91 results about "Microwave radiometer" patented technology

The invention provides an intelligent quality control and inversion method for electric power meteorological multi-source data, and relates to the field of data processing. In the method, a multi-view polarized brightness temperature vector structure is constructed by using original brightness temperature observation data acquired by a plurality of satellite-borne microwave radiometers in a near-synchronous orbit intersection area, and a multi-dimensional radiation transmission equation set driven by an earth ellipsoid path integral model is input to generate a brightness temperature prediction result; an inversion optimization model is constructed based on view angle invariant residual constraint, initialization is carried out based on historical data and ground data, and variational inversion solving is carried out to obtain a joint inversion result; and evaluating the credibility through a profile quality vector, and finally supporting stability early warning and load correction in electric power meteorology. By implementing the technical scheme provided by the invention, the quality control and inversion precision of the power meteorological multi-source data profile can be improved.

The invention relates to a satellite-borne microwave radiometer cold air calibration attitude planning method based on multi-objective optimization, and belongs to the field of satellite microwave remote sensing, and the method comprises the steps: building a satellite attitude kinematics model and an attitude dynamics model through a geocentric equator inertial coordinate system, an orbital coordinate system and a satellite body coordinate system; establishing a brightness temperature sum model received by the microwave radiometer in the cold air calibration process; according to the method, a microwave radiometer receiving brightness temperature sum, brightness temperature fluctuation, platform maneuvering capability, energy and a satellite sensor field of view are comprehensively considered, a multi-target optimization model of microwave radiometer cold air calibration consideration constraints is established, solving is performed, constraint conditions are established, and a solution or a solution set is obtained. According to the method, the brightness temperature sum and the brightness temperature fluctuation in the observation area of the microwave radiometer in the cold air calibration process are optimized by adopting multi-objective optimization, and the on-orbit cold air calibration effect and the system reliability of the satellite-borne microwave radiometer are improved.

The invention discloses a space-time matching comparison and uniformity evaluation method for a three-dimensional atmosphere live field fusion product. The method comprises the steps of constructing a multi-source data verification framework, implementing refined space-time matching, executing multi-level quality control, comprehensively inspecting and analyzing and outputting a product specification. By constructing a multi-source collaborative verification framework, integrating sounding, microwave radiometer, satellite and foundation observation data, and establishing a refined space-time matching model and a multi-level quality control system, the error condition of a live product can be quantitatively given. The method is suitable for space-time matching comparison and homogeneity inspection of air temperature, humidity and horizontal wind speed / wind direction elements, and supports meteorological model optimization and low-altitude economic application.

The invention discloses a differential measurement-based satellite-borne synthetic aperture microwave radiometer imaging correction method, which comprises the following steps of: respectively selecting a reference area and a correction area in a global range, and respectively intercepting scientific data and auxiliary data in a specific time period in the reference area and the correction area based on load normal earth observation data; averaging the visibility functions intercepted in the reference area to obtain a reference visibility function; generating a reference brightness temperature and a correction brightness temperature through a simulation model by using the auxiliary data intercepted in the reference area and the correction area respectively; performing difference and inversion processing on the normal earth observation visibility function to be subjected to imaging processing by using the reference visibility function to obtain a difference inversion brightness temperature; calculating a correction coefficient by using the reference visibility function, the reference brightness temperature, the visibility function intercepted in the correction area and the correction brightness temperature; and correcting and compensating the differential inversion brightness temperature by using the correction coefficient and the reference brightness temperature to obtain the final inversion brightness temperature.

The invention relates to a system deviation correction method for improving the salinity inversion precision of an interference type microwave radiometer, and relates to the technical field of satellite ocean remote sensing data processing. The method comprises the following steps of: acquiring an area, strictly purifying and screening observed brightness temperature data of a preset time window in the area to eliminate the influence of radio frequency interference, sun and moon pollution and the like, acquiring high-purity original data, calculating simulated brightness temperature by utilizing a radiation transmission model, and subtracting the simulated brightness temperature from the purified observed brightness temperature to obtain a brightness temperature deviation sample; and then a robust statistical method based on a sliding window and a median is adopted to carry out statistical calculation on the deviation sample to obtain a stable and reliable deviation correction value, and finally a two-dimensional lookup table is generated and applied to sea surface salinity inversion. According to the method, the observation brightness temperature for salinity inversion can be efficiently and accurately corrected from the source, and the contradiction between stability and adaptability in the prior art is solved.

