A port channel underwater terrain monitoring and analyzing system

Abstract

The present application relates to underwater surveying and mapping and channel engineering technical field, specifically relates to a kind of port channel underwater topography monitoring analysis system, including water unmanned measurement module and distributed environment perception module, space-time dynamic compensation analysis module, scouring and silting evolution early warning module;The present application is physically coordinated by constructing distributed multi-source heterogeneous environment perception network and water unmanned measurement platform, introduces unstructured grid driven shallow water dynamics equation and empirical orthogonal function based on surface bottom constraint, realizes the dynamic fitting of measured area instantaneous three-dimensional tidal level surface and the real-time reconstruction of full-depth sound velocity profile, eliminates the systematic height error introduced by the spatial gradient difference of complex water area tidal level and the sound ray refraction of variable density water body from physical model;At the same time, through low-power environmental adaptive sampling and edge hardware time synchronization mechanism, the process of frequent stopping ship to measure sound velocity in traditional operation is avoided, and uninterrupted continuous automatic high-precision measurement is realized.

Description

Technical Field

[0001] This invention relates to the field of underwater surveying and waterway engineering technology, specifically to an underwater topographic monitoring and analysis system for ports and waterways. Background Technology

[0002] Underwater topographic monitoring of ports and waterways is a core foundation for ensuring safe navigation and guiding dredging projects. With the development of multibeam echo sounding technology, the coverage of underwater topographic data acquisition has been significantly improved. However, in complex hydrological environments such as wide ports, estuaries, and brackish water confluences, existing underwater topographic monitoring systems have revealed the following core technical deficiencies in practical engineering applications:

[0003] First, the distortion of the spatial gradient of the water surface leads to significant errors in the instantaneous elevation calculation. Existing multibeam echo sounding systems typically rely on single-point or sparsely distributed shore-based tide gauge stations to provide water level compensation data when converting water depth data to an absolute elevation datum. This traditional compensation model implicitly assumes that the instantaneous water level across the entire survey area is an absolute horizontal plane. However, in actual wide waterways, the combined effects of hydrodynamic factors such as wind stress, seabed friction resistance, and shallow-water tidal waveform variations result in significant spatial gradient differences in the instantaneous absolute water level at different spatial nodes within the waterway. When the surveying vessel is far from the tide gauge station, directly applying the single-point shore-based water level for elevation subtraction inevitably introduces a systematic vertical error that increases with distance, leading to spatial steps or overall tilting of the topographic elevation surface after large-scale splicing.

[0004] Second, the acoustic refraction distortion caused by the high-frequency evolution of denser water cannot be corrected in real time. The edge beam accuracy of multibeam echo sounders is highly dependent on accurate water velocity profile (SVP) data to correct the underwater propagation path of sound waves. In brackish water areas, the temperature and salinity structure of the water is strongly disturbed by tides and density currents, causing the full-depth acoustic velocity profile to exhibit high-frequency, dynamic, and dramatic evolution in both time and space. Existing technologies mainly rely on manually interrupting measurement operations and deploying CTD (Conductivity, Temperature, and Depth) meters from ships to obtain static acoustic velocity profiles, resulting in extremely poor sampling timeliness. When using lagging or spatially offset acoustic velocity profiles to calculate using Snell's law, it is impossible to accurately reproduce the actual bending trajectory of sound waves in non-uniformly denser water layers, leading to serious deviations in the calculation of horizontal ray offset and vertical penetration depth. Ultimately, this results in systematic upward or downward distortion of data at the edge regions of the 3D topographic point cloud. Summary of the Invention

[0005] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a port and waterway underwater topography monitoring and analysis system, including: an unmanned surface measurement module equipped with a multibeam echo sounder and a surface sound velocity meter, used to acquire the coordinates of the measurement area, surface sound velocity and basic depth measurement data; The distributed environmental sensing module includes tide gauges and underlying sound velocity beacons deployed in the waterway, used to collect instantaneous water level and underlying sound velocity data from multiple nodes; The spatiotemporal dynamic compensation analysis module is communicatively connected to the unmanned water surface measurement module and the distributed environmental perception module. It is used to construct a three-dimensional tidal surface based on the instantaneous water level data to extract the instantaneous water level surface for elevation reduction, and to invert the full-depth dynamic sound velocity profile by combining the surface and bottom sound velocity data. It also performs ray tracing compensation on the sounding base data to generate high-precision three-dimensional terrain data. The scouring and silting evolution early warning module is connected to the spatiotemporal dynamic compensation analysis module. It is used to generate a current digital elevation model from the high-precision three-dimensional terrain data, compare it with the benchmark model to generate a terrain difference matrix, and trigger an early warning based on a preset navigation water depth safety threshold.

[0006] Furthermore, the unmanned surface measurement module also includes an attitude positioning subsystem and a time synchronization center; The attitude positioning subsystem includes an RTK-GNSS antenna and an inertial navigation unit that are rigidly connected to each other, and is used to collect the three-dimensional spatial coordinates of the unmanned surface measurement module in real time, as well as instantaneous attitude data including roll angle, pitch angle, heading angle and heave displacement. The time synchronization center is used to provide a unified PPS second pulse signal to the multibeam echo sounder, surface velocity meter and attitude positioning subsystem to generate the basic echo sounding data with an absolute timestamp.

