52 results about "Atmospheric sounding" patented technology

The embodiment of the invention provides a radar echo extrapolation prediction method and system based on a test time training strategy. According to the embodiment of the invention, the method comprises the steps: carrying out the time axis calibration and space grid alignment processing of a radar echo historical collection sequence collected by an atmosphere detection system, and generating radar echo sequence data with time-space consistency; constructing an echo evolution relevance representation model based on the data, and generating an echo evolution dependency graph and a multi-step extrapolation initial condition set; then introducing a test time training strategy to carry out adaptive prediction processing, and adjusting edge weight parameters in real time to obtain a radar echo multi-step extrapolation prediction sequence with time dynamic characteristics; and finally, according to the sequence, extracting an echo intensity change characteristic and a space movement track rule, and combining historical climate cycle evolution data to generate a climate evolution trend description set containing an echo intensity trend curve and a path offset vector so as to realize more accurate climate evolution prediction and weather forecast.

The embodiment of the invention provides a spaceborne radar and ground-based millimeter wave cloud radar reflectivity factor uniformity evaluation method, which is applied to the technical field of atmospheric detection. The method comprises the following steps: acquiring reflectivity factor data of a spaceborne radar and a ground-based millimeter wave cloud radar; establishing reflectivity factor space-time matching data of the spaceborne radar and the ground-based millimeter wave cloud radar according to the reflectivity factor data by taking vertical direction scanning as a reference; preprocessing the time-space matching data of the reflectivity factors; and based on a preset uniformity evaluation algorithm, an evaluation result is calculated according to the preprocessed reflectivity factor space-time matching data. In this way, errors between original data can be better revealed, and a good foundation is laid for product inversion in the next step.

The embodiment of the invention provides a multi-source wind profile data fusion method and device, equipment and a storage medium, and is applied to the technical field of atmospheric exploration. The method comprises the following steps: acquiring Beidou sounding ascending section data, Beidou sounding descending section data and wind profile radar data; based on a preset data space-time matching algorithm, the Beidou sounding ascending section data and the Beidou sounding descending section data are matched with the wind profile data, and a Beidou sounding ascending section and wind profile matching data set and a Beidou sounding descending section and wind profile matching data set are obtained; and based on a preset data evaluation algorithm and a preset data fusion algorithm, according to the same-address L-band sounding data and the ERA5 reanalysis data, respectively evaluating and fusing the Beidou sounding ascending section and wind profile matching data set and the Beidou sounding descending section and wind profile matching data set to obtain a continuous wind profile fusion product data set. In this way, the consistency of the wind speed and the wind direction can be improved, and then the accuracy of wind field data is improved.

The invention relates to a high-angular-resolution atmospheric detection laser radar acquisition and control system, and belongs to the technical field of atmospheric detection laser radar data acquisition. The system comprises an ARM main control module, an acquisition card and a scanning module, wherein the ARM main control module is internally provided with a multi-core CPU (Central Processing Unit), and when the system runs, a data reading process, a data processing process and a data storage process are respectively distributed to different cores of the multi-core CPU for parallel execution; the ARM main control module is used for issuing an instruction to the acquisition card and reading a hardware accumulation result of the acquisition card for processing and storing; the scanning module is controlled by the ARM main control module to perform continuous scanning; and the acquisition card is used for performing high-angle-resolution acquisition on aerosol observation data obtained in the continuous and rapid scanning process of the scanning module according to an instruction of the ARM main control module. According to the invention, the real-time monitoring capability of aerosol space-time distribution in a complex atmospheric environment is improved.