The invention belongs to the technical field of atmospheric microwave remote sensing and monitoring, and relates to a rapid temperature and humidity profile inversion method for a multi-frequency atmospheric microwave radiometer. Acquiring a brightness temperature data set of the multi-frequency atmospheric microwave radiometer, performing space-time matching on the brightness temperature data set and corresponding ERA5 reanalysis or sounding balloon temperature and humidity profile data, constructing a matched data set, and dividing the matched data set into a test set, a training set and a verification set; establishing an atmosphere temperature and humidity profile inversion model based on a CNN-LSTM combined neural network; and training the model by using the training set, guiding the model optimization process by using the verification set, finally inputting multi-frequency brightness temperature data measured by the multi-frequency microwave radiometer into the trained model, and carrying out inversion to obtain an atmosphere temperature and humidity profile. According to observation data of the multi-frequency atmosphere microwave radiometer, regional atmosphere temperature and humidity profile data are rapidly and accurately obtained, and efficient inversion of the temperature and humidity profile is achieved; the vertical detection advantage of the multi-frequency microwave radiometer is exerted, the inversion efficiency is improved, and the method has a wide application prospect.

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.

The invention discloses a microwave radiometer stripe elimination preprocessing method based on moving median smoothing, and the method comprises the following steps: 1, carrying out the circular scanning through a microwave radiometer, and obtaining a heat source count value Cw, a cold source count value Cc, an observation target count value Ce, a heat source brightness temperature Tw, and a cold source brightness temperature Tc; step 2, performing noise smoothing on moving medians between scanning lines on the heat source observation count value Cw and the cold source count value Cc to obtain a smoothed heat source observation count value and a smoothed cold source count value; and step 3, performing two-point calibration by using the heat source brightness temperature Tw and the cold source brightness temperature Tc obtained in the step 1 and the smoothed heat source observation count value and the smoothed cold source count value obtained in the step 2 to obtain the stripe-eliminated observation target brightness temperature Te. The method provided by the invention can effectively solve the problem of influence of stripe noise on the data quality of the microwave radiometer in the existing stripe elimination method.

This application provides a method, device, and computer-readable storage medium for evaluating the on-orbit calibration error of a microwave radiometer calibration system used in geostationary orbit. The application evaluates the on-orbit calibration error of the microwave radiometer calibration system by determining the errors of the calibration cold source, calibration heat source, Earth observation radiation brightness temperature, and Earth target brightness temperature. By separately evaluating the errors of the calibration cold source, calibration heat source, Earth observation radiation brightness temperature, and Earth target brightness temperature in the microwave radiometer calibration system used in geostationary orbit, each error is quantified, thus quantifying the on-orbit calibration error of the microwave radiometer calibration system. Furthermore, the different radiation transmission paths are considered during the evaluation of each error, making the evaluation of the sources of on-orbit calibration error of the microwave radiometer calibration system used in geostationary orbit not only effective and accurate but also highly implementable.

The application relates to a reconfigurable metasurface for electrically-controlled scanning of a real-aperture microwave radiometer, which comprises a plurality of array-distributed basic units, the basic unit comprising a top metal patch, a first dielectric layer, a metal reflection layer, a second dielectric layer and a bottom metal layer which are sequentially stacked from top to bottom; the top metal patch comprises two cross-connected I-shaped patches and a triangular metal branch located in the cross region and having a certain gap with the I-shaped patch; the I-shaped patch comprises a straight arm and end arms located at both ends of the straight arm and having a certain gap with the straight arm; a PIN diode is connected between the straight arm and the end arms; the end arms are connected with each other through a metal feed line, and an isolation resistor is arranged on the metal feed line; the application dynamically controls the reflection phase according to the working state of the diode combination, and has high reflectivity and reflection bandwidth and small loss.

The utility model provides a multichannel millimeter wave radiometer signal intensifier. Relates to the technical field of microwave radiometers. The multi-channel millimeter wave radiometer comprises a mounting plate, a multi-channel millimeter wave radiometer and a fixing mechanism, a multi-channel millimeter wave radiometer and a signal intensifier are fixedly installed on the installation plate, a plurality of jacks are formed in one side of the multi-channel millimeter wave radiometer, second connecting terminals are arranged in the jacks, a wire is connected to the signal intensifier, and one end of the wire is connected with a first connecting terminal. The multichannel millimeter wave radiometer signal enhancer provided by the utility model has the following advantages: through cooperation of the components, the multichannel millimeter wave radiometer and the signal enhancer can be rapidly assembled and disassembled; in addition, the effect of avoiding poor connection between the first connecting terminal and the second connecting terminal can be achieved, and the effect of protecting the jacks can be achieved while the first connecting terminal is pulled out.

