23 results about "Satellite altimeter" patented technology

The invention discloses a tidal flat terrain inversion method and system, and the method comprises the following steps: 1, obtaining a multi-source remote sensing image and ICESat-2 satellite altimeter data under the condition of less clouds or no clouds, and carrying out the preprocessing of the multi-source remote sensing image and ICESat-2 satellite altimeter data; 2, classifying the preprocessed multi-source remote sensing images by using a support vector machine algorithm, and extracting submerging frequency information of the tidal flat; 3, analyzing photon topographic features of ICESat-2 satellite altimeter data, and accurately extracting prior elevation information of the tidal flat by adopting a multi-stage denoising fusion method; step 4, enabling the tidal flat submerging frequency to be in one-to-one correspondence with the prior elevation information, constructing a tidal flat terrain inversion universal model, and mapping the submerging frequency into the tidal flat terrain; and 5, performing precision evaluation on the inverted tidal flat terrain by using the high-precision airborne LiDAR data. The relation between the tidal flat elevation and the submerging frequency is established, the method can be used for inverting the interannual tidal flat terrain, and high-frequency monitoring of the tidal flat terrain is achieved.

The present invention belongs to the field of satellite altimeter data deviation correction, and specifically relates to a method for correcting the deviation of a domestic satellite altimeter fusion product based on deep learning. The present invention includes the following steps: S1, obtaining satellite remote sensing data as input and label data, and integrating the obtained input and label data sets into a certain organizational structure and dividing them into subsets for model training, verification and testing; S2, building a deep learning network A2A; S3, using the data set obtained in step S1 to alternately train and verify the deep learning network A2A obtained in step S2; S4, using the trained deep learning network A2A to correct the domestic satellite altimeter fusion product, that is, to obtain domestic satellite altimeter data with higher accuracy. The present invention builds a model based on a deep learning framework and uses public data sets for model training and prediction. It is more convenient to operate and has stronger generalization ability than traditional methods, and provides a new and effective way to improve the accuracy of domestic satellite altimeter fusion products.

The invention discloses an ocean mesoscale vortex intelligent identification method and system based on flow field geometric features and a satellite altimeter, and the method comprises the steps: obtaining the synchronous SSHA data of at least three satellites, and carrying out the calibration according to the actual measurement data of a buoy; on the basis of the calibrated SSHA data, utilizing a ground-to-balance equation to calculate weft-direction and warp-direction ground-to-balance flow velocity components; generating a flow field geometric feature VG vortex center criterion; dynamically adjusting VG vortex core criterion parameters according to the ocean dynamic environment; converting the SSHA and geostationary flow field data into a grayscale image, marking vortex polarity and a bounding box, and adding a salt and pepper noise expansion sample through random rotation; resNet-50 is adopted as a backbone network, and a bidirectional feature pyramid network BiFPN is added to optimize multi-scale feature fusion; and inputting the VG preliminary identification result into the trained ResNet-BiFPN model, and outputting the vortex position, radius and polarity. The technical defects of a traditional method in weak vortex recognition, background noise interference and calculation timeliness are overcome.

The invention discloses a satellite height measurement data optimal interpolation fusion method based on cross calibration and spectrum analysis, and the method comprises the steps: carrying out the sea surface height anomaly calculation and power spectrum analysis, and calculating the sea surface height anomaly of a satellite altimeter according to the precise orbit determination coordinates of a satellite and the distance measurement value of the altimeter; the related scale of adjacent observation points of the to-be-fused satellite altimeter is obtained through the power spectrum analysis of the sea surface height anomaly of the to-be-fused satellite altimeter; cross calibration: performing cross calibration on sea surface height anomaly of the fusion satellite altimeters by using the sea surface height anomaly of the reference satellite altimeter to obtain system deviation in the to-be-fused satellite altimeters; performing self-crossing calibration by using sea surface height anomaly of the satellite altimeter to be fused to obtain a diagonal element of an observation error covariance matrix; constructing a covariance matrix, wherein a non-diagonal element of the observation error covariance matrix is a product of a standard deviation at the two measurement points and a correlation function of the two measurement points; and fusing the fused satellite altimeter and the background field data by using an optimal interpolation method.