The invention relates to an atmospheric boundary layer height inversion method and system based on a laser radar, and belongs to the field of atmospheric detection, and the method comprises the steps: employing the laser radar to carry out the vertical detection of a to-be-detected region, obtaining an echo signal, and carrying out the preprocessing of the echo signal, and obtaining a preprocessed echo signal; obtaining an optimal scale parameter of wavelet covariance transformation by using a particle swarm optimization algorithm, and carrying out wavelet covariance transformation on the preprocessed echo signal based on the optimal scale parameter to obtain a wavelet covariance coefficient curve; the local maximum value position of the wavelet covariance coefficient curve is used as an ABLH candidate value; calculating feature data of the preprocessed echo signals, and clustering the preprocessed echo signals into an aerosol layer, a cloud layer and a common atmosphere based on the feature data and an optimal covariance coefficient corresponding to the optimal scale parameter; setting the maximum aerosol concentration change position in the aerosol layer as an ABLH threshold value; the ABLH candidate value closest to the ABLH threshold value is determined to be the atmospheric boundary layer height.

The invention belongs to the technical field of atmosphere detection remote sensing, and discloses an atmosphere multi-element integrated multi-wavelength coherent differential absorption laser radar system. Lambda on1 wavelength laser generated by the first frequency stabilization seed laser, lambda on2 wavelength laser generated by the second frequency stabilization seed laser and lambda off wavelength laser generated by the third frequency stabilization seed laser are transmitted to the switching module for time domain modulation to obtain an output signal, and the output signal is decomposed into local oscillation light and a main signal by the first coupler. A main signal is modulated by the pulse modulator, amplified by the amplification module and then transmitted to the optical transceiver module, backward scattered light scattered by the atmosphere is transmitted to the second coupler and is subjected to coherent coupling and equalization with local oscillation light, and coherent electric signals are transmitted to the data analysis module through the balance detector to be analyzed. The water vapor concentration, the wind speed and the atmospheric temperature in the propagation path are obtained. Through the coherent detection technology, the signal-to-noise ratio of signals is remarkably improved, and high-precision atmospheric humidity and wind field detection is achieved.

The embodiment of the invention provides a spaceborne laser radar wind field UV wind vector inversion method, device and equipment, and is applied to the technical field of atmospheric detection. The method comprises the following steps: acquiring optimal pairing data of a satellite horizontal sight wind speed, a data profile top height, a data profile bottom height, a site latitude and longitude, a satellite azimuth angle and a sounding wind speed and wind direction of a satellite-borne laser radar wind field, inputting the optimal pairing data into a constructed wind speed and wind direction inversion algorithm model, and outputting a UV wind vector. In this way, a satellite-borne laser Doppler radar wind field inversion model, namely a wind speed and wind direction inversion algorithm model, is established based on ERA5 analysis field data, Beidou sounding data, foundation wind profile radar data and satellite data by using a plurality of machine learning methods based on a satellite-borne laser Doppler radar wind field inversion technology of machine learning; the function of obtaining the UV wind vector, namely the weft wind component and the warp wind component, through horizontal sight line wind observation inversion is successfully achieved.

The invention relates to the technical field of satellite remote sensing, in particular to a geometric simulation and registration method for an infrared hyperspectral atmospheric detector, which comprises the following steps of: constructing a visual vector of a pixel in a reference ellipsoid coordinate system by acquiring detection time, ground longitude, ground latitude and satellite position of the pixel FOV of the HIRAS; simulating the imaging range of an HIRAS pixel on the ground based on the size of a pixel field angle by adopting a Rodrigues rotation formula, searching an MERSI pixel in the same platform by using a KD-tree, and respectively calculating the equivalent brightness temperature of the HIRAS pixel and the equivalent brightness temperature of an MERSI simulation image according to a spectrum convolution function and a blackbody radiation formula; and counting the root mean square error of the brightness temperature difference between the HIRAS pixel and the MERSI pixel through multi-row accumulation, and arranging the root mean square error according to an OR row time sequence to obtain the geometric positioning accuracy of the HIRAS in the along-rail and cross-rail directions. According to the invention, the rapid search of the pixel closest to the visual vector range is realized, and the accurate position determination of the registration error is realized.

