Method and system for measuring in very shallow water based on a tilt-mounted single-beam bathymeter

Abstract

The present application relates to single-beam echo sounder shallow water measurement technology field, especially in kind of based on the single-beam echo sounder shallow water measurement method and system of tilt installation, the method comprises the following steps: obtaining single-beam echo sounder operation data, identifying measurement route and collecting environmental change, the simulated sounding process is combined to generate sounding simulation data;According to the environmental change and the disturbance response data of sounding angle, the environmental measurement coupling interference intensity is calculated, the dynamic abnormal condition of sound wave propagation path is identified;Detect the frequency drift phenomenon of sound wave in the shallow water area, and the error propagation prediction is carried out accordingly, the error propagation growth data is obtained, the deviation degree of the tilt sounder is evaluated based on the error propagation condition, and the deviation degree data is generated;The original sounding data is corrected to obtain the corrected sounding value;The present application realizes single-beam echo sounder shallow water measurement more accurately and efficiently by single-beam echo sounder shallow water measurement correction.

Description

Technical Field

[0001] This invention relates to the field of single-beam echo sounder measurement technology in extremely shallow waters, and particularly to a method and system for measuring extremely shallow waters using a single-beam echo sounder with an inclined mounting. Background Technology

[0002] In extremely shallow water environments, the water depth changes drastically, the seabed structure is complex, and wave interference is frequent. Traditional single-beam echo sounders often face problems such as decreased measurement accuracy, signal distortion, and data offset in these environments. Especially when the equipment is installed at an angle, the direction of the sound wave emission deviates from the water surface normal, which can easily lead to abnormal sound wave incident angles, distorted reflection paths, enhanced multipath interference, and severe waveform overlap, resulting in increased depth measurement errors and failing to meet high-precision measurement requirements. Currently, commonly used single-beam echo sounder systems mainly rely on fixed installation methods and perform water depth calculations based on idealized vertical incidence models. They lack adaptive modeling and error correction capabilities for environmental factors such as actual navigation attitude changes, tilted installation angles, and wave disturbances. Particularly when operating in extremely shallow waters or complex nearshore areas, the accumulation of errors leads to inaccurate judgments of information such as seabed profiles and sedimentary structure, and may even cause collision risks. However, traditional tilted single-beam echo sounders in extremely shallow water measurements suffer from inaccurate detection of dynamic anomalies in sound wave propagation paths and inaccurate detection of the intensity of environmental coupling interference. Summary of the Invention

[0003] Therefore, it is necessary to provide a method and system for measuring extremely shallow waters using a single-beam echo sounder with tilted installation, in order to solve at least one of the aforementioned technical problems.

[0004] To achieve the above objectives, a method for measuring extremely shallow waters using a tilted single-beam echo sounder includes the following steps:

[0005] Step S1: Acquire single-beam echo sounder operating data; identify single-beam echo sounder measurement route data based on single-beam echo sounder operating data; collect environmental changes along the measurement route based on single-beam echo sounder measurement route data; perform echo sounder depth measurement simulation based on single-beam echo sounder measurement route data to obtain single-beam echo sounder depth measurement simulation data.

[0006] Step S2: Detect the dynamic disturbance response data of the sounding angle based on the environmental changes of the measurement route using the single-beam echo sounder's sounding simulation data; determine the environmental measurement coupling interference intensity of the echo sounder based on the environmental changes of the measurement route and the dynamic disturbance response data of the sounding angle; determine the dynamic anomaly of the acoustic wave propagation path based on the environmental measurement coupling interference intensity of the echo sounder.

[0007] Step S3: Detect the acoustic frequency drift phenomenon in extremely shallow waters based on the dynamic anomaly of the acoustic propagation path; predict the depth sounder error spread based on the acoustic frequency drift phenomenon in extremely shallow waters to obtain depth sounder error spread growth data.

[0008] Step S4: Based on the error expansion growth data of the depth sounder, evaluate the degree of deviation of the tilted depth sounder to obtain the deviation degree data of the tilted depth sounder; perform single-beam depth sounder measurement value correction processing on the deviation degree data of the tilted depth sounder to obtain the single-beam depth sounder measurement value correction data.

[0009] This invention acquires single-beam echo sounder operational data and identifies measurement route data, enabling accurate reconstruction of measurement tracks and operational trajectories, thus enhancing environmental awareness during the echo sounding process. By collecting environmental changes along the measurement route and combining them with echo sounding simulation data to analyze the dynamic disturbance response of the echo sounding angle, it effectively reflects the influence of factors such as waves and ship attitude on the change of the incident angle, improving the accuracy of anomaly identification. Based on the disturbance data, it determines the intensity of environmental coupling interference and the dynamic anomalies of the acoustic wave propagation path, enhancing the system's response to complex changes in the acoustic wave propagation path and reducing sources of echo sounding errors. Furthermore, it detects frequency drift and performs error propagation prediction, improving the system's ability to predict and respond to errors caused by signal instability in extremely shallow waters. By assessing the degree of deviation of the tilt echo sounder and correcting the echo sounding values, it enables real-time optimization of measurement data, ensuring that echo sounding accuracy and system stability are maintained even in non-standard installations and complex water environments, significantly improving the reliability and practicality of single-beam echo sounders in extremely shallow water applications. Therefore, this invention is an optimization of traditional single-beam echo sounder measurements in extremely shallow waters. It solves the problems of inaccurate detection of dynamic anomalies in the sound wave propagation path and inaccurate detection of the coupling interference intensity of the sounder's environment in extremely shallow waters. It improves the accuracy of detecting dynamic anomalies in the sound wave propagation path and the accuracy of detecting the coupling interference intensity of the sounder's environment.

[0010] The present invention also provides a system for measuring extremely shallow waters using a tilted-mounted single-beam echo sounder, for performing the aforementioned method for measuring extremely shallow waters using a tilted-mounted single-beam echo sounder. This system includes:

[0011] The depth sounder simulation module is used to acquire single-beam depth sounder operating data; identify single-beam depth sounder measurement route data based on the single-beam depth sounder operating data; collect environmental changes along the measurement route based on the single-beam depth sounder measurement route data; and perform depth sounder simulation based on the single-beam depth sounder measurement route data to obtain single-beam depth sounder simulation data.

[0012] The propagation path dynamic anomaly determination module is used to detect dynamic disturbance response data of the sounding angle in the single-beam depth sounder's depth sounding simulation data based on changes in the measurement route environment; determine the intensity of environmental measurement coupling interference of the depth sounder based on changes in the measurement route environment and the dynamic disturbance response data of the sounding angle; and determine the dynamic anomaly status of the acoustic wave propagation path based on the intensity of environmental measurement coupling interference of the depth sounder.

[0013] The error propagation prediction module is used to detect the acoustic frequency drift phenomenon in extremely shallow waters based on the dynamic anomalies of the acoustic propagation path; and to predict the error propagation of the depth sounder based on the acoustic frequency drift phenomenon in extremely shallow waters, thereby obtaining the error propagation growth data of the depth sounder.

[0014] The depth sounding value correction processing module is used to evaluate the degree of deviation of the tilted depth sounder based on the depth sounder error expansion growth data, and obtain the tilted depth sounder deviation data; and to perform single-beam depth sounding value correction processing on the tilted depth sounder deviation data, and obtain single-beam depth sounding value correction data.

[0015] The present invention relates to a tilt-mounted single-beam echo sounder system for measuring extremely shallow waters. This system can realize any tilt-mounted single-beam echo sounder method for measuring extremely shallow waters according to the present invention. It serves as a medium for coordinating the operation and signal transmission between various modules to complete the tilt-mounted single-beam echo sounder method for measuring extremely shallow waters. The internal modules of the system cooperate with each other, improving the depth measurement accuracy, stability and data reliability of the tilt-mounted single-beam echo sounder in complex environments of extremely shallow waters. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the steps involved in a method for measuring extremely shallow water using a tilted single-beam echo sounder.

[0017] Figure 2 for Figure 1 A detailed flowchart illustrating the implementation steps of step S3.

[0018] Figure 3 This is a diagram of the metal equipment for a single-beam depth sounder.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0021] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0022] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0023] To achieve the above objectives, please refer to Figures 1 to 3 A method for measuring extremely shallow water using a tilted single-beam echo sounder includes the following steps:

[0024] Step S1: Acquire single-beam echo sounder operating data; identify single-beam echo sounder measurement route data based on single-beam echo sounder operating data; collect environmental changes along the measurement route based on single-beam echo sounder measurement route data; perform echo sounder depth measurement simulation based on single-beam echo sounder measurement route data to obtain single-beam echo sounder depth measurement simulation data.

[0025] In this embodiment of the invention, a HydroLite-TM single-beam echo sounder is used. The sounder is mounted on the underside of the starboard side of the measuring vessel, fixed to a rigid mounting bracket, with a preset installation tilt angle of 11°. The installation angle is recorded in real time by an integrated tilt sensor, calibrated after installation, and the data is uploaded to the control processing unit. The echo sounder communicates in real time with the main control data acquisition unit via an RS-232 serial port, acquiring operational data including attitude information (pitch, roll, yaw), operating frequency, sound velocity setting, signal gain, echo intensity, power supply voltage, and current load. The sampling frequency is set to 5Hz. During measurement, the control unit synchronously receives position information provided by a high-precision GPS module, with a positioning accuracy of 0.3 meters. The GPS timestamp is correlated with the echo sounder data timestamp to align the operational data with the spatial position. During path identification, a moving average filter is used to smooth the GPS trajectory, eliminating trajectory jumps caused by satellite obstruction or reflection. Then, based on the smoothed path, segmentation is performed, and different path segments are divided by combining the velocity curve and steering angle information. Along the measurement path, the control unit retrieves seabed topographic maps, hydrological data, and wave field data stored in the Geographic Information System (GIS) for the area. Combined with data collected by wave height and water quality sensors (including turbidity, bubble concentration, and seabed type), an environmental sampling point is taken every 100 meters along the path to establish an environmental change database for the measurement route. Using data on installation angle and attitude changes, and layered sound velocity data measured by a sound velocity profiler, a simulated bathymetry path is constructed using ray tracing. In the simulation, the sound wave propagation path is calculated based on the oblique angle of incidence and the change in water layer refraction ratio, outputting the predicted echo time, path distance, and bathymetry value. This simulation result is linked to the location of each point on the path, forming a "location-simulated bathymetry value" mapping table, which serves as the output of the bathymetry simulation data.

[0026] Step S2: Detect the dynamic disturbance response data of the sounding angle based on the environmental changes of the measurement route using the single-beam echo sounder's sounding simulation data; determine the environmental measurement coupling interference intensity of the echo sounder based on the environmental changes of the measurement route and the dynamic disturbance response data of the sounding angle; determine the dynamic anomaly of the acoustic wave propagation path based on the environmental measurement coupling interference intensity of the echo sounder.