[PROBLEM] Provided are a weather observation device, a weather observation system, an estimation method, and a computer program. [SOLUTION] A weather observation device comprises: an acquisition unit for acquiring observation data based on received radio waves of a microwave radiometer and an environmental temperature of an environment in which the microwave radiometer is installed; a conversion unit for converting the observation data into first luminance temperature data having luminance temperature as a physical dimension; an estimation unit for estimating second luminance temperature data which serves as a base when calculating the luminance temperature data in the sky above the microwave radiometer from the environmental temperature; and a calculation unit for calculating the luminance temperature data in the sky above the microwave radiometer from the first luminance temperature data and the second luminance temperature data.

The invention discloses an in-orbit calibration method for correcting self-radiation of a heat mirror of a microwave imager based on reference radiation. The method comprises the following steps: calculating an included angle between the heat mirror of the microwave imager and the sun; calculating the earth observation brightness temperature of the microwave imager; calculating the observed brightness temperature of the reference microwave radiometer; simulation brightness temperature of the reference microwave radiometer and the microwave imager is obtained based on radiation transmission model simulation; calculating an observation brightness temperature deviation and a simulation brightness temperature deviation, and calculating a system error between the reference microwave radiometer and the microwave imager; based on the system error, the included angle between the microwave imager heat mirror and the sun is adopted for function relation fitting, and the heat mirror self-radiation brightness temperature of the reference microwave radiometer is calculated; the included angle between the microwave imager heat mirror and the sun is calculated on orbit in real time, and the earth observation brightness temperature of the microwave imager is corrected based on the self-radiation brightness temperature of the heat mirror. The self-radiation of the heat mirror is solved in real time by taking double deviations of observation brightness temperature and simulation brightness temperature as constraints, and the problem that the temperature of the heat mirror of the microwave imager cannot be actually measured in orbit is solved.

The invention discloses a method for inverting warm cloud microphysical parameters based on a ground-based millimeter wave cloud radar and a microwave radiometer, and the method comprises the steps: 1, obtaining the observation data of the millimeter wave cloud radar, and obtaining a whole-layer liquid water path and a temperature gallery line through the microwave radiometer; 2, identifying warm cloud in millimeter wave cloud radar observation by using a temperature gallery line T; 3, constructing an initial liquid water content profile based on the reflectivity factor and the particle concentration in the warm cloud layer, and calculating an initial liquid water path of the warm cloud layer; 4, the whole-layer liquid water path obtained by the microwave radiometer is used as whole-layer constraint, the initial particle concentration and the initial liquid water content at the vertical height in the warm cloud layer are calibrated according to the proportion, the adjusted warm cloud layer liquid water content and the adjusted warm cloud layer inner particle concentration are obtained, and a physical boundary constraint interval is applied to the particle concentration; and 5, calculating the effective radius of the particles in the warm cloud layer according to the adjusted liquid water content of the warm cloud layer and the particle concentration in the warm cloud layer. According to the method, high-precision warm cloud microphysical parameter vertical distribution can be obtained.

The present application relates to a kind of sea ice surface snow depth combined estimation method, based on the characteristics that microwave radiometer brightness temperature decreases with the increase of sea ice surface snow depth, FY brightness temperature data is used to calculate the brightness temperature of open water at different frequencies, then the brightness temperature of sea ice surface of 10 sub-channels and 20 polarization gradient rate characteristics are calculated using open water brightness temperature and FY brightness temperature data.The OIB airborne data is gridded, and the daily average OIB snow depth of 12.5 km resolution is obtained.The correlation between 30 brightness temperature characteristics and OIB snow depth is calculated, and the linear regression model and machine learning model of one-year ice and multi-year ice surface snow depth estimation are established by selecting 5 sub-features with high correlation, thereby developing the combined estimation model of snow depth.The above is the sea ice surface snow depth combined estimation method proposed by the present application, which improves the estimation accuracy of polar sea ice surface snow depth.