[0007] Furthermore, the basic depth sounding data includes the two-way travel time of the multibeam acoustic wave, the transmit and receive beam angles, and the corresponding instantaneous attitude data; The unmanned surface measurement module also includes an edge control computing unit. The edge control computing unit is used to perform spatiotemporal alignment of the instantaneous attitude data with the two-way travel time of the multi-beam acoustic wave based on the absolute timestamp, and to perform attitude wave compensation on the transmission and reception pointing angles of the depth sounding beam using the attitude data. The compensated data is then packaged and sent to the spatiotemporal dynamic compensation analysis module.

[0008] Furthermore, the distributed environment perception module adopts a non-uniform deployment topology architecture based on hydrodynamic gradient; In the brackish water confluence area and the area of ​​dramatic seabed topography changes of the channel, the deployment density of the tide gauges and bottom sonic beacons is greater than that in conventional straight channel areas. Both the tide gauge and the underlying acoustic beacon have built-in clock synchronization chips, and transmit the instantaneous water level and underlying acoustic velocity data with absolute timestamps and three-dimensional spatial coordinates to the spatiotemporal dynamic compensation analysis module through narrowband Internet of Things or underwater acoustic communication self-organizing network nodes.

[0009] Furthermore, the underlying acoustic beacon integrates a high-frequency acoustic transceiver transducer, a temperature-salinity depth sensing unit, and a low-power wake-up control circuit. The underlying sound velocity beacon is configured with an environment-adaptive sampling mode: under normal conditions, it collects underlying sound velocity data at a first preset frequency; when the temperature, salinity, and depth sensing unit detects that the rate of change of water salinity or temperature exceeds a preset threshold, it triggers the low-power wake-up control circuit to switch the acquisition frequency of the underlying sound velocity data to a second preset frequency higher than the first preset frequency, so as to capture high-frequency hydrological changes under tidal surges.

[0010] Furthermore, the specific steps for constructing the three-dimensional tidal surface and performing elevation reduction in the spatiotemporal dynamic compensation analysis module include: Using the instantaneous water level data from the tide gauges at each node of the distributed environmental perception module, a two-dimensional unstructured spatial grid is constructed with the channel centerline and edge line as boundaries; Real-time wind field data and bottom friction coefficient of the survey area are introduced as boundary driving conditions. The two-dimensional shallow water dynamic equations are solved within the two-dimensional unstructured spatial grid. In the spatiotemporal dimension, an instantaneous three-dimensional tidal surface covering the entire survey area is generated by fitting the equations. ; Extracting the unmanned water surface measurement module in Instantaneous tide level corresponding to the coordinates of the time. The instantaneous tide level value is subtracted from the original elevation data collected by the multibeam echo sounder to complete the spatial gradient error compensation caused by the water level.

[0011] Furthermore, the specific steps for constructing the three-dimensional tidal surface and performing elevation reduction in the spatiotemporal dynamic compensation analysis module include: Using the instantaneous water level data from the tide gauges at each node of the distributed environmental perception module, a two-dimensional unstructured spatial grid is constructed with the channel centerline and edge line as boundaries; Real-time wind field data and bottom friction coefficient of the survey area are introduced as boundary driving conditions. The two-dimensional shallow water dynamic equations are solved within the two-dimensional unstructured spatial grid. In the spatiotemporal dimension, an instantaneous three-dimensional tidal surface covering the entire survey area is generated by fitting the equations. ; Extracting the unmanned water surface measurement module in Instantaneous tide level corresponding to the coordinates of the time. Subtract the instantaneous tide level value from the original elevation data collected by the multibeam echo sounder to complete the spatial gradient error compensation caused by the water level. Combined with the real-time surface sound velocity obtained by the surface sound velocity meter and the underlying sound velocity obtained from the underlying sound velocity beacon. As constraints at both ends, the reconstruction coefficients of each order of empirical orthogonal functions are solved by least squares fitting, and the full-depth dynamic sound velocity profile under the current measurement trajectory is generated by inversion. ; Take the unmanned water surface measurement module in Instantaneous tide level corresponding to the coordinates of the time. The instantaneous tide level value is subtracted from the original elevation data collected by the multibeam echo sounder to complete the spatial gradient error compensation caused by the water level.

[0012] Furthermore, the specific steps of the spatiotemporal dynamic compensation analysis module inverting the full-depth dynamic sound velocity profile and performing ray tracing compensation include: Extracting a pre-defined historical water body temperature, salinity, and characteristic library, and then extracting the features through principal component analysis. Order-order empirical orthogonal functions ,in and For water depth; Combined with the real-time surface sound velocity obtained by the surface sound velocity meter and the underlying sound velocity obtained from the underlying sound velocity beacon. As constraints at both ends, the reconstruction coefficients of each order of empirical orthogonal functions are solved by least squares fitting, and the full-depth dynamic sound velocity profile under the current measurement trajectory is generated by inversion. .

