168 results about "Brightness temperature" patented technology

The invention discloses a radio frequency interference positioning method and device combining a brightness temperature image and a subspace, and the method comprises the steps: obtaining an original scene brightness temperature image for observing an earth scene, constructing a simulation background brightness temperature image of the earth scene, and obtaining a brightness temperature image after the first SNR is improved; carrying out image processing on the brightness temperature image of the original scene, generating a radio frequency interference (RFI) mask corresponding to the brightness temperature image of the original scene, and obtaining a brightness temperature image after the SNR is improved for the second time; and constructing a covariance matrix of the brightness temperature image after the second SNR improvement, carrying out subspace decomposition on the covariance matrix, and carrying out geolocation on an RFI source observed in an observation image view field. According to the method provided by the invention, the positioning precision of the RFI source under the condition of low signal-to-noise ratio is improved.

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 belongs to the technical field of remote sensing, and relates to an SMAP high-resolution sea surface salinity inversion method based on a multi-scale feature fusion network, and the method comprises the steps: obtaining low-resolution and high-resolution brightness temperature data, and carrying out the segmentation to form one-to-one matched low-resolution and high-resolution data pairs which are used for a brightness temperature super-resolution reconstruction model; the method comprises the following steps: designing an improved U-shaped network model by integrating a pyramid pooling module, performing resolution reconstruction on low-resolution brightness temperature data to obtain reconstructed high-resolution brightness temperature data, and performing space-time matching, resampling, high rainfall value elimination and missing value elimination on all the data; and on the basis of the reconstructed high-resolution brightness temperature data, constructing a DNN inversion model to obtain a salinity inversion result. The method does not depend on prior knowledge, can quickly and directly convert a low-resolution image into high-resolution salinity data, shows extremely high stability under various marine environments and extreme weather conditions, and is of great significance to marine scientific research, resource development and the like.

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 discloses a satellite-borne synthetic aperture microwave radiometer multi-angle brightness temperature noise suppression method, which belongs to the technical field of microwave remote sensing, and comprises the following steps: acquiring historical marine physical parameters, and calculating to obtain multi-angle brightness temperature according to the historical marine physical parameters; fitting the multi-angle brightness temperature, and establishing a relational expression of the brightness temperature and the observation angle under different physical parameters; and calculating the slope of the fitting curve, calculating the deviation between the brightness temperature of the multiple angles and the brightness temperature of any single angle, and establishing a deviation lookup table of the brightness temperature of the multiple angles and the brightness temperature of the specific angle under different physical parameters. The brightness temperature correction value of the corresponding angle is searched in the lookup table, and the brightness temperature of SMOS multi-angle observation is mapped to a single angle; and averaging the mapped single-angle brightness temperature to obtain the noise-suppressed single-angle brightness temperature.

The invention discloses a method for polar region all-day cloud detection by using FY-3D infrared channel brightness temperature, and relates to the technical field of cloud detection, and the method comprises the following steps: obtaining CALIOP data and FY-3D / MERS-II data, specifically CALIOP cloud layer product data and MERS-II observation data and positioning data, carrying out the preprocessing, and carrying out the preprocessing to obtain an FY-3D infrared channel brightness temperature; according to the method, space-time matching is carried out according to transit trajectories of CALIOP and FY-3D satellite MERS-II sensors, matched infrared channel radiance information is extracted, calculation is carried out based on the matched infrared channel radiance information, and the brightness temperature and the brightness temperature difference are calculated. CALIOP data are combined with FY-3D / MERS-II data, the CALIOP is used as a truth value standard of cloud detection, space-time matching is carried out with the FY-3D / MERS-II data, and the brightness temperature difference is calculated. The polar region all-time cloud detection is realized, the accuracy of the cloud detection is improved, and a high-quality data set is provided for the training of a subsequent machine learning model, so that the effects of being not limited by the dependence of visible light and stably working under an all-time condition are achieved.

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.

According to the receiver noise coefficient testing method based on high-precision radiation measurement, a calibration source outputs different brightness temperature signals to calibrate a receiver in real time, and high-precision measurement of the noise coefficient of the receiver can be achieved by calculating the equivalent noise temperature. An actual brightness temperature scene is integrally simulated, the radiation measurement method is more accurate, and the test precision is improved; the calibration source realizes accurate and stable cold source and heat source based on liquid nitrogen refrigeration and physical heating, and has the advantages of high output precision, long stabilization time and the like, and the long-time stabilization precision can reach 0.1 k / 3 days; and meanwhile, the output brightness temperature of the high-precision calibration source is between 90K and 330K and is closer to an actual brightness temperature scene, so that a relatively large nonlinear error caused by nonlinearity of an internal amplifier of the receiver can be avoided, and the test precision is greatly improved.

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 provides a method for remote sensing detection of a Jinstar intermediate layer atmosphere horizontal wind field profile by using a microwave limb radiometer, and the method comprises the steps: designing a detection channel of the Jinstar intermediate layer atmosphere horizontal wind field profile based on the characteristics of a Jinstar gas spectral line, obtaining radiation brightness temperature observation values of the detection channel at different tangent heights in two orthogonal directions through a microwave limb radiometer carried by a star orbiter; the characteristics of the golden star gas spectral lines are as follows: in a microwave frequency band, the golden star atmospheric trace gas spectral lines are rich and have obvious absorption peaks, and the high-speed atmospheric motion of the middle layer enables the gas absorption spectral lines to generate obvious Doppler frequency shift; and through physical iteration inversion, inversion is carried out based on the radiation brightness temperature observation value to obtain a golden star intermediate layer atmosphere horizontal wind field profile. The method has the advantages that back scattering and other intermediate processes are not needed, the method is basically not affected by ground surface high-temperature radiation, and continuous, stable, high-temporal-spatial-resolution and high-precision star intermediate layer atmosphere horizontal wind field profile information can be obtained all day long.