[0027] In this embodiment of the invention, after the depth sounding simulation data is generated, the pitch and roll angle changes obtained from the three-axis gyroscope and accelerometer in the shipborne inertial navigation system (INS) are used to establish an attitude disturbance sequence for the measurement path. The sampling frequency is 50Hz, and a sliding window with a window width of 5 seconds is used for attitude change detection. Within each window, the mean, variance, and maximum change amplitude of the pitch and roll angles are calculated; when the pitch change amplitude exceeds 1.2° and the roll exceeds 0.9° within a certain window, it is defined as a dynamic disturbance event. For the identified disturbance events, a coupling mapping between disturbance and environmental change is established by combining meteorological monitoring data (wind speed and direction instrument), wave intensity changes identified from the water surface video stream, and measured water surface bubble concentration data. The disturbance coupling index I is used to represent the interference intensity, and the calculation method is: I = K × wave height change rate × bubble concentration × ship heel angle increase, where K is the amplification factor (experimentally determined to be 3.2). If the I value exceeds 1.0, it is determined that there is significant environmental coupling interference. In the current measurement segment, I=1.38, indicating that environmental disturbances are amplified through installation angle coupling, resulting in increased attitude instability. Next, based on the I value, the acoustic wave path is re-simulated in the ray tracing module to observe for anomalies such as multipath propagation, reversal, deviation, and sudden changes in refraction angle. When the echo reversal angle in the simulated path exceeds 15% of the incident angle, it is marked as a dynamic path anomaly. Combining the sound velocity data and the echo signal intensity trend, it is determined that there is a dynamic anomaly in the acoustic wave propagation path in the current segment, and the anomaly type and intensity data are output as input for the next step.

[0028] Step S3: Detect the acoustic frequency drift phenomenon in extremely shallow waters based on the dynamic anomaly of the acoustic propagation path; predict the depth sounder error spread based on the acoustic frequency drift phenomenon in extremely shallow waters to obtain depth sounder error spread growth data.

[0029] In this embodiment of the invention, after identifying a dynamic anomaly in the sound wave propagation path in the current measurement area in step S2, the recorded raw echo signal data is analyzed point by point. A high-frequency sound wave acquisition module is used to extract data from each echo signal, including echo delay, echo amplitude, waveform envelope, and the original sound wave signal sequence within the corresponding time period. The above signal data is then sent to the sound wave signal processing module, where the waveform analysis processor embedded in the high-speed acquisition system is used to detect the waveform stability of each sound wave signal segment. In extremely shallow water areas, where the water depth is less than 3 meters, the echo return speed is extremely fast, and the increased surface disturbance leads to frequent changes in the incident angle, resulting in decreased signal path stability. The system compares the echo characteristic curves under the same installation angle and sound speed conditions during normal operation to determine abnormal changes in the current data. It is found that some signals exhibit irregular waveform extension, delayed echoes, and a shift in the position of the energy concentration peak. The signal characteristics no longer present a regular single-peak shape but instead show multiple secondary peaks or main peak drift, indicating a frequency drift phenomenon. The frequency drift data, along with records of acoustic path anomalies and sea surface disturbance data (wave height, wave frequency, and current velocity), are jointly input into the error prediction model. The model employs a static neural network structure trained using historical error expansion samples. Instead of relying on real-time simulation, the model directly outputs the magnitude and trend of error expansion within the current time period through classification decision rules. The model assesses the rate of decline in the current depth sounder's measurement accuracy by comparing input factors such as the current environmental disturbance level, path change intensity, and wave impact cycle, combined with the acoustic anomaly category. Results show that the depth sounding error has increased by approximately 2.4 meters in the past 15 minutes, and the error continues to rise. Predicted data indicates that the error will increase by another 0.8 meters in the next 10 minutes, affecting all depth sounding points within the current path segment. The predicted error expansion results are output as a time- and spatially labeled error expansion growth data table, containing fields such as timestamp, geographical location, error trend category, and error growth value for each measurement point, for use in step S4.

[0030] Step S4: Based on the error expansion growth data of the depth sounder, evaluate the degree of deviation of the tilted depth sounder to obtain the deviation degree data of the tilted depth sounder; perform single-beam depth sounder measurement value correction processing on the deviation degree data of the tilted depth sounder to obtain the single-beam depth sounder measurement value correction data.

[0031] In this embodiment of the invention, based on the data containing the error propagation growth of each measurement point obtained in step S3, the installation angle information of the tilt sounder and the corresponding historical sequences of pitch and roll angles are called. By aligning with the corresponding time of the echo data within the path segment, a one-to-one match between the angle data and the error propagation data is achieved. For each measurement point, the system calls the hull attitude change curve in the path, and calculates the potential observation offset caused by tilt at that position by combining the installation tilt angle (e.g., 11°) and the actual dynamic attitude angle change amplitude. Then, it compares with the error propagation data to identify which offsets are due to the cumulative deviation caused by the coupling of attitude tilt and error. Furthermore, all deviation data are classified by path segment to form a statistical result of the degree of deviation. For example, in the segment with path number R13, the error propagation growth value is generally higher than 2.5 meters. Combined with the record of frequent pitch angle changes (more than 1.5° multiple times within 1 minute), this path segment is marked as a high deviation area. The system automatically calculates the average deviation degree of this segment and marks it as a "high-risk deviation segment". The statistical results are organized into an tilt sounder deviation dataset according to path segment number, coordinates, and timestamp. The output includes fields such as deviation level (low, medium, high), average deviation value, maximum deviation, and signal stability level. After acquiring the deviation data, the correction process begins. The correction process does not perform simple linear regression but uses a preset correction rule table. This rule table is built based on empirical correction coefficients obtained from field measurements of multiple water areas and installation combinations with multiple attitudes, and is multi-dimensionally mapped according to the sounder's tilt angle range, pitch angle variation, and water depth interval. The system reads the error data, installation angle, current attitude angle, and path segment characteristics of each measurement point, automatically matches the corresponding correction rule, and applies the correction value to replace each original sounding value. The corrected data is then bound to the original location and timestamp for output, forming a corrected single-beam echo sounder sounding value correction data file. This file format conforms to the XYZ three-column standard format and can be imported into surveying post-processing software for operations such as 3D terrain reconstruction, contour line extraction, or error analysis. The entire correction process is traceable, supports accuracy verification and data review, and is compatible with national standards requiring water depth accuracy within ±0.2m.

[0032] Preferably, step S1 includes the following steps:

[0033] Step S11: Obtain single-beam echo sounder operating data;

[0034] In this embodiment of the invention, operational data is acquired in real time through a single-beam echo sounder integrated on the ship's hull. The system's core components include a main control unit, a data acquisition unit, an attitude sensor (IMU), a GPS positioning module, and acoustic wave transmitting and receiving devices. During the operational data acquisition process, the following information is recorded synchronously at a second-level frequency: current timestamp of the echo sounder, real-time ship speed (in knots), heading angle (in degrees), echo sounder pitch and roll angles, acoustic wave transmission frequency, echo reception time difference, transmission power intensity, sounding distance (in meters), water depth value, and positioning coordinates (WGS-84 format). All data communicates via a CAN bus and high-speed Ethernet, and is initially filtered and stored by an embedded data processing platform.

[0035] Step S12: Determine the installation data of the single-beam echo sounder based on the operating data of the single-beam echo sounder;

[0036] In this embodiment of the invention, the average installation attitude state of the depth sounder during the entire measurement period is extracted using the attitude sensor output information included in the operational data collected in step S11. Installation data refers to the installation angle of the single-beam depth sounder relative to the ship's coordinate system, including the longitudinal tilt angle (pitch offset angle) and the lateral roll angle (roll offset angle), in degrees. Using the continuous angular velocity and angle change sequence provided by the attitude inertial navigation system (IMU), attitude data segments are selected during the ship's stable navigation phase (velocity change rate < 0.2 knots / second, direction change < 1 degree / second), and the angle between the depth sounder's orientation and the theoretical vertical direction during this time period is calculated. For example, in a certain operating path, if the ship maintains uniform linear motion for 5 minutes, during which the attitude angle is stable at a pitch angle of 11.5° and a roll angle of 1.8°, the depth sounder installation is calculated to have a forward tilt of 11.5° and a right tilt of 1.8° relative to the vertical direction, which is the tilted installation state.

[0037] Step S13: Identify the single-beam echo sounder measurement route data based on the single-beam echo sounder operation data;

[0038] In this embodiment of the invention, in the raw operational data collected in step S11, the GPS data provided by the positioning module gives the latitude and longitude coordinates corresponding to each time point in a time series manner. These coordinate data are imported into a GIS data processing platform to form a flight path trajectory on the base map. To ensure path continuity and spatial resolution, data is sampled at 1-second intervals to generate a high-precision measurement path point sequence with time stamps. A spatial coordinate trajectory line fitting method (such as five-point Bézier curve fitting) is used to eliminate minor path jumps caused by GPS signal jitter, making the path smooth for subsequent environmental parameter registration. Simultaneously, according to the flight path segment division rules, the entire operational path is divided into segments and marked. Segment numbers such as R1, R2, R3, etc., are generated according to the principle that each segment length is not less than 100 meters, and the start and end points, path length, average speed, and average attitude angle of each segment are recorded. The output of this step is a complete "measurement route dataset," which is used for subsequent environmental change analysis and simulation.

[0039] Step S14: Collect data on environmental changes along the measurement route based on the single-beam echo sounder measurement route data;

[0040] In this embodiment of the invention, after acquiring the measurement route data, the system utilizes a multi-source environmental monitoring device to extract environmental elements along the route. This environmental acquisition system includes a wave height radar, wind speed and direction sensors, a turbidity meter, a water temperature sensor, and a water flow direction / velocity measurement device. The system performs paired sampling for each measurement route segment's navigation time interval and records the following data: wave height (meters), average wave period (seconds), main wave direction (degrees), water turbidity (NTU), wind speed (m / s), and surface bubble density (bubbles / m²). Data is collected in sets of data every 5 seconds, with each set containing a spatial label and a route segment label. For example, in the R3 route, the average wave height was measured to be 0.8 meters, the main wave direction was 212 degrees, the wind speed was 4.3 m / s, and the surface bubble density was approximately 56 bubbles / m². Combining this with the acoustic penetration capability of the depth sounder, these data were used as input parameters for environmental disturbances to form an environmental change database, which will be used to provide data support for subsequent analysis of acoustic wave propagation path disturbances, incident angle fluctuations, etc.

[0041] Step S15: Perform depth sounding simulation based on the single-beam echo sounder measurement route data and single-beam echo sounder installation data to obtain single-beam echo sounder depth sounding simulation data.