[0013] Furthermore, based on Snell's law, layer-by-layer ray tracing calculations are performed on the transmitted beam of the multibeam echo sounder. According to the dynamic sound velocity and beam incident angle of each water layer, the bending path and two-way travel time of the sound wave in the non-uniform water body are corrected, and high-precision three-dimensional terrain data with "smiley face / crying face" edge distortion is output.

[0014] Furthermore, the specific steps for the scour and sedimentation evolution early warning module to generate the terrain difference matrix include: The high-precision three-dimensional terrain data is interpolated into a grid to generate the current digital elevation model. Retrieve the baseline elevation model of the completed or previous measurement of the waterway, and perform spatial grid alignment and algebraic subtraction operation on the current digital elevation model and the baseline elevation model based on the same coordinate datum to generate a high-dimensional topographic difference matrix that reflects the changes in the elevation of the waterway bed. The maximum scour depth, maximum siltation thickness, and corresponding spatial coordinates are extracted from the high-dimensional topographic difference matrix, and the overall change in scour and siltation volume in the survey area is calculated.

[0015] Furthermore, the specific logic for triggering the early warning based on a preset navigation depth safety threshold is as follows: Obtain the draft of the target navigable vessel Safe, prosperous and deep water and the current reference water level of the waterway. ; By combining the maximum siltation thickness in the high-dimensional topographic difference matrix, the actual water depth value of the corresponding grid is extracted. ; The actual water depth value Introducing a dynamic early warning model: judging inequalities If the condition is met, it is determined that the current water depth cannot meet the navigation safety requirements, triggering a navigation restriction warning instruction, and packaging the spatial coordinates corresponding to the maximum value of the siltation thickness as target point data of the key dredging area and sending it to the port dispatch terminal.

[0016] Beneficial effects

[0017] This invention achieves dynamic fitting of the instantaneous three-dimensional tidal surface and real-time reconstruction of the full-depth sound velocity profile by constructing a distributed multi-source heterogeneous environmental perception network and an unmanned surface measurement platform. It introduces unstructured grid-driven shallow water dynamic equations and empirical orthogonal functions based on surface and bottom constraints. This eliminates systematic elevation errors introduced by the spatial gradient differences of tidal levels in complex waters and the refraction of sound rays in denser waters from the physical model. At the same time, through low-power environment adaptive sampling and edge hardware time synchronization mechanism, it eliminates the process of frequently stopping the ship to measure sound velocity in traditional operations, realizing uninterrupted continuous automated high-precision measurement. The digital model after elevation reduction is directly converted into a difference matrix that includes verification of physical navigation force boundaries, providing highly timely and data-closed-loop quantitative support for precise dredging and navigation scheduling of port channels. Attached Figure Description

[0018] Figure 1 This is a diagram showing the overall system architecture modules of the present invention; Figure 2 This is a flowchart of the core algorithm for spatiotemporal dynamic compensation and early warning of the present invention; Figure 3 This is a cross-sectional schematic diagram of the physical deployment and application scenarios of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but includes other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] The present invention will now be described in further detail with reference to the accompanying drawings: Example: Figures 1-3 As shown, a port channel underwater topography monitoring and analysis system includes: The unmanned surface measurement module is equipped with a multibeam echo sounder and a surface sound velocity meter to acquire the coordinates of the measurement area, surface sound velocity, and basic depth measurement data. The distributed environmental sensing module includes tide gauges and underlying sound velocity beacons deployed in the waterway, used to collect instantaneous water level and underlying sound velocity data from multiple nodes; The spatiotemporal dynamic compensation analysis module communicates with the unmanned water surface measurement module and the distributed environmental perception module. It is used to construct a three-dimensional tidal surface based on instantaneous water level data to extract the instantaneous water level surface for elevation reduction, and combine surface and bottom layer sound velocity data to invert the full-depth dynamic sound velocity profile. It performs ray tracing compensation on the sounding base data to generate high-precision three-dimensional terrain data. The scouring and silting evolution early warning module is connected to the spatiotemporal dynamic compensation analysis module. It is used to generate a current digital elevation model from high-precision three-dimensional terrain data, compare it with the benchmark model to generate a terrain difference matrix, and trigger an early warning based on a preset navigation water depth safety threshold.

[0022] Furthermore, the specific operation procedure for the unmanned surface measurement module is as follows: The unmanned surface measurement module serves as the front-end physical platform for spatial data acquisition, and its physical carrier is an unmanned vessel equipped with multiple sensors. The core of this module integrates a multibeam echo sounder, a surface velocity meter, an attitude positioning subsystem, a time synchronization center, and an edge control computing unit.