This invention discloses a method and system for investigating subsurface eddies and their submesoscale processes in the ocean. The method includes acquiring three-dimensional temperature, salinity, depth, and current data for a designated sea area, and plotting vertical distribution maps of temperature, salinity, density, and flow field; screening isodense surfaces based on vertical density anomalies and the location of maximum flow velocity; identifying subsurface eddies based on the geopotential height contour maps and vertical flow field maps of the identified isodense surfaces; acquiring satellite altimeter data for the designated sea area and plotting satellite orbit distribution maps for different dates; designing and plotting flight routes for the identified subsurface eddies and satellite orbit distribution maps; and plotting station distribution maps based on the flight route distribution maps for hydrological surveys. This invention aims to provide a solution for identifying and locating subsurface eddies, investigating and analyzing submesoscale processes of subsurface eddies, and designing observation flight routes, thereby solving the problems of difficulty in locating and observing subsurface eddies and their submesoscale processes in the ocean.

The application discloses a cross-dimension multi-source satellite altimeter sea level anomaly joint estimation method and system, and relates to the field of ocean remote sensing.The joint estimation method comprises the following steps: obtaining multi-source observation data of a target sea area about a target period, forming a corrected joint observation data set through cross-dimension data processing and reconstruction operation and bias correction operation, and mapping the corrected joint observation data set to a corresponding regular space-time grid of the target sea area; based on a preset space-time search radius, constructing an observation operator, a background covariance matrix and an observation error covariance matrix corresponding to each grid point in the regular space-time grid, and generating a regular gridded sea level anomaly product of the target sea area about the target period through an optimal interpolation method without performing explicit system error correction.The application can consider large-scale background consistency and small and medium-scale structure resolution capability on multiple spatial scales, and improves the spatial continuity, statistical consistency and overall stability of the sea level anomaly estimation result.

The application belongs to the technical field of circulation mixing coefficient estimation, and discloses a global estimation method, system, device and terminal of a wave-induced turbulent mixing model, the global estimation method of the wave-induced turbulent mixing model comprising: estimating the global three-dimensional structure of the internal tide-induced turbulent mixing coefficient based on the wave-induced turbulent mixing coefficient, the internal tide information extracted by the satellite altimeter and the WOA13 temperature and salinity data; determining the structure of the global internal wave spectrum; and estimating the distribution characteristics of the global annual average internal wave-induced turbulent mixing coefficient BVIW. The internal tide information extraction comprises: obtaining, processing and filtering satellite along-track sea surface height anomaly data, performing tidal harmonic analysis on the filtered data, and obtaining the internal tide harmonic constant of the global ocean tidal frequency M2. According to the derived mixing coefficient, new mixing is not created, but a mixing process that is not available under the existing framework and is rich in physical connotation is created, and the important significance of wave mixing to the circulation is given.

The invention discloses a sea surface height continuous expression and reconstruction method and system for sparse satellite orbit observation, and the method comprises the steps: forming an input-output data pair according to three-dimensional time-space coordinates of an observation point of a satellite altimeter and an original along-orbit sea surface height observation value of the satellite altimeter; the three-dimensional time-space coordinates are converted into meshless continuous input coordinates; constructing a space-time continuous expression model based on implicit neural representation on the basis of a network structure of a sine cycle activation function, introducing gradient field consistency constraint and total variation regularization, and constructing comprehensive loss; and according to global sea surface height estimation output by the model, reconstructing a regular grid, calculating a sea surface height gradient, gradient change, local curvature and power agent quantity, completing continuous expression and reconstruction of the sea surface height, and realizing synchronous and high-quality reconstruction of a fine structure and an overall scene of a sea surface height field. And the defects of non-uniform sampling, high-gradient recovery and micro-analysis capability in the prior art can be effectively overcome.

The present application belongs to the field of marine surveying and geodetic surveying, and discloses a far-sea GNSS buoy height reference transmission method combined with satellite altimeter, aiming to solve the technical problems of difficult transmission of 1985 national height reference in far-sea area and large height measurement error of GNSS buoy antenna, the method establishes height reference conversion relationship through shore-based leveling joint measurement, carries out precise positioning and calculation on far-sea GNSS buoy observation data, and retains effective sea surface information through low-pass filtering processing; combines satellite altimeter data to carry out space-time matching, inverses and dynamically corrects the height of buoy antenna, converts the ellipsoidal height of buoy sea surface into 1985 national height through geodetic datum difference correction, and finally outputs the results through quality evaluation. The method realizes accurate transmission of far-sea height reference and dynamic correction of the height of buoy antenna, guarantees the reliability of far-sea sea surface height calculation, and provides accurate height data support for far-sea marine observation, marine engineering and other fields.

