19 results about "Sea surface wind" patented technology

This invention discloses a method for inverting sea surface wind speed from GNSS reflected signals based on mask perception and image-based Mamba-CNN. The method includes: performing spatiotemporal matching and interpolation processing on multi-source spaceborne GNSS-R observation data and ERA5 reanalysis data; gridding the processed observation parameters according to geographical location to obtain a multi-channel grid image and acquiring a binarized occupancy mask; inputting the multi-channel grid image and the binarized occupancy mask into a mask perception Mamba-CNN model; calibrating the grid features through a mask conditional encoder and a feature linear modulation layer, and performing spatial modeling using feature extraction blocks combining convolutional and Mamba state space paths to obtain the wind speed inversion result; aggregating the extracted features using center-perception pooling, and outputting the final sea surface wind speed inversion image through a regression network. This invention can significantly reduce computational complexity, effectively reconstruct the continuous wind field structure, and improve the inversion accuracy and robustness in high-wind-speed areas.

The application discloses a global average sea clutter near real-time estimation method, system, device and storage medium, including the following steps: obtaining multi-source satellite-borne radar historical backscattering coefficient data, and performing time and space matching and binning on the ERA5 wind field; an average sea clutter estimation model is established according to a geophysical model function fitting; the satellite-borne microwave scatterometer wind field is corrected in deviation and fused with a numerical weather prediction wind field, so that a high-coverage, continuous near real-time global sea surface wind field is obtained; the relative azimuth is calculated in combination with radar observation parameters and fused wind direction, and global average sea clutter data is obtained by using the model; the application improves the precision and application range of sea clutter estimation under the condition of medium and small incident angles, provides a high-quality input wind field through a multi-source wind field fusion technology, realizes rapid, stable and near real-time estimation of global average sea clutter, has high timeliness and business feasibility, and can meet the needs of near real-time sea clutter monitoring and ocean remote sensing application.

The application discloses a kind of anti-rainfall wind speed inversion methods based on same satellite platform GNSS-R and dual-frequency scatterometer, utilize same platform dual-frequency scatterometer data and synchronous precipitation data, construct dual-band rainfall detection model, identify the rainfall area in the observation width of scatterometer;In the identified rainfall area, the observation point that coincides with same platform GNSS-R space-time is screened, and the anti-rainfall wind speed inverted by GNSS-R is used as reference true value, trains dual-band wind speed inversion model specially used in rainfall condition;The trained model is applied to the entire scatterometer observation width, and the unit determined as rainfall is corrected for wind speed, and the non-rainfall unit is inverted using the standard model, so as to generate high-precision, full-coverage sea surface wind field product under rainfall condition.The application makes full use of the anti-interference characteristics of GNSS-R under rainfall condition, the wide-width detection capability of dual-frequency scatterometer and the advantages of synchronous observation time of same platform, and improves the precision, reliability and spatial integrity of wide-width sea surface wind field product under complex weather.

This invention provides a method and system for assimilating tropical cyclone wind speeds using spaceborne GNSS-R, comprising: partitioning the tropical cyclone (TC) structure based on a matching dataset of massive historical SAR and ERA5 reanalysis data, and statistically decoupling the radial and tangential correlation scales of the wind corona discharge (BEC) within each partition; establishing an empirical mapping model between BEC statistics and key TC parameters; and driving the empirical model to construct a flow-dependent anisotropic BEC matrix based on real-time TC parameters provided by the international best path archive, and introducing it into a variational assimilation system to assimilate multi-source spaceborne GNSS-R observation data, reconstructing a high-resolution TC sea surface wind field analysis field. This invention, starting from a physical mechanism, effectively suppresses the gradient smoothing effect of background errors in the eyewall region, reducing the root mean square error of the background field by 33% under extreme wind speeds, significantly improving the engineering and operational capabilities of spaceborne GNSS-R data in TC intensity and structure monitoring.

The application provides a kind of offshore wind farm hub height wind speed calculation method, it is related to offshore wind resource evaluation technical field. Including: obtaining the satellite SAR of target sea area is retrieved sea surface wind speed, and simultaneously in the wind farm area is arranged not less than three floating laser radar to measure high altitude three-dimensional wind speed profile, the two kinds of data sources are matched in time and space, to the data after time and space matching constructs training sample set, and with sea surface wind speed, atmospheric stability, sea surface roughness as input characteristics, hub height wind speed as output label, trains machine learning model, the global SAR sea surface wind speed data is batch calculated to hub height, finally generates the hub height wind resource atlas covering the whole target sea area;Data source level realizes the organic complement of planar sea surface wind field and point vertical profile, improves the accuracy of data, improves the calculation accuracy, improves the accuracy and reliability from sea surface to hub height wind speed calculation.