[0023] To address the spatial physical layout and multi-sensor integration, and to eliminate system positioning errors introduced by the spatial position differences of multiple source devices, the phase center of the RTK-GNSS receiving antenna, the measurement center of the inertial navigation unit (INS), and the acoustic center of the transducer of the multibeam echo sounder in the attitude positioning subsystem are physically fixed together using high-strength rigid supports. During system initialization, the relative spatial position vectors of these measurement centers in the ship's servo coordinate system, i.e., the lever arm vectors, are pre-measured and calibrated. These lever arm vectors are stored in the memory of the edge control computing unit for subsequent three-dimensional spatial coordinate lever arm effect compensation.

[0024] To address the timing synchronization issue of multi-source heterogeneous data, the time synchronization center uses the absolute time output by the GNSS system as the reference time source, periodically broadcasting a unified PPS second pulse signal and an NMEA time message containing absolute time information to the multibeam echo sounder, surface velocity meter, and attitude positioning subsystem. Upon detecting the rising edge of the PPS second pulse signal, the hardware control board of each underlying sensor triggers a hardware interrupt, extracting the current sampling period's basic depth sounding data, surface velocity, and instantaneous attitude data, and binding them to the absolute timestamp corresponding to that rising edge. This hardware-level interrupt mechanism ensures that the time alignment accuracy of multi-sensor data in high-frequency dynamic sampling environments is controlled within the microsecond range.

[0025] In the basic data acquisition and bottom compensation stage of sounding, the multibeam echo sounder continuously transmits wide-sector acoustic waves and receives seabed echoes, generating a raw data stream containing the two-way travel time of the multibeam acoustic waves, the transmit beam angle, and the receive beam angle. The edge control computing unit receives the raw sounding data stream, surface sound velocity data, and instantaneous attitude data with the same absolute timestamp via an internal industrial Ethernet bus. The instantaneous attitude data is output in real time by the inertial navigation unit, including the roll angle of the unmanned vessel in a wave environment. Pitch angle Heading angle and vertical heave displacement .

[0026] After the edge control computing unit completes the spatiotemporal alignment of heterogeneous data using absolute timestamps, it performs hardware-level attitude and wave compensation for each sounding beam of the multibeam echo sounder. The specific calculation logic is as follows: based on the instantaneously acquired roll, pitch, and yaw angles, the edge control computing unit calculates the direction cosine matrix from the ship's servo coordinate system to the local horizontal reference coordinate system according to a preset three-dimensional rotation sequence. Subsequently, the original beam spatial pointing vector output from the multibeam echo sounder transducer array is extracted and multiplied by the direction cosine matrix on the left. Through the coordinate transformation matrix multiplication operation, the beam pointing angle that is relatively tilted in the servo coordinate system is converted into an absolute horizontal reference spatial pointing angle that is not affected by the instantaneous rolling of the ship.

[0027] After completing the baseline conversion of the beam pointing angle, the edge control computing unit superimposes the corrected spatial pointing angle, acoustic two-way travel time, real-time surface sound velocity, and absolute three-dimensional spatial coordinates after RTK-GNSS and boom compensation with the heave displacement in the elevation direction. All the basic data after edge-side attitude and elevation compensation are finally packaged and encapsulated by the edge control computing unit into a sounding basic data packet with a unique time frame sequence number, and transparently transmitted to the spatiotemporal dynamic compensation analysis module in the cloud through the onboard wireless communication link protocol.

[0028] Furthermore, the specific operation process of the distributed environment perception module is as follows: The distributed environmental perception module is constructed as a bottom-layer physical field perception network covering the target survey area. This module employs a non-uniform deployment topology based on hydrodynamic gradients for node configuration. Specifically, during the system planning phase, historical three-dimensional temperature, salinity, and flow field data of the waterway are pre-extracted, and the absolute value of the hydrodynamic gradient for each spatial grid within the survey area is calculated. In straight waterway areas where the absolute value of the hydrodynamic gradient is less than a set conventional smooth threshold, perception nodes are deployed at equal intervals according to a first spatial interval. In areas identified as brackish water confluence zones (i.e., salinity gradient extreme value zones) and areas of dramatic change where the rate of change in seabed topography elevation exceeds a preset elevation threshold, high-density node deployment is carried out at a second spatial interval less than the first spatial interval.

[0029] The distributed environmental sensing module comprises intelligent tide gauges located above the water surface or on shore, and bottom-mounted acoustic beacons anchored to the seabed. Both the tide gauges and the bottom-mounted acoustic beacons integrate independent high-precision real-time clock (RTC) chips and GNSS timing receiver modules on their internal motherboards. During operation, each node uses GNSS second pulse signals to periodically calibrate the phase of its local RTC chip, ensuring that the local time of all nodes within the distributed heterogeneous network maintains a unified absolute time reference at the microsecond level. When collecting instantaneous water level data or bottom-mounted acoustic velocity data, each node's local microprocessor stitches this data with the current absolute timestamp and pre-calibrated three-dimensional spatial coordinates of the node, encapsulating it into a standardized bottom-mounted sensing data packet. The intelligent tide gauge directly transmits the data packet to the spatiotemporal dynamic compensation analysis module via its internally integrated narrowband Internet of Things (NB-IoT) communication module; the bottom-mounted acoustic beacon, through its integrated underwater acoustic communication modem, transmits the data packet to the unmanned surface measurement module or shore-based receiving node in a multi-hop underwater acoustic self-organizing network routing mode.

