36 results about "Bathymetry" patented technology

The invention belongs to the technical field of underwater navigation, and particularly relates to a multi-AUV (Autonomous Underwater Vehicle) collaborative SLAM (Simultaneous Localization and Mapping) method based on multi-beam water depth measurement data, which comprises the following steps: a plurality of AUVs synchronously run in a task area, and a multi-beam depth sounding sonar is respectively used for acquiring local water depth data and generating an internal water depth sub-graph set; each AUV performs sparse processing on the internal water depth sub-graph; the AUV receiving the sub-graph performs interpolation reconstruction on the sparse sub-graph by using a GPR algorithm; each AUV constructs a collaborative SLAM factor graph containing a pushing factor, an internal water depth closed-loop factor, an external water depth closed-loop factor and an inter-AUV distance observation factor based on self navigation data, the internal water depth sub-graph and the external water depth sub-graph; and solving the factor graph through a distributed optimization algorithm, and outputting an optimized pose and a global map of each AUV. According to the method, the positioning precision and reliability of the underwater SLAM are remarkably improved.

The invention discloses an ALB sounding point cloud filtering and recovering method for complex terrains such as a submarine abrupt slope, belongs to the technical field of data processing, and solves the problems that the I-class misjudgment rate is high, topographic features are smoothed or weakened and effective point clouds at the submarine abrupt slope are easily filtered out excessively in an existing method. The method comprises the steps of performing sea surface elevation estimation and separation processing on original point cloud, processing underwater point cloud based on a self-adaptive morphology water body filtering method, introducing a recovery mechanism based on hyperboloid fitting, recovering abrupt slope area point cloud misjudged as a water body noisy point through residual analysis, and obtaining a water body noisy point. According to the method, a fine processing strategy of filtering first and then recovering is adopted, and water body noisy points are accurately removed through self-adaptive morphological filtering in the earlier stage in combination with grid reference surface and spatial multi-dimensional binary tree index neighborhood analysis. A recovery mechanism based on hyperboloid fitting is introduced, and the abrupt slope area point cloud misjudged as the noisy point is recovered through residual analysis. And the misjudgment rate in a submarine abrupt slope area is effectively reduced.

This invention discloses a design method for a deep-sea in-situ fine-scale detection framework based on acoustic-optical remote sensing and VR technology. The main steps include: (1) studying the structure of the photon-counting lidar scanning system and the dynamic geometric relationship between the mother ship and the submersible, and constructing a calculation model for the lidar bathymetry point coordinates in the WGS84 spatial rectangular coordinate system; (2) considering the submersible's attitude, and based on the ray-tracking model and the geometric relationship between the mother ship and the submersible, constructing a calculation model for the multibeam bathymetry point coordinates in the WGS84 spatial rectangular coordinate system; (3) fusing the lidar and multibeam bathymetry points to construct a seabed topographic map; (4) proposing a development scheme and detection method for a deep-sea functional imaging spectrometer; and (5) constructing a VR environment for the deep-sea target survey area using a three-dimensional seabed topography model, rendering technology, and binocular stereo imaging technology. Through these steps, deep-sea in-situ fine-scale detection based on acoustic-optical remote sensing technology and the construction of a VR environment for the survey area can be achieved.

This invention relates to the field of laser water depth detection, specifically to a method for compensating for water surface fluctuations in laser depth measurement. This method addresses the inaccuracy and surface fluctuation interference issues inherent in traditional depth measurement techniques in extremely shallow waters. By using a turbidity sensor, an IMU zero-bias compensation sensor, and a laser displacement sensor, the measured water depth is corrected to improve measurement accuracy. This solution significantly enhances the stability and accuracy of depth measurement in extremely shallow waters, possesses strong environmental adaptability, and offers broad application prospects.

Described are systems and techniques for processing airborne lidar bathymetry (ALB) data. A plurality of lidar frames can be obtained, each associated with a respective measurement swath within a surveyed area and a first coordinate system corresponding to an ALB system. A plurality of multibeam echo sounder (MBES) bathymetry data points can be obtained, indicative of seabed locations within the surveyed area, and associated with a second coordinate system corresponding to the surveyed area. A subset of corresponding MBES data points can be determined for the respective measurement swath of each lidar frame based on projection between the first and second coordinate systems, and can be used to generate annotation information indicative of seabed locations within each lidar frame. A machine learning network can be trained to identify seabed bathymetry features within input lidar frames, using training data comprising the plurality of lidar frames and the generated annotation information. Unlocking insights from Geo-Data, the present invention further relates to improvements in sustainability and environmental developments: together we create a safe and liveable world.

The invention provides a shallow sea underwater terrain inversion method and system based on a video SAR, and belongs to the synthetic aperture radar signal processing field and the ocean remote sensing application field, and the method comprises the steps: obtaining multi-frame SAR data with sea wave characteristics in a shallow sea area based on the video SAR; registering the obtained multi-frame SAR data with characteristics in the shallow sea area to obtain a video SAR image; every two frames of video SAR images are uniformly divided into sub-image blocks in an overlapped mode, and the wave lengths and the wave velocities of the sub-image blocks are estimated respectively; inverting water depths corresponding to all the sub-image blocks by using a linear dispersion relationship to obtain multiple groups of underwater terrain inversion results; and fusing multiple groups of underwater topography inversion results, and taking the result as a final underwater topography detection result of the research area. According to the invention, more refined water depth inversion can be realized.

This invention relates to the field of beam fusion technology and discloses a method for underwater topography mapping of irregular waters based on multi-beam fusion. The method includes: acquiring multi-voyage bathymetry data of the target irregular waters using a multi-platform multi-beam bathymetry system such as a patrol vessel or unmanned survey vessel; after sound velocity profile correction, attitude correction, and tidal level calculation, unifying the data to the same spatiotemporal reference and Cartesian coordinate system; constructing an initial underwater topography digital elevation model within the irregular water area using Gaussian weighted interpolation; delineating the influence area centered on the hydraulic structure; decomposing the local topography into background topography and scour residual; performing polar coordinate transformation and angular topographic spectrum analysis within the influence area to calculate the axisymmetric morphological dominance index of the scour pit; constructing a topography shaping factor based on the axisymmetric morphological dominance index of the scour pit, the maximum scour depth, and the influence radius; frequency-domain modulation of the Fourier coefficients; and reconstructing the corrected local topography to obtain the final underwater topography DEM.

To provide a rubble leveling device capable of improving rubble leveling accuracy by a weight lifted by a floating crane.SOLUTION: A rubble leveling device 100 comprises a sounding information acquisition unit 112 that acquires sounding information. The rubble leveling device 100 comprises a LiDAR information acquisition unit 113 that acquires LiDAR information acquired by a LiDAR device. The rubble leveling device 100 comprises a positioning oscillation information acquisition unit 114 that acquires positioning oscillation information indicating oscillation of a floating crane 10. The rubble leveling device 100 comprises a three-dimensional point group data generation unit 115 that generates three-dimensional point group data of a weight on the basis of the LiDAR information. The rubble leveling device 100 comprises a weight position calculation unit 116 that calculates position information of the weight on the basis of the three-dimensional point group data and the positioning oscillation information. Further, the rubble leveling device 100 comprises a topography model generation unit 117 that generates a topography model indicating an underwater state on the basis of the sounding information and the position information of the weight.SELECTED DRAWING: Figure 5

An adaptive fuzzy integral differential line-of-sight (AFIDLOS) method for path tracking of a laser bathymetry unmanned surface vehicle is provided. The AFIDLOS method includes determining an AFIDLOS manner, establishing an unmanned surface vehicle control model, determining an LQR heading controller, and determining a path tracking manner by combining the AFIDLOS manner and the LQR controller to realize a path tracking control of an unmanned surface vehicle in a microcontroller. The method for path tracking is verified in experiments. Experimental results show that, compared with a traditional LOS guidance rate, 79.85% reduction in overshoot, and 55.32% shorter adjustment time are achieved by the AFIDLOS manner in simulation experiments, while 9.5% of an average lateral error is reduced in the Beihai Beach experiment, and an overlap rate between strips reaches 30% in the Pinqing Lake experiment, which meets the accuracy requirements of bathymetric mapping.

The invention discloses an airborne laser radar depth sounding land waveform classification method, and relates to the technical field of marine surveying and mapping and remote sensing information processing, and the method comprises the steps: obtaining airborne laser radar depth sounding (ALB) full waveform data of a target region; the full waveform data at least comprises infrared laser waveform data and waveform data of a deep water channel and a shallow water channel of blue-green laser; based on the amplitude characteristics of the infrared laser waveform data, clustering the collected laser foot points for the first time to obtain an initial classification result containing a water body point set, a land point set and an undetermined point set; fusing the three-dimensional space position information of the laser foot points, and carrying out space density clustering analysis on the to-be-determined point set; by adopting a three-stage progressive strategy of waveform amplitude preliminary screening, spatial relationship correction and multi-feature fusion fine judgment, the classification uncertainty of different layers is solved layer by layer, misclassification caused by noise, special ground features and boundary fuzzy regions is effectively reduced, and the overall classification precision is remarkably improved.

Methods and systems for determining depths of a waterway are disclosed. A system may receive depth data measured by a vessel in a waterway, the depth data being a part of crowdsourced depth data measured by multiple vessels. To achieve a standardization of the depth data measured by multiple vessels, the system may transform the depth data to elevation data, the transforming based on an elevation standard and a location having an established elevation. The location may be determined from a bathymetric survey that includes the established elevation, a fixed point in the waterway, or a crossing of a track of the vessel with a track of another vessel having the established elevation. Waterway depths, universally based on the elevation standard, may be determined based on the elevation data.

The present invention discloses a method for ocean surveying and mapping based on multi-beam bathymetric correction, belonging to the technical field of ocean surveying and mapping. This method uses a multi-beam sonar array, an acoustic tomography transceiver array, and a laser Raman probe to collect bathymetric echo signals, acoustic wave propagation delay data, and temperature data. This method then fuses these data to construct a dynamic refractive index field model, uses an adaptive variable step-size algorithm to correct for acoustic ray refraction distortion, and performs weighted distribution and data fusion on spatiotemporally adjacent beams to obtain high-confidence water depths and generate bathymetric topographic maps. This method solves the refraction distortion problem through multi-source data fusion, dynamically optimizes the acoustic ray tracking step-size, and uses weighted fusion to suppress noise interference, significantly improving the accuracy and reliability of topographic mapping in complex environments such as deep-sea hydrothermal areas.

The present invention relates to the technical field of dynamic draft data processing for survey vessels, specifically disclosing a method for calculating the dynamic draft of a survey vessel based on shipborne GNSS geodetic height. The method comprises the following steps: S01, acquiring real-time shipborne GNSS geodetic height data; S02, correcting the GNSS geodetic height data based on synchronized data collected in real time by a multi-beam bathymetry system to obtain necessary data containing only the dynamic draft and water level of the survey vessel; S03, adding Gaussian white noise to the to-be-decomposed signal contained in the necessary data based on an ensemble empirical mode decomposition method to alter the distribution of extreme points in the original sequence, summing the IMF components obtained each time, and extracting the average value; S04, after ensemble empirical mode decomposition, extracting water level information based on the period of each characteristic component. This invention improves operational efficiency, reduces project production costs and the technical level requirements of technicians, is simple to operate, and achieves high accuracy in dynamic draft calculation.

The invention provides a small sample shallow sea reef detection method based on airborne LiDAR sounding data, and belongs to the technical field of marine surveying and mapping. Original waveform data are processed and analyzed for airborne LiDAR sounding data, and waveform and topographic features are extracted; based on a Relief-F feature optimization model, high-contribution-rate features are screened out, the contribution rate serves as the weight, and a sample set is constructed for feature images through normalization; a small sample training module combining sample expansion and meta-learning is provided, a support set is diversified and enhanced, and a global parameter initialization strategy of meta-learning is combined, so that the generalization and rapid adaptive capacity of the detection method under small sample conditions is enhanced; then, a two-dimensional parallel attention mechanism module is constructed, a network neck structure is established, and parallel optimization is performed through a channel and a space attention mechanism; the information perception capability is enhanced, the problems of low precision and small samples in shallow sea underwater reef detection are effectively solved, and effective technical support is provided for ship navigation and ocean engineering construction.

This invention provides a method and system for shallow water depth inversion based on multi-temporal satellite imagery guided by laser bathymetry. The method includes: extracting water body pixels from Sentinel-2 imagery; extracting water depth photons from satellite-borne laser bathymetry data and performing refraction correction to obtain water depth values ​​along the orbital direction; utilizing the strong correlation between the water depth values ​​along the orbital direction and the reflectivity of the blue and green bands of Sentinel-2 imagery to calculate multi-temporal image fusion weights and generate a weighted fused image; based on water column layer-by-layer inversion and / or seabed classification inversion strategies, dividing the weighted fused image into multiple homogeneous regions according to the water penetration capabilities of blue and green light; using LLM and / or LRM to invert water depth layer by layer in the multiple homogeneous regions; and fusing the results of different regions through a buffer zone to obtain the water depth inversion result for the entire shallow sea area. This invention can achieve high-precision and high-stability shallow water depth inversion.

An apparatus for artificial intelligence (AI) bathymetry is disclosed. The apparatus includes a sonic unit attached to a boat, the sonic unit configured to generate a plurality of metric data as a function of a plurality of ultrasonic pulses and a plurality of return pulses. An image processing module is configured to generate a bathymetric image as a function of the plurality of metric data, identify, as a function of the bathymetric image, an underwater landmark, and register the bathymetric image to a map location as a function of the underwater landmark. A communication module is configured to transmit the registered bathymetric image to at least a computing device. An autonomous navigation module is configured to determine a heading for the boat as a function of a path datum and command boat control to navigate the boat as a function of the heading.

The present invention relates to the field of multi-beam bathymetry technology, and in particular to a multi-beam point cloud filtering method for adaptive terrain trends. The method comprises the following steps: obtaining original multi-beam Ping data, extracting the attributes of each beam point in each Ping, and obtaining a beam point attribute data set; performing multi-threshold condition screening on the beam point attribute data set, and eliminating abnormal beam points to obtain a preliminary filtered point cloud data set; performing linear interpolation on the inter-Ping gaps in the eliminated area of ​​the preliminary filtered point cloud data set to obtain a complete point cloud data set; extracting the central beam point data of three adjacent survey lines based on the complete point cloud data set, and performing coordinate transformation and fitting modeling on the central beam point data to obtain a long-wave term function model. The present invention accurately eliminates anomalies, repairs gaps, and corrects system errors through an automated process, thereby achieving high-precision restoration and real-time processing of multi-beam point cloud data, and improving the consistency and reliability of bathymetry results.

This invention discloses an anomaly cleaning method for multibeam bathymetry point clouds, belonging to the field of data cleaning technology. It includes: acquiring multibeam bathymetry data to obtain a multibeam bathymetry point cloud dataset; performing data augmentation on the multibeam bathymetry point cloud dataset based on a depth-beam adaptive augmentation method to obtain a training dataset that conforms to the physical error laws of multibeam bathymetry; constructing a planar neighborhood local self-attention network to detect point cloud anomalies; training the planar neighborhood local self-attention network using the training dataset; and using the trained planar neighborhood local self-attention network, employing a hierarchical iterative threshold strategy to clean the original point cloud to be detected. The samples generated by this invention more closely approximate the real marine environment, thus enabling the trained model to possess strong generalization capabilities across water depths and incident angles. Simultaneously, modeling the Ping-Beam structural features of the point cloud effectively achieves automated, high-precision processing of multibeam data under complex sea conditions.

This invention belongs to the field of marine acoustic detection and remote sensing technology, and discloses a method and system for inverting the abundance of deep-sea mixed sediments based on bottom echo data. The method involves preprocessing the bottom echo waveforms of multibeam bathymetry data to obtain a bottom echo sequence; extracting features from the bottom echo sequence waveforms and concatenating these features to the corresponding bottom echo waveforms to form a new waveform sequence; fusing the enhanced waveform sequences to construct an observation matrix Y; decomposing the observation matrix Y into an endmember waveform matrix H′ and an abundance distribution matrix W′, and introducing a minimum volume constraint during the decomposition process; adding a spectral reconstruction error term based on dynamic time warping to the loss function; iteratively optimizing H′ and W′ using gradient descent or multiplicative update rules until convergence; and obtaining the endmember waveform H′, which represents the acoustic response waveform of typical sediment types, and the abundance matrix W′, which reflects the mixing ratio of each endmember at different sampling points, demonstrating high classification accuracy.

The present invention relates to the field of marine geological exploration technology, and specifically to a method for identifying and dating submarine landslides based on big data analysis. The method comprises the following steps: S1, collecting multi-source data such as multi-beam bathymetry, sidescan sonar, and shallow stratigraphic profiles, constructing a dynamic weight allocation model, and fusing these data to generate a three-dimensional terrain model; S2, extracting slope abrupt change zones and acoustic chaos zones based on the terrain model as initial boundaries, verifying the validity of these boundaries by combining shear wave velocity difference ratios, introducing turbidity correction coefficients, and outputting the final landslide region; S3, extracting profile sequence features and constructing a feature vector group. This is then combined with benthic foraminifera oxygen isotope data from core samples to establish a mapping table, and using a matching algorithm to output the age interval of the sedimentary unit. The present invention achieves high-precision identification of submarine landslides and intelligent dating of sedimentary units through multi-source data fusion, intelligent landslide boundary correction, and sequence-fossil combination matching.

This invention discloses a method and device for detecting weak signals in spaceborne lidar depth sounding that takes into account terrain continuity. It is used in a two-stage depth photon extraction method based on terrain continuity constraints. After underwater photon extraction, the method reduces density differences along the track through point cloud homogenization and scaling transformation, laying the foundation for subsequent two-stage underwater photon extraction. The first stage uses a globally adaptive density threshold to extract high-reliability underwater terrain photons. In the second stage, weak underwater terrain photons are recovered by propagating terrain continuity constraints from the high-reliability underwater terrain photons, ultimately obtaining a complete depth point cloud data map displaying the seabed topography. This method utilizes terrain continuity as a strong constraint and further improves the density distinction between weak depth signals and noise by using an enhanced density index. It can robustly recover valuable weak signals that traditional methods often miss in complex environments with high-density noise and sparse signals.

This invention discloses a siltation early warning method based on the fusion of towed sonar and multi-source hydrological parameters, belonging to the field of underwater topographic monitoring and engineering safety early warning technology. The method first plans the survey lines for the target area and simultaneously collects multibeam sonar bathymetry data, CTD multi-parameter data, platform attitude data, tow cable status data, positioning and navigation data, and time synchronization information during towed platform operation. Then, it performs time alignment, outlier removal, missing value compensation, and noise suppression on the multi-source data. A sound velocity profile is constructed based on the CTD multi-parameter data, and the sound velocity of the multibeam sonar bathymetry data is corrected. Geometric compensation is also performed by combining platform attitude data, tow cable status data, and positioning and navigation data. Finally, the corrected bathymetry data is... The results are mapped to a preset coordinate system to construct an underwater cross-section model, a grid elevation model, or a bed sediment point cloud model for the current time period. Historical baseline models are retrieved for coordinate unification, overlapping area identification, and adaptive registration. Based on this, elevation difference analysis, slope change analysis, regional thickness statistics, and calculations of sediment thickness, changed area, and sediment volume are performed. Furthermore, short-term trend predictions are made by combining historical observations from multiple time periods with environmental driving factors such as flow velocity, tide level, temperature, salinity, turbidity, and sediment content. Finally, a warning level is generated based on a risk threshold, and warning information is output. This invention improves the comparability of multi-time period towed sonar measurement results and the accuracy of sediment identification, enabling continuous monitoring, quantitative analysis, and proactive warning of bed sedimentation status in target areas. It is applicable to port channels, inland waterways, estuaries, reservoir areas, and near-shore engineering areas.

This invention relates to the field of marine engineering surveying technology, specifically providing a method for topographic correction in marine engineering surveying based on multibeam bathymetry. By synchronously acquiring multi-source data, a ground vibration-sound velocity coupling model is constructed to generate a dynamic sound velocity correction term. Static sound velocity profiles, internal wave disturbance terms, and sound velocity correction terms are fused to establish a spatiotemporally evolving time-shifted sound velocity field. Based on the ship's attitude and the time-shifted sound velocity field, dynamic spatial repositioning calculation is achieved through a dual-axis decoupled rotation matrix. Spatial adaptive filtering technology is employed to suppress tunneling noise. The topographic deformation rate is calculated using continuous periodic data, and a deformation threshold is dynamically set using soil mechanics parameters to trigger graded safety warnings. A high-precision three-dimensional topographic model eliminating sound velocity errors and noise interference is output. This invention solves the problems of insufficient compensation for geological activity interference, inadequate suppression of tunneling noise, and large dynamic environment repositioning errors in traditional surveying, significantly improving the reliability of topographic measurements in complex sea areas.

The present invention provides a method and system for remote sensing detection of shallow-water multi-band bottom reflectance. This method combines four-band multispectral data and ICESat‑2 laser bathymetry data. By selecting characteristic points and iteratively searching for the optical parameters of the water body, the method uses the exponential relationship between the semi-analytical bottom reflectance and the spectral parameters to globally constrain the radiation transfer model, and constructs a quadratic polynomial model between the chlorophyll concentration of the characteristic points and the remote sensing reflectance of the blue and green bands, achieving large-scale rapid inversion of the optimal water body attenuation coefficient; further combined with the surface remote sensing reflectance product, a climatological monthly average deep-water reflectance data set is constructed, achieving large-scale and efficient detection of optical shallow-water multi-band bottom reflectance without the support of measured data. The present invention improves the application efficiency of four-band multispectral data, which has the richest historical data. The method is highly practical and has important significance for the protection and management of the benthic ecology of shallow-water coral reefs.

This invention provides a method, medium, and apparatus for power optimization control of a multibeam bathymetry sonar transmitting array. The method includes: S1, obtaining the natural directivity of the transmitting array: designing a semi-cylindrical multibeam sonar transmitting array with N elements evenly spaced at angles and obtaining its natural array pattern P(θ); S2, generating a power optimization function based on the scattering loss distribution: assuming a scattering loss distribution of Q(θ) under a certain seabed medium, generating a power optimization function S(n) for different elements based on the scattering loss distribution Q(θ); S3, weighting the signals of each element of the transmitting array using the power optimization function S(n) to obtain an optimized pattern P2(θ), ensuring that this pattern P2(θ) can cancel out the scattering loss Q(θ), thereby achieving wide transmission coverage. This invention can achieve uniform echo signal energy in all directions, improving the sonar coverage range.

The invention provides an adaptive robust submarine topography tracking method and system for multi-beam sounding, and the method comprises the steps: S1, predicting the depth of a next to-be-detected beam based on the historical successfully detected beam information, and setting a main search gate and an auxiliary search gate; s2, performing primary detection in the main search gate, if the primary detection succeeds, marking a current beam as a normal point, and executing a step S4, and if the primary detection fails, executing a step S3; s3, performing secondary detection in the auxiliary search gate, if the secondary detection succeeds, marking the current beam as a recovery point, and executing the step S4, and if the secondary detection fails, marking the current beam as an invalid point, keeping the current historical queue unchanged, and executing the step S4; and S4, outputting the depth value and the state mark of the current wave beam, judging whether a to-be-processed wave beam exists or not, and if so, repeating the steps S1 to S4. According to the method, by introducing a secondary failure protection detection and intelligent recovery mechanism, the violent fluctuation of the submarine topography can be effectively handled, and the optimal balance of efficiency and robustness is realized.

The invention belongs to the technical field of marine surveying and mapping, discloses an airborne LiDAR sounding point cloud filtering method and system for shallow sea reef terrain, and aims to solve the problems that a coastal zone reef beach area is large in topographic relief and complex in water environment, and excessive filtering and residual noise points are prone to occurring in a traditional filtering algorithm. The invention provides a multi-stage and multi-feature constraint filtering method and a multi-stage and multi-feature constraint filtering system. Accurate identification and elimination of sea surface point clouds are realized based on DBSCAN clustering of echo intensity and point cloud density constraint and triangulation network broken line segmentation; secondly, a robust statistical model containing spatial distance, normal consistency, plane residual error and curvature characteristics is utilized, and a Mahalanobis distance is combined to optimize an SOR filter, so that discrete noisy points of a water body are effectively removed; and finally, performing direction slicing and curve fitting on the reef terrain point cloud by adopting a progressive profile analysis method to realize terrain contour correction and detail recovery. According to the method, the phenomena of wrong filtering and filtering leakage can be remarkably reduced in a complex shallow sea environment, and the integrity and continuity of terrain point cloud are improved.

The invention relates to the technical field of multi-beam sounding, in particular to a multi-beam point cloud filtering method adaptive to a terrain trend. The method comprises the following steps: acquiring original multi-beam Ping data, and extracting the attribute of each beam point in each Ping to obtain a beam point attribute data set; performing multi-threshold condition screening on the wave beam point attribute data set, and removing abnormal wave beam points to obtain a preliminary filtering point cloud data set; performing linear interpolation on the inter-Ping vacant points of the rejected area in the preliminary filtering point cloud data set to obtain a complete point cloud data set; extracting central beam point data of three adjacent measuring lines based on the complete point cloud data set, and performing coordinate conversion and fitting modeling on the central beam point data to obtain a long-wave term function model. According to the invention, abnormity is accurately eliminated through an automatic process, vacancies are repaired, system errors are corrected, high-precision restoration and real-time processing of multi-beam point cloud data are realized, and consistency and reliability of sounding results are improved.

The invention relates to a submarine pipeline bare leakage anti-interference segmentation method based on multi-beam sounding data, and belongs to the technical field of ocean engineering detection, and the method comprises the steps: calculating the depth gradient amplitude and elevation anomaly of the preprocessed multi-beam sounding data, and screening out candidate points with pipeline features to form a candidate region set; calculating micro-scale surface features, macro-scale profile morphological features and relative elevation features of the candidate region set to construct feature vectors; inputting the feature vector into a gradient lifting decision tree model to output a refined segmentation result of pipeline leakage; and inputting the refined segmentation result into the trained double-branch feature fusion network to obtain an optimized segmentation result. According to the method, multi-scale geometric morphology analysis, physically-guided deep learning and multi-source geographic information verification are combined, so that the difficulty in distinguishing pipeline exposure and various interferents in a complex seabed environment is effectively solved, and the segmentation accuracy, robustness and engineering practicability are remarkably improved.

The present invention relates to a wave pool for surfing comprising a wave generation system formed by individual modules, the movement variables of which are controlled sequentially as a whole and individually via a centralised control system to push a mass of water forward and backward using partially submerged gates. Depending on the geometry of the pool, these two movements can be used to provide two waves with identical characteristics on each side of the pool. Alternatively, a single side can be used in conjunction with the modules located at a 45° angle to maximise the energy of each movement, provide an increasingly longer wave, and have pools with considerable lengths. Once movement is generated, the pushed mass of water travels a ride length before reaching the reef that is arranged at a diagonal angle to the trajectory of said water, and, upon encountering same, the wave breaks. This break gives rise to a wave that can differ depending on its initial characteristics, which exist throughout the bathymetry, which exhibits specific fixed characteristics. The shape of the pool is contained by a structure that is defined to achieve harmony in terms of frequency and quality of the generated waves and that sends the water resulting from the generation of waves to a mitigation channel located at each end of the pool. The mass of water resulting from these movements is collected in this channel and prevents water reflection and turbulence, in turn allowing the water to return naturally by gravity to maintain the level of water in the pool. A tank outside the pool can be used to raise or lower the water level, simulating the effect of a tide in a controlled environment based on the type of waves required, allowing different configurations of both individual and group waves for different surfer skill levels such as beginner, intermediate and advanced.