292 results about "Sea level" patented technology

The invention provides a floating object track prediction method, device and equipment and a storage medium, and relates to the technical field of marine environment scientificity, and the floating object track prediction method comprises the steps: obtaining the state information of a target floating object and the information of the environment where the target floating object is located; processing the state information and the environment information by using a Lagrange particle tracking method, and determining a first moving trajectory of the target floating object; the first moving track comprises displacement in a three-dimensional direction; correcting the first moving trajectory based on a biological influence factor to obtain a target moving trajectory; the biological influence factors comprise displacement of the target floating object in the direction perpendicular to the sea level caused by the gathering effect of biological fouling or ocean snow, and the loss rate of the target floating object in the running process. According to the invention, the Lagrange particle tracking method is utilized to realize accurate tracking of the target floating object in the transportation process in the ocean three-dimensional space, and the accuracy of simulating the migration path of the target floating object is improved.

The invention belongs to the technical field of ocean observation, and discloses an ocean wave field reconstruction method and device based on binocular vision. An ocean wave field reconstruction method based on binocular vision comprises the steps that internal parameters of a camera are calibrated through a Bouguet calibration algorithm, a binocular camera provided with an IMU sensor is used for collecting images and pose information, feature points are extracted through an SURF algorithm, feature matching is completed under a game theory framework, and abnormal points are removed through an RANSAC algorithm. Then, camera parameters are calculated based on an eight-point method, and the camera parameters and three-dimensional point coordinates are optimized through an SBA algorithm; thirdly, generating a disparity map by adopting epipolar correction and an SGM algorithm, and performing morphological processing on the disparity map; and the processed image is subjected to triangulation to generate a three-dimensional point cloud, and filtering is carried out. And finally, estimating a sea level position through an RANSAC algorithm, and optimizing a result through a least square method to complete three-dimensional reconstruction of ocean waves.

The invention provides a sea level rise influence risk assessment method, medium and system, and belongs to the technical field of risk prediction and assessment, and the method comprises the steps: firstly, analyzing historical sea level data through wavelet decomposition and an ARIMA model, and predicting a future change trend; meanwhile, a digital elevation model is established by using Kriging interpolation, and dynamic change of the terrain is described by combining real-time monitoring data. Secondly, identifying key infrastructures and influence factors by applying an analytic hierarchy process and principal component analysis, and extracting key features through singular value decomposition; and based on a singular value decomposition result, constructing a sensitivity and vulnerability matrix, calculating the exposure degree in combination with Monte Carlo simulation, and comprehensively evaluating the regional vulnerability. Furthermore, asset loss is predicted by applying a random forest algorithm, economic loss is calculated, and an ecological vulnerability index matrix is established to evaluate ecological influence. And finally, realizing quantitative risk assessment by adopting fuzzy comprehensive evaluation of an entropy weight method and a risk prediction model of support vector regression.

The invention discloses a method for predicting the change of a high-resolution three-dimensional temperature and salt field by using multi-source ocean data. According to the method, three-dimensional temperature and salinity forecasting is converted into ocean surface element forecasting in the horizontal direction and joint inversion of subsea surface temperature and salinity, firstly, a sea surface temperature forecasting model and a sea level anomaly forecasting model are constructed by using low-resolution satellite remote sensing data and using an M-ViT model; carrying out difference value matching on the predicted sea surface temperature and sea level anomaly prediction data and high-resolution undersea three-dimensional thermohaline data, and constructing an undersea three-dimensional thermohaline prediction model by using a SimVP-gsta model to realize undersea three-dimensional thermohaline high-resolution prediction on the sea surface temperature and sea level anomaly low-resolution data. According to the method, the data size problem caused by stacking of high-resolution historical data is avoided, the prediction time efficiency can be effectively improved on the premise that the time resolution and the space resolution of a prediction result are not reduced, and the ocean temperature and salinity can be accurately predicted in most layers.