The present disclosure relates to a system, method, and apparatus for mapping the fallout of atmospheric sounding devices such as radiosondes. This technology provides a mechanism for receiving launch data, plotting launch sites, and displaying trajectory heatmaps through a graphical user interface. The system includes features for overlaying concentric range circles, offering interactive timelines, and distinguishing between radiosonde altitudes using color indicators. Additional functionalities enable the display of detailed fallout data, calculation of Circle Error Probable (CEP) for estimating landing sites, and generation of fallout density heatmaps. These capabilities facilitate a comprehensive understanding and management of radiosonde deployment and environmental impact, enhancing the efficiency of meteorological data collection and analysis.

This application provides a hardware-software heterogeneous data processing system and method for atmospheric sounding lidar, relating to the technical field of embedded architecture for atmospheric remote sensing and scientific instruments. The system includes: a PL (Plug-in) terminal, which performs preliminary processing on lidar signal data to generate target data; a PS (Power Controller) terminal, including an internal cache and a processing core, with a virtual spatial filter configured within the processing core; the target data is stored in the internal cache via an ACP (Automatic Component Processing Filter); the processing core schedules the PL terminal to perform preliminary processing on the digital signal, reads the target data from the internal cache, and runs the virtual spatial filter to filter the target data; the virtual spatial filter performs register-level single-loop fusion of each independent algorithm node, completing the calculation of each independent algorithm within the single loop fusion, and all intermediate data resides in the register file. Relying on the ACP and single-loop fusion architecture, the bus occupancy rate and system latency of data flow are reduced, thereby achieving high throughput and zero bottlenecks at the system level.

The embodiment of the application provides a radar echo extrapolation prediction method and system based on a test time training strategy. The embodiment of the application first performs time axis calibration and spatial grid alignment processing on a radar echo historical collection sequence collected by an atmospheric detection system, to generate radar echo sequence data with time and space consistency; then constructs an echo evolution correlation representation model based on the data, to generate an echo evolution dependency graph and a multi-step extrapolation initial condition set; then introduces a test time training strategy for adaptive prediction processing, to adjust the edge weight parameter in real time, to obtain a radar echo multi-step extrapolation prediction sequence with time dynamic characteristics; finally extracts echo intensity variation characteristics and spatial movement trajectory rules according to the sequence, and generates a climate evolution trend description set containing an echo intensity trend curve and a path offset vector in combination with historical climate period evolution data, to realize more accurate climate evolution prediction and weather forecasting.

The invention relates to a 4DVAR wind field inversion lambda value prediction method based on a random forest, and belongs to the technical field of atmospheric exploration and data assimilation. Real-time accurate prediction of a lambda value in a 4DVAR wind field inversion process is realized through global candidate lambda setting, batch 4DVAR inversion, data processing and random forest model training, the 4DVAR wind field inversion efficiency and precision are improved, and the method is suitable for large-scale popularization and application. The method achieves the real-time precise prediction of the lambda value, greatly shortens the obtaining time of the lambda value, improves the efficiency and precision of 4DVAR wind field inversion, and meets the real-time demands of services.

The application relates to the technical field of atmospheric detection, and particularly provides a device and a method for measuring atmospheric transmittance, the device comprising a sensing and executing layer and a supporting layer, wherein the sensing and executing layer comprises a long-distance subsystem, a short-distance subsystem and a meteorological detection device; the distance between the long-distance subsystem and a measurement target is equal to a to-be-measured distance of the atmospheric transmittance; the distance between the long-distance subsystem and the measurement target is greater than the distance between the short-distance subsystem and the measurement target; the long-distance subsystem and the short-distance subsystem both comprise a multi-spectrum device; the multi-spectrum device of the long-distance subsystem collects a first multi-spectrum radiation image of the measurement target; at the same time, the multi-spectrum device of the short-distance subsystem collects a second multi-spectrum image of the measurement target; the atmospheric transmittance is calculated based on the radiation path difference of the first and second multi-spectrum radiation images; and the meteorological detection device is used for collecting meteorological data of a measurement environment, and the meteorological data is used for compensating for the environmental error of the atmospheric transmittance.

