127 results about "Brightness temperature" patented technology

The invention provides a lightning proximity prediction method based on a space-time separation convolutional neural network. The method comprises the following steps: S1, acquiring satellite infrared brightness temperature observation data and lightning positioning data; s2, performing spatial resolution adjustment and standardization processing on the satellite infrared brightness temperature observation data; gridding and de-noising processing is carried out on the lightning positioning data; s3, defining a prediction task; s4, establishing a space-time sequence prediction model; based on the processed data, storing the processed data in a numpy file format according to a time point sequence, dividing the processed data into a training set, a verification set and a test set, and loading the training set, the verification set and the test set to a space-time sequence prediction model for model training to obtain an optimization model; and based on the prediction task, using the optimization model to carry out lightning approaching prediction to obtain lightning prediction data. According to the method, the development of cumulus cloud is captured by using satellite infrared brightness temperature observation data and brightness temperature difference data, so that the problem that thunder and lightning inception cannot be effectively predicted is solved.

The invention belongs to the field of ocean remote sensing detection, and particularly relates to an ocean surface salinity inversion method, system and device and a storage medium, and the method comprises the steps: obtaining training day brightness temperature data and training month salinity data of an ocean surface; preprocessing the brightness temperature data of the training day and then carrying out regional screening to obtain regional brightness temperature data; performing interpolation processing on the training month salinity data to obtain interpolation salinity data; performing time alignment on the regional brightness data and the interpolation salinity data to obtain a brightness temperature data set and a salinity data set; extracting features according to the brightness temperature data set to obtain brightness temperature features, inputting the brightness temperature features into the salinity intelligent inversion network model to obtain an output salinity value, calculating the output salinity value and an output loss value of the salinity data set through a loss function, and adjusting model parameters of the salinity intelligent inversion network model according to the output loss value to obtain an optimization model; and inputting the actual brightness temperature data into the optimization model to obtain a salinity value. The method has the effect of improving the inversion precision.

The invention provides a multispectral radiation temperature measurement method and system, and belongs to the field of signal acquisition and processing in an infrared radiation temperature measurement technology. The problems of poor inversion precision and applicability of multispectral radiation temperature measurement are solved. The multispectral radiation temperature measurement method comprises the following steps of: measuring radiation information of the surface of a to-be-measured target by using a multi-wavelength pyrometer; the beam splitting system obtains radiation information of different spectrum channels; photoelectric conversion: converting the optical signal into an electric signal; constructing a target equation and a constraint optimization condition according to the brightness temperature model; carrying out multispectral data processing by utilizing an improved multi-population mixed pigeon inspired optimization algorithm; and the final real temperature and emissivity values are obtained. The device is mainly used for multispectral radiation temperature measurement.

The invention discloses an inter-ice water channel inversion method based on multi-channel satellite data, and belongs to the technical field of satellite image processing, and the method comprises the steps: obtaining a reflectivity abnormal value of a visible light radiation brightness value and an initial value of a reflectivity abnormal threshold value, and obtaining a brightness temperature abnormal value BTA of a thermal infrared radiation brightness value and an initial value of a brightness temperature abnormal threshold value; step 2, acquiring a pixel credibility matrix; and step 3, adjusting a brightness temperature abnormal threshold value and a reflectivity abnormal threshold value by adopting an iterative dual-threshold adaptive optimization algorithm based on fuzzy classification, calculating a brightness temperature abnormal value membership degree and a reflectivity abnormal value membership degree, and judging the comprehensive probability that the pixel belongs to the inter-ice water channel according to each membership degree and the pixel credibility matrix. According to the method, the dynamic complexity of the polar region environment can be better adapted by utilizing the advantages of the visible light data in the aspect of identifying the boundary and texture of the ground features and the advantages of the thermal infrared data in the aspect of distinguishing the ground features at different temperatures, and the inversion precision of the inter-ice water channel is improved.