The invention discloses an ozone concentration forecasting method based on peak value perception and influence factor analysis, which utilizes continuous online observation data and meteorological observation data of multi-site pollutants, processes abnormal and missing data, and combines with boundary layer height, radiation and sea level air pressure provided by an ECMWF meteorological forecasting product to forecast ozone concentration. Building a high-quality Yunnan region large database for supporting deep learning according to hour-scale meteorological numerical simulation data of vertical wind speed, and building an ozone forecasting model based on influence factor analysis and peak value perception; capturing a global dependency relationship among historical meteorology, pollutant data and an ozone long-time sequence and a nonlinear relationship between ozone and an influence factor, so that the model can better understand context information and a related mechanism influencing ozone generation; the defect of long-time sequence dependence of a traditional deep learning method is overcome, the influence of influence factors on ozone concentration prediction is ignored, and the accuracy of ozone prediction is improved.

The invention provides a high-temporal-spatial-resolution full-profile real-sea accurate corrosion test method and system, and the method comprises the steps: dividing the sea level into three layers of monitoring regions, namely an atmospheric near-sea-level layer, a sea-gas boundary layer and a seawater mixing layer, deploying corresponding sensor arrays in each monitoring region, and synchronously collecting the environmental parameters of each layer in real time; a standard corrosion coupon and a corrosion monitoring sensor for monitoring the local corrosion state of the sample are arranged in each monitoring area; performing space-time alignment on the acquired data to form an environment-corrosion strong association data set; an atmosphere-ocean coupling forecasting system is constructed, simulation and prediction of future environmental parameters are achieved, simulation results serve as input variables of a corrosion prediction model, and a material corrosion life prediction model is established in combination with historical test data. According to the invention, synchronous monitoring of multi-dimensional environmental parameters and material corrosion data within a range of 30 meters above and below the sea level can be realized, and an accurate basis is provided for material selection and corrosion prediction of marine equipment.

The invention discloses an ocean mesoscale vortex segmentation method based on edge attention, and relates to the field of semantic segmentation. The problems that an existing model is poor in vortex edge information extraction effect, and the shape and the position of the segmented ocean mesoscale vortex are not accurate enough are solved. The method specifically comprises the following steps of (1) obtaining sea level abnormal data SLA, performing visualization processing on the SLA to generate a sea mesoscale vortex image data set, performing labeling, dividing image data into a training set, a verification set and a test set, and performing preprocessing by using image enhancement operation; (2) creating a network model, inputting the preprocessed ocean mesoscale vortex image data set into an ocean mesoscale vortex segmentation network based on edge attention, namely an EGA-AFFUNet model, for training, and segmenting ocean mesoscale vortexes in the ocean mesoscale vortex image data set; and comparing a test result with the vortex label data set on the test set to obtain an evaluation index.

The invention provides an island shoreline erosion risk prediction method based on computer vision, and belongs to the technical field of island shoreline erosion risk analys.The island shoreline erosion risk prediction method comprises the steps that firstly, a high-resolution remote sensing image is obtained, island contour information is extracted, and a shoreline initial model is constructed through a small grid approximation method; generating multi-level grid representation through grid merging operation and storing the multi-level grid representation as a shoreline feature matrix; then collecting a multi-time sequence remote sensing image, calculating a change matrix set of adjacent time points, and analyzing a shoreline evolution mode; establishing a coast erosion kinetic equation model by combining the wave action intensity, the tide amplitude, the sea level rising rate, the geological structure coefficient and the shoreline slope angle; a shoreline change rule is analyzed by applying a map attention grid evolution model, and finally, an uncertainty analysis module is introduced, a multi-scale erosion risk assessment map is generated, a high-risk area is identified and output as a prediction result, so that the technical problem that the complicated island shoreline erosion risk is difficult to accurately predict is solved.