This invention relates to the field of intelligent ship navigation, specifically to a wind speed inversion deviation correction method based on shipborne GNSS-R, comprising the following steps: acquiring time-delay Doppler image data and a reference wind speed; preprocessing the time-delay Doppler image data and outputting valid data; extracting observations related to sea surface wind speed and dividing them into training and test sets; calculating the initial inversion wind speed based on the training set and constructing initial inversion residual samples, establishing a marginal probability distribution model; establishing a joint probability distribution model based on the initial inversion residual samples and the reference wind speed; constructing test inversion residual samples based on the test set, calculating the conditional estimate of wind speed deviation based on the joint probability distribution model, correcting the deviation of the initial inversion wind speed, and calculating the corrected inversion wind speed. This invention effectively reduces the impact of systematic and random errors, significantly improves the accuracy and robustness of sea surface wind speed inversion, and provides reliable environmental perception support for intelligent ship navigation.

This utility model relates to the field of marine rescue equipment technology, and in particular to a rapidly deployable sea rescue net. This utility model provides such a rapidly deployable sea rescue net, including a fixed base, a support shell, a servo motor, and a connecting plate. The support shell is fixedly connected to the bottom of the fixed base, and the servo motor is installed at the bottom of the support shell. The connecting plate is connected to the output shaft of the servo motor. The servo motor drives the connecting plate to rotate, causing a slider to slide on a guide rail. This, through a diamond-shaped sleeve, moves the connecting base, support base, and support tube on both sides away from each other, thereby rapidly deploying the rescue net. This solves the problem that existing marine rescue equipment often requires manual deployment, which is slow and easily affected by environmental factors such as sea waves, resulting in the inability to deploy the rescue net in time to cover the person in the water, thus delaying the best rescue opportunity.

The application provides a four-rotor unmanned aerial vehicle three-dimensional trajectory tracking control method for sea surface wind wave disturbance, and belongs to the field of trajectory tracking control. The method establishes a four-rotor six-degree-of-freedom dynamics simulation model and adopts a fourth-order Runge-Kutta method to update the state; a multi-unmanned aerial vehicle three-dimensional reference trajectory generation mechanism is constructed; a six-dimensional comprehensive disturbance model containing wave-induced vertical force, gust horizontal force and attitude disturbance torque is established; a PID control law based on position / velocity error is designed in the outer loop, the desired acceleration is generated by combining gain gradual entry and integral anti-windup; an attitude controller is designed to output three-axis torque, and disturbance observation compensation is introduced to improve the anti-disturbance performance; comparative simulation is carried out under different sea state levels, and three-dimensional tracking error and control input are output to verify the control effect.

The application discloses a sea surface wind speed inversion method based on a marine radar image and belongs to the technical field of ocean remote sensing. The application solves the problem of low wind speed inversion precision of the existing method. The technical scheme of the application is as follows: step 1, original radar image sets are obtained by reading radar files offline, each original radar image is processed to obtain the full distance integral area of the counter-wind direction corresponding to each original radar image, and then a function relationship between the wind speed and the full distance integral area of the counter-wind direction is established according to the wind speed when each original radar image is collected; step 2, the full distance integral area of the counter-wind direction of the radar image to be measured is calculated; and step 3, the full distance integral area of the counter-wind direction calculated in step 2 is substituted into the function of the wind speed and the full distance integral area of the counter-wind direction established in step 1 to obtain the sea surface wind speed when the radar image read in step 2 is collected. The method can be applied to sea surface wind speed inversion.

A method, system, device, and medium for sea surface wind speed inversion based on time-delayed Doppler images and Swin Transformer are disclosed. The method involves constructing a time-delayed Doppler image DDM simulation model, outputting DDM simulation images, and building a DDM simulation image dataset. The DDM simulation image dataset is preprocessed. A Swin Transformer wind speed prediction regression model is constructed and trained using the preprocessed DDM simulation image dataset. The trained model is then used to predict and invert sea surface wind speed. A piecewise smooth activation function is designed to control the quality of the predicted wind speed values, thus completing the sea surface wind speed inversion prediction. This invention, by constructing a Swin Transformer wind speed prediction regression model and designing a piecewise smooth activation function, utilizes the self-attention mechanism and hierarchical structure of the Swin Transformer to achieve high-precision inversion over a wide wind speed range, exhibiting stronger robustness and physical interpretability.