[0042] In this embodiment of the invention, based on the measurement route data obtained in step S13 and the installation data in step S12, the path segment, ship speed, and installation tilt angle are used as inputs, combined with the sound wave emission parameters (emission frequency of 200kHz and sound speed of 1500m / s), to construct a simulation process for back-calculating the sound wave path. A ray tracing propagation path analysis method is employed to calculate the direction angle of the sound wave from the emission point (affected by the tilt angle), the location of the incident point (calculated by the ship's attitude and water depth), and the echo path (including single reflection and multiple path retracing), generating a theoretical depth sounder. Environmental disturbance parameters, such as wave surface disturbance angle ±2.1 degrees, water surface reflection loss coefficient of 0.25, and wave impact frequency of 0.18Hz, are introduced during the sound wave path simulation to correct the sound wave incident angle and simulate the propagation trajectory of the sound wave in dynamic water. During the simulation, all echo point locations, propagation times, and expected depth sounders are recorded at high resolution (0.01-meter accuracy). In path segment R3, simulation calculations show that the original installation angle is 11.5°, and the average wavefront disturbance angle is ±2.1°, causing the acoustic wave incident angle to dynamically change within the range of [9.4°, 13.8°]. The corresponding echo point depth values ​​at different angles differ within a range of ±0.7 meters. This step outputs a single-beam echo sounder depth sounding simulation data table, with fields including path segment number, theoretical depth value, incident angle, echo time, and fluctuation correction value, providing basic data support for subsequent depth sounding deviation analysis and error prediction.

[0043] Preferably, step S15 includes the following steps:

[0044] Step S151: Identify the installation attitude data of the single-beam echo sounder based on the installation data of the single-beam echo sounder;

[0045] In this embodiment of the invention, based on the single-beam echo sounder installation data determined in step S12, the triaxial acceleration and angular velocity data collected by the attitude sensor (inertial measurement unit, IMU) during the measurement are extracted. An attitude calculation algorithm (such as a Kalman filter) is used to filter and fuse the raw IMU sensor signals, eliminating vibration interference and obtaining accurate attitude angle information. The attitude data includes pitch, roll, and yaw angles, in degrees. Using this data, a time series of installation attitude data is formed to identify the stable range and trend of the installation attitude. Combined with the ship's geometric model, the installation attitude of the echo sounder relative to the ship's coordinate system is determined, i.e., the angular relationship between the echo sounder's orientation and the ship's longitudinal, lateral, and vertical directions. The time series file format of the attitude data is JSON, containing timestamp, pitch, roll, and yaw angle fields. This data provides the basic input for subsequent installation angle measurements.

[0046] Step S152: Measure the installation angle of the depth sounder based on the installation attitude data of the single-beam depth sounder to obtain the tilt installation angle data of the depth sounder;

[0047] In this embodiment of the invention, the installation attitude data obtained in step S151 is statistically analyzed and filtered to select stable attitude data within the measurement time period. Specifically, values ​​with instantaneous anomalies or large fluctuations are excluded, and continuous time periods with pitch and roll angle fluctuations less than ±0.3 degrees are retained. The overall tilt angle of the depth sounder is obtained by averaging the pitch and roll angles within this continuous interval. Here, the pitch angle represents the forward and backward tilt of the depth sounder relative to the vertical line of the hull, and the roll angle represents the left and right tilt. Assuming the calculated results are a pitch angle of 11.3 degrees and a roll angle of 2.1 degrees, the installation direction deviation of the depth sounder is determined based on these angles and the hull reference coordinate system.

[0048] Step S153: Determine the changes in the trajectory of the ship where the depth sounder is installed based on the measurement route data of the single-beam echo sounder;

[0049] In this embodiment of the invention, the trajectory of the vessel on which the depth sounder is installed is extracted based on the measurement route data identified in step S13. The trajectory data consists of latitude and longitude coordinates collected every second by the GPS module. Combined with heading angle and speed data, spatial interpolation and filtering are used to calculate the trajectory curvature, speed change rate, and heading angle change rate of the vessel. Curve fitting technology is used to smooth the trajectory points, eliminating GPS signal jitter errors. Subsequently, based on the time series of the trajectory points, the dynamic change indicators of the vessel trajectory are calculated, including the heading change rate (unit: degrees / second), speed change rate (unit: knots / second), and trajectory curvature radius (unit: meters). For example, if the average heading change rate is measured to be 0.15 degrees / second in a certain segment, the trajectory curvature radius is approximately 300 meters, and the speed change rate is less than 0.1 knots / second. This data clarifies the dynamic motion characteristics of the vessel during the measurement process, providing a basis for the vertical offset of the depth sounder's incident angle.

[0050] Step S154: Based on the changes in the trajectory of the depth sounder installation and the data of the depth sounder tilt installation angle exceeding 9.5°, perform a vertical offset measurement of the depth sounder incident angle to obtain the vertical offset data of the depth sounder incident angle.

[0051] In this embodiment of the invention, it is determined whether the tilt installation angle (mainly pitch angle) measured in step S152 exceeds a threshold of 9.5 degrees. If it exceeds this threshold, the incident angle vertical offset measurement process is initiated. Based on the dynamic index of the ship trajectory change measured in step S153, combined with the depth sounder installation tilt angle, the actual offset angle of the incident sound wave relative to the vertical direction is calculated using a geometric projection method. Specifically, the method is as follows: by superimposing the depth sounder tilt angle with the ship's heading change angle, the dynamic offset of the instantaneous sound wave incident angle is obtained; the actual offset angle of the sound wave incident angle on the vertical plane is calculated using trigonometric functions, in degrees.

[0052] Step S155: Determine the sound velocity echo path of the probe based on the vertical offset data of the incident angle of the depth sounder, and obtain the sound velocity echo path data of the probe.

[0053] In this embodiment of the invention, based on the vertical offset data of the incident angle obtained in step S154, the acoustic echo path is determined using an acoustic propagation path tracing method. Utilizing the principle of sound wave propagation and combining it with the seawater sound velocity profile (determined by depth sounding and temperature-salinity data to show the sound velocity variation with depth), the actual path of the sound wave from the emission point to the seabed and back to the receiver is simulated. Based on the dynamic offset of the sound wave incident angle, the propagation distance and path shape of the sound wave at each moment are calculated, including the direct path, the reflected path, and the multi-path interference path. A ray tracing algorithm is used to simulate the refraction and reflection process of the sound wave in the water medium, obtaining the propagation time and distance of each path. These echo path data are organized into a time series to form a sound velocity echo path dataset for the sounder, with fields including path type, propagation time, propagation distance, and the corresponding incident angle. This data provides core acoustic path information for subsequent depth sounder simulation models.

[0054] Step S156: Construct a simulation model of a single-beam echo sounder based on the sounder's acoustic echo path data and the changes in the ship's trajectory when the echo sounder is installed.

[0055] In this embodiment of the invention, the acoustic echo path data in step S155 and the dynamic change data of the ship's trajectory in step S153 are integrated to construct a comprehensive depth sounding simulation model. This simulation model employs a numerical simulation platform based on a combination of physical acoustics and kinematics to achieve full dynamic simulation of the depth sounder's measurement process. Model parameters include: sound velocity profile parameters, acoustic wave emission frequency and power, ship motion speed and attitude change data, depth sounder installation angle, and dynamic incident angle offset data. The simulation process simulates the propagation and echo reception of each acoustic wave emission cycle in time intervals, calculating the expected depth sounding value and its error distribution. The simulation results provide the theoretical depth sounding value at each time point, the impact of the incident angle offset on the depth sounding error, and the measurement deviation caused by the variable acoustic wave path. The simulation model is developed using the Simulink platform, and the output data format is a time-series structure containing fields such as timestamp, theoretical water depth, and path error.

[0056] Step S157: Perform depth sounding simulation based on the single-beam echo sounder simulation model to obtain single-beam echo sounder depth sounding simulation data.

[0057] In this embodiment of the invention, the simulation model established in step S156 is used to run simulation calculations step by step according to the time sequence of the measurement route. By inputting the real-time trajectory and attitude data of the hull, combined with the acoustic propagation path, the actual propagation distance of the sound wave and the expected depth measurement value at each moment are calculated. During the simulation, the effects of the depth sounder's tilt angle, vertical offset of the incident angle, and the dynamic motion of the hull on the sound wave propagation are considered in real time. The depth measurement error is calculated to obtain a complete depth measurement simulation dataset, including depth measurement time, theoretical depth measurement value, error compensation value, sound wave path information, and dynamic disturbance index. This data is saved in CSV format, with clear fields and a complete structure, providing direct data support for subsequent error analysis and deviation correction. By comparing the measured data with the simulation data, the impact of tilted installation on depth measurement accuracy can be effectively verified, achieving accurate measurement in extremely shallow waters.

[0058] Preferably, step S2, which involves detecting dynamic disturbance response data of the depth sounding angle based on changes in the environmental conditions of the measurement route using the single-beam echo sounder depth sounding simulation data, includes:

[0059] Analyze the temporal changes in the environmental conditions of the measurement route based on the changes in the measurement route environment;

[0060] In this embodiment of the invention, based on the environmental change data of the measurement route collected in step S1, time-series analysis is performed on the environmental parameters within the measurement time series. Environmental parameters include surface wind speed, wind direction, wave height, wave period, air temperature, salinity, and seawater temperature profile. These data are provided by fixed environmental monitoring sensors (such as wave buoys and weather stations) and underwater acoustic detection equipment, with a sampling frequency of 1Hz to 10Hz. The aforementioned time-series environmental data undergoes smoothing filtering to remove abnormal abrupt changes, and moving averages and low-pass filters are used to maintain data continuity. Based on time-series statistical analysis methods, such as autocorrelation function and power spectral density analysis, the changing trends and periodic characteristics of the environmental parameters are identified. By calculating the time-varying mean and variance of the environmental parameters, an environmental change trend curve is formed. The analysis results output an environmental time-series change data file, containing timestamps and corresponding changes in each environmental parameter. This data provides a spatiotemporal environmental basis for determining the ship's disturbance factors.

[0061] Determine the joint disturbance factor data of the hull based on the temporal changes in the environmental conditions along the measurement route;

[0062] In this embodiment of the invention, environmental time-series change data is used in conjunction with the ship's own dynamic characteristics to calculate the joint disturbance factor. The joint disturbance factor mainly includes wind and wave forces, wind load moments, wave-induced ship acceleration, and inertial forces. Based on classical ocean engineering theory, the Morison equation and ship response spectrum analysis method are used to calculate the wind and wave disturbance forces. Specifically, based on wave height and period data, the time variation characteristics of wave forces applied to different parts of the ship are calculated; based on wind speed and direction data, the wind load moment is calculated. Combining the ship's natural frequency and damping characteristics, the ship's motion response is obtained. Using a three-degree-of-freedom motion model of the ship, the acceleration and angular velocity of the ship in the pitch (about the transverse axis), roll (about the longitudinal axis), and yaw directions are calculated. The joint disturbance factor is expressed in time-series form, including the dynamic disturbance amplitude and rate of change in each direction. This data provides a quantitative basis for identifying changes in the installation attitude of the depth sounder.

[0063] Based on the joint disturbance factor data of the installed hull, the attitude changes of the hull where the depth sounder is installed are identified from the depth sounding simulation data of the single beam depth sounder.

