5 results about "Satellite altimetry" patented technology

The present application relates to the technical field of satellite altimetry and ocean surveying and mapping, and in particular to a GNSS-R sea surface height measurement method based on variable step line segment intermediate frequency data processing, which can effectively improve the measurement accuracy and efficiency, comprising obtaining satellite-borne GNSS-R original intermediate frequency data, calculating mirror reflection points through a new variable step line segment (NVSLSM), generating a delay Doppler map (DDM), and performing sea surface height inversion. Compared with the prior art, the NVSLSM is used to process the mirror reflection points, the calculation time is increased by about 2.04 times and 1.47 times compared with the line segment bisection method and the QH method, and on the premise of ensuring the convergence accuracy, the stable solution can be reached through fewer iteration steps, thereby reducing the calculation cost per sample; in the delay Doppler map generation link, the overall calculation efficiency is increased by more than about 90%.

The present application relates to the technical field of satellite altimetry and ocean surveying and mapping, and in particular to a GNSS-R sea surface height measurement method based on variable step line segment intermediate frequency data processing, which can effectively improve the measurement accuracy and efficiency, comprising obtaining satellite-borne GNSS-R original intermediate frequency data, calculating mirror reflection points through a new variable step line segment (NVSLSM), generating a delay Doppler map (DDM), and performing sea surface height inversion. Compared with the prior art, the NVSLSM is used to process the mirror reflection points, the calculation time is increased by about 2.04 times and 1.47 times compared with the line segment bisection method and the QH method, and on the premise of ensuring the convergence accuracy, the stable solution can be reached through fewer iteration steps, thereby reducing the calculation cost per sample; in the delay Doppler map generation link, the overall calculation efficiency is increased by more than about 90%.

The application discloses a gravity anomaly calculation method, device, equipment, storage medium and product, relates to the satellite altimetry data processing technical field, and the gravity anomaly calculation method comprises: obtaining sea surface height data observed by an altimetry satellite; according to the sea surface height data, a plurality of residual geoid gradients in different directions are calculated; the plurality of residual geoid gradients in different directions are fused by a Bayesian triangular cap method, and an east-west direction component and a south-north direction component of the residual geoid gradient are obtained; and based on the east-west direction component and the south-north direction component of the residual geoid gradient, the marine gravity anomaly of a target region is calculated by a gravity anomaly inversion algorithm. The application solves the technical problems of low utilization rate of multi-direction gradient information of a single altimetry satellite and insufficient component extraction precision, realizes mining and optimization of multi-direction gradient information of a single satellite, and improves the inversion precision of the marine gravity anomaly.

This invention relates to a high-precision tropospheric wet delay estimation method based on optimal interpolation, used for wet delay correction of wide-swath satellite altimetry SWOT observation data over land. The technical approach is as follows: First, initial wet delay values ​​for the swath calculation point and GNSS station are obtained through spatiotemporal interpolation using ECMWF reanalysis data, and the deviation between the initial values ​​and measured values ​​is calculated at the GNSS station. Then, assuming that the water vapor observations at the GNSS station are of equal precision, and in the absence of other external observations, the weighting function is simplified to a weight determined by the equivalent wet distance from the GNSS station to the swath calculation point. Finally, the optimal interpolation method is used to complete the wet delay correction estimation for the swath calculation point. The advantage of this method is that it can transfer the high temporal resolution and accuracy of the measured values ​​from the GNSS station, improve the initial values ​​to obtain a more accurate optimal swath interpolation, and significantly improve the estimation accuracy of wet delay.

The invention discloses a sea surface height anomaly (SLA) multi-step space-time prediction method based on combination of self-attention Transform and a recurrent neural network, and the method comprises a data preprocessing module, a space-time feature extraction module, a prediction generation module and a space reconstruction module, and comprises the following steps: inputting SLA data obtained by satellite height measurement into the data preprocessing module; performing blocking and normalization processing to generate a standardized input sequence; inputting the standardized sequence into a spatio-temporal feature extraction module, extracting global spatial dependency characteristics by using a self-attention Transform module, and extracting dynamic change characteristics of time dimensions through a recurrent neural network; recursively generating SLA prediction data of a plurality of time steps by using a prediction generation module to form a multi-step prediction sequence; and finally, the multi-step prediction sequence is restored to the original spatial resolution through a spatial reconstruction module, and a final prediction result is obtained. According to the method, the self-attention Transform and the recurrent neural network are innovatively combined, the limitation of a traditional method in modeling of the complex spatial-temporal dynamic characteristics of the SLA is broken through, the multi-step prediction precision is remarkably improved, and effective technical support is provided for ocean mesoscale vortex monitoring and environment forecasting.