and target surface temperature in the weather; sequentially simulating and calculating target spectrum entrance pupil radiation brightness and target center brightness temperature so as to transmit and determine a target center spectrum brightness temperature curve corresponding to each atmospheric height under the weather; and after wave band selection is carried out based on channel correlation of the target center spectrum brightness temperature curve corresponding to each atmospheric height, spectral angles of the real single-star image brightness temperature curve and the target center spectrum brightness temperature curve under each atmospheric height are respectively calculated, so that the atmospheric height with the highest spectral similarity is determined as the target height obtained by inversion. Therefore, the height inversion of the single-satellite imaging aerial target is realized.

The invention discloses a shipborne marine atmospheric boundary layer refractive index profile detection system and method, and relates to the technical field of marine atmospheric environment monitoring and electromagnetic wave propagation safeguard.The method comprises the steps that sea-air downlink infrared radiation spectrum data and sea surface air temperature, relative humidity and air pressure data are obtained; constructing a background atmosphere profile by using the reanalysis data, and correcting an initial profile bottom layer by using sea surface observation air temperature, relative humidity and air pressure data to form a prior state vector; constructing an inversion cost function including an observation residual term, a background prior term and a sea surface boundary constraint term, and performing inversion to obtain an atmospheric temperature profile and a relative humidity profile; and calculating an atmospheric refractive index profile according to the temperature profile, the relative humidity profile and the air pressure profile. According to the method, the marine atmospheric refractive index profile can be continuously obtained under the shipborne dynamic observation condition, and reliable data support is provided for marine electromagnetic propagation environment analysis and waveguide diagnosis.

The application discloses an aerosol correction method and system suitable for a hyperspectral resolution laser radar, and relates to the technical field of laser radar detection. Specifically, the method comprises the following steps: a first auxiliary detection channel and a second auxiliary detection channel specially added and containing iodine molecular absorption cells are used to filter out aerosol Mie scattering components in specific frequency laser echoes; pure first atmospheric temperature data is obtained based on data inversion of the auxiliary detection channels; atmospheric aerosol backscattering ratios are calculated in combination with reference channel data; the backscattering ratios are used to correct wind speed and temperature inversion models of the laser radar, and then corrected atmospheric wind speed and temperature data are obtained. The application aims to expand the minimum detection height of a hyperspectral resolution Rayleigh temperature and wind measurement laser radar by accurately quantifying and eliminating aerosol interference, and to realize high-precision synchronous measurement of wind speed and temperature in low-altitude and aerosol-rich areas.

The present invention discloses a method for correcting the temperature of the middle and upper atmosphere of MIGHTI based on a BP neural network optimized by a genetic algorithm. The present invention optimizes the BP neural network inversion model through a genetic algorithm, establishes an optimal mapping relationship with the calibration atmospheric temperature, and optimizes the BP neural network inversion model through a genetic algorithm. Compared with the existing "peeling onion" algorithm for obtaining the temperature of the middle and upper atmosphere of MIGHTI, the use of the BP neural network inversion method solves the problems of large amount of calculation and long time required for inversion while ensuring temperature accuracy. The BP neural network of the present invention makes full use of the line of sight intensity value data related to temperature in the MIGHTI data set for feature learning, reduces the amount of calculation and shortens the time consumption while ensuring inversion accuracy, and has the characteristics of a simple and fast model and high inversion accuracy.

Diagnostic device for an internal combustion engine (1), wherein the internal combustion engine (1) comprises a blow-by gas passage (10) through which blow-by gas flows, and wherein the diagnostic device (100) comprises: a temperature sensor (20) that detects a temperature within the blow-by gas passage (10); an atmospheric temperature sensor (40) for detecting the atmospheric temperature; and an abnormality detection unit (30) comprising an atmospheric temperature map (M1) defining a relationship between the atmospheric temperature (TA) detected by the atmospheric temperature sensor (40) and a correction coefficient (KA), wherein the abnormality detection unit (30) detects an abnormality by comparing the detected value of the temperature sensor (20) with an abnormality threshold (TH) and corrects the abnormality threshold (TH) based on the atmospheric temperature (TA), and wherein the abnormality detection unit (30) repeatedly updates the corrected abnormality threshold value (TH) by multiplying a reference abnormality threshold value (TH0) by the correction coefficient (KA) corresponding to the atmospheric temperature (TA) defined by the atmospheric temperature map (M1) detected by the atmospheric temperature sensor (40).

The invention relates to a verification method and a verification device for earth atmospheric temperature distribution rule causes, the verification device comprises two sets of same container sets, and each container set comprises a container, a driver, a sensor and an observation window; the container comprises a shell wall, a piston and a sensor mounting hole; the shell wall is rigid; the piston is movably mounted in the shell wall and is sealed with the shell wall side; the sensor mounting hole is formed in the shell wall; the driver is connected with the piston and can drive the piston to move in the shell wall so as to change the volume of the container; the observation window is a transparent part on the shell wall; the sensor is provided with a sensitive part, a mounting part and a signal output part, and the sensitive part extends into the inner cavity of the container; the mounting part is fixed on the shell wall through the sensor mounting hole and is sealed with the shell wall; and the signal output part extends out of the shell wall and is used for detecting the information of the sensor in real time from the outside of the shell wall.

The application provides a kind of atmospheric temperature and humidity profile retrieval method and device based on satellite hyperspectral data, comprising: constructing background temperature and humidity profile using numerical mode historical forecast data, and calculating the background error between it and actual observation;Substitute the background profile into the radiation transfer model to simulate satellite radiation value, and obtain radiation simulation error according to satellite hyperspectral observation;Calculate the nonlinear distance correlation coefficient of each channel radiation simulation error and each pressure layer background temperature and humidity error, and use the first M channels with the highest correlation coefficient as the retrieval preselected channel of the layer;The background error and related data are divided into first and second data sets.Use the first data set, for each pressure layer, use the radial basis function neural network model of 1 to M channel number to establish the relationship between radiation error and background temperature and humidity error;Use the second data set to evaluate the retrieval error under each channel combination, select the optimal channel combination as the standard of minimum error, and thus obtain the final optimized neural network retrieval model.

A device for rapidly detecting atmospheric temperature and wind speed profiles comprises a laser, a VIPA etalon, an imaging lens and a CCD camera, the imaging lens is connected with the VIPA etalon and the CCD camera, one end, far away from the imaging lens, of the VIPA etalon is connected with a cylindrical lens, a receiving lens is arranged between the cylindrical lens and the laser, and the receiving lens is connected with the CCD camera. The laser outputs high-energy narrow-linewidth single-longitudinal-mode continuous laser beams to interact with gas, then Rayleigh-Brillouin scattering signals are generated at all positions of the laser beams, scattering light beams are collected through the receiving lens and compressed and focused in the direction perpendicular to the light beams through the cylindrical lens, the light beams enter the VIPA etalon for spectral analysis, and the spectral analysis result is obtained. Rayleigh-Brillouin scattering spectrums are converged to the CCD camera through the imaging lens to be collected. According to the device, temperature inversion is carried out on Rayleigh-Brillouin scattering spectrums of different detection distances through a theoretical model, so that atmospheric temperature profile detection is rapidly and accurately realized, and measurement of a wind speed profile is realized by calculating Doppler frequency shift of the Rayleigh-Brillouin scattering spectrums.