[0064] In this embodiment of the invention, the attitude changes of the hull where the depth sounder is installed are analyzed based on the aforementioned joint disturbance factor. The depth sounder's attitude data is synchronized with the hull's joint disturbance factor using a timestamp synchronization method, combined with the depth sounder's angular velocity and acceleration data collected by the inertial measurement unit (IMU). Through kinematic derivation, a mapping relationship between the depth sounder's attitude changes and the hull's disturbances is established. Fourier transform analysis is used to analyze the spectral characteristics of the depth sounder's angular velocity data to distinguish between low-frequency hull swaying and high-frequency mechanical vibration. The time-varying curves of pitch and roll angles are extracted as a key focus. During the identification process, a threshold method is used to filter time periods with significant attitude changes, and the instantaneous amplitude and rate of change of attitude angles are calculated to form a dataset of the attitude changes of the hull where the depth sounder is installed. This data provides input for subsequent sway direction classification.

[0065] The ship's attitude changes after the depth sounder is installed are processed by dividing the ship's swing direction to obtain the ship's forward and backward swing data around the transverse axis and the ship's left and right tilt data around the longitudinal axis.

[0066] In this embodiment of the invention, the attitude change data obtained before the steps are divided directionally according to the coordinate axes. Specifically, the attitude change is decomposed into two components: the yaw (forward and backward swaying of the hull) and the roll (left and right tilting of the hull). A three-dimensional coordinate transformation matrix is ​​used to transform the depth sounder's attitude angle from the sensor coordinate system to the hull coordinate system. Through matrix operations, the angular changes around the yaw and roll axes are extracted. The forward and backward sway angles and the left and right tilt angles corresponding to different time points are calculated. The maximum sway amplitude and average angular velocity in these two directions are statistically analyzed to form two time series: the forward and backward sway data around the yaw axis and the left and right tilt data around the roll axis. This divided data provides a basis for detecting changes in pitch and roll angles.

[0067] The pitch angle change of the single-beam depth sounder is detected based on the data of the ship's forward and backward swaying around the transverse axis.

[0068] In this embodiment of the invention, the pitch angle change signal of a single-beam echo sounder is extracted using the time series data of the ship's swaying around the transverse axis obtained before the steps. Specifically, the pitch angle time series reflects the dynamic angular fluctuation of the echo sounder around the ship's transverse axis by real-time acquisition of the ship's rotation angle changes by an inertial measurement unit (IMU) sensor installed on the ship. The first-order differential operation is performed on this pitch angle time series signal to obtain the pitch angle change rate curve, which is used to quantify the speed and dynamic characteristics of the angle change. Simultaneously, the pitch angle data is compared with the acceleration data acquired by the IMU sensor in time synchronization. A filtering algorithm is used to eliminate short-term abnormal signals caused by non-swaying factors such as ship vibration or water waves, thereby ensuring that the extracted pitch angle change signal accurately reflects the actual swaying motion of the ship around the transverse axis. Furthermore, statistical parameters, including maximum, minimum, mean, and standard deviation, are calculated on the processed pitch angle data to form a complete pitch angle change statistical report. This report details the vertical deflection of the incident angle when the depth sounder emits sound waves, quantifies the amplitude and dynamic characteristics of the pitch angle change in the sound wave emission direction, and provides necessary angle deflection parameters and time series data for the comprehensive calculation of the degree of change in the sound wave emission direction in subsequent steps.

[0069] The roll angle of the single-beam depth sounder is detected based on the ship's tilt data around its longitudinal axis.

[0070] In this embodiment of the invention, by acquiring the left and right tilt angle data of the hull around its longitudinal axis, the data is preprocessed to obtain the roll angle variation of the depth sounder. A digital filtering technique combining high-pass and low-pass filtering is used to effectively remove random noise and environmental interference from the sensor, ensuring the smoothness and continuity of the roll angle signal. Subsequently, the instantaneous change value of the filtered roll angle data is calculated to reflect its dynamic tilt amplitude at any time point. Statistical methods are used to analyze the roll angle amplitude distribution characteristics, revealing the central tendency and dispersion of the tilt amplitude. Polynomial fitting or curve fitting techniques are used to mathematically model the roll angle variation trend, describing its change law over time. Key parameters, including the maximum roll angle value and standard deviation, are extracted from the fitting results as important indicators for evaluating the dynamic fluctuation amplitude of the roll angle, forming a complete time series data of roll angle variation. This data reflects in detail the dynamic tilt characteristics of the depth sounder in the longitudinal direction of the hull, providing accurate input data for the subsequent calculation of the acoustic wave emission direction offset, ensuring the scientific accuracy of the quantitative analysis of the tilt effect.

[0071] The degree of change in the acoustic wave emission direction of the sounder is determined based on the changes in the pitch angle and roll angle of the single-beam echo sounder.

[0072] In this embodiment of the invention, the actual offset angle of the acoustic wave emission direction is calculated using a spatial vector superposition method, combining the change data of pitch and roll angles. Specifically, the pitch and roll angles are converted into angular offset components in two orthogonal directions, and then vectorized to obtain the deflection angle of the acoustic wave emission direction in three-dimensional space. Based on time-series data, the magnitude of the change in the acoustic wave emission direction at each moment is calculated, and its rate of change is analyzed. By comparing the emission direction under static installation with the direction under dynamic conditions, the degree of change in the acoustic wave emission direction is determined. A dataset of the degree of change in the acoustic wave emission direction is output, with fields including timestamp, total deflection angle, pitch contribution angle, and roll contribution angle. This data provides a key indicator for dynamic disturbance response detection.

[0073] The dynamic disturbance response data of the depth sounding angle are detected based on the degree of change in the direction of acoustic wave emission from the depth sounder.

[0074] In this embodiment of the invention, time-series statistical analysis is performed on the data on the degree of change in the sound wave emission direction obtained before the steps to accurately characterize the dynamic disturbance response of the depth sounding angle. The specific operation process is as follows: Discrete-time sampling processing is performed on the sequence of sound wave emission direction deflection angle changes over time to ensure that the sampling frequency covers the dynamic disturbance frequency band of interest. Subsequently, by setting a dynamic disturbance response threshold, usually determined based on historical data experience or on-site calibration results, a disturbance event is considered to begin when the deflection angle exceeds the threshold, and to end when it falls below the threshold, thus accurately defining the start and end times of each dynamic disturbance. Next, for the defined disturbance interval, its disturbance amplitude curve is extracted, the envelope of the disturbance signal is calculated to capture the overall amplitude change trend, and the spectral density is calculated using the Fast Fourier Transform (FFT) method to identify the main frequency components and energy distribution characteristics of the disturbance signal. Spectral analysis can distinguish different disturbance types; for example, periodic changes with lower frequencies and larger amplitudes are classified as low-frequency oscillation disturbances, while those with higher frequencies and drastic amplitude changes are classified as high-frequency vibration disturbances. To further quantify the disturbance characteristics, it is also necessary to statistically analyze the maximum peak amplitude, duration of the disturbance, and timestamp of the disturbance event. All these disturbance parameters are then integrated to form a dynamic disturbance response dataset for the bathymetry angle. This dataset includes key indicators such as the start time, end time, duration, peak amplitude, dominant frequency, and energy distribution of each disturbance. This dataset serves as the core input for determining the intensity of coupled interference in the bathymetry environmental measurements in subsequent steps, ensuring the accurate response analysis of the bathymetry to angle disturbances in complex marine environments.

[0075] Preferably, in step S2, determining the environmental measurement coupling interference intensity of the depth sounder based on changes in the measurement route environment and dynamic disturbance response data of the depth sounding angle includes:

[0076] Determine the trend of wave enhancement in the environmental environment along the measurement route based on changes in the environmental conditions.

[0077] In this embodiment of the invention, when determining the wave enhancement trend of the measurement route based on environmental changes, the dynamic changes of the environmental waves are quantitatively analyzed using statistical analysis and trend fitting methods, based on the acquired environmental data of the measurement route, including time-series data such as sea surface wind speed, wind direction, wave height, and period. Wave spectrum analysis technology is used to calculate wave energy distribution and determine the trend characteristic parameters of wave enhancement, such as wave height growth rate, period variation trend, and wave direction change. By comparing environmental data from different time periods, it is determined whether the wave energy shows an increasing trend, obtaining wave enhancement trend data, which serves as the basic input for subsequent coupling interference analysis.

[0078] Estimate the growth of the bubble layer on the water surface along the measurement route based on the trend of enhanced environmental waves.

[0079] In this embodiment of the invention, when estimating the growth of the bubble layer on the water surface along the measurement route based on the wave enhancement trend, a bubble generation model is applied based on known ocean physics principles and wave enhancement trend parameters. Specifically, the bubble generation rate and distribution density are calculated by leveraging the correlation between sea surface turbulence intensity and wave breaking frequency, deriving the variation curves of bubble layer thickness and volume fraction. Combined with on-site observed sound velocity profile data, the bubble layer estimation results are further refined to obtain data on the growth of the bubble layer on the water surface based on the wave enhancement trend, which is used to assess its impact on sound wave propagation.

[0080] The wear and tear of the single-beam depth sounder was detected based on the increasing trend of environmental waves along the measurement route.

[0081] In this embodiment of the invention, when detecting the wear growth of a single-beam echo sounder based on the wave enhancement trend of the measurement route environment, the relationship between the wave enhancement trend and the stress on the equipment is analyzed. Vibration sensors and accelerometers are used to collect mechanical vibration data at the echo sounder's installation location. Through vibration amplitude and wave frequency matching analysis, the periodicity and intensity of wear intensification are determined. Combining equipment usage time and cumulative vibration amplitude, a wear growth curve model is established to calculate the wear changes of key echo sounder components such as the probe surface and housing, generating wear growth data to provide a quantitative basis for subsequent structural damage assessment.

[0082] The wear growth of a single-beam depth sounder and the dynamic disturbance response data of the depth sounding angle were used to examine the damage to the fastener structure of the depth sounder.

[0083] In this embodiment of the invention, when examining the structural damage of fasteners in a depth sounder based on wear growth data and dynamic disturbance response data of the sounding angle, ultrasonic testing and structural health monitoring technologies are employed to perform non-destructive testing on the fastener connection areas. Vibration mode recognition and dynamic response analysis are used to detect structural loosening, crack initiation, and propagation. Combined with wear growth data, changes in the mechanical properties of the fasteners are assessed, forming a structural damage probability index. Simultaneously, dynamic disturbance data is used to analyze the stress state of the fasteners under different dynamic loads, achieving comprehensive detection of fastener structural damage.

[0084] The extent of erosion on the probe surface is detected based on the growth of the bubble layer on the water surface along the route.

[0085] In this embodiment of the invention, when detecting the erosion intensification of the probe surface based on the growth of the bubble layer on the water surface along the route, high-frequency acoustic scattering technology is used to perform detailed detection of the probe surface. This technology obtains the scattering characteristics of the probe surface structure by emitting sound waves of a specific frequency and receiving the reflected signals, generating high-resolution sonar images. Probe surface data is continuously acquired over multiple measurement cycles to ensure sufficient time intervals to capture the dynamic changes in corrosion development. Comparative analysis of sonar images at different time points is performed, and image processing algorithms are used to identify changes in surface texture, the number, area, and distribution of corrosion pits, achieving a quantitative assessment of the probe corrosion degree. Trend analysis is conducted using multi-time period image data to reveal the relationship between corrosion expansion rate and bubble layer thickness and density. Simultaneously, chemical parameters of the aquatic environment, including dissolved oxygen concentration, pH value, salinity, and water temperature, are collected. Combined with water flow velocity and turbulence intensity data, the physicochemical mechanism of probe surface corrosion is comprehensively analyzed, focusing on the promoting effect of the bubble layer on the corrosion reaction rate. By establishing a time-series model of corrosion intensification, the influence of bubble layer growth on the erosion rate of the probe material is quantitatively described, forming erosion intensification data with temporal and spatial resolution. This data provides a solid foundation for a comprehensive assessment of the amplification of environmental disturbances in the depth sounder, and supports the accurate determination of the degree of impact of environmental factors on equipment performance.

[0086] Estimate the amplification of environmental disturbances in the tilt sounder based on the trend of enhanced environmental waves along the measurement route;

[0087] In this embodiment of the invention, when estimating the amplification of environmental disturbances in an inclined depth sounder based on the wave enhancement trend of the measurement route, wave enhancement trend data within the measurement route is collected. This data, including parameters such as wave height, wave period, and wave direction, is acquired by wave sensors installed around the hull of the measuring vessel. Simultaneously, data on the distribution and concentration of the bubble layer on the water surface are collected. An acoustic Doppler current profiler (ADCP) and an acoustic scattering instrument are used to monitor the characteristics of the bubble layer in real time, obtaining information such as bubble density and size distribution. Simultaneously, the measuring instrument itself is equipped with high-precision accelerometers and vibration sensors to collect mechanical vibration data of the equipment, including vibration frequency, vibration amplitude, and vibration direction. The above three types of data are time-synchronized to ensure consistency of timestamps from different data sources, thus ensuring the accuracy of subsequent analysis. Frequency response analysis is used to perform spectral analysis on the wave, bubble layer, and mechanical vibration signals, and the main vibration frequency components and their amplitude characteristics are extracted using Fast Fourier Transform (FFT). A coupled vibration transmission model was established by combining the natural frequency and damping characteristics of the depth sounder structure. This model uses finite element analysis to simulate how mechanical vibrations caused by waves and bubbles propagate through the support structure and mounting device of the depth sounder, focusing on calculating the vibration amplification factor and dynamic response amplitude. The model inputs include wave excitation force, acoustic pressure waves caused by bubbles, and the vibration state of the equipment itself. The response amplitude of the depth sounder under different frequencies is obtained by solving the structural dynamics equations. The output results are data on the amplification of environmental disturbances, quantitatively reflecting the degree of vibration enhancement of the depth sounder caused by wave and bubble disturbances transmitted through the structure. This data serves as an important indicator of the intensity of environmental coupled interference, providing key parameter support for subsequent error correction and depth sounding value correction.

[0088] The intensity of environmental measurement coupling interference of the depth sounder is determined based on the intensification of surface erosion of the probe and the amplification of environmental disturbances of the tilting depth sounder.

[0089] In this embodiment of the invention, when determining the coupling interference strength of the tilt sounder's environmental measurement based on the intensification of surface erosion and the amplification of environmental disturbances, the collected surface corrosion data of the probe and the amplified environmental disturbance data of the tilt sounder are synchronously integrated. The probe corrosion data includes corrosion area, depth distribution, corrosion rate, and corrosion morphology characteristics. The amplified environmental disturbance data covers the mechanical vibration amplification coefficient caused by waves, the acoustic scattering effect generated by the bubble layer, and the structural resonance enhancement effect. A multivariate comprehensive evaluation method is adopted. By establishing a multidimensional feature space, corrosion indicators and disturbance amplification indicators are used as input variables. Historical maintenance records and actual operating parameters of the equipment are introduced, such as equipment usage time, maintenance cycles, and auxiliary parameters such as operating environment temperature and salinity, to construct a quantitative model of the coupling effect between environmental factors and equipment aging. This model uses weight allocation and normalization techniques to standardize each variable, ensuring the comparability of data with different dimensions. A comprehensive evaluation function is formed through weighted superposition. By employing statistical regression analysis and machine learning regression algorithms, combined with historical equipment performance monitoring and actual deviation data of depth sounding errors, model parameters are calibrated to achieve accurate prediction of coupling interference intensity. The generated environmental measurement coupling interference intensity index is a comprehensive value that clearly reflects the combined impact of environmental disturbances and wear on the depth sounder under specific environmental conditions and equipment status. This index serves as an input parameter, directly used in the depth sounding error correction module to assist in adjusting the weight allocation of the depth sounding correction algorithm, thereby improving the accuracy and reliability of measurements in extremely shallow waters.

[0090] Please see Figure 3 This is a schematic diagram of the metal fatigue degree detection of the single-beam depth sounder in this invention;

[0091] Preferably, step S2, determining the dynamic anomaly of the sound wave propagation path based on the coupling interference intensity measured by the depth sounder environment, includes:

[0092] The resonance aggravation of a single-beam depth sounder is estimated based on the coupling interference intensity measured in the environment of the depth sounder.

[0093] In this embodiment of the invention, the resonance aggravation of a single-beam echo sounder is estimated based on environmental coupling interference intensity data. Specifically, vibration sensors and accelerometers are deployed at key structural parts of the echo sounder to collect mechanical vibration signals in real time. Spectrum analysis is used to decompose the collected vibration signals into frequency components, identifying the energy change trend within the resonance frequency range. The continuous rise in vibration energy and the concentration of peak frequencies indicate the resonance aggravation state. This process is recorded using high-speed data acquisition equipment, and combined with environmental coupling interference intensity data, a vibration-environment coupling relationship curve is established, thereby obtaining a quantitative estimate of the resonance aggravation.

[0094] Detecting the degree of metal fatigue in a single-beam depth sounder based on the intensification of resonance;

[0095] In this embodiment of the invention, the fatigue degree of a single-beam depth sounder is further detected based on resonance aggravation data. During implementation, ultrasonic testing technology is used to periodically scan the surface and internal structure of key metal components of the depth sounder, collecting the acoustic signal reflection intensity and scattering characteristics of metal fatigue cracks. Combined with the distribution of stress concentration areas caused by resonance, the generation and propagation degree of metal fatigue cracks are inferred using acoustic emission analysis. Fatigue degree quantification employs a fatigue damage accumulation model, combined with resonance state parameters, to derive the current metal fatigue index, reflecting the proximity of the equipment structure to its safety boundary.

[0096] Predicting the accumulation of microcracks in a single-beam echo sounder based on the degree of metal fatigue;

[0097] In this embodiment of the invention, a detailed description of an example of predicting the accumulation of microcracks in a single-beam echo sounder based on the degree of metal fatigue is provided below. Combining fracture mechanics theory from materials mechanics, and using fatigue crack propagation rate as a fundamental parameter, a microcrack growth prediction model is constructed based on the material properties of key metal components of the echo sounder and historical operational fatigue data. This model comprehensively considers the range of stress intensity factors, the stress field distribution at the crack tip, and the relationship between crack propagation rate and cyclic load, accurately depicting the evolution process of microcracks under repeated stress. To obtain real-time dynamic information about the cracks, multi-frequency ultrasonic phased array detection technology is used to continuously monitor the metal structure of the echo sounder. This technology, by adjusting the ultrasonic emission frequency and phase, achieves high-resolution crack location and morphological identification, effectively enhancing the detection capability of early-stage microcracks. During the detection process, spatial dimensional changes such as crack length, width, and depth are collected to form a time-series dataset. Advanced time-series analysis methods, including trend analysis, spectral analysis, and prediction algorithms, are applied to this time-series data to accurately predict the future development trend of crack propagation and identify acceleration or deceleration stages of crack propagation rate. By combining predictive models with measured dynamic data, a refined prediction of microcrack accumulation can be achieved, forming a microcrack accumulation prediction dataset that includes crack size change trajectory, growth rate, and predicted future crack propagation amplitude. This provides a scientific basis for the safety assessment and maintenance planning of the depth sounder structure, ensuring the operational stability and reliability of key components of the depth sounder.

[0098] Calculate the collision probability data of the depth sounder in extremely shallow waters based on the depth sounding simulation data of the single beam echo sounder;

[0099] In this embodiment of the invention, a comprehensive analysis of the water depth distribution, acoustic reflection intensity, and detection blind zone of the current operating area of ​​the depth sounder is conducted based on depth sounding simulation data to accurately define the spatial distribution range of potential obstacles in extremely shallow waters. Using environmental measurement coupling interference intensity parameters, combined with underwater acoustic signal attenuation characteristics, the location and dynamic changes of underwater obstacles are further identified, including drift speed, direction, and deformation information. The trajectory data of the depth sounder mounted on the hull and real-time speed data are simultaneously collected and processed, and the real-time spatial position relationship of the depth sounder relative to obstacles is determined through a high-precision navigation system. A probabilistic statistical method is used to incorporate the uncertainty of underwater obstacle positions and the dynamic changes in the depth sounder's trajectory into the collision risk analysis framework. Specifically, Monte Carlo simulation technology is used to randomly generate a large number of navigation path samples, combining path deviations caused by environmental interference and changes in the depth sounder's attitude to simulate the motion state of the depth sounder under different conditions in extremely shallow waters. Collision determination is performed between each sample path and the spatial position of the obstacle, and the number of collision events and their temporal distribution are statistically analyzed. By statistically analyzing all sample path collision events, the frequency and probability distribution of collision events are calculated, forming collision probability data reflecting the collision risk of the depth sounder. This data specifically includes the numerical value of the collision probability, risk fluctuations within the corresponding time period, and the spatial distribution of high-risk areas, providing scientific and quantitative indicator support for the safe operation risk management of the depth sounder. This collision probability data can serve as input parameters for subsequent depth sounding data correction and risk early warning systems, achieving safety assurance and dynamic risk control for depth sounding operations in extremely shallow waters.

[0100] Based on the collision probability data of the depth sounder in extremely shallow water and the accumulation of microcracks in the single-beam depth sounder, the water seepage situation of the depth sounder micropores is predicted;

[0101] In this embodiment of the invention, the micropore seepage status of the depth sounder is estimated based on collision probability data and microcrack accumulation in extremely shallow water. The finite element method is used to analyze the seepage of key structures of the depth sounder, considering the impact of microcracks on the integrity of the waterproof layer. The process of water seepage through microcracks is simulated by combining material permeability and micropore size distribution parameters. The seepage rate and depth are calculated by combining structural deformation caused by collisions and crack propagation. The seepage risk is graded and assessed, generating micropore seepage status data to provide a basis for subsequent maintenance decisions.

[0102] The dynamic anomalies of the sound wave propagation path are determined based on the seepage status of the micropores in the depth sounder and the dynamic disturbance response data of the depth sounding angle.

[0103] In this embodiment of the invention, dynamic anomalies in the acoustic wave propagation path are comprehensively determined based on micropore seepage data from the depth sounder and dynamic disturbance response data from the sounding angle. Multi-source data fusion technology is used to combine structural changes caused by seepage with acoustic wave offset data resulting from angular disturbances, and spatiotemporal synchronous analysis is employed to identify anomalous characteristics of the acoustic wave propagation path. Anomalies are categorized, identifying enhanced reflection, multipath propagation, and signal distortion, thus forming quantitative descriptive data of the dynamic anomalies in the acoustic wave propagation path. This data serves as the core input for subsequent depth sounding error prediction and correction, ensuring the accuracy of the depth sounder in extremely shallow water environments.

[0104] Preferably, step S3 includes the following steps:

[0105] Step S31: Determine the multipath interference situation of the depth sounder based on the dynamic anomaly of the sound wave propagation path;

[0106] In this embodiment of the invention, the multipath interference of the depth sounder is determined based on the dynamic anomalies of the sound wave propagation path. Using the dynamic anomaly parameters of the sound wave propagation path obtained in the preceding steps, combined with the water sound velocity distribution, water depth changes, and seabed reflection characteristics in the actual measurement environment, a multipath sound wave propagation model is constructed. Through spatiotemporal variation analysis of the sound wave propagation path, the reflecting and refractive interfaces causing multipath interference are identified, including the water surface, seabed, and interfaces of different density layers in the water body. High-resolution acoustic signal processing equipment is used to perform time-frequency domain analysis on the received echo signal, detecting signal overlap and time delay distribution, and identifying abnormal waveforms and interference intensity caused by multipath signals. By quantitatively calculating the amplitude attenuation, phase change, and time delay difference of the multipath interference signal, multipath anomaly interference characteristic data is formed, providing a basic input for subsequent signal distortion prediction. This data reflects in detail the dynamic anomalies of sound wave propagation in the complex environment of extremely shallow water, including indicators such as the number of interference paths, signal superposition intensity, and time distribution.

[0107] Step S32: Predict the signal distortion of the single-beam depth sounder based on the multipath abnormal interference of the depth sounder;

[0108] In this embodiment of the invention, the signal distortion of a single-beam echo sounder is predicted based on the multipath interference of the echo sounder. The multipath interference characteristic data obtained in step S31 is combined with the echo sounder's signal receiving mechanism to analyze the impact of multipath interference on the amplitude, phase, and frequency response of the echo signal. A high-precision sonar signal analyzer is used to extract the nonlinear distortion components, distortion index, and signal-to-noise ratio changes of the signal. Combined with the acoustic wave propagation characteristics under the special hydrological conditions of extremely shallow waters, the signal delay spread and spectral broadening phenomena caused by multipath effects are identified. By comparing and analyzing historical echo sounding data, a correspondence between signal distortion and multipath interference is established, predicting the signal distortion trend and amplitude range under the current environment. A prediction dataset containing signal distortion levels, distortion duration, and frequency band influence range is formed, providing support for acoustic wave frequency drift detection in extremely shallow waters.

[0109] Step S33: Detect the acoustic frequency drift phenomenon in extremely shallow waters based on the multipath abnormal interference of the depth sounder and the signal distortion of the single-beam depth sounder.

[0110] In this embodiment of the invention, the frequency drift phenomenon of acoustic waves in extremely shallow waters is detected based on the multipath interference of the depth sounder and the signal distortion of the single-beam depth sounder. The frequency stability of the acoustic signal is analyzed using multipath interference and signal distortion data. A high-resolution spectrum analyzer is used to monitor the instantaneous frequency changes and frequency shift trends of the echo signal. The influence of environmental factors on frequency drift is decoupled by combining the changes in sound velocity caused by variations in water temperature, salinity, and water flow in extremely shallow waters. By comparing the theoretical acoustic wave transmission frequency with the actual received frequency, the amplitude and rate of frequency shift are accurately identified. Time series analysis is performed on continuous measurement data to determine the periodic and non-periodic characteristics of the frequency drift. Frequency drift phenomenon data, including frequency drift amplitude, drift rate, and time distribution, is generated, providing a quantitative basis for predicting depth sounding error expansion.

[0111] Step S34: Based on the acoustic frequency drift phenomenon in extremely shallow waters, predict the error spread of the depth sounder to obtain the error spread growth data of the depth sounder.

[0112] In this embodiment of the invention, the error propagation prediction of a depth sounder is performed based on the frequency drift phenomenon of acoustic waves in extremely shallow waters, resulting in depth sounder error propagation growth data. Using the frequency drift parameters detected in step S33, and combining the conversion relationship between acoustic wave propagation time and water depth, the error impact of frequency drift on the depth sounding results is calculated. Through numerical analysis of the cumulative effect of frequency drift error over time, the propagation trend of the depth sounding error is inferred. A time-resolved error prediction method is employed to generate an error growth curve, clarifying the dynamic evolution law of the error with changes in operating time and environment. The error propagation growth data is refined into error amplitude, growth rate, and critical error time point, forming a complete error propagation prediction dataset. This data serves as the basis for the measurement correction of an inclined single-beam echo sounder in extremely shallow waters, supporting the implementation of subsequent depth sounding value correction processing.

[0113] Preferably, step S31 includes the following steps:

[0114] Step S311: Detect the irregular reflection enhancement status of the water surface based on the abnormal situation of the sound wave propagation path;

[0115] In this embodiment of the invention, the irregular reflection enhancement of the water surface is detected based on anomalies in the sound wave propagation path. Specifically, the echo signal from a single-beam echo sounder is received, and the water surface reflection waveform in the echo signal is analyzed in both the time and frequency domains. A high-precision time-frequency analysis instrument is used to capture abnormal changes in the reflection intensity in the echo signal, focusing on identifying abrupt changes in the amplitude of the reflected wave and irregularities in time delay. Combined with environmental data from the measurement route, the dynamic changes in the water surface wave morphology are analyzed, paying particular attention to the impact of irregular waves, wind waves, and swells on the sound wave reflecting surface. By continuously monitoring the changing trend of the water surface reflection signal, the temporal distribution and spatial expansion characteristics of the reflection enhancement phenomenon are assessed. This step obtains quantitative data on the irregular reflection enhancement of the water surface, providing a basis for multiple reflection analyses.

[0116] Step S312: Determine multiple reflection data of sounding waves based on the irregular reflection enhancement of the water surface;

[0117] In this embodiment of the invention, multiple reflection data of sounding waves are determined based on the irregular reflection enhancement of the water surface. During operation, the water surface reflection enhancement information obtained in step S311 is used, combined with sound wave propagation path simulation technology, to infer the frequency and path of multiple reflections of sound waves in the water. A precise time delay estimation device is used to measure the temporal distribution and energy attenuation of multiple reflection waves in the echo signal. By analyzing the repetitive structure of the echo signal, specific parameters of the multiple reflection signals are determined, such as the number of reflections, path length, and reflection surface position. This step forms a multiple reflection dataset, covering the number of reflections and corresponding reflection intensities, providing data support for echo overlap and waveform distortion detection.

[0118] Step S313: Determine the overlap of the sounding echoes based on the multiple reflection data of the sounding waves and the irregular reflection enhancement of the water surface;

[0119] In this embodiment of the invention, the overlap of sounding echoes is determined based on multiple reflection data of sounding waves and the irregular reflection enhancement of the water surface. This operation identifies the overlap intervals of different reflected waves on the time axis based on the temporal and intensity characteristics of the multiple reflection signals. High-resolution signal deconvolution technology is used to separate the overlapping waveforms into independent echoes, assessing the degree of interference of the overlapping signals on the sounding results. The spatial dynamics of the enhanced water surface reflection are combined to analyze the changing trends of the overlap intervals and their impact on the sounding signal quality. Detailed echo overlap data is generated, including overlap duration, intensity superposition ratio, and spatial distribution, providing a quantitative basis for waveform distortion analysis.

[0120] Step S314: Inspect the degree of distortion of the sounding waveform based on the overlap of the sounding echoes;

[0121] In this embodiment of the invention, the degree of waveform distortion of the sounding wave is examined based on the overlap of the sounding wave echoes. Specifically, signal processing equipment is used to analyze the waveform of the overlapping echo signal, measuring waveform distortion parameters such as peak variation, waveform stretching, and phase shift. A time-frequency joint analysis method is employed to accurately capture the time-varying characteristics of waveform distortion. By comparing the deviation between the normal waveform and the actual received waveform, the percentage value of the waveform distortion degree is calculated. This step outputs waveform distortion degree data, serving as an important indicator for judging the severity of multipath interference.

[0122] Step S315: Inspect the degree of offset of the depth sounder's measuring point position based on the abnormality of the sound wave propagation path;

[0123] In this embodiment of the invention, the degree of positional shift of the depth sounder's measuring point is examined based on anomalies in the sound wave propagation path. The operation process utilizes spatiotemporal anomaly data of the sound wave propagation path, combined with the known installation location of the depth sounder and positioning system data, to calculate the spatial offset of the measuring point. By comparing continuous measurement data, the positional drift of the measuring point caused by multipath reflection and propagation anomalies is identified. Three-dimensional positioning and trajectory reconstruction technology is employed to accurately determine the offset distance and direction of the measuring point. This generates data on the degree of positional shift of the measuring point, reflecting the impact of sound wave propagation anomalies on the accuracy of the depth sounding position.

[0124] Step S316: When the distortion of the sound wave waveform is >8%, the multipath abnormal interference of the sounder is determined by the offset of the sounder measuring point position.

[0125] In this embodiment of the invention, when the distortion of the sounding waveform exceeds 8% and the offset of the depth sounder's measuring point exceeds a set threshold, the multipath interference situation of the depth sounder is determined by combining the above data. Through a data fusion algorithm, the waveform distortion and measuring point offset data are weighted and synthesized to generate a multipath interference evaluation index. This index quantifies the intensity and scope of multipath interference, providing a basis for subsequent signal processing and error correction. It forms multipath interference data for the depth sounder, clarifies the interference level and its spatiotemporal distribution, and provides technical support for ensuring the accuracy of depth sounding data in extremely shallow water measurement environments.

[0126] Of particular importance, step S32 includes the following steps:

[0127] Step S321: Determine the irregular changes in signal peak based on the multipath abnormal interference of the depth sounder;

[0128] In this embodiment of the invention, based on the "echo sounder multipath anomaly interference" dataset obtained in step S31, this data includes information such as the number of multipath reflected signals, time delay deviation, intensity ratio, and superposition degree. For each echo event, the time-domain waveform of the received echo signal is extracted and peak identification processing is performed. A high-precision time-frequency signal analysis instrument is used to detect the main peak in the echo at each moment, obtaining the peak amplitude and occurrence time. Subsequently, peak fluctuation analysis is performed to statistically analyze the difference between the standard deviation and mean of the main peak amplitude in the echo signal, as well as the jumps in the main peak occurrence time. By comparing with the statistical benchmark of the main peak amplitude variation range under normal conditions (e.g., ±0.2dB), the intervals where the peak exhibits irregular changes under the influence of multipath anomalies are identified, such as amplitude deviation exceeding ±0.5dB or the occurrence of delayed peak time offset exceeding 0.1 milliseconds. The output "peak irregular change dataset" includes the main peak amplitude and time difference change sequences in each echo sequence, and the abnormal band identifier.