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 discloses a biological tissue internal temperature microwave chromatography method and system, and belongs to the technical field of microwave measurement. The problem that the internal temperature of the biological tissue cannot be accurately obtained by adopting a microwave radiation temperature measurement technology nowadays is solved. The method comprises the following steps: acquiring environmental thermal radiation rates under different environmental conditions, and acquiring temperature distribution data of a human tissue profile to be subjected to temperature measurement along with depth change under different environmental conditions by utilizing a real three-dimensional anatomical model, a heat conduction equation and a thermal radiation equation of the human tissue to be subjected to temperature measurement; calculating dielectric constants of the human tissue to be subjected to temperature measurement under different frequencies, and obtaining radiation brightness temperature data of different frequencies under different environmental conditions by combining the temperature distribution data and a real three-dimensional anatomical model of the human tissue to be subjected to temperature measurement; constructing a brightness temperature-temperature conversion matrix by adopting a least square method; and acquiring brightness temperature data of different frequencies of human tissue to be subjected to temperature measurement, substituting the brightness temperature data into the brightness temperature-temperature conversion matrix, and performing inversion to obtain temperatures of different depths of the human tissue to be subjected to temperature measurement. The method is suitable for temperature measurement.

The invention provides an atmospheric humidity profile inversion method based on a Unet3 + neural network. The atmospheric humidity profile inversion method comprises the following steps: constructing an atmospheric humidity profile inversion model based on Unet3 + MHS microwave data; performing radiometric calibration, projection conversion and quality control on the multi-channel brightness temperature observed by the original satellite; the method comprises the following steps: selecting long-time scale radiation brightness temperature data in a Chinese area range and specific humidity data of ERA-5 corresponding to time and space to make a data set; and performing humidity profile inversion according to the humidity profile inversion model of the brightness temperature data constructed in the step S1. The method has the advantages that the Unet3 + model in deep learning and microwave sensor data which are not affected by time and weather are combined, and the problems that the space distribution of the atmospheric humidity profile is small, and the time resolution is low can be further solved; the method provides atmospheric condition data with higher temporal and spatial resolution for numerical weather forecast research, and has good application value.

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 provides an Antarctic sea ice snow melting characteristic monitoring method and system based on wind cloud satellite active and passive microwave collaboration, and relates to the technical field of remote sensing satellites, and the method comprises the steps: constructing a characteristic parameter data set containing brightness temperature daily poorer and / or backscattering daily poorer; aiming at each space pixel, based on the time sequence data of the brightness temperature daily worse and / or the backscattering daily worse of the space pixel, automatically determining a freeze-thaw state discrimination threshold value of the pixel through an iterative optimization algorithm taking inter-class difference maximization as a target; for each pixel, comparing the day-by-day characteristic parameter value of the pixel with an adaptive threshold value, judging the freeze-thaw state of the pixel every day according to a preset continuity condition, and generating a time-space continuous freeze-thaw state sequence; and generating a snow melting monitoring result on the surface of the Antarctic sea ice based on the freeze-thaw state sequence. According to the invention, the accuracy of annual freeze-thaw state identification and spring and summer typical thawing initial day detection is improved.

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.

The present invention discloses a method for determining an on-orbit calibration nonlinear coefficient of a satellite-borne microwave radiometer before launch. The method comprises: sequentially observing three calibration blackbodies by the satellite-borne microwave radiometer to be measured within a scanning cycle to obtain observation voltages and brightness temperatures corresponding to three different temperatures; the three calibration blackbodies comprise: a cold calibration blackbody at the boiling point of liquid nitrogen, a hot calibration blackbody at ambient temperature, and a calibration blackbody at an intermediate temperature between the cold and ambient temperatures; obtaining a secondary calibration curve from the observation voltages and brightness temperatures at the three different temperatures; determining virtual cold space data from the secondary calibration curve through virtual cold space observation; if observation data at an intermediate value between the virtual cold space data and the hot calibration blackbody data can be determined from the virtual cold space data and the hot calibration blackbody data, calculating the nonlinear coefficient from the virtual cold space data and the hot calibration blackbody data; otherwise, calculating the nonlinear coefficient from the virtual cold space data, the hot calibration blackbody data, and the intermediate temperature blackbody data.

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.

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 discloses a kind of multi-physical field antenna radiation characteristic inversion method and device, wherein the method includes: constructing the test platform including reflecting surface, variable temperature source and feed receiving calibration system, and it is placed in vacuum environment, by actively heating reflecting surface and using feed receiving calibration system to carry out continuous calibration.Based on the system output brightness temperature after calibration, the known emissivity at reference normal temperature is used to correct the self-radiation contribution of reflecting surface, and the brightness temperature residual after self-radiation correction is calculated. From the heating process, select multiple time points where the weighted temperature of the reflecting surface is in a stable state, and extract the brightness temperature residual corresponding to the multiple time points. With the emissivity at the reference normal temperature as the benchmark, combined with the brightness temperature residual data at each stable temperature point and the corresponding reflecting surface weighted temperature, the actual emissivity of the reflecting surface at each temperature point is calculated. Therefore, the application solves the problem of accurately inverting the temperature characteristics of the emissivity of the reflecting surface in a vacuum environment.