The invention discloses a method for completing an autonomous deep-sea exploration task by a deep-sea cross-domain unmanned aerial vehicle. The method comprises the following steps: determining a target area; taking off to a specified height from the sea level, receiving a task execution command and then flying to a target area; when the relative distance between the current position and the coordinates of the target area reaches a preset value, descending; when it is detected that the device is contacted with seawater, the device dives through gravity; when it is detected that the set depth is reached, the propeller is restarted, and the detection task is executed; after the detection task is completed, the standby battery is rejected and ascends; after leaving the water surface, rising to a specified height and switching to a homeward flight mode; and when the deep-sea cross-domain unmanned aerial vehicle is within the sight distance range, a manual landing task is executed. The invention further discloses the deep-sea cross-domain unmanned aerial vehicle. According to the unmanned aerial vehicle and the method, autonomous switching operation between an air medium and an underwater medium can be realized, and the unmanned aerial vehicle has the capability of autonomously completing detection and water body sampling in an extreme deep sea environment.

The invention discloses a GNSS (Global Navigation Satellite System) water level inversion model, which belongs to the technical field of water disaster prevention and marine environment monitoring, and comprises the following steps: S1, acquiring original data: an SNR (Signal to Noise Ratio) observation value and a GNSS observation value; s2, setting parameters: determining cut-off elevation angle information and azimuth angle information according to the surrounding environment of the shore-based GNSS monitoring station; s3, direct reflection signal separation: selecting IMF components containing main water level information to perform water level inversion and addition output; and S4, solving h by utilizing spectral analysis: analyzing the IMF component segment containing the water level information by utilizing a Lomb-Scargle algorithm to solve a main frequency f, and converting according to a formula to obtain a required vertical reflection distance h. The GNSS water level inversion model has the advantages of global coverage, no need of manual intervention, economy, effectiveness and simplicity and convenience in maintenance, and is suitable for monitoring tides, rivers, lakes and sea level; the accuracy of water level inversion can be improved, and key water level information is prevented from being lost in traditional denoising.

The invention relates to the technical field of mariculture, and discloses mariculture equipment and an offshore wind power system.The mariculture equipment comprises a mounting frame, a net cage and a lifting assembly, a containing cavity is formed in the mounting frame, an opening is formed in the top of the mounting frame, the bottom of the mounting frame is suitable for being arranged in water, and the top of the mounting frame is exposed out of the water surface; one end of the lifting assembly is fixed to the mounting frame, the other end of the lifting assembly is connected with the net cage, and the lifting assembly has a first state for driving the top of the net cage to sink into the sea and a second state for driving the net cage to float out of the sea surface. The distance between the top of the net cage and the average sea level exceeds the maximum wave height, the impact of stormy waves on the net cage can be reduced, the net cage is prevented from being damaged, and after the typhoon is finished, the net cage is driven to restore the original position through the lifting assembly and lifted to the second state of floating out of the water surface through the lifting assembly so that the net cage can be maintained conveniently.

The present invention discloses a water photovoltaic mooring equipment, a mooring system and an installation method. The water photovoltaic mooring equipment includes a buffer component, a sliding component, an adaptive retractable component and a vertically arranged pile frame group. A vertical perforated sliding frame is arranged on the pile frame group. A buffer component is installed at each of the upper and lower ends of the perforated sliding frame. The sliding component is slidably installed in the perforated sliding frame and is located between two buffer components. The sliding component moves up and down in the perforated sliding frame as the sea level rises or falls. The sliding component is connected to the adaptive retractable component, and the adaptive retractable component is connected to a photovoltaic support. The present invention adopts the water photovoltaic mooring equipment, which is suitable for shallow sea areas with complex water environment, large water depth variation range, large morning and evening tidal difference, and large wind and waves.