[0129] Step S322: Determine the irregular changes in signal valleys based on the multipath interference of the depth sounder;

[0130] In this embodiment of the invention, the troughs (local minima) in the echo signal are identified and analyzed using the characteristics of multipath anomalies from the same source. Through time-domain signal processing, the echo waveform is normalized, and the location and amplitude of the first trough after a significant reflection in each echo are extracted. The trough depth (e.g., -30dB) and location parameters (corresponding to 30–40 microseconds after the main peak) during normal environmental conditions are compared to calculate the trough offset and depth fluctuation. If the trough amplitude offset exceeds ±3dB due to multipath interference, or if multiple troughs appear continuously instead of a single trough, it is considered an "irregular trough change." All measured trough fluctuation timestamps, amplitude deviations, and location changes are statistically analyzed to generate an "irregular trough change dataset" for subsequent error detection.

[0131] Step S323: Check the echo peak value judgment error based on the irregular changes in signal troughs and signal peaks;

[0132] In this embodiment of the invention, the data output from steps S321 and S322 are jointly analyzed. The irregular peak variation intervals and abnormal trough intervals are spatiotemporally compared to identify time periods where both peak amplitude shift and trough structure anomalies occur simultaneously. During these time periods, the system compares the peak identification processing results with the actual waveform structure to determine if a peak extraction error has occurred. By calculating the amplitude ratio between the primary peak and the second primary peak, and the difference in inter-peak time delay (e.g., the intensity of the second primary peak reaches more than 80% of the primary peak and the time difference is less than 5 microseconds), a peak identification error is determined to exist. These error periods are recorded as "echo peak judgment error" events, forming an error dataset containing the event start and end times, peak amplitude deviation, corresponding troughs, and inter-peak time differences, for subsequent distortion prediction.

[0133] Step S324: Based on the echo peak value, determine the error status and predict the signal distortion status of the single-beam depth sounder.

[0134] In this embodiment of the invention, error events are identified based on the echo peak values ​​obtained in S323, and the signal distortion trend is predicted. The frequency, duration, and average peak deviation of all error events are statistically analyzed. Combined with the signal-to-noise ratio (SNR) data of the echo signal (typically below 10 dB indicating severe noise), the distortion level is quantified, such as: mild distortion (deviation < 0.1 m), moderate distortion (deviation 0.1–0.5 m), and severe distortion (deviation > 0.5 m). During periods of concentrated event occurrence, the predicted signal distortion will frequently alternate between moderate and severe levels. A "signal distortion prediction dataset" is output, including: prediction start and end times, high distortion frequency ranges, signal deviation level distribution, and cumulative distortion time ratio. This data serves as input for subsequent depth sounding error extension (S34), ensuring accurate identification of depth sounding data variations caused by multipath interference during extremely shallow water measurements.

[0135] Of particular importance, step S34 includes the following steps:

[0136] Step S341: Determine the frequency component shift of the echo signal based on the acoustic frequency drift phenomenon in extremely shallow water.

[0137] In this embodiment of the invention, in extremely shallow waters, due to the shallow water depth, strong interface reflection, and frequent water disturbances, sound waves are subjected to complex interference during propagation, resulting in frequency shift. In this step, raw echo signal data transmitted from a tilted single-beam echo sounder across different flight segments are acquired, and real-time demodulation and spectrum extraction are performed using time-frequency analysis equipment. The echo data is processed in segments using short time windows, and the main frequency components in each time segment are extracted using a spectrum scanner and compared with the standard transmission frequency. Once a measurable offset is found between the received frequency and the standard frequency, it is determined that frequency component drift has occurred. This drift result is recorded in the form of a frequency component offset record table, including the time point, echo segment number, reference frequency value, actual frequency value, and the degree of deviation.

[0138] Step S342: Detect the degree of peak time point shift of the received signal based on the frequency component shift of the echo signal;

[0139] In this embodiment of the invention, based on the frequency component offset data obtained in the previous step, a further refined analysis of the time-domain changes in the signal waveform is performed. During this process, a signal comparison and analysis module is used to compare the echo signal with a standard waveform template segment by segment. By scanning point by point, the actual occurrence time of the signal peak is determined and compared with the theoretical propagation time, thereby extracting the offset value of the received peak time. This offset characterizes the degree of time-domain distortion caused by frequency instability during the propagation of the sounding signal. The result is represented in the form of a received signal peak time offset table, which includes each received time point, the corresponding frequency offset, the actual arrival time of the peak, and its deviation from the theoretical time.

[0140] Step S343: Estimate the spread of depth sounder measurement error based on the degree of shift in the peak time point of the received signal;

[0141] In this embodiment of the invention, the change in sounding error caused by the wave crest offset time data is evaluated through analysis. Specifically, each time offset value is converted into a corresponding depth error growth value, calculated based on the direct conversion relationship between the speed of sound propagation in water and time deviation. The time offset data of each measuring point are processed sequentially to form a corresponding error value dataset, which is then arranged in chronological order to observe the trend of error expansion. The processed results generate a sounding error expansion table, which includes the time point, wave crest time offset value, and corresponding sounding error value. After visual analysis of the data, the temporal characteristics of error expansion are further identified.

[0142] Step S344: Estimate the cumulative error effect data based on the depth sounder measurement error spread;

[0143] In this embodiment of the invention, the extended depth sounding error data is sequentially superimposed to analyze the cumulative effect of error during continuous measurement. During execution, the error values ​​at each sampling point of each segment or survey line are accumulated and statistically analyzed to form a sequence of total error values ​​that increases with measurement duration. Further, time series analysis methods are used to analyze the rate of change and growth pattern of the cumulative error, identifying whether there are accelerated growth phenomena or abrupt change points. The error accumulation effect data is presented in tabular and graphical form, including measurement number, single-point error value, cumulative error value, and error growth rate, to quantify the degree of error accumulation in extremely shallow water environments.

[0144] Step S345: Based on the error accumulation effect data, predict the depth sounder error expansion to obtain the depth sounder error expansion growth data.

[0145] In this embodiment of the invention, based on understanding the error accumulation trend, error growth is predicted and evaluated for future measurement tasks. In this step, historical cumulative error data is used for trend fitting to extract the growth pattern of error over time or with the number of measurement points. By observing the trend of the cumulative error curve, it is determined whether the error growth exhibits linear growth, exponential growth, or periodic fluctuations. Based on this, the trend extrapolation results for future errors are presented in an error expansion growth prediction table, which includes the prediction time point, the corresponding error value, and the magnitude of error growth. This prediction data can provide a reference for subsequent tilt angle correction, signal compensation, and trajectory planning.

[0146] Preferably, step S4 includes the following steps:

[0147] Step S41: Examine the gradient decay of depth sounding accuracy based on the data of depth sounder error spread growth;

[0148] In this embodiment of the invention, the gradient decay of depth sounding accuracy is examined based on the error spread growth data of the depth sounder. This step uses high-precision depth measurement equipment to acquire error spread growth data, recording in detail how the error changes with measurement distance and time. By constructing an error gradient curve, the decay trend of the error in the spatial and temporal dimensions is quantified. Specifically, data analysis tools are used to segment and statistically analyze the error data, calculating the error increase rate and its gradient change with distance. Combined with the depth sounder's measurement frequency and acoustic wave propagation environment parameters, the spatial distribution law of error spread is determined to form depth sounding accuracy gradient decay data, reflecting the actual impact of error spread on depth sounding accuracy and providing basic data for subsequent performance decay analysis.

[0149] Step S42: Determine the degradation trend of the depth sounder's detection performance based on the depth accuracy gradient attenuation status and the error expansion growth data of the depth sounder;

[0150] In this embodiment of the invention, the degradation trend of the depth sounder's detection performance is determined based on the gradient attenuation of depth sounding accuracy and the error spread growth data. By integrating the error gradient attenuation curve and error spread data, the changes in the depth sounder's detection performance in extremely shallow water environments are analyzed. Statistical regression analysis is used to fit a degradation model of detection performance over time and distance, clarifying the rate and magnitude of performance decline. This step utilizes detection performance indicators such as signal-to-noise ratio, echo intensity, and depth sounding repeatability to comprehensively evaluate the depth sounder's detection capability. The degradation trend data of the depth sounder's detection performance is output, providing a technical basis for subsequent tilting depth sounder deviation assessment.

[0151] Step S43: Evaluate the degree of deviation of the tilt sounder based on the decay trend of the sounder's detection performance, and obtain the deviation data of the tilt sounder;

[0152] In this embodiment of the invention, the deviation degree of the tilt sounder is evaluated based on the degradation trend of the sounder's detection performance, resulting in tilt sounder deviation degree data. This operation combines the degradation trend of detection performance with the tilt angle data of the sounder installation to analyze the impact of tilt installation on sounding error. An error propagation analysis method is used to calculate the increase in sounding error caused by the tilt angle. The accuracy of the error model is verified by comparing measured data. The spatial distribution characteristics of the deviation degree are quantified by combining the mechanical structural parameters of the sounder. This step generates tilt sounder deviation degree data, which serves as a key input for sounding error correction.

[0153] Step S44: Perform single-beam echo sounder depth measurement correction processing on the deviation data of the tilted installation echo sounder to obtain single-beam echo sounder depth measurement correction data.

[0154] In this embodiment of the invention, the deviation data of an inclined depth sounder is processed using a single-beam echo sounder to correct the depth readings, resulting in corrected single-beam echo sounder depth readings. Specifically, based on the deviation data of the inclined depth sounder, a depth reading correction algorithm is constructed, and correction coefficients are calculated for different measurement angles and deviation levels. The original depth sounder measurement data is multiplied by the correction coefficients to adjust the depth readings. The correction accuracy is verified using on-site calibration data and historical measurement records to ensure that the corrected depth readings match the actual water depth. The corrected depth readings output in this step provide accurate foundational data for subsequent depth sounding data analysis and applications, ensuring the accuracy and reliability of measurements in extremely shallow waters.

[0155] The present invention also provides a system for measuring extremely shallow waters using a tilted-mounted single-beam echo sounder, for performing the aforementioned method for measuring extremely shallow waters using a tilted-mounted single-beam echo sounder. This system includes:

[0156] The depth sounder simulation module is used to acquire single-beam depth sounder operating data; identify single-beam depth sounder measurement route data based on the single-beam depth sounder operating data; collect environmental changes along the measurement route based on the single-beam depth sounder measurement route data; and perform depth sounder simulation based on the single-beam depth sounder measurement route data to obtain single-beam depth sounder simulation data.