The present application provides a kind of sea surface foam thickness remote sensing inversion method and system, for the L-Ka dual-band of sea surface foam coverage, foam thickness is cooperatively inverted, from the multi-band microwave radiation transmission characteristics, utilize the radiation characteristic difference of foam layer under different frequencies, establish the foam brightness temperature prediction model based on microwave band, the model considers the emission and scattering characteristics of the medium in foam layer, the emissivity of different thickness foam layer is calculated using radiation transfer equation.Then, the quantitative relationship between foam thickness and sea surface wind speed is established, by coupling sea surface foam model and wave spectrum model, sea surface foam coverage, thickness inversion is realized.The method and system provided by the present application can break through the limitation of traditional hydrodynamic model, realize large-scale, high spatio-temporal resolution observation of sea surface foam thickness, provide a new observation method for in-depth understanding of sea-air interface dynamics process.

The application discloses a photovoltaic cable for a sea surface wind power system, which comprises copper conductors twisted by a plurality of copper wires, a surface of the copper conductors is coated with an insulating layer, and a sheath layer is coated on the outer surface of the insulating layer; the sheath layer is composed of the following components in parts by weight: ethylene-octene copolymer 50 parts, ethylene-vinyl acetate copolymer 20-40 parts, LLDPE resin 15-30 parts, organic flame retardant 8-20 parts, anti-UV agent 0.3-1 part, irradiation sensitizer 0.5-1.2 parts, lubricant 1-2 parts, antioxidant 0.5-1.5 parts, maleic anhydride 1-3 parts, and oleic acid amide 0.7-2 parts; the irradiation sensitizer is at least one of triallyl isocyanurate, triallyl isocyanurate, and diallyl phthalate. The photovoltaic cable for the sea surface wind power system improves the color stability of the sheath layer of the cable in day-night seasonal changes and improves the weather resistance of the cable according to the harsh use environment of the offshore photovoltaic cable.

This invention discloses a method for sea surface wind vector inversion based on optimal fitting of the wave spectrum of a shore-based GNSS-R system. Relating to the field of microwave remote sensing technology, it addresses the technical problems of existing nearshore GNSS-R technologies, such as ineffective wind direction inversion, difficulty in signal separation, and lack of a synchronous inversion mechanism. The method includes: acquiring direct and reflected signals from a shore-based receiver; separating specular reflection and multi-order Bragg scattering spectral components using the MUSIC algorithm combined with iterative Gaussian fitting; extracting spectral width features from the specular reflection spectral components and extracting the positive-to-negative peak ratio and normalized Doppler frequency ratio features from the Bragg scattering spectral components; constructing a wind speed cost function based on the spectral width features and minimizing this function to invert wind speed; and constructing a wind direction cost function based on the two features and minimizing this function to invert wind direction. This invention enables synchronous wind speed and direction inversion on a shore-based platform, requires no external auxiliary data, effectively extracts weak Bragg scattering components, and exhibits high nearshore inversion accuracy and stability.

This invention discloses a method for correcting incoming wind speed in offshore wind farms based on SAR satellite observations. First, SAR satellite images are preprocessed and masked to remove interference from bright targets such as wind turbines. Then, a high-resolution near-sea surface wind speed is retrieved from the images using an improved ConvNeXtv2 deep learning network. This is then matched with numerical weather prediction (NMR) wind fields, and the amplitude and spatial structure of the NMR wind fields are corrected using the LightGBM model. Finally, the wind shear index is corrected by combining atmospheric elements at the wind height level with the wind speed extrapolation formula, thereby correcting the extrapolation ratio and obtaining high-precision wind speed extrapolation results at the wind turbine hub height. This invention integrates the high spatial resolution of SAR with the continuity of numerical weather prediction, effectively eliminating wind turbine target interference and numerical weather prediction system bias, significantly improving the accuracy of incoming wind speed at the wind turbine hub height, and providing reliable wind field data for offshore wind farm power prediction and safe operation.