The invention provides a synthetic aperture radiometer radio frequency interference detection method and system based on sub-band brightness temperature. The method comprises the following steps: sorting all brightness temperature data along a sub-band sequence; traversing all the sub-bands, performing fixed threshold detection on brightness temperature data of each sub-band, and marking detected radio frequency interference as abnormal; traversing all the sub-bands, performing two-dimensional airspace radio frequency interference detection on the brightness temperature of each sub-band, and marking the detected radio frequency interference as abnormal; and centralizing the brightness temperature of each sub-band, and then performing threshold detection on the absolute value of the centralized brightness temperature data of each sub-band to obtain the brightness temperature of the sub-band after radio frequency interference suppression. The method has the advantages that the method can be embedded into a real-time radio frequency interference detection module of a satellite-borne synthetic aperture radiometer, brightness temperature data of multiple sub-bands are jointly processed, the method has the advantages of simple steps and high detection capability, and most radio frequency interference presented by the brightness temperature of the sub-bands can be effectively detected.

[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 provides a method for evaluating the influence of damage to a wave-absorbing coating of an aircraft on the low scattering performance of the wave-absorbing coating, and belongs to the field of material performance evaluation.The method comprises the steps that regional decomposition is conducted on the aircraft, the aircraft is divided into a plurality of regions according to parts, each region is further decomposed into a plurality of sub-regions, and therefore targeted analysis can be conducted on damage of different parts; the method comprises the following steps: pre-estimating the low scattering performance of an aircraft wave-absorbing coating before damage, and calculating the radiation sectional area of each region by establishing a radiometer radiation sectional area model, so as to determine the low scattering performance reference of an aircraft in an undamaged state; carrying out radiation calculation on the passive millimeter wave absorbing coating; implementing brightness temperature imaging simulation of the passive millimeter wave absorbing coating; the low scattering performance of the airplane wave-absorbing coating after damage is evaluated, the influence of damage on the low scattering performance is quantified through a low scattering effect concept, and a basis is provided for repair decision making.

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 satellite receiving system GT value automatic test method, equipment, a medium and a product, and relates to the field of satellite ground station automatic test. The method comprises the following steps: firstly, calculating factors by adopting a radio power source direct method test process; calculating an atmospheric correction coefficient according to environmental parameters actually measured by the ground station; acquiring a real-time radiation source angle diffusion coefficient by using moon observation data of Chang'e 2 and an antenna working frequency band; obtaining the real-time average brightness temperature of the moon according to moon observation data of Chang'e 2; and then the G / T value of the receiving system is obtained through calculation, and automatic testing of the G / T value of the receiving system is completed.

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 kind of based on deep learning's full-waveband microwave radiation transmission simulation method and system, method includes: based on global reanalysis data and surface type product, obtain atmospheric profile and surface parameter, adopt near neighbor search and de-redundancy, construct representative "surface parameter-atmospheric profile" database;Using high-precision microwave radiation transmission mode, simulate and calculate the atmospheric top layer brightness temperature covering full-waveband microwave, construct training sample pair;Calculate the correlation coefficient between all output channels, and select the representative channel subset with reduced number from threshold value;Build a fully connected neural network, with the brightness temperature of the representative channel subset as the intermediate feature layer, and use a phased composite loss function strategy for training;Surface parameters and atmospheric profile are input into the trained model to obtain full-waveband brightness temperature prediction results, and / or using automatic differentiation mechanism, the trained model is used as a differentiable operator to calculate the Jacobian matrix of the output brightness temperature relative to the input parameters.