The embodiment of the invention provides a weather radar consistency evaluation method and device based on raindrop spectrum parameters, and is applied to the technical field of atmospheric detection. The method comprises the following steps: carrying out quality control processing on raindrop spectrometer data; performing radar reflectivity factor data space matching on the weather radar data and the quality-controlled raindrop spectrometer data based on a preset space matching rule to obtain a radar reflectivity factor value and scanning time of the weather radar corresponding to the raindrop spectrometer position; based on a preset time matching rule, according to the radar reflectivity factor value of the weather radar corresponding to the raindrop spectrometer position and the scanning time, carrying out radar reflectivity factor data time matching on the weather radar data and the raindrop spectrometer data after quality control to obtain matched raindrop spectrum parameters; and evaluating the matched raindrop spectrum parameters based on a preset evaluation rule. In conclusion, on the basis of ground raindrop spectrum parameters, verification and evaluation of weather radar reflectivity factor data can be carried out through space-time matching.

The invention provides an atmospheric waveguide measurement system, and mainly relates to the technical field of atmospheric detection. The atmospheric waveguide measurement system comprises an unmanned aerial vehicle-mounted device and a ground device, and the ground device is in communication connection with the unmanned aerial vehicle-mounted device; the unmanned aerial vehicle-mounted device comprises an unmanned aerial vehicle platform; one end of the measuring cable is fixedly connected with the unmanned aerial vehicle platform, and the swing angle of the measuring cable is smaller than a preset swing angle threshold value; the vertical sensor array comprises a plurality of meteorological sensing units which are arranged at intervals along the extension direction of the measuring cable and is used for synchronously acquiring meteorological data of a plurality of height layers; and the ground device is used for processing the meteorological data to obtain atmospheric waveguide parameters.

The invention relates to the technical field of multi-source meteorological observation in atmospheric exploration, and discloses an integrated learning method for automatically predicting thunder and lightning based on physical characteristics and a storage medium, and the method comprises the steps: determining multiple types of meteorological element input data for model training and corresponding thunder and lightning label data, and carrying out the time-space matching and data set division; training an integrated learning model through the input data of the various meteorological elements and the corresponding lightning label data, wherein the integrated learning model comprises a prediction module, a base learner module and a meta learner module which are connected in sequence; and inputting real-time multi-class meteorological element data of an area to be subjected to lightning prediction into the trained integrated learning model, and obtaining lightning prediction results in the future 1-6 hours. By means of the method, whether thunder and lightning exist within 1-6 hours or not can be automatically, efficiently and accurately predicted.

The application discloses a method for extracting middle layer top temperature multi-period characteristics and analyzing influencing factors, and belongs to the technical field of atmospheric detection and meteorological data analysis. The method first extracts time series data of the middle layer top temperature based on the 90km height and the lowest temperature point standard, then completes time domain trend and mutation analysis through seasonal departure and Mann-Kendall test, adopts discrete wavelet decomposition to obtain four main oscillation periods of 3 years, 7 years, 11 years and 22 years, then uses continuous wavelet to obtain the length of the fine-calibrated period, and finally performs cross wavelet analysis on the quasi-biennial oscillation, the El Nino effect and the solar activity index to obtain the final correlation and time lag results. The application realizes joint time-frequency domain analysis of discrete wavelet transform, continuous wavelet transform and cross wavelet transform, effectively improves the cycle recognition accuracy, quantifies the multi-scale correlation and time sequence hysteresis of each factor, and provides a new research idea for high-altitude atmospheric climate influencing factor analysis.