The invention discloses an absolute sea surface elevation measurement system based on an offshore mobile platform, which relates to the field of marine surveying and mapping and satellite remote sensing calibration and comprises an offshore mobile platform part, a shore-based static GNSS (Global Navigation Satellite System) base station and a data processing module, the offshore mobile platform part is integrated with a GNSS antenna and receiver, an attitude sensor, a radar tide gauge and a data acquisition and storage module; the shore-based static GNSS base station provides static coordinates and GNSS observation data, and the data processing module comprises a shore-based base station resolving module for resolving to obtain three-dimensional coordinates; the offshore platform GNSS dynamic resolving module is used for resolving a dynamic position; and the absolute sea surface height calculation module is used for calculating the initial sea surface height and outputting a final result through low-pass or median filtering. The device does not need to distribute a buoy, can be directly carried on a ship, a floating platform and other mobile platforms, realizes high-precision, continuous and safe absolute sea surface elevation measurement, and is suitable for satellite altimeter calibration and other application scenes.

The present invention provides a method, medium and system for collecting ocean internal wave data, which belongs to the field of ocean hydrological observation technology. The present invention collects water body movement data through an acoustic Doppler current profiler and seawater parameters through a temperature-salinity-depth profiler, and combines satellite altimeter and drifting buoy data. Time-frequency analysis is performed on the water body movement data and bandpass filtering is used to obtain internal wave candidate data. A set of internal wave mathematical equations including basic fluid mechanics equations, buoyancy frequency, dispersion relationship, etc. is constructed to verify and filter out valid data. The valid data is input into a pre-trained classification model to determine the internal wave type, and finally the key waveform segment is extracted through a preset extraction equation set to generate and output internal wave characteristic waveform data. The present invention combines multi-source observation data and mathematical and physical models to realize the identification, classification and feature extraction of ocean internal waves, solving the current problem of the lack of a data acquisition method that can effectively extract effective ocean internal wave signals and accurately identify internal wave characteristics.

The invention discloses a ConvLSTM sea level height change prediction method based on reduced gravity hypothesis, and the method is suitable for the prediction of global sea level height anomaly (SLA). The method comprises the following steps: S1, acquiring and preprocessing global satellite altimeter data; s2, based on a ConvLSTM model, extracting spatio-temporal characteristics of sea level height anomaly; s3, introducing wind stress data, and combining physical constraints of a reduced gravity model to enhance the prediction capability of the model for wind-driven Rogobby waves; and S4, outputting a high-precision sea level height prediction result through error evaluation and optimization. According to the method, global satellite altimeter data in 1993-2014 are used for training, experiments in a black tide extension sea area show that the prediction correlation coefficient reaches 0.98, the effective prediction time efficiency can reach 365 days, the performance is more excellent in a low-frequency change area, and the accuracy, stability and timeliness of sea level prediction are remarkably improved.

The invention discloses a self-adaptive statistical modeling method and system for mesoscale vortex spatio-temporal evolution characteristic parameters. The method comprises the following steps: cooperatively acquiring initial parameters of a target sea area through a satellite altimeter and an Argo buoy array; calculating a vortex characteristic scale Rd based on a Ross-Be deformation radius formula; defining a state vector, and establishing a nonlinear state equation to construct a spatio-temporal evolution statistical model; dynamically correcting a prediction error by adopting variational Bayes-square root cubature Kalman filter (VB-SRCKF); obtaining vortex kinetic energy spatial distribution EKE, and processing a flow velocity abnormal component by adopting a discretization grid integral method; an incidence matrix Mlink is generated, and the element Mlink (i, j) of the incidence matrix Mlink is formed by linear combination of EKE and SLA; dimensionality reduction is carried out on the Mlink based on t-SNE manifold learning, and nonlinear features of vortex intensity-radius-life cycle are extracted; the method has the advantages of noise adaptive correction, nonlinear feature recognition enhancement, VB-SRCKF parallelization acceleration, manifold learning acceleration and the like.