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 brightness temperature imaging method and system for air hidden detection, and the method comprises the following steps: 1, carrying out the modeling of an air shielding detection model, and obtaining a model that a radiometer is buried in sandy soil and a detection object is above the sandy soil; 2, the model is subdivided into a plurality of small areas or grids; 3, setting different dielectric constants on the measured surfaces of the target object, the sandy soil and the atmosphere, performing ray tracing, and simulating a propagation path of millimeter waves from the sky to the ground; 4, taking the Green's second theorem as a starting point, and utilizing a Kirchhoff residence phase approximation method and a Kirchhoff scalar approximation method to solve the transmission scattering problem of the Gaussian rough surface; 5, inverting the brightness temperature to the emission source point according to the brightness temperature and the transmission coefficient of the ray terminal to obtain the total brightness temperature of each position; generating an unprocessed brightness temperature map in the detected scene through accumulation calculation of multiple reflections and transmissions of rays in each medium; and 6, performing data processing on the brightness temperature map by using Gaussian filtering, and outputting a brightness temperature imaging result.

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 belongs to the technical field of one-dimensional synthetic aperture near-shore data processing, and relates to a one-dimensional synthetic aperture microwave radiometer near-shore brightness temperature increasing method based on node sampling, which comprises the following steps: initializing parameters, and carrying out oversampling processing on frequency domain signals containing Gibbs pollution; nodes in the oversampling brightness temperature image are searched through positive and negative values of a second derivative, and common nodes and abrupt change nodes are screened; performing iterative correction on the common nodes, including calculating a high-resolution Laplacian operator, updating brightness temperature values of the common nodes, and performing loop iteration; brightness temperature correction is performed on the abrupt change node, a trend factor is calculated according to the brightness temperature difference value of the nearest adjacent node, and the brightness temperature value of the abrupt change node is updated; and outputting the corrected near-shore data brightness temperature value. According to the method, Gibbs oscillation elimination and sea-land buffer area reduction are carried out by using a node sampling method, and on the basis that iteration of all common nodes is completed, mutation nodes are corrected by calculating trend factors, so that the purpose of reducing the sea-land buffer area is achieved.

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 discloses an all-sky total cloud cover detection method, and relates to the technical field of meteorology, and the method comprises the steps: based on the characteristic that the brightness temperature data in an atmosphere background state is greatly different from the brightness temperature data of cloud, under the characteristic that the atmosphere background state has continuity and does not suddenly change instantly, calculating the brightness temperature data of the cloud; performing data screening on observation data in a historical acquisition period in a clear sky state before a current detection moment, adding the data into a data processing pool, extracting historical minimum brightness temperature data in each elevation angle range in the data processing pool, and performing fitting to obtain an all-sky clear sky model; the method is used for representing the characteristics of brightness temperature data in an atmosphere background state at a current detection moment, and then the total cloud cover of the whole sky can be obtained according to the whole sky infrared brightness temperature data at the current detection moment in combination with a whole sky clear sky model. According to the method, the dependence on a large amount of historical data is reduced, the detection convenience and accuracy are high, and the application range is wide.

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 invention discloses a large-aperture antenna microwave radiometer on-orbit calibration method based on cold air analysis, belongs to the technical field of microwave radiometer calibration, and is applied to stationary orbit microwave radiometer calibration. The implementation method comprises the following steps: 1, observing an atmospheric target by using an antenna to obtain atmospheric radiation energy; 2, the receiver determines the gain of the receiver in a gain mode; 3, the microwave radiometer observes cold air through the receiver to obtain cold air radiation energy; 4, the microwave radiometer observes the cold air through the antenna to obtain cold air radiation energy; and 5, observing the atmosphere target and the antenna error by using the antenna to obtain the atmosphere target brightness temperature. In order to correct the deformation and self-radiation influence of the main reflecting surface and the auxiliary reflecting surface of the external antenna, a receiver can directly observe the cold air and can also observe the cold air through the antenna surface, and the overall influence of the real-time antenna is obtained through an offset modeling mode, so that the correction on the overall influence of the antenna in the calibration process is realized. And the problem that the large-aperture antenna microwave radiometer is difficult to calibrate can be solved.

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 invention belongs to the technical field of surface temperature inversion, and relates to a surface temperature split window remote sensing inversion method and system based on a virtual channel. The method comprises the steps of constructing a simulation data set, constructing a virtual channel, determining a split window coefficient and determining a target surface temperature. According to the method, through angle normalization of on-satellite brightness temperature, the influence of a surface temperature angle effect caused by different vegetation coverage projection areas under different observation zenith angles on ground mixed pixels is eliminated, so that observation data under different observation zenith angles have comparability; through a PSO-BP neural network model, time correction and spectrum conversion of on-satellite brightness temperature are realized, and virtual channel construction of an eleventh channel of the Landsat-8 TIRS is realized; according to the method, the appropriate split window coefficient of the subinterval is reselected through the surface temperature approximate value, the atmospheric water vapor content and the average surface emissivity, and the more accurate surface temperature can be estimated.

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.