The invention provides a laser radar continuous scanning detection method based on user-defined path planning, and belongs to the field of atmospheric detection laser radars, and the method comprises the steps: receiving a path planning instruction inputted from the outside, and analyzing the path planning instruction into a discrete sequence composed of a plurality of path points; defining a path section between any two adjacent path points as a scanning interval, and marking an observation interval or a transition interval; for the scanning interval marked as the observation interval, the scanning mechanism is controlled to smoothly move at a preset observation angular speed at a constant speed and continuously collect echo data, and for the scanning interval marked as the transition interval, the scanning mechanism is controlled to operate at a maximum acceleration and a maximum angular speed allowed by the system; and after the motion of the last scanning interval is completed, automatically returning to the initial position and repeatedly executing the previous steps until an instruction of stopping or reconfiguring the path is received. According to the invention, the transient change of the atmospheric process can be captured more quickly, and the detection efficiency is improved.

The invention relates to a multi-aperture spaceborne atmospheric detection laser radar transmit-receive matching method. The method comprises the following steps: establishing a laser radar transmit-receive matching system; the laser emitting unit emits reference laser to enter the first receiving telescope unit; receiving and transmitting matching adjustment of the first receiving telescope unit is completed; the laser emitting unit emits main laser, and the N receiving telescope units perform imaging; imaging of the first receiving telescope unit is taken as a standard, and transmitting-receiving matching adjustment of the rest N-1 receiving telescope units is realized through the comprehensive control processing unit; the laser emitting unit emits main laser to realize integral imaging; the equivalent receiving area of a large-aperture telescope can be realized by splicing a plurality of small-aperture telescopes, the volume and the weight of the receiving telescope can be compressed by utilizing the characteristic of short focal length of the small-aperture telescope, and meanwhile, the small-aperture telescope has the advantages of low processing cost, short period, good stability and the like.

The present invention relates to the field of atmospheric detection technology, and discloses a boundary layer height inversion method based on a LEOSPHERE 100S laser radar. The method comprises: in DBS mode, using a laser radar and completing a directional scan every 4 seconds according to a set azimuth and elevation angle, and obtaining the radial wind speed corresponding to the azimuth angle; collecting laser radar observation data for 24 hours a day, calculating the signal-to-noise ratio of each laser radar observation data, and retaining only radial wind speeds with a signal-to-noise ratio CNR ≥ 22dB; collecting data within every 50-meter range in the vertical scan, constructing a vertical wind speed time series, and calculating the second-order partial derivative of the vertical wind speed for 30 minutes; determining the second-order partial derivative threshold and determining the daytime boundary layer height by using a potential temperature profile method of a tethered sounding; determining the nighttime boundary layer height by the maximum value of the horizontal wind speed shear in the vertical direction; and fusing the daytime boundary layer height and the nighttime boundary layer height to obtain a comprehensive all-day boundary layer height. The present invention can more accurately determine the boundary layer height throughout the day.

The invention belongs to the technical field of flight control atmosphere detection systems, and discloses a mechanical structure of an extension type atmosphere product, which comprises a sensor, a lifting disc, a screw rod, a gear set, a cabin door, a bearing, a limiting mechanism, a motor, a gear rack and a compression spring, the sensor is used as atmospheric equipment; the sensor is installed on the lifting disc, a ball on the lifting disc is matched with a guide rail of the screw rod, the bottom of the screw rod is connected with the gear set, the gear set is connected with the cabin door, bearings are installed on the upper portion and the lower portion of the screw rod, a telescopic spring bolt of the limiting mechanism is combined with a small hole in the lifting disc, the motor is installed on the lifting disc, and a gear in a gear rack is installed on the motor.