The invention discloses a sea surface temperature space-time sequence acquisition method and system based on sea surface temperature inversion, and the method comprises the steps: obtaining a GF-5A satellite image and an MODIS remote sensing image, and obtaining a sea surface temperature (SST) inversion image of the corresponding MODIS remote sensing image and the brightness temperature of a thermal infrared band 3 and a thermal infrared band 4 of the GF-5A satellite image; obtaining a sea surface temperature inversion image of the GF-5A satellite image; establishing an SRCNN super-resolution reconstruction model, taking the sea surface temperature inversion image of the MODIS remote sensing image as input, training to obtain a sea surface temperature super-resolution reconstruction image of the MODIS remote sensing image, and performing verification by using the sea surface temperature inversion image of the GF-5A satellite image; and obtaining a sea surface temperature space-time sequence based on the super-resolution reconstruction result of the sea surface temperature inversion image of the MODIS remote sensing image. According to the invention, high-resolution sea surface temperature inversion and space-time sequence acquisition are realized.

The application discloses a satellite observation operator construction method and system for a differentiable earth system, comprising the following steps: decomposing a satellite radiation transmission physical process into a plurality of differentiable calculation nodes, constructing a forward calculation graph, calculating an atmospheric state tensor, a prediction factor tensor, a total layer optical thickness tensor, a transmittance tensor, a top layer radiance tensor and an observed brightness temperature tensor through the differentiable calculation nodes, constructing a backward propagation calculation graph according to the forward calculation graph, and encapsulating the forward calculation graph, the backward propagation calculation graph and a standardized calling interface into a satellite observation operator. The method can not only realize end-to-end gradient propagation of an observation physical process, output observation and gradient information of the observation on an earth system state variable, but also has good interpretability and can be directly applied to a satellite observation operator construction system.

The invention provides a brightness temperature simulation calculation method conforming to a radiation transfer theory. The method comprises the following steps: establishing a radiation transfer model based on a radiance Stokes vector in a (Il, Ir, U, V) T form; collecting radiance simulation parameters; if the radiation transmission model is a scalar radiation transmission model, the atmospheric thermal radiation is a vector radiation transmission model, and if the radiation transmission model is a vector radiation transmission model, the atmospheric thermal radiation is obtained by calculating atmospheric particle scattering phase function information, atmospheric single scattering albedo, surface reflectance information and surface emissivity according to radiance simulation parameters; substituting the radiance simulation parameter, the atmospheric thermal radiation, the atmospheric particle scattering phase function information, the atmospheric single scattering albedo, the surface reflectance information and the surface emissivity into a radiation transmission model for calculation to obtain a radiance simulation result; and converting the simulation result of the radiance into the brightness temperature. The invention further provides a brightness temperature analog calculation device and equipment and a storage medium. The brightness temperature simulated by the method is consistent with a theoretical value.

The present invention belongs to the field of climate and environmental monitoring technology and specifically provides a method and system for the simultaneous simulation and inversion of land surface temperature and land surface emissivity. The method comprises: simulating and generating global thermal infrared channel brightness temperature data based on observational parameters of thermal infrared channels from different geostationary meteorological satellites using the thermal infrared radiation transfer equation; adding random Gaussian noise to the brightness temperature data, using this as the observed brightness temperature, and performing simultaneous inversion of land surface temperature and emissivity. By combining observational data from geostationary meteorological satellites from different countries around the world and leveraging the multispectral and high-frequency observational characteristics of the new generation of geostationary meteorological satellites, a physical algorithm for simultaneous inversion of land surface temperature (LST) and land surface emissivity (LSE) is developed. This allows for simultaneous simulation and inversion of LST / LSE on a global scale, providing a reference for quantitative inversion of LST / LSE at high temporal and spatial resolutions worldwide. Satellite observations confirm that underlying surfaces with large diurnal temperature variations, such as deserts, are more conducive to the separation of land surface temperature and emissivity.

The invention discloses a satellite infrared multi-probe metadata homogenization method based on variational self-encoding, which comprises the following steps of: acquiring multichannel observation brightness temperature data of a satellite large-array infrared detector, constructing a variational self-encoder model, designing a comprehensive loss function, adopting a dynamic weight scheduling mechanism, gradually adjusting the weight of each loss item in a training process, and carrying out uniformization on the multi-channel observation brightness temperature data of the satellite large-array infrared detector. And carrying out iterative training by adopting Adam and a piecewise learning rate, storing an optimal model, reconstructing observation data by utilizing the trained model, and outputting homogenized multi-detection-element hyperspectral brightness temperature data. The method can automatically extract and learn the complex nonlinear characteristics of the hyperspectral data, has higher accuracy and robustness compared with an empirical correction method, and improves the consistency and stability of the data of the large-array detector; and the method has relatively high expandability and universality.