The invention discloses a PM2.5 forecasting method based on weather circulation and a stability index, and relates to the technical field of air pollution prevention and control, and the method comprises the steps: carrying out the calculation according to the monitoring data of a target region, obtaining a sea level air pressure distance flat field of the target region, carrying out the clustering, and obtaining a weather type; calculating the circulation index value of each meteorological station, and determining the circulation type of the target area; calculating an atmospheric stability index of the target area, and determining a K index interval of the target area; according to the PM2.5 concentration time sequence of each monitoring point position in the target area, establishing a PM2.5 concentration historical data set by matching weather typing, circulation typing and a K index interval of corresponding time; and according to meteorological observation data of a future time period, calculating a weather type, a circulation type and a K index interval of the future time period, and searching a PM2.5 concentration historical data set to obtain a PM2.5 concentration prediction result. The prediction time can be shortened, and the interpretability of the prediction result can be improved.

The invention provides a sea level rise influence risk assessment method based on multi-source data fusion, a medium and a system, and belongs to the technical field of marine disasters. Basic feature data are obtained by constructing a multi-dimensional data acquisition network, nonlinear time series decomposition is performed by applying multi-scale wavelet analysis, and the risk assessment result is obtained by analyzing the nonlinear time series; establishing a prediction model based on a deep learning neural network; determining key vulnerabilities by using a minimum cut maximum flow algorithm; establishing a regional vulnerability scoring system; generating a comprehensive risk assessment matrix by using a Bayesian network ensemble analysis method; and finally, generating an evaluation report by using the coastline adaptability gating model. According to the model, a multi-head time sequence attention mechanism and bidirectional autoregression coding are fused, parameters are dynamically adjusted by adopting a regional adaptability gating weighting function, and accurate evaluation and dynamic tracking of sea level rising influence risks in a complex geographical environment are realized.

To provide a stability maintenance device of a gliding ship capable of suppressing the side-to-side rocking and the rapid rise of a bow elevation angle of a high-speed ship gliding at high speed on the sea surface.SOLUTION: A frame 10 protruding to the rear of a hull and a plate 11 attached to the tip thereof are provided as means and device to suppress the increase in an elevation angle above a certain level when a gliding ship suddenly rises due to high waves and so on. The frame 10 projects horizontally on a deck about half length of a total ship hull length. The plate 11 does not touch the sea surface while the hull sails almost horizontally to the sea surface, but the plate 11 is set to touch the sea surface when the hull suddenly turns upwards. This prevents the bow from jumping-up, that is, the plate 11 suppresses the bouncing of the bow with very strong upward force while the gliding ship sails at the high speed of 100 km / h or over.SELECTED DRAWING: Figure 2

The invention discloses a cooperative control simulation system for an underwater robot and an umbilical cable system, belongs to the technical field of ocean engineering simulation and automatic control, and is used for analyzing system dynamic characteristics in the research and development stage of deep sea operation equipment. Comprising an environment initialization and marine environment construction module, a mother ship model construction module, an underwater robot and umbilical cable coupling module, an instruction generation module, a man-machine interaction control module and a data acquisition and storage module. According to the method, an external interference source with physical authenticity is provided for a control algorithm by combining an energy density function and simulating a composite environment modeling method of a sea level height field and an LOD dynamic grid, and a distributed model prediction control algorithm for uniformly optimizing underwater robot trajectory tracking and umbilical cable tension safety maintenance is constructed; data such as the motion state of the underwater robot and the tension of the umbilical cable can be output in real time, algorithm performance testing is completed in a virtual environment, and dependence on high-cost sea testing is not needed.

The invention belongs to the technical field of ocean laser radar remote sensing detection, and particularly relates to a multiple scattering correction method for a spaceborne photon counting laser radar water body diffuse attenuation coefficient. Comprising the following steps: preprocessing a point cloud signal; calculating an average sea level; extracting a water body photon signal, and performing refractive index correction; performing histogram statistics on the water photons to obtain pseudo echo signals; correcting the transient response of the detector; calculating the attenuation coefficient of the laser radar system; matching a water body diffuse attenuation coefficient; establishing a multiple scattering correction empirical model; and inputting the calculated attenuation coefficient of the laser radar system into the established multi-scattering correction model so as to obtain an accurate water body diffuse attenuation coefficient. According to the invention, data inconsistency caused by multiple scattering can be effectively reduced. Through the improved multiple scatter correction method, the Kd coefficient can be estimated from the laser radar data more accurately, so that more reliable data support is provided for marine scientific research and environmental monitoring.