An image capture apparatus comprises a focal plane array and a filter device. The focal plane array comprises a plurality of detectors and the filter device is coupled with and covering the focal plane array. The filter device comprises at least one set of spectral filters, comprising at least a first spectral filter, which comprising a first wavelength range, and a second spectral filter, which comprises a second wavelength range that is different from the first wavelength range. The filter device also comprises a plurality of polarization channels, each having a polarization value that is different than the polarization value of any other of the plurality of polarization channels. The filter device further comprises a plurality of sounding filters, each operable within a spectral wavelength range and each configured to determine a characterization of atmospheric conditions.

The present application belongs to the technical field of atmospheric detection and prediction, and particularly relates to a credibility quantification method, system and device based on vertical atmospheric prediction. The method dynamically constructs a vertical correlation graph based on the vertical correlation between a single detection height and the target height for any number of target heights, and then learns the vertical correlation between the detection height and each target height in parallel through a vertical graph attention network to output meteorological variable prediction results. The uncertainty of each target height prediction result is quantified based on the vertical correlation strength and decomposed into two types of uncertainty, namely inherent and cognitive uncertainty. Finally, a unified credibility index is output. The training and verification process is combined to ensure the applicability of the method. The present method can be flexibly adapted to different target height number scenarios, aiming to achieve accurate prediction from a single detection height to any number of target heights, and to provide quantitative credibility evaluation for the prediction results, thereby providing a reliable basis for decision-making in the field of atmospheric science.

The invention provides a raindrop size distribution inversion method and system based on a micro-rain radar, and relates to the technical field of atmospheric exploration, and the method comprises the steps: collecting a backscattering signal of a raindrop through the micro-rain radar; wherein the back scattering signal comprises a distance library identifier, a raindrop diameter, a radar wavelength and a reflectivity spectrum; determining a height correction factor of the raindrop based on the distance library identifier; based on the height correction factor and the raindrop diameter, determining the falling speed of the raindrop; determining a velocity reflectance density spectrum relative to the falling velocity based on the falling velocity and the reflectance spectrum; determining a backscattering cross section of the raindrop based on the raindrop diameter and the radar wavelength; and determining raindrop size distribution based on the velocity reflectivity density spectrum, the falling velocity, the raindrop diameter and the backscattering cross section. According to the method, various factors influencing raindrop size distribution inversion can be fully considered, errors caused by inaccurate parameters, incomplete factor consideration and the like are effectively reduced, and the inversion result is more accurate and reliable.

The present application relates to GNSS radio occultation atmospheric sounding technical field, especially in kind based on big dipper satellite signal carries out GPS occultation observation method and system.The present application method includes: through the signal received by GNASS occultation receiver is captured and tracked positioning receiver, obtains GNSS occultation receiver in big dipper satellite system space-time coordinate under the time and position information, after big dipper positioning result is converted into GPS positioning result, and according to GPS positioning result, the position of GPS satellite is solved, GPS occultation prediction and occultation capture tracking are realized based on GPS satellite position, and GPS occultation observation is completed.The system of one kind for carrying out GPS occultation observation of the present application based on big dipper satellite signal includes three parts of radio frequency front end, FPGA end and ARM end.The present application need not be separately assigned positioning channel resource for GPS system, saves system resource, saves operation time.

The invention, which belongs to the technical field of atmospheric environment remote sensing monitoring, provides an embedded miniature atmospheric detection laser radar control platform comprising an ARM master control core board, an FPGA acquisition card and a bottom board. The ARM main control core board is in communication connection with the FPGA acquisition card through an FSPI bus, and the ARM main control core board is in detachable stacking connection with the bottom board through an industrial-grade board-to-board connector; the bottom plate is provided with a laser control interface, a scanning mechanism control interface and a network communication interface which are respectively used for connecting a laser emitting unit, a scanning mechanism and external communication equipment; an embedded operating system, laser radar control and inversion algorithm software, a data storage module and a network communication function module are integrated in the ARM master control core board. According to the invention, the laser radar system can meet the requirements of unmanned aerial vehicle load, field observation and other application scenes with strict limitation on weight and space.