The application discloses a kind of methods and systems for calculating the rotation angle of spaceborne L-band microwave radiometer, method includes: obtaining the satellite orbit parameters and the brightness temperature data of ocean time of spaceborne L-band microwave radiometer;Simulate horizontal polarization, vertical polarization and cross-polarization radiation brightness temperature data;The stokes radiation brightness temperature data obtained by simulation is converted into the brightness temperature data under antenna coordinate system using rotation matrix;Using joint cost function, the above-mentioned simulation and conversion are carried out using nonlinear iteration until the rotation angle change is less than the first set threshold and the sea surface salinity change is less than the second set threshold, solve the rotation angle and sea surface salinity;According to the rotation angle, recalculate the rotation matrix;According to the new rotation matrix, the obtained brightness temperature data is converted into corresponding horizontal polarization TH, vertical polarization TV, cross-polarization T3 and T4, complete the accurate conversion of spaceborne L-band microwave radiometer brightness temperature.

The application discloses a method for tracking and monitoring satellites by using a ground-based microwave radiometer, wherein the equivalent radiation power, orbit and orbit parameters of the satellites can be calculated by using the ground-based microwave radiometer to remotely sense the electromagnetic wave radiation intensity and direction of the satellites, and the tracking and monitoring of the satellite orbit and the electromagnetic wave power information can be realized without other professional and complex testing instruments and equipment, so that the method has the advantages of low requirement on the observation environment, easy realization, automatic tracking and observation, etc.

The invention relates to the field of sea ice remote sensing, and discloses a sea ice thickness measuring method based on solar microwave radiation enhancement, which comprises the following specific steps of: calculating a solar altitude angle and an azimuth angle at a current position and moment; setting a microwave radiometer overlook sea ice area based on the solar altitude angle and the azimuth angle, and receiving a reflection signal of solar microwave heat radiation; extracting the relative propagation delay inequality of the reflected signal; and calculating the thickness of the sea ice according to the relative propagation delay inequality. The ice thickness is measured by using the characteristics of strong solar microwave radiation and related reception, the problem that the sun is regarded as a harmful factor in the existing remote sensing technology is solved, and the method has the characteristic of being capable of reducing data acquisition and processing pressure.

The present application belongs to the technical field of marine remote sensing, and particularly relates to a kind of full wind speed inversion methods based on spaceborne microwave active and passive combination physical statistics network, comprising the following steps: obtaining the brightness temperature data and backscattering coefficient of microwave radiometer and scatterometer, and performing data quality control;Construct sample data set;Load physical statistics constraint deep learning inversion algorithm model for training;Physical statistics constraint deep learning inversion algorithm model includes: input layer, network layer, physical layer, output layer;Network layer is composed of residual neural network, and physical layer is composed of Log formula of microwave radiometer and Log formula of microwave scatterometer to form microwave statistical matrix P matrix, which is a nonlinear matrix, and provides physical statistics constraint for the whole model;Output the wind speed of current full sea area.The present application effectively solves the problem of lack of physical support in the process of deep learning in marine parameter inversion, and provides high-quality and reliable wind speed products suitable for full wind speed range.

This invention discloses a microwave-laser composite detection method and system based on spatiotemporal matching of heterogeneous data, specifically relating to the field of microwave and laser atmospheric remote sensing radar data fusion technology. It addresses the problem of insufficient physical consistency in data fusion caused by existing composite detection methods neglecting the intrinsic differences in the observation processes of the two devices. First, observation data from both devices are acquired, and their corresponding spatiotemporal representation ranges are determined. Then, the overlapping region of the spatiotemporal representation ranges is calculated, and the potential interference of the laser radar scanning process on the microwave radiometer observations is analyzed within this region to obtain interference assessment results. Next, the data fusion reliability is evaluated by combining the spatiotemporal coverage relationship and the interference assessment results. Finally, based on this reliability, strategies such as joint inversion, weighted averaging, or independent output are adaptively selected to fuse the two types of observation data, thereby achieving physically consistent and reliable composite detection.

A passive remote sensing and reconnaissance integrated detection method based on a conical scanning system belongs to the technical field of space microwave remote sensing, and comprises the following steps: carrying out AD acquisition on an intermediate frequency signal output by a multi-band radiometer receiver; carrying out FFT (Fast Fourier Transform) change on the data acquired by the AD to divide the data into a plurality of channels, and carrying out RFI (Radio Frequency Identification) detection on each channel; if the RFI exists in the channel, IFFT and SFFT are sequentially carried out on a channel result with the RFI to obtain channel time-frequency information, parameterized measurement is carried out on the channel time-frequency information to obtain target pulse description word information, and then the target pulse description word information and channel data without RFI detection are packaged and output together. According to the invention, joint detection of satellite-borne microwave radiation detection and electronic reconnaissance is realized, the signal-to-noise ratio of satellite-borne electronic reconnaissance detection is improved, the detection capability is improved, the influence of RFI on the satellite-borne microwave radiometer is reduced, and the high-precision detection capability of a radiometer system is ensured.