[0157] The propagation path dynamic anomaly determination module is used to detect dynamic disturbance response data of the sounding angle in the single-beam depth sounder's depth sounding simulation data based on changes in the measurement route environment; determine the intensity of environmental measurement coupling interference of the depth sounder based on changes in the measurement route environment and the dynamic disturbance response data of the sounding angle; and determine the dynamic anomaly status of the acoustic wave propagation path based on the intensity of environmental measurement coupling interference of the depth sounder.

[0158] The error propagation prediction module is used to detect the acoustic frequency drift phenomenon in extremely shallow waters based on the dynamic anomalies of the acoustic propagation path; and to predict the error propagation of the depth sounder based on the acoustic frequency drift phenomenon in extremely shallow waters, thereby obtaining the error propagation growth data of the depth sounder.

[0159] The depth sounding value correction processing module is used to evaluate the degree of deviation of the tilted depth sounder based on the depth sounder error expansion growth data, and obtain the tilted depth sounder deviation data; and to perform single-beam depth sounding value correction processing on the tilted depth sounder deviation data, and obtain single-beam depth sounding value correction data.

[0160] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for measuring extremely shallow water using a tilted single-beam echo sounder, characterized in that, Includes the following steps: Step S1: Acquire single-beam echo sounder operating data; identify single-beam echo sounder measurement route data based on single-beam echo sounder operating data; collect environmental changes along the measurement route based on single-beam echo sounder measurement route data; perform echo sounder depth measurement simulation based on single-beam echo sounder measurement route data to obtain single-beam echo sounder depth measurement simulation data. Step S2: Detect the dynamic disturbance response data of the sounding angle based on the environmental changes of the measurement route using the single-beam echo sounder's sounding simulation data; determine the environmental measurement coupling interference intensity of the echo sounder based on the environmental changes of the measurement route and the dynamic disturbance response data of the sounding angle; determine the dynamic anomaly of the acoustic wave propagation path based on the environmental measurement coupling interference intensity of the echo sounder. Step S3: Detect the acoustic frequency drift phenomenon in extremely shallow waters based on the dynamic anomaly of the acoustic propagation path; predict the depth sounder error spread based on the acoustic frequency drift phenomenon in extremely shallow waters to obtain depth sounder error spread growth data. Step S4: Based on the depth sounder error expansion growth data, evaluate the degree of deviation of the tilt sounder to obtain the deviation data of the tilt sounder; The deviation data of the tilted depth sounder is processed by the single-beam depth sounder depth sounding value correction process to obtain the single-beam depth sounder depth sounding value correction data.

2. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Obtain single-beam echo sounder operating data; Step S12: Determine the installation data of the single-beam echo sounder based on the operating data of the single-beam echo sounder; Step S13: Identify the single-beam echo sounder measurement route data based on the single-beam echo sounder operation data; Step S14: Collect data on environmental changes along the measurement route based on the single-beam echo sounder measurement route data; Step S15: Perform depth sounding simulation based on the single-beam echo sounder measurement route data and single-beam echo sounder installation data to obtain single-beam echo sounder depth sounding simulation data.

3. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 2, characterized in that, Step S15 Includes the following steps: Step S151: Identify the installation attitude data of the single-beam echo sounder based on the installation data of the single-beam echo sounder; Step S152: Measure the installation angle of the depth sounder based on the installation attitude data of the single-beam depth sounder to obtain the tilt installation angle data of the depth sounder; Step S153: Determine the changes in the trajectory of the ship where the depth sounder is installed based on the measurement route data of the single-beam echo sounder; Step S154: Based on the changes in the trajectory of the depth sounder installation and the data of the depth sounder tilt installation angle exceeding 9.5°, perform a vertical offset measurement of the depth sounder incident angle to obtain the vertical offset data of the depth sounder incident angle. Step S155: Determine the sound velocity echo path of the probe based on the vertical offset data of the incident angle of the depth sounder, and obtain the sound velocity echo path data of the probe. Step S156: Construct a simulation model of a single-beam echo sounder based on the sounder's acoustic echo path data and the changes in the ship's trajectory when the echo sounder is installed. Step S157: Perform depth sounding simulation based on the single-beam echo sounder simulation model to obtain single-beam echo sounder depth sounding simulation data.

4. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 1, characterized in that, In step S2, the dynamic disturbance response data of the depth sounding angle of the single-beam echo sounder depth sounding simulation data is detected based on the environmental changes along the measurement route. This includes: Analyze the temporal changes in the environmental conditions of the measurement route based on the changes in the measurement route environment; Determine the joint disturbance factor data of the hull based on the temporal changes in the environmental conditions along the measurement route; Based on the joint disturbance factor data of the installed hull, the attitude changes of the hull where the depth sounder is installed are identified from the depth sounding simulation data of the single beam depth sounder. The ship's attitude changes after the depth sounder is installed are processed by dividing the ship's swing direction to obtain the ship's forward and backward swing data around the transverse axis and the ship's left and right tilt data around the longitudinal axis. The pitch angle change of the single-beam depth sounder is detected based on the data of the ship's forward and backward swaying around the transverse axis. The roll angle of the single-beam depth sounder is detected based on the ship's tilt data around its longitudinal axis. The degree of change in the acoustic wave emission direction of the sounder is determined based on the changes in the pitch angle and roll angle of the single-beam echo sounder. The dynamic disturbance response data of the depth sounding angle are detected based on the degree of change in the direction of acoustic wave emission from the depth sounder.

5. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 1, characterized in that, Step S2, based on changes in the measurement route environment and dynamic disturbance response data of the depth sounder angle, determines the environmental measurement coupling interference intensity of the depth sounder, including: Determine the trend of wave enhancement in the environmental environment along the measurement route based on changes in the environmental conditions. Estimate the growth of the bubble layer on the water surface along the measurement route based on the trend of enhanced environmental waves. The wear and tear of the single-beam depth sounder was detected based on the increasing trend of environmental waves along the measurement route. The wear growth of a single-beam depth sounder and the dynamic disturbance response data of the depth sounding angle were used to examine the damage to the fastener structure of the depth sounder. The extent of erosion on the probe surface is detected based on the growth of the bubble layer on the water surface along the route. Estimate the amplification of environmental disturbances in the tilt sounder based on the trend of enhanced environmental waves along the measurement route; The intensity of environmental measurement coupling interference of the depth sounder is determined based on the intensification of surface erosion of the probe and the amplification of environmental disturbances of the tilting depth sounder.

6. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 1, characterized in that, Step S2, which determines the dynamic anomalies in the acoustic wave propagation path based on the environmental measurement of the depth sounder and the coupling interference intensity, includes: The resonance aggravation of a single-beam depth sounder is estimated based on the coupling interference intensity measured in the environment of the depth sounder. Detecting the degree of metal fatigue in a single-beam depth sounder based on the intensification of resonance; Predicting the accumulation of microcracks in a single-beam echo sounder based on the degree of metal fatigue; Calculate the collision probability data of the depth sounder in extremely shallow waters based on the depth sounding simulation data of the single beam echo sounder; Based on the collision probability data of the depth sounder in extremely shallow water and the accumulation of microcracks in the single-beam depth sounder, the water seepage situation of the depth sounder micropores is predicted; The dynamic anomalies of the sound wave propagation path are determined based on the seepage status of the micropores in the depth sounder and the dynamic disturbance response data of the depth sounding angle.

7. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 1, characterized in that, Step S3 includes the following steps: Step S31: Determine the multipath interference situation of the depth sounder based on the dynamic anomaly of the sound wave propagation path; Step S32: Predict the signal distortion of the single-beam depth sounder based on the multipath abnormal interference of the depth sounder; Step S33: Detect the acoustic frequency drift phenomenon in extremely shallow waters based on the multipath abnormal interference of the depth sounder and the signal distortion of the single-beam depth sounder. Step S34: Based on the acoustic frequency drift phenomenon in extremely shallow waters, predict the error spread of the depth sounder to obtain the error spread growth data of the depth sounder.

8. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 7, characterized in that, Step S31 Includes the following steps: Step S311: Detect the irregular reflection enhancement status of the water surface based on the abnormal situation of the sound wave propagation path; Step S312: Determine multiple reflection data of sounding waves based on the irregular reflection enhancement of the water surface; Step S313: Determine the overlap of the sounding echoes based on the multiple reflection data of the sounding waves and the irregular reflection enhancement of the water surface; Step S314: Inspect the degree of distortion of the sounding waveform based on the overlap of the sounding echoes; Step S315: Inspect the degree of offset of the depth sounder's measuring point position based on the abnormality of the sound wave propagation path; Step S316: When the distortion of the sound wave waveform is >8%, the multipath abnormal interference of the sounder is determined by the offset of the sounder measuring point position.

9. The method for measuring extremely shallow waters using a single-beam echo sounder based on tilted installation according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: Examine the gradient decay of depth sounding accuracy based on the data of depth sounder error spread growth; Step S42: Determine the degradation trend of the depth sounder's detection performance based on the depth accuracy gradient attenuation status and the error expansion growth data of the depth sounder; Step S43: Evaluate the degree of deviation of the tilt sounder based on the decay trend of the sounder's detection performance, and obtain the deviation data of the tilt sounder; Step S44: Perform single-beam echo sounder depth measurement correction processing on the deviation data of the tilted installation echo sounder to obtain single-beam echo sounder depth measurement correction data.

10. A single-beam echo sounder system for measuring extremely shallow waters based on tilted installation, characterized in that, For performing the method for measuring extremely shallow waters using a tilted-mounted single-beam echo sounder as described in claim 1, the tilted-mounted single-beam echo sounder system for measuring extremely shallow waters comprises: The depth sounder simulation module is used to acquire single-beam depth sounder operating data; identify single-beam depth sounder measurement route data based on the single-beam depth sounder operating data; collect environmental changes along the measurement route based on the single-beam depth sounder measurement route data; and perform depth sounder simulation based on the single-beam depth sounder measurement route data to obtain single-beam depth sounder simulation data. The propagation path dynamic anomaly determination module is used to detect dynamic disturbance response data of the sounding angle in the single-beam depth sounder's depth sounding simulation data based on changes in the measurement route environment; determine the intensity of environmental measurement coupling interference of the depth sounder based on changes in the measurement route environment and the dynamic disturbance response data of the sounding angle; and determine the dynamic anomaly status of the acoustic wave propagation path based on the intensity of environmental measurement coupling interference of the depth sounder. The error propagation prediction module is used to detect the acoustic frequency drift phenomenon in extremely shallow waters based on the dynamic anomalies of the acoustic propagation path; and to predict the error propagation of the depth sounder based on the acoustic frequency drift phenomenon in extremely shallow waters, thereby obtaining the error propagation growth data of the depth sounder. The depth sounding value correction processing module is used to evaluate the degree of deviation of the tilted depth sounder based on the depth sounder error expansion growth data, and obtain the tilted depth sounder deviation data; and to perform single-beam depth sounding value correction processing on the tilted depth sounder deviation data, and obtain single-beam depth sounding value correction data.

Images