The invention relates to the field of slope foundation trench excavation, is used for solving the problem that a square grid method has a large error in earthwork excavation amount evaluation of a complex terrain, and particularly relates to a BIM model-based hydraulic reclamation foundation slope foundation trench excavation engineering amount evaluation system. Comprising a scanning generation unit, an elevation analysis unit, an engineering quantity calculation unit, a grid adjustment unit and a result output unit. According to the method, when the earthwork excavation volume is estimated, modeling analysis is carried out on the seabed surface and the excavation position on the basis of the scanned and measured seabed surface through the BIM technology, so that the earthwork volume needing to be excavated is obtained, estimation of the earthwork excavation volume is achieved, and meanwhile, when the earthwork excavation volume is estimated, the earthwork excavation volume is accurately estimated. Different sizes of the square grids are determined according to different flatness degrees of the seabed surface, so that the sizes of the square grids can actively adapt to the flatness degree of the sea level, the convenience of square grid earthwork volume evaluation is ensured, and the accuracy degree of earthwork excavation volume estimation under the complex terrain is improved.

The invention discloses a navigation radar guided photoelectric unmanned ship horizontal plane target detection and positioning method, which comprises the following steps: carrying out zero calibration on a pose measurement device, a navigation radar and a photoelectric device which are deployed on an unmanned ship, and establishing an unmanned ship body coordinate system; obtaining the pose data of the unmanned ship based on the pose measurement equipment; adjusting the pitch angle of the photoelectric equipment based on the unmanned ship rolling data or adjusting the azimuth angle of the photoelectric equipment based on the unmanned ship pitching data, so that the sea level is located in the middle of the picture of the photoelectric equipment; the optoelectronic device receives the orientation of the to-be-tracked target detected by the navigation radar, the navigation radar guides the optoelectronic device to adjust the azimuth angle, and a photoelectric target detection module of the optoelectronic device detects the to-be-tracked target; the photoelectric device locks a to-be-tracked target, and the distance between the unmanned ship and the to-be-tracked target is measured through laser ranging; and determining the longitude and latitude of the to-be-tracked target based on the distance and the unmanned ship pose data. According to the method, the detection accuracy of the unmanned ship on surrounding targets is improved.

The invention provides an aircraft cockpit pollutant concentration monitoring and processing system and method and an aircraft, and relates to the technical field of aircraft cockpit environment monitoring, and the system comprises a monitoring subsystem which is provided with a plurality of sensors, and the plurality of sensors are used for continuously monitoring the pollutant concentration in a cockpit according to a preset time interval; the control subsystem is connected with the monitoring subsystem, and is used for receiving the pollutant concentration data from the monitoring subsystem, correcting the pollutant concentration data by using the measured sea level temperature and pressure data, comparing the corrected actual pollutant concentration value with a preset alarm threshold value, and sending the alarm to the monitoring subsystem. And determining whether to start an alarm according to the comparison result. According to the invention, accurate monitoring and timely warning of the concentration of pollutants in the aviation cockpit are realized.

An apparatus and method for predicting sea level fluctuations are disclosed. The method for predicting sea level fluctuations includes: acquiring past time-series data of past wind stress and past sea level height, determining an optimal length of a time lag of a response function representing a convolution relationship between the past wind stress and the past sea level height and a future sea level height, determining weighting factors of the past wind stress and the past sea level height in the response function to which the determined optimal length of the time lag is applied, and calculating the future sea level height using the response function to which the determined weighting factors are applied.