[0030] The underlying acoustic beacon's internal hardware architecture and control logic physically integrate a high-frequency acoustic transceiver transceiver, a temperature, salinity, and depth (CTD) sensor unit, and a low-power wake-up control circuit within its sealed pressure chamber. The low-power wake-up control circuit includes a microcontroller unit (MCU) and a power management chip connected to its pins. To resolve the conflict between power consumption during long-term underwater monitoring and the ability to detect high-frequency hydrological changes, the microcontroller unit is programmed with an environment-adaptive sampling logic control program.

[0031] Under normal operating conditions, the microcontroller unit controls the high-frequency acoustic transceiver transceiver to be in sleep mode via the power management chip, and briefly wakes it up at relatively long time intervals (i.e., a first preset frequency) to obtain underlying sound velocity data. Simultaneously, the temperature, salinity, and depth sensing unit continuously collects real-time analog signals of the water's conductivity (salinity) and temperature at a fixed reference frequency, and inputs these signals to the microcontroller unit after analog-to-digital conversion. The microcontroller unit's internal arithmetic unit calculates the time derivatives (i.e., rates of change) of the salinity and temperature values ​​within adjacent sampling periods in real time.

[0032] When the absolute value of the salinity or temperature change rate over time exceeds the preset abrupt trigger threshold in the microprocessor's internal register (this physical state indicates that the underlying layer of the survey area is experiencing tidal surges or high-intensity density current intrusion), the microcontroller unit's internal comparator immediately flips its level, generating a hardware interrupt signal. This interrupt signal directly triggers the power management chip in the low-power wake-up control circuit, causing it to supply full power to the high-frequency acoustic transceiver transceiver. The microcontroller unit then forcibly switches the sampling timing of the high-frequency acoustic transceiver transceiver to a second preset frequency, which is several times the first preset frequency, via internal bus instructions. The high-frequency acoustic transceiver transceiver continuously transmits and receives acoustic pulses at the second preset frequency, densely acquiring the underlying sound velocity data stream under abrupt change conditions. When the temperature, salinity, and depth sensing unit detects that the salinity and temperature change rates for several consecutive cycles have fallen back to the preset stable threshold range, the microcontroller unit cancels the interrupt signal, instructs the power management chip to reduce the power supply level, and restores the high-frequency acoustic transceiver transceiver to the normal sampling mode at the first preset frequency.

[0033] Furthermore, the specific operation procedure of the spatiotemporal dynamic compensation analysis module is as follows: The spatiotemporal dynamic compensation analysis module is deployed on a cloud server or a shore-based high-performance computing cluster. Its core function is to receive heterogeneous sensing data transmitted through the underlying hardware network and eliminate systematic environmental errors in underwater acoustic measurements through real-time solution of the physical field mathematical model. The module's internal operating logic is mainly divided into two continuous computational stages: "construction of three-dimensional tidal surface and elevation reduction" and "inversion of full-depth sound velocity profile and ray tracing compensation".

[0034] In the three-dimensional tidal surface construction and elevation calculation stage, the receiving port of the spatiotemporal dynamic compensation analysis module first parses the standardized low-level sensing data packets sent by the distributed environmental sensing module, extracting the three-dimensional spatial coordinates and instantaneous water level data of the intelligent tide gauges at each node. Subsequently, the grid division unit within the module extracts the electronic nautical chart data of the survey area, using the channel centerline and the land-water boundary lines on both sides of the channel as rigid calculation boundaries, and employs the Delaunay triangulation algorithm to generate a two-dimensional unstructured spatial grid covering the entire survey area. The node density of this grid is positively correlated with the hydrodynamic gradient.

[0035] After spatial discretization, the fluid dynamics computational unit uses the instantaneous water level data from the tide gauges at each node as the forced water level boundary conditions for the internal nodes. Simultaneously, it accesses real-time wind stress vector data and the topographic friction coefficient of the channel bed through external meteorological and hydrological interfaces, inputting these as source terms into the two-dimensional shallow water dynamic equations. These equations consist of the mass conservation equation (continuity equation) and the momentum conservation equation. The fluid dynamics computational unit uses the finite volume method to solve this nonlinear partial differential equation system through explicit time integration. Through iterative calculations at each time step, the absolute water level elevation at the current moment is output at all nodes of the two-dimensional unstructured spatial grid, thus fitting a continuous three-dimensional tidal surface in space.

[0036] When processing the depth sounding baseline data uploaded by the unmanned surface measurement module, the elevation compensation unit reads the absolute timestamp from the header of the data packet. and absolute spatial coordinates after RTK-GNSS compensation The elevation compensation unit utilizes a bilinear interpolation algorithm on the three-dimensional tidal surface. Accurately extract the instantaneous tide level elevation under the corresponding spatiotemporal coordinates. Finally, the instantaneous tide level elevation is subtracted from the original absolute elevation of the seabed topography output by the multibeam echo sounder. This completes the elevation reduction to eliminate spatial gradient distortion of the water surface.