This invention discloses a method for enhancing the brightness temperature resolution of a microwave radiometer, along with related devices, equipment, and storage media. It relates to the field of spaceborne microwave radiometer technology and aims to solve the problems of insufficient brightness temperature resolution, sidelobe-induced reconstruction distortion, and the difficulty in balancing resolution and stability in spaceborne real-aperture microwave radiometers. The method includes: acquiring relevant data; constructing a convex optimization model with sidelobe suppression constraints and solving for initial weights; iterating with the initial weights, adaptively updating until a termination condition is met, and outputting the optimal weights; using the optimal weights to reconstruct the original brightness temperature data, outputting a result with enhanced resolution and no obvious oscillation artifacts. This invention requires no hardware modification, balances sidelobe suppression and resolution through algorithmic optimization, takes into account both accuracy and stability, adapts to the real-time requirements of spaceborne systems, provides support for meteorological and oceanographic monitoring, and discloses corresponding devices, equipment, and storage media.

Provided is a precipitable water amount estimation system and method, a learning system and method, and a storage medium, which can observe water vapor in a local range without using liquid nitrogen for calibration. A learning system (4) of a precipitable water amount estimation model according to the present application includes: a radio wave intensity acquisition unit (40) that acquires radio wave intensities of a plurality of frequencies in radio waves received by a microwave radiometer (3); a precipitable water amount acquisition unit (41) that acquires a precipitable water amount calculated based on an atmospheric delay of a GNSS signal received by a GNSS receiver (2); and a learning unit (43) that causes a learning model (43a) to perform machine learning in a manner in which input data based on the radio wave intensities of the plurality of frequencies is input and the precipitable water amount is output, based on the radio wave intensities of the plurality of frequencies and the precipitable water amount at a plurality of time points in a prescribed period.

This application provides a method and system for correcting the brightness temperature of a spaceborne one-dimensional integrated aperture microwave radiometer. The method includes: acquiring two-dimensional observed brightness temperature data O along the vertical satellite orbit and along the satellite orbit for different ascent and descent orbits of the microwave radiometer; acquiring external data such as atmospheric profiles, surface data, and sea surface salinity along the radiation transmission path to obtain simulated Earth radiation brightness temperature data B, and removing outlier data; subtracting the observed brightness temperature data from the simulated brightness temperature data to obtain O-B data for multiple single orbits, and removing outlier data; taking the median of the O-B data to obtain the average difference in O-B brightness temperature and the two-dimensional corrected brightness temperature; dividing the average difference in O-B brightness temperature by the observed brightness temperatures in the corresponding two vertical directions to obtain two-dimensional relative brightness temperature correction coefficients based on different ascent and descent orbits; and correcting the observed brightness temperature using the two-dimensional relative brightness temperature correction coefficients or the two-dimensional corrected brightness temperature. The advantage of this application is that the established two-dimensional correction coefficients have a better correction effect.

The application provides a spaceborne discrete multi-beam radar precipitation data reconstruction method, product and equipment. The method comprises the following steps: obtaining a measured reflectivity factor through a spaceborne discrete multi-beam radar; obtaining brightness temperature data of different channels through a spaceborne microwave radiometer; inputting the reflectivity factor and the brightness temperature data into a pre-trained precipitation data reconstruction model to obtain a complete reflectivity factor profile, and the precipitation data reconstruction model is used for fusing the precipitation characteristics of the brightness temperature data on the basis of the reflectivity factor, reconstructing the precipitation data of the discrete beams and outputting the complete reflectivity factor profile, so as to complete the discrete beam observation. Through the method, the spatial vacancy of the discrete multi-beam observation can be effectively filled without increasing the hardware cost, the observation width of the precipitation profile is significantly improved, the physical continuity and the reconstruction precision of the precipitation structure are ensured, and reliable algorithm support is provided for a spaceborne low-cost high-temporal-and-spatial-resolution precipitation observation system.