The invention discloses a sea ice concentration space prediction method based on an MLR model, and the method comprises the steps: calculating lead-lag correlation coefficients between the Wild sea ice concentration and global sea surface temperature, average sea level pressure and surface temperature in different lead periods, so as to determine atmosphere and ocean prediction factors which affect Wild sea SIC; an MLR space prediction model is constructed based on the prediction factors, and SIC data of past 12 months are obtained in the prediction factors; and according to a predicted object, the MLR model carries out multiple linear regression on the SIC of each lattice point in the South Pole Wild sea area according to the six prediction factors, and monthly prediction of sea ice space distribution is realized. According to the method, the Wildhai SIC space monthly prediction model is established based on the MLR statistical method, remote atmosphere and ocean climate signals can be brought into sea ice prediction, the influence of the continuity of atmosphere, ocean and sea ice on prediction can be considered respectively, and the MLR model shows good prediction capacity.

The invention relates to the technical field of marine litter monitoring, and discloses a digital traceability method and system for marine waste, and the method comprises the steps: dividing a target sea area according to a preset rule, and obtaining center influence data corresponding to a center detection region and edge influence data corresponding to an edge region; determining a reflection influence degree value according to the center influence data and the edge influence data, then correcting the initial detection image according to the reflection influence degree value and a color correction algorithm to obtain a target detection image, and finally inputting the target detection image into a pre-constructed garbage classification model to obtain a garbage category. Therefore, the reflection effect of the sea level is effectively identified, the detection error is reduced, the identification accuracy of the garbage target is improved, then path prediction is performed through the garbage distribution diagram and the real-time environment data, tracing processing is performed in combination with the preset path inversion algorithm, and the garbage source is accurately tracked.

The invention relates to the technical field of trestle construction platforms, in particular to an offshore lamplight trestle construction platform which comprises a supporting column, a bridge floor is detachably installed at the upper end of the supporting column, limiting seats are fixedly connected to the upper end and the lower end of the supporting column, the outer surface of the supporting column is sleeved with a movable barrel, the outer surface of the supporting column is further sleeved with a balance weight ring, and the balance weight ring is located below the movable barrel. The outer surface of the movable cylinder is sleeved with an auxiliary ring, the outer surface of the auxiliary ring is rotationally provided with a plurality of extension rods, the outer surfaces of the extension rods are sleeved with floating belts, the floating belts can float above the sea level, the movable cylinder automatically ascends and descends along with the sea level under the buoyancy action of the floating belts, and the communication cylinder is kept in isobaric communication with an external water body. The water column pressure formed in the rising process of sea waves and tides can automatically drive the turbofan in the driving barrel to rotate, so that continuous mechanical energy output can be achieved without additional power, and then the cleaning ring is driven to circularly clean the outer surface of the supporting column.

The invention provides an improved ship target distance measurement method and system, and the method comprises the steps: calculating the radial and tangential distortion parameters of a camera and the internal reference of the camera through a camera calibration technology, building a mapping relation through a distortion automatic correction algorithm, carrying out the reverse mapping calculation, carrying out the restoration and filling of vulnerability pixel points, and generating a distortionless correction image. A deep learning model is used to identify a sea level line in a camera video picture, a distortion automatic correction algorithm is used to correct the sea level line into a horizontal straight line, and according to a camera imaging principle, a proportional relation of a tangent function related to a camera lens direction and a sea level angle is constructed. Automatically calculating the installation angle of the camera by using an arc tangent function; and according to the automatically calculated camera installation angle and the pixel point coordinates of the distortionless correction image, the distance between the position of the opposite ship on the corrected sight line video picture and the world coordinate system of the camera is obtained, the ship target distance measurement improvement is realized, and the method has usability and high precision.

The offshore wind power foundation with the scouring panoramic monitoring function comprises a pile foundation and a sensing device, the pile foundation comprises a first foundation section, the first foundation section is located below the sea level, the first foundation section is partially buried below the seabed surface, the sensing device comprises a plurality of sensing assemblies, and the sensing assemblies are connected with the pile foundation. The multiple sensing assemblies are distributed in the circumferential direction of the first foundation section at intervals, each sensing assembly comprises at least one of a vibration sensor, a force sensor, a position sensor and a light sensor, and the vibration sensors, the force sensors and the position sensors are attached to the circumferential wall of the pile foundation. And the light sensor is embedded below the seabed surface. Panoramic monitoring is carried out on the pile foundation through the multiple sensing assemblies distributed in the circumferential direction by adopting multiple monitoring means so that early warning can be carried out in advance, measures can be taken in time to reduce losses, and stable operation of a wind turbine generator and a booster station can be guaranteed.