[0037] In the full-depth sound velocity profile inversion and ray tracing compensation stage, the aim is to address the acoustic ray bending distortion caused by the confluence of fresh and salt water. The sound velocity inversion unit within the spatiotemporal dynamic compensation analysis module pre-extracts a matrix of measured temperature, salinity, and depth (CTD) profiles for the sea area over the past year from a local database. The matrix dimensionality reduction unit calculates the covariance matrix of this measured profile data matrix and performs eigenvalue decomposition (principal component analysis) to extract the previous... Rank (usually) Choose 3 to 5) empirical orthogonal functions that maximize the contribution rate to variance. ,in Represents discrete water depth variables. The order empirical orthogonal functions constitute the basis vectors for the current vertical distribution of sound speed in the water area.

[0038] During real-time measurement, the sound velocity inversion unit synchronously receives the surface sound velocity acquired by the unmanned surface measurement module. (corresponding depth) ) and the underlying sound velocity reported by the underlying sound velocity beacon (corresponding depth) These two measured physical boundary values ​​are used as strong constraints and substituted into the sound velocity profile reconstruction equation. Among them This is a historical average sound speed profile. The reconstruction coefficients are to be determined. The sound velocity inversion unit is constructed with respect to the reconstruction coefficients. The overdetermined linear equations are solved using the least squares method to obtain the reconstruction coefficients for the current instantaneous state. Substituting these coefficients back into the reconstruction equations allows for the inversion and generation of a continuous, high-resolution, full-depth dynamic sound velocity profile. .

[0039] After acquiring the full-depth dynamic sound velocity profile, the ray tracing unit will transmit the multi-beam acoustic wave beam angle (i.e., the initial incident angle) from the sounding baseline data. and sound wave two-way travel time Input the Snell's law calculation model. The ray tracing unit is based on... The vertical resolution divides the water body into equal intervals. Each layer is a horizontal micro-layer. The computational microprocessor substitutes the Snell constant formula layer by layer from the surface to the bottom. The actual incident angle of the sound ray in each microlayer was calculated sequentially. Then, the path of the sound ray through each microlayer was calculated. One-way travel time and horizontal propagation distance and vertical penetration depth .

[0040] During the cumulative calculation process, the ray tracing unit continuously determines the cumulative time. The calculation checks whether half of the total two-way travel time recorded by the depth sounder has been reached. When this critical time condition is met, the iterative calculation terminates. At this point, the cumulative horizontal propagation distance of all microlayers represents the actual horizontal offset of the sounding beam's seabed footprint under the current complex sound velocity field, and the cumulative vertical penetration depth of all microlayers represents the true water depth without tidal correction. Through the rigorous physical layer ray integration described above, the trajectory curvature of the sound wave caused by refraction in denser water is corrected, resulting in high-precision 3D topographic point cloud data with eliminated edge beam "smile / sad face" distortion.

[0041] Furthermore, the specific operation procedure of the scour and sedimentation evolution early warning module is as follows: The siltation and erosion evolution early warning module serves as the computational hub connecting underwater topographic physical mapping and port navigation scheduling engineering. Its core program runs on the server cluster of the port command center. The module's operation begins by receiving high-precision 3D topographic data output from the spatiotemporal dynamic compensation analysis module. During the data gridding stage, the module's internal spatial modeling unit uses high-precision 3D topographic data in discrete point cloud format as the input set. It employs a standard kriging spatial interpolation algorithm, combined with a semi-variance function model of the survey area's topography, to calculate the elevation spatial weights of each discrete point in a unified two-dimensional horizontal coordinate system. Through spatial interpolation, the non-uniformly distributed point cloud is forcibly resampled into regular grid data with a fixed planar resolution, thereby generating the current digital elevation model (DEM) matrix.

[0042] After generating the current period's digital elevation model (DEM), the difference analysis unit of the scour and sedimentation evolution early warning module retrieves the benchmark elevation model for the corresponding channel section from the background relational database. This benchmark elevation model is either the design water depth matrix at the time of channel completion and acceptance or the historical matrix from the last routine measurement. The difference analysis unit first executes the coordinate system registration command to verify the planar projection zones and elevation reference surfaces of the current period's DEM and the benchmark elevation model. After confirming that both are on the same absolute spatial coordinate datum, a strict grid node alignment operation is performed. After alignment, the arithmetic unit performs element-wise algebraic subtraction according to the corresponding row and column indices, that is, subtracting the elevation matrix of the benchmark elevation model from the elevation matrix of the current period's DEM, generating a high-dimensional topographic difference matrix reflecting the vertical displacement of the channel bed. In this difference matrix, the set of elements with positive difference values ​​indicates that the channel bed has undergone sedimentation, and the set of elements with negative difference values ​​indicates that the channel bed has undergone scour.

