High-precision underwater relative spatial ranging method for shallow sea environment based on pressure signal

Abstract

This invention relates to a high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals, comprising: S1: defining a spatial coordinate system; S2: synchronously acquiring wave pressure time-series data and attitude time-series data of each node; S3: obtaining the equivalent sea surface wave height time-series of each node by inverting the wave pressure time-series data through the water depth transfer function; S4: calculating the wave number vector of the sea waves in the measurement area based on the equivalent sea surface wave height time-series of the main measurement node and the auxiliary wave parameter calculation node; S5: calculating the wave height time-series cross-correlation function of the main measurement node and the sub-measurement node to be measured in the two sets of wave propagation directions, and calculating the projected distance of the sub-measurement node to be measured in the two sets of wave propagation directions; S6: calculating the horizontal two-dimensional relative coordinates of the sub-measurement node to be measured based on the projected distance, and obtaining the vertical relative coordinates by combining the depth time-series data of each node, to obtain the complete three-axis relative spatial coordinates of the sub-measurement node to be measured.

Description

Technical Field

[0001] The present invention relates to the technical field of marine underwater engineering measurement, in particular to a high-precision underwater relative space ranging method based on pressure signals for shallow sea environments. Background Art

[0002] In marine engineering operations such as construction of offshore fixed and floating industrial platforms, layout of underwater piping systems, and installation of marine structures, spatial relative positioning and ranging of underwater targets is a core construction link. To meet engineering requirements such as reliable docking of underwater piping systems and refined design of installation schemes, it is necessary to accurately obtain full-dimensional information of each target to be measured in the underwater three-dimensional space, including spatial attitude parameters such as pitch angle, roll angle and yaw angle of the target to be measured, as well as complete position relationship parameters such as two-dimensional horizontal relative distance and vertical depth difference between different measurement points. The above data are the core basic data for constructing the overall engineering coordinate system, carrying out three-dimensional spatial modeling of underwater structures, and formulating rigorous construction plans, which put forward a rigid requirement of centimeter-level relative error for measurement accuracy.

[0003] At present, there are a variety of technical solutions for underwater spatial ranging in shallow sea environments, among which: Traditional mechanical cable-type measurement method: This method relies on divers manually pulling cables underwater to complete ranging and attitude calibration. In the marine environment, the cable ranging method is affected by ocean currents. The ocean current exerts a lateral load proportional to the square of the flow velocity on the flexible cable with extremely low lateral stiffness, which causes bending deflection and vortex-induced vibration of the cable, damages the straight reference and causes ranging deviation. Errors are coupled and accumulated in three-dimensional space, and errors are nonlinearly amplified in large-span scenarios, which cannot guarantee the measurement accuracy under complex spatial attitudes, and it is difficult to adapt to the measurement requirements of large-span piping systems. Acoustic ranging method: This method realizes ranging by transmitting acoustic signals through underwater acoustic transducers. However, when sound waves propagate in the marine environment, they are easily affected by factors such as seabed reflection, water flow disturbance, water body scattering and marine biological noise, resulting in a large amount of clutter interference and large ranging errors. It cannot meet the centimeter-level high-precision measurement requirements required for specific scenarios, and cannot be used as a reliable data basis for high-precision marine engineering such as pipeline connection design.

[0004] Optical ranging method: Such methods include blue-green laser time-of-flight method, visual image method and other methods, which are mainly realized based on the optical transmission window characteristic of seawater. However, this method has inherent physical limitations: the measuring range is greatly limited by water attenuation, it is almost ineffective in turbid water and is seriously affected by obstacles; water body scattering and solar background light have strong interference, and temperature and salinity changes easily cause system ranging errors; the light source has high power consumption, high engineering cost, poor target adaptability, and there are risks to human eye safety and marine ecological compliance.

[0005] In summary, existing technologies struggle to achieve high-precision spatial relative positioning measurements between points under shallow-sea construction conditions with no fixed reference datum and high sea state interference. They lack a stable and reliable global spatial reference datum, and their measurement accuracy, environmental adaptability, and operational efficiency fail to meet the construction requirements of marine underwater engineering, severely restricting the accuracy of marine engineering design and the reliability of construction schemes. To address these issues, there is currently no integrated measurement method capable of simultaneously achieving target attitude calculation, centimeter-level three-axis relative distance measurement, adaptation to complex shallow-sea conditions, and global unified calibration of the local coordinate system. Therefore, there is an urgent need to develop an underwater relative spatial ranging method that supports target attitude calculation, is less affected by sea state interference, and offers high accuracy in three-axis relative distance measurement. Summary of the Invention

[0006] This application addresses the aforementioned problems and technical requirements by proposing a high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals. It utilizes the spatial consistency and linear propagation characteristics of ocean wave fields within a small area of ​​open shallow sea as its theoretical foundation. The natural ocean wave field serves as a unified spatial measurement benchmark across the entire area. Wave pressure data is synchronously collected using a pressure sensor array (using a three-element array as an example in this step) with pre-calibrated geometric positions. Key parameters such as wave propagation direction and wave number vector are accurately calculated to establish a spatial measurement coordinate system based on wave propagation. Furthermore, through temporal correlation analysis of wave height at primary and secondary measuring points, the projected distance of the measured point in different wave propagation directions is calculated. Finally, combined with depth data, the full-dimensional calculation of the three-axis relative coordinates of the measured point is completed, achieving high-precision relative spatial positioning and unified attitude calibration of underwater targets.