The present invention provides a method for estimating the precipitable water in cloud and sky atmosphere based on meteorological satellites, belonging to the technical field of meteorological satellite detection. Cloud detection is carried out using the relative humidity threshold method based on the atmospheric sounding profile, and the radiative simulation calculations of the near-infrared and thermal-infrared water vapor channels of meteorological satellites in the case of cloud and sky are carried out using the atmospheric radiative transfer model MODTRAN. The near-infrared and thermal-infrared water vapor channels can detect the precipitable water in the atmosphere above the cloud, and the numerical prediction model can provide the temperature, humidity profile distribution of the whole atmosphere and the total precipitable water in the atmosphere. It is assumed that the form of the atmospheric profile in the numerical prediction is correct, but bias correction is required. Taking the radiation of the near-infrared and thermal-infrared water vapor channels and the temperature and humidity profiles predicted by the model as inputs, a convolutional neural network is used to construct an estimation model for the precipitable water in cloud and sky atmosphere. The present invention uses multi-band observations and numerical prediction model information, takes into account the atmospheric radiative transfer process, and obtains a relatively high accuracy of the precipitable water in cloud and sky atmosphere.

The invention provides an atmospheric detection laser radar observation method based on an unmanned aerial vehicle, and relates to the technical field of laser radar atmospheric detection, and the method comprises the steps: constructing a detection subsystem independent of an unmanned aerial vehicle flight control system; the unmanned aerial vehicle carrier and the detection subsystem are started, and current spatial position information and attitude information are calculated and output in real time; planning a flight route covering the target area; the unmanned aerial vehicle carrier is controlled to fly along the planned flight route, and the atmospheric detection laser radar executes continuous collection operation; the atmospheric detection laser radar reads the spatial position information and attitude information at the current moment output by the high-precision positioning and orientation module in real time through the electrical communication interface; and combining the read spatial position information and attitude information with the original echo data by the atmospheric detection laser radar to form observation data with geographic space-time labels, and storing the observation data until flight tasks of all air routes are completed. According to the invention, the fine observation requirement of pollutant traceability in a complex scene is met.

The present invention discloses a tropospheric atmospheric ozone detection system, which relates to the technical field of atmospheric detection. A partition support plate is installed at the top of a fixed dark box. One side of the top of the partition support plate is connected through a transparent limiting hopper. Symmetrically installed at the inner bottom end of the transparent limiting hopper are filter light positioning sleeves. A number of visible light filters are equidistantly embedded in the inner sides of the filter light positioning sleeves. A number of in-out electric push rods are equidistantly clamped at one end of the transparent limiting hopper. The present invention effectively solves the problems in the prior art that millimeter wave devices are affected by the migration of tropospheric atmospheric ozone, resulting in data deviation in the feedback of the millimeter waves emitted during detection. At the same time, it solves the problem that the overall size of the device is too large and it cannot be quickly carried and moved, resulting in a fixed detection position. When detecting tropospheric atmospheric ozone, the detection efficiency can be effectively improved, and detection feedback can be carried out in real time, improving the detection range and detection effect.

The invention belongs to the technical field of atmospheric detection and prediction, and particularly relates to a credibility quantification method, system and equipment based on vertical atmospheric prediction, and the method comprises the steps: for any number of target heights, based on a vertical association relationship between a single detection height and the target height, dynamically constructing a vertical association graph, vertical correlation between the detection height and each target height is learned in parallel through a vertical graph attention network to output meteorological variable prediction results, the uncertainty of each target height prediction result is quantified based on vertical correlation strength and decomposed into inherent and cognitive uncertainty, and finally a unified credibility index is output. And meanwhile, the applicability of the method is guaranteed by combining training and verification links. The method can flexibly adapt to scenes of different target height numbers, aims to realize accurate prediction from a single detection height to any number of target heights, provides quantitative credibility evaluation for a prediction result, and further provides a reliable basis for decision making in the atmosphere related field.