[0043] After matrix subtraction, the statistical algorithm unit within the module performs a global traversal search of the high-dimensional topographic difference matrix, extracting the positive element with the largest numerical value and the negative element with the largest absolute value, and locking their corresponding two-dimensional grid row and column numbers. It then calculates the geodetic coordinates of these extreme points in real physical space, marking them as the points with the maximum siltation thickness and the maximum scour depth, respectively. Simultaneously, the statistical algorithm unit uses a numerical integration algorithm to perform a double integral summation of the values ​​of all positive elements in the difference matrix with their corresponding grid plane areas to obtain the overall siltation volume of the current survey area; similarly, it performs area integral summation calculations on all negative elements to obtain the overall scour volume.

[0044] For the physical early warning mechanism directly linked to navigation safety, the navigation discrimination unit within the siltation evolution early warning module is equipped with a dynamic early warning model based on physical boundaries. During system operation, the navigation discrimination unit obtains the physical parameters of the target vessel about to enter the port through the port's Automatic Identification System (AIS) data interface or a manual input terminal. These parameters include the target vessel's full-load draft and the safe margin depth for that tonnage vessel as required by industry standards. The current reference water level of the channel is obtained by reading the lowest astronomical tide level data from the local tide table.

[0045] The navigation discrimination unit then extracts the absolute value of the physical water depth at that point, excluding tidal levels, from the current digital elevation model, based on the grid index of the previously identified maximum siltation thickness point. The microprocessor substitutes the aforementioned physical variables into the inequality logic gates in memory: This logic gate is used to verify whether the remaining water depth at the shallowest point of the channel can accommodate the sum of the ship's draft and the available water depth under the most extreme low water conditions. When the arithmetic unit determines that this inequality is true (i.e., it holds), the system's underlying layer confirms that the current physical hydrological and topographical conditions have encroached upon the ship's safe navigation boundary. At this point, the output interface of the navigation discrimination unit immediately generates a series of restricted navigation warning instruction data packets containing high-level interruption flags. Simultaneously, the program clusters and extracts the three-dimensional spatial coordinates of the maximum siltation thickness point and its surrounding continuously exceeding grid nodes, packaging them into target point data for key dredging areas. Finally, this warning instruction data packet and the target point data for key dredging areas are pushed to the display panel of the port scheduling terminal in real time via the TCP / IP protocol, forcibly triggering port restricted navigation scheduling and subsequent precise dredging projects based on the absolute result of the underlying physical calculations.

[0046] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A port and waterway underwater topography monitoring and analysis system, characterized in that, include: The unmanned surface measurement module is equipped with a multibeam echo sounder and a surface sound velocity meter to acquire the coordinates of the measurement area, surface sound velocity, and basic depth measurement data. The distributed environmental sensing module includes tide gauges and underlying sound velocity beacons deployed in the waterway, used to collect instantaneous water level and underlying sound velocity data from multiple nodes; The spatiotemporal dynamic compensation analysis module is communicatively connected to the unmanned water surface measurement module and the distributed environmental perception module. It is used to construct a three-dimensional tidal surface based on the instantaneous water level data to extract the instantaneous water level surface for elevation reduction, and to invert the full-depth dynamic sound velocity profile by combining the surface and bottom sound velocity data. It also performs ray tracing compensation on the sounding base data to generate high-precision three-dimensional terrain data. The scouring and silting evolution early warning module is connected to the spatiotemporal dynamic compensation analysis module. It is used to generate a current digital elevation model from the high-precision three-dimensional terrain data, compare it with the benchmark model to generate a terrain difference matrix, and trigger an early warning based on a preset navigation water depth safety threshold.

2. The underwater topography monitoring and analysis system for ports and waterways according to claim 1, characterized in that, The unmanned surface measurement module also includes an attitude positioning subsystem and a time synchronization center; The attitude positioning subsystem includes an RTK-GNSS antenna and an inertial navigation unit that are rigidly connected to each other, and is used to collect the three-dimensional spatial coordinates of the unmanned surface measurement module in real time, as well as instantaneous attitude data including roll angle, pitch angle, heading angle and heave displacement. The time synchronization center is used to provide a unified PPS second pulse signal to the multibeam echo sounder, surface velocity meter and attitude positioning subsystem to generate the basic echo sounding data with an absolute timestamp.

3. The underwater topography monitoring and analysis system for port channels according to claim 2, characterized in that, The basic depth sounding data includes the two-way travel time of the multibeam acoustic wave, the transmit and receive beam angles, and the corresponding instantaneous attitude data; The unmanned surface measurement module also includes an edge control computing unit. The edge control computing unit is used to perform spatiotemporal alignment of the instantaneous attitude data with the two-way travel time of the multi-beam acoustic wave based on the absolute timestamp, and to perform attitude wave compensation on the transmission and reception pointing angles of the depth sounding beam using the attitude data. The compensated data is then packaged and sent to the spatiotemporal dynamic compensation analysis module.