The invention relates to an East India Ocean sea level height positive anomaly next year ENSO event forecasting method, and the method comprises the steps: employing the mark parameters of the sea abnormally descending Kelvin wave of the tropical East India Ocean during the India Ocean negative dipole event, such as the sea level height anomaly or the subsurface sea temperature anomaly; comprising the following steps: using near equatorial sea level height or subsurface sea temperature abnormity of Indonesian sea or Western Pacific Ocean, or Kelvin wave of East India Ocean obtained through India Ocean wind field, using a regression forecasting model, and using path change of old flow of Pacific Ocean cotton lancea in winter and spring or Western Pacific Ocean west wind outbreak index as a logic switch, and the starting process and the explosion intensity of the ENSO event can be forecasted. According to the method, spring obstacles can be broken through, and the outbreak and the intensity of the El Nino and La Nina events can be successfully forecasted.

The invention discloses a cloud gypsum rock cycle division and sea level lifting reconstruction method and system based on rock electricity response, and the method comprises the steps: carrying out the recognition of a symbiotic sequence of carbonatite and evaporite based on a logging curve, and summarizing the type of a mineral combination sequence on the logging curve; based on the logging curve and the symbiotic sequence type of the carbonate rocks and the evaporative rocks, high-frequency cycle division containing the evaporative rock sequence is carried out on the test well; based on the high-frequency cycle data of the test well, an accumulated deviation value of the high-frequency cycle data is obtained, and a Fischer diagram of the test well is drawn; and sea level lifting curve characteristic comparison data of the test well is further obtained, and cloud gypsum rock cycle division and sea level lifting reconstruction of the test well are completed. According to the method, high-frequency cycle division and strata series comparison in a small area range are completed by using logging rock electricity response characteristics, and a working basis is provided for work such as fine description, development law and reservoir prediction of the inter-salt thin reservoir.

The invention discloses an air temperature spatial interpolation method considering altitude and four-season change, which comprises the following steps: S1, calculating empirical air temperature direct reduction rates considering altitude and four-season change: calculating air temperature direct reduction rates of all station pairs under each elevation zone in a research area, taking the average value of all the air temperature direct reduction rates under the same elevation band as the empirical air temperature direct reduction rate under the elevation band; and S2, calculation of air temperature raster data considering altitudes and four-season changes: restoring the air temperature data to a unified sea level based on empirical air temperature direct reduction rates under different altitudes and time, and restoring the restored air temperature data of the unified sea level to an original elevation after inverse distance interpolation. The method has the advantages that the accuracy and reliability of air temperature interpolation are improved, the application field of air temperature data is expanded, and more reliable and accurate air temperature data support is provided for research and application of related fields.

The invention discloses a visual inertial pressure fusion underwater pose estimation method based on bidirectional pre-integration, and the method comprises the steps: employing the obtained visual observation constraint of each key frame; the optimization problem constructed by the IMU pre-integration observation constraint and the pressure gauge pre-integration constraint can efficiently and accurately realize the scale of the system state parameters, the speed of the key frame, the zero offset of the acceleration and the initial value of the distance between the pressure gauge and the sea level, realize the initialization of the system state parameters, facilitate the subsequent parameter updating, and improve the system performance. According to the method, the initial parameter is taken as a starting point, the parameter is updated through the maximum posteriori estimation problem constructed by the IMU pre-integration residual error, the pressure gauge bidirectional pre-integration residual error and the visual reprojection residual error, and the underwater pose estimation can be accurately realized.