The invention discloses an active lightning protection fan blade based on lightning monitoring. The active lightning protection fan blade comprises a lightning early warning subsystem, an active protection subsystem and an energy discharge subsystem. The thunder and lightning early warning subsystem realizes multi-modal data acquisition and fusion analysis through a three-dimensional omnidirectional electric field instrument, a multi-station positioning lightning monitoring network, an atmospheric potential gradient sensor array and a microwave radiometer, and carries out early recognition and early warning on thunder and lightning leader; and the active protection subsystem forms an active lightning guide area at the tip end of the blade through a telescopic plasma lightning arrester based on early warning information, and optimizes lightning current guide in combination with a modified blade surface with a gradient impedance coating and an embedded conductive grid. The energy discharge subsystem realizes high-efficiency and low-damage discharge of lightning current through a sectional multi-channel down lead, a magnetohydrodynamic discharge device and a grounding grid chemical resistance reduction module; the problems of lightning receiving blind areas, secondary damage and grounding in mountainous areas of the large fan blade are effectively solved, and the lightning protection reliability of the fan blade is remarkably improved.

The application belongs to the technical field of metamaterials, and particularly relates to a stealth super surface with synergistic regulation of infrared and microwave emissivity, comprising a plurality of periodically arrayed basic units, wherein the basic unit comprises an infrared emissivity regulation layer and a microwave emissivity regulation layer which are sequentially stacked from top to bottom, and the microwave emissivity regulation layer comprises a second ITO layer, a third ITO layer and a fourth ITO layer which are sequentially stacked from top to bottom; the application can simultaneously realize low emissivity in the infrared frequency band and high emissivity in the microwave frequency band, thereby reducing the visibility of the target in the infrared thermal imager and the microwave radiometer.

This application discloses a method for predicting insect stratification behavior, relating to the field of insect radar technology. The method includes: acquiring phased array insect radar echo data in the target airspace, as well as vertical profile meteorological data collected by laser wind radar and microwave radiometer; generating a spatiotemporal distribution heatmap based on the echo data; mapping the vertical profile meteorological data to the spatiotemporal distribution heatmap using a spatiotemporal interpolation algorithm to obtain a spatiotemporally aligned multidimensional meteorological feature heatmap; labeling the multidimensional meteorological feature heatmap to obtain a labeled sample dataset, and training an XGBoost prediction model using the sample dataset; and using the trained XGBoost prediction model to perform forward inference on real-time meteorological data to obtain prediction results, including the probability of stratification, predicted height, and estimated intensity. This application achieves a leap from empirical guesswork to intelligent and interpretable prediction of insect stratification behavior through the above method.

The invention discloses a method for predicting an insect gathering layering behavior, and relates to the technical field of insect radar. The method comprises the steps that phased array insect radar echo data of a target airspace and vertical profile meteorological data collected by a laser wind finding radar and a microwave radiometer are acquired; generating a space-time distribution thermodynamic diagram based on the echo data; through a space-time interpolation algorithm, mapping the vertical profile meteorological data to the space-time distribution thermodynamic diagram to obtain a space-time aligned multi-dimensional meteorological characteristic thermodynamic diagram; labeling the multi-dimensional meteorological characteristic thermodynamic diagram to obtain a sample data set attached with a label, and training an XGBoost prediction model through the sample data set; and performing forward inference on the real-time meteorological data by using the trained XGBoost prediction model to obtain a prediction result, the prediction result comprising a layering occurrence probability, a prediction height and a prediction intensity. According to the method, the crossing from empirical guessing to intelligent and explainable prediction of insect gathering layering behaviors is realized.

The invention discloses an online denoising method for output voltage of a microwave radiometer receiver, and belongs to the technical field of data optimization. The method comprises the following steps: firstly, acquiring a receiver voltage time sequence as observation data, and generating prediction output and error measurement thereof based on a state transition relation; then, the interference intensity and trend are described through the observation residual error and the change rate of the observation residual error, the interference intensity and trend are input into a fuzzy rule base, and increment used for adjusting the zoom coefficient of an observation noise covariance matrix is output; and realizing self-adaptive updating under the condition of ensuring matrix symmetric positive definite and adjusting amplitude and rate constraint, and determining a filtering gain by combining prediction error measurement so as to correct prediction output to obtain a de-noised voltage estimation value and posterior error measurement thereof. According to the method, the observation noise covariance is dynamically adjusted, the observation weight is reasonably distributed in the interference enhancement, sudden change and recovery stages, direct description of noise time-varying characteristics and rapid, stable and interpretable self-adaptive adjustment are achieved, and therefore the voltage output denoising effect is improved.