4. The underwater topography monitoring and analysis system for port channels according to claim 3, characterized in that, The distributed environment perception module adopts a non-uniform deployment topology architecture based on hydrodynamic gradient. In the brackish water confluence area and the area of ​​dramatic seabed topography changes of the channel, the deployment density of the tide gauges and bottom sonic beacons is greater than that in conventional straight channel areas. Both the tide gauge and the underlying acoustic beacon have built-in clock synchronization chips, and transmit the instantaneous water level and underlying acoustic velocity data with absolute timestamps and three-dimensional spatial coordinates to the spatiotemporal dynamic compensation analysis module through narrowband Internet of Things or underwater acoustic communication self-organizing network nodes.

5. The underwater topography monitoring and analysis system for ports and waterways according to claim 4, characterized in that, The underlying sound speed beacon integrates a high-frequency sound wave transceiver transducer, a temperature, salinity and depth sensing unit, and a low-power wake-up control circuit. The underlying sound velocity beacon is configured with an environment-adaptive sampling mode: under normal conditions, it collects underlying sound velocity data at a first preset frequency; when the temperature, salinity, and depth sensing unit detects that the rate of change of water salinity or temperature exceeds a preset threshold, it triggers the low-power wake-up control circuit to switch the acquisition frequency of the underlying sound velocity data to a second preset frequency higher than the first preset frequency, so as to capture high-frequency hydrological changes under tidal surges.

6. The underwater topography monitoring and analysis system for ports and waterways according to claim 5, characterized in that, The specific steps for constructing the three-dimensional tidal surface and performing elevation reduction in the spatiotemporal dynamic compensation analysis module include: Using the instantaneous water level data from the tide gauges at each node of the distributed environmental perception module, a two-dimensional unstructured spatial grid is constructed with the channel centerline and edge line as boundaries; Real-time wind field data and bottom friction coefficient of the survey area are introduced as boundary driving conditions. The two-dimensional shallow water dynamic equations are solved within the two-dimensional unstructured spatial grid. In the spatiotemporal dimension, an instantaneous three-dimensional tidal surface covering the entire survey area is generated by fitting the equations. ; Extracting the unmanned water surface measurement module in Instantaneous tide level corresponding to the coordinates of the time. The instantaneous tide level value is subtracted from the original elevation data collected by the multibeam echo sounder to complete the spatial gradient error compensation caused by the water level.

7. The underwater topography monitoring and analysis system for ports and waterways according to claim 6, characterized in that, The specific steps of the spatiotemporal dynamic compensation analysis module inverting the full-depth dynamic sound velocity profile and performing ray tracing compensation include: Extracting a pre-defined historical water body temperature, salinity, and characteristic library, and then extracting the features through principal component analysis. Order-order empirical orthogonal functions ,in and For water depth; Combined with the real-time surface sound velocity obtained by the surface sound velocity meter and the underlying sound velocity obtained from the underlying sound velocity beacon. As constraints at both ends, the reconstruction coefficients of each order of empirical orthogonal functions are solved by least squares fitting, and the full-depth dynamic sound velocity profile under the current measurement trajectory is generated by inversion. .

8. The underwater topography monitoring and analysis system for ports and waterways according to claim 7, characterized in that, Based on Snell's law, the transmitted beam of the multibeam echo sounder is subjected to layer-by-layer ray tracing calculation. According to the dynamic sound velocity and beam incident angle of each water layer, the bending path and two-way travel time of the sound wave in the non-uniform water body are corrected, and high-precision three-dimensional terrain data with "smiley face / crying face" edge distortion is output.

9. The underwater topography monitoring and analysis system for ports and waterways according to claim 8, characterized in that, The specific steps for the scouring and sedimentation evolution early warning module to generate the terrain difference matrix include: The high-precision three-dimensional terrain data is interpolated into a grid to generate the current digital elevation model. Retrieve the baseline elevation model of the completed or previous measurement of the waterway, and perform spatial grid alignment and algebraic subtraction operation on the current digital elevation model and the baseline elevation model based on the same coordinate datum to generate a high-dimensional topographic difference matrix that reflects the changes in the elevation of the waterway bed. The maximum scour depth, maximum siltation thickness, and corresponding spatial coordinates are extracted from the high-dimensional topographic difference matrix, and the overall change in scour and siltation volume in the survey area is calculated.

10. A port and waterway underwater topography monitoring and analysis system according to claim 9, characterized in that, The specific logic for triggering the early warning based on a preset navigation depth safety threshold is as follows: Obtain the draft of the target navigable vessel Safe, prosperous and deep water and the current reference water level of the waterway. ; By combining the maximum siltation thickness in the high-dimensional topographic difference matrix, the actual water depth value of the corresponding grid is extracted. ; The actual water depth value Introducing a dynamic early warning model: judging inequalities If the condition is met, it is determined that the current water depth cannot meet the navigation safety requirements, triggering a navigation restriction warning instruction, and packaging the spatial coordinates corresponding to the maximum value of the siltation thickness as target point data of the key dredging area and sending it to the port dispatch terminal.

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