[0007] To achieve the above objectives, the technical solution of the present invention includes: A high-precision underwater relative spatial ranging method based on pressure signals in shallow marine environments, comprising: S1: Defines the spatial coordinate system including the main measurement node, auxiliary wave parameter calculation node, and the sub-measurement node to be measured; S2: Synchronously acquire wave pressure time series data, attitude time series data and depth time series data of each node; S3: The equivalent sea surface wave height time series of each node is obtained by inverting the wave pressure time series data through the water depth transfer function; S4: Based on the equivalent sea surface wave height time series of the main measurement node and the auxiliary wave parameter calculation node, calculate the wave number vector of the sea waves in the measurement area and obtain two sets of independent wave propagation directions; S5: Calculate the wave height time-series cross-correlation function of the main measurement node and the sub-measurement node under test in the two sets of wave propagation directions respectively, obtain the time delay, and then calculate the projected distance of the sub-measurement node under test in the two sets of wave propagation directions; S6: Calculate the horizontal two-dimensional relative coordinates of the sub-measurement node to be measured based on the projection distance, and obtain the vertical relative coordinates by combining the depth time series data of each node, so as to obtain the complete three-axis relative spatial coordinates of the sub-measurement node to be measured.

[0008] A further improvement of the present invention is that the main measurement node and the two auxiliary wave parameter calculation nodes together constitute a three-element array wave parameter sensing subsystem. The three are rigidly fixed on the same reference structure, arranged non-collinearly, and their geometric positions have been pre-calibrated with high precision.

[0009] A further improvement of the present invention is that the main measurement node, the auxiliary wave parameter calculation node, and the sub-measurement node under test are all equipped with a pressure sensor, a three-axis attitude sensor, a depth sensor, a synchronization clock module, and a data storage and transmission module.

[0010] A further improvement of the present invention is that step S3 includes preprocessing the wave pressure time series data of each node, and the preprocessing process includes: Eliminate the DC component and remove the fixed bias caused by the hydrostatic pressure at the measuring point; A bandpass filter covering the dominant frequency range of shallow sea waves was used to filter the wave pressure time series data; The filtered wave pressure time series data were processed using the least squares method to remove the trend term, in order to eliminate the trend interference caused by ship vibration and long-period tidal level changes.

[0011] A further improvement of the present invention is that, in step S3, the expression for the water depth transfer function is: In the formula, The density of seawater, It is the acceleration due to gravity. The wave angular frequency, Wave number To measure the total water depth of the area, The vertical depth of the measuring point from the still water surface. The frequency domain sequence of sea surface wave height, The frequency domain sequence for preprocessing the post-wave pressure time series; Among them, wave number With angular frequency Satisfies the linear wave dispersion relation: ; The corresponding wave angular frequency is obtained by iteratively solving the linear wave dispersion relation. wavenumber The equivalent sea surface wave height time series of the measurement points was obtained by inversion using inverse fast Fourier transform. .

[0012] A further improvement of the present invention is that step S4 specifically includes: S41: Perform fast Fourier transform on the equivalent sea surface wave height time series of the main measurement node and the two auxiliary wave parameter calculation nodes to obtain the frequency domain complex signal; S42: For frequency points within the effective frequency band, calculate the phase difference between the two auxiliary wave parameter solution nodes and the main measurement node; S43: Based on the linear wave propagation theory, establish a system of linear equations relating the wave height phase difference between two points to the dot product of the wave number vector, and solve for the wave number vector components corresponding to each effective frequency point. S44: Weighted average is performed using the spectral energy of the frequency points as weights to obtain the final wave number vector, and the propagation direction of the main wave is calculated. S45: Obtain two sets of independent wave propagation directions with an angle ≥30° to the main wave direction. , .

[0013] A further improvement of the present invention is that: in step S41: obtaining the independent wave propagation direction. , The methods include: main wave rotation and multi-band wave separation.

[0014] A further improvement of the present invention is that step S5 includes: The Pearson correlation coefficient was used to calculate the wave propagation directions of the primary measurement node and the secondary measurement node under test in two independent sets of wave propagation directions. , The cross-correlation function of wave height time series; Extract the relative time delay corresponding to the maximum value of the cross-correlation function, multiply it by the wave phase velocity in the corresponding propagation direction, and obtain the projected distance of the sub-measurement node relative to the main measurement node in the two propagation directions.