The invention provides a global dynamic ocean front identification method based on remote sensing data. The global dynamic ocean front identification method based on remote sensing data comprises the following steps: S1, acquiring and preprocessing infrared satellite remote sensing data and satellite altimeter data; s2, based on a double-threshold method of a Bayes decision model, identifying an ocean peak region; s3, identifying the ocean frontal line based on a kinetic method of a geostationary flow speediness mechanism; s4, performing space-time distribution tracking analysis on the identified ocean frontal line based on a tracking algorithm of connected region centroid matching; and S5, carrying out feature analysis on the tracked ocean frontal line. The global dynamic ocean front identification method based on remote sensing data provided by the invention has the advantages that the ocean front can be comprehensively identified by using the temperature gradient and the earth turning flow velocity, so that the accuracy and continuity of ocean front identification are improved.

The invention discloses a mesoscale vortex three-dimensional temperature and salt field reconstruction method and system based on an ROMS mode and data assimilation. The method comprises the steps that sea surface temperature data and vertical salinity profile data are acquired; initializing an ROMS mode control equation set; optimizing the vertical resolution of the ROMS mode control equation set by adopting Sigma coordinate transformation; constructing an ensemble Kalman filtering assimilation kernel function; adopting a nonlinear covariance localization function to suppress sampling noise of the assimilation core of the ensemble Kalman filter; generating a bit vortex conservation constraint function based on satellite altimeter data, and converting sea surface height anomaly into three-dimensional density disturbance; assimilation iteration is executed, and a plurality of set members are generated to update the temperature and salt field; embedding a temperature-salt constraint module; based on the output vorticity field, obtaining a vorticity field optimized vortex structure; and outputting the three-dimensional warm salt field. According to the method, the parameter precision is improved, the calculation efficiency is optimized, and the application value is expanded.

The invention provides a data processing method based on ocean tide quasi-harmonic analysis, and relates to the technical field of physical oceanography. The data processing method based on ocean power flow quasi-harmonic analysis comprises the following steps: S1, based on satellite altimeter surface flow velocity data, coastal radar horizontal flow field data and buoy vertical profile data, aligning a space-time reference by adopting a space-time registration algorithm, dynamically fusing three types of data sources through Bayesian weighted Kalman filtering, eliminating instrument system errors, and obtaining a time-space reference; and generating a three-dimensional power flow reference data set. By fusing multi-source ocean observation data and applying space-time registration and dynamic filtering technologies, high-precision three-dimensional power flow reference data is constructed, the data coverage range and reliability are remarkably expanded, in a partial tide parameter analysis stage, a least square fitting and complex vector superposition method is adopted, elliptic motion elements of a key partial tide are accurately solved, and the maximum power flow is obtained. And the integrity of tide motion rule description is ensured.

The present application relates to the technical field of ocean observation and remote sensing data processing, in particular to a kind of ocean three-dimensional detection method and system based on unmanned aerial vehicle fusion microwave and laser, comprising: target sea area identification and task planning;Based on satellite altimeter sea surface height anomaly data, determine target area and unmanned aerial vehicle route;Multi-sensor synchronous acquisition synchronous detection data;Synchronous detection data driven ocean structure joint inversion: microwave and laser synchronous detection result co-registration fusion and ocean quasi-three-dimensional structure construction.The present application takes microwave and laser synchronous detection result as data basis, after sea surface height anomaly calculation, internal thermal structure inversion, chlorophyll anomaly profile inversion, realizes the mutual corresponding ocean quasi-three-dimensional detection between sea surface dynamic signal, upper ocean internal thermal structure and water vertical parameter.

The application discloses a method for correcting wave height data of a sea wave model by using satellite data, and comprises the following steps: traversing the satellite data, and matching the satellite data with corresponding sea wave model data; establishing a preset full connection neural network with the sea wave integral parameter of the wave height of the sea wave component as input and the corrected component wave height as output; establishing a preset full connection neural network with the component residual wave height as input and the corrected component residual wave height as output; connecting the plurality of preset component wave height correction networks and the preset residual wave height correction network in parallel, and taking the square root of the sum of the output items of each network as the total output, namely the corrected overall significant wave height; training the preset parallel network by minimizing the mean square error of the overall significant wave height output by the parallel network and the matched satellite altimeter significant wave height, so as to obtain a neural network model for correcting the significant wave height data of the sea wave model; and applying the model to the output result of the sea wave model which needs to be corrected, so as to improve the accuracy of the sea wave model data.

The invention discloses a water level monitoring method and equipment of a double-satellite altimeter and a medium, and belongs to the technical field of hydrological remote sensing. Performing spatial resolution matching and preprocessing on the ICESat-2 and GEDI data, and extracting surface photon data; the method comprises the following steps: for a land surface region, extracting land surface cross observation points of two satellites, which are overlapped in space, by adopting a graph intersection method, screening effective paired data by combining an abnormal value elimination method, and constructing a land surface elevation correction model based on weighted least square regression; for a water body area, extracting observation photons falling in a water body range, respectively estimating average water levels measured by ICESat-2 and GEDI, and establishing a water level calibration model between the ICESat-2 and GEDI; and fusing the land elevation correction model and the water level calibration model to form a weighted correction function, correcting the GEDI observation water level, and finally obtaining a water level monitoring result of the research area. High-coverage and high-precision remote sensing monitoring of the water level of a water body in a research area is achieved.

The present application belongs to the field of marine remote sensing measurement technology, and specifically relates to a dual GNSS buoy wide-swath altimeter wavenumber spectrum slope calibration method and system. The present application combines the wavenumber spectrum-frequency spectrum model, processes and numerically analyzes the frequency spectrum data obtained by the buoy, and thus quantitatively evaluates the wavenumber spectrum slope of the wide-swath satellite altimeter. This technical solution effectively compensates for the shortcomings of traditional single-point measurement, reduces the evaluation cost and implementation difficulty, and realizes reliable verification of the wavenumber spectrum characteristics of the two-dimensional sea surface height in the spatial domain of the wide-swath altimeter.

The invention discloses a river water level time sequence encryption method for an observation station missing region based on a remote sensing virtual station, and the method comprises the steps: taking a measurement foot point of a satellite-borne satellite altimeter as a virtual station of a river channel, and extracting a river reach water area based on the satellite height measurement data of a river reach where the virtual station is located at the same time and a remote sensing image; and constructing an empirical model of the water level and the water area of the river virtual station. And encrypting a long-time-period, high-time-frequency and near-real-time river water level time sequence by using the empirical model and a water area time sequence observed by a remote sensing virtual constellation in a high-time-frequency manner. The method is mainly oriented to an observation station missing area, the defect of low time resolution of satellite height measurement is overcome through the high time frequency observation advantage of a virtual constellation constructed by multi-source optics and radar remote sensing satellites, and method support is provided for understanding the river hydrological situation time-space evolution characteristics of the observation station missing area.

The invention provides a model training method, a mesoscale eddy identification method and application, and aims to overcome the defects of mesoscale eddy detection by an existing artificial intelligence method and obtain a mesoscale eddy detection model based on loss function gradient optimization. The model training method comprises the following steps: firstly, constructing a mesoscale eddy data set according to satellite altimeter remote sensing data and global marine physical reanalysis data, and generating a label for the data set through a PET method and a Shapley tool; then, a mesoscale eddy detection model is realized based on a U-Net architecture, and meanwhile, an attention mechanism and a cross-level feature fusion module are added according to the characteristics of multi-source data to optimize the performance of the model. And finally, introducing a feature map gradient difference constraint term on the basis of the cross entropy loss function, and improving the feature extraction capability of the model through joint optimization of a prediction result and edge gradient information. Compared with a U-Net reference model of a single data source, the mesoscale eddy detection model provided by the invention remarkably improves the mesoscale eddy identification capability of an artificial intelligence method.

This invention relates to the field of ocean current velocity inversion technology, specifically to a method for calculating trans-shelf water flux at a shelf break in the East China Sea. The method includes: obtaining long-term series observation data; establishing a regional coordinate system: establishing a moving coordinate system that changes with the continental slope topography, a coordinate system (n) across the 200-meter isobath, a coordinate system (l) along the 200-meter isobath, and a coordinate system (z) perpendicular to the sea surface; and constructing a dynamic equation: constructing the trans-shelf water flux q, which is the trans-shelf water flux in the horizontal direction, by vertical integration along the 200-meter isobath. This method is primarily based on satellite altimeter data and historical field observation data, using a reasonable dynamic model to calculate the trans-shelf water flux. It avoids the need for extensive field ocean current observation equipment and numerical calculation methods that require significant computational resources, offering advantages such as better economy, increased safety, reliable measurement accuracy, and greater convenience.