[0015] A further improvement of the present invention is that step S6 includes: the expression for the horizontal two-dimensional relative coordinates of the sub-measuring node to be measured is: in: The coordinates of the sub-measuring node to be measured; These represent the angles of the two sets of wave propagation directions; These are the projected distances from the measured sub-measuring node to the two independent wave propagation directions, respectively; Depth of the sub-measuring node to be measured The expression is: in: The absolute depth of the sub-measuring node to be measured. The absolute depth of the primary measurement node.

[0016] Compared with existing technologies, the method of this invention uses the natural ocean wave field as a unified spatial reference benchmark across the entire domain. It eliminates the need for manual deployment of benchmark targets and underwater manual measurement operations, completely solving the problems of low efficiency, high risk, and large errors due to ocean currents in traditional string-based methods. At the same time, it avoids the inherent defects of acoustic methods such as multipath interference and optical methods such as water attenuation. Through three-element array frequency domain phase difference analysis, the wave propagation direction and wave number vector can be stably calculated with small wave direction estimation errors and a stable and controllable measurement benchmark. By calculating the horizontal coordinates through bidirectional projection distances and combining them with high-precision depth sensors to obtain vertical coordinates, the complete three-axis relative position and attitude parameters of the measurement point can be calculated at one time. The measurement dimensions are complete and there are no blind spots. Even in complex shallow sea conditions, centimeter-level measurement accuracy can still be stably achieved. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the relative spatial ranging method of this application.

[0018] Figure 2 This is a schematic diagram of the geometric principle for solving the horizontal coordinates of the node to be measured under the double wave propagation direction.

[0019] Figure 3 This is a schematic diagram of the deployment of the measurement sensing array of this application in an underwater measurement scenario. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0021] like Figure 1 , Figure 2 , Figure 3As shown, embodiments of the present invention provide a high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals. This method is based on the spatial consistency and linear propagation characteristics of ocean wave fields within a small area of ​​open shallow sea. It uses the natural ocean wave field as a unified spatial measurement benchmark across the entire area. Wave pressure data is synchronously collected using a pressure sensor array (using a three-element array as an example in this step) with pre-calibrated geometric positions. Key parameters such as wave propagation direction and wave number vector are accurately calculated to establish a spatial measurement coordinate system based on wave propagation. Then, through wave height temporal correlation analysis of the main and secondary measuring points, the projected distance of the measured point in different wave propagation directions is calculated. Finally, combined with depth data, the full-dimensional calculation of the three-axis relative coordinates of the measured point is completed, achieving high-precision relative spatial positioning and unified attitude calibration of underwater targets. This method eliminates the need for manual deployment of artificial benchmark targets and complex underwater operations by divers, completely avoiding the environmental adaptability defects of traditional measurement methods. It can stably achieve centimeter-level measurement accuracy in complex shallow sea conditions. Specifically, it includes: Step S1: Measurement System Construction and Spatial Coordinate System Definition The core objective of this step is to build a hardware measurement system and establish a unified spatial and temporal benchmark, providing a basic framework for subsequent data acquisition and processing.

[0022] The measurement system consists of one main measurement node, two auxiliary wave parameter calculation nodes, and N auxiliary measurement nodes (N≥1). All nodes integrate high-precision pressure sensors, three-axis attitude sensors, depth sensors, synchronization clock modules, and data storage and transmission modules. The main measurement node and the two auxiliary wave parameter calculation nodes together constitute a three-element array wave parameter sensing subsystem. All three are rigidly fixed to the same reference structure, and their geometric positions are pre-calibrated for accurate measurement. The main measurement node is defined as the coordinate origin, and the horizontal coordinates of the two auxiliary calculation nodes relative to the main node are... , Furthermore, the three elements must satisfy the non-collinearity condition (the determinant of the coordinate matrix must be non-zero) to ensure that the wavenumber vector solution has a unique solution.

[0023] The origin is the center of the pressure sensor sensitive surface of the main measurement node. Construct a right-handed rectangular coordinate system - ,in: The axis perpendicular to sea level and pointing downwards is positive. The axis points to the geographical east. The axis points to geographic north; the spatial coordinates of the main measurement node are defined as follows: , any number The spatial coordinates of the sub-measurement nodes to be measured are: ,in , The horizontal two-dimensional relative coordinates, Using vertical depth relative coordinates, the core objective of this method is to solve for... The complete three-axis coordinates and corresponding attitude parameters.

[0024] Meanwhile, the synchronous clock module enables nanosecond-level synchronization of the sampling clocks of all nodes, ensuring that the timing data collected by all nodes has a unified time reference and avoiding phase difference and delay calculation errors caused by time asynchrony.

[0025] Step S2: Acquisition of full array synchronization timing data The core objective of this step is to obtain the raw measurement data of the entire array under a unified time reference, providing raw data support for subsequent wavefield inversion and positioning calculations.

[0026] Set a uniform sampling frequency Sampling duration Number of sampling points The synchronization clock module triggers all nodes to synchronously collect data, where: The main measurement node acquires the reference wave pressure time series data. Reference three-axis attitude timing data , , Reference depth time series data ; Wave pressure time series data were acquired by two auxiliary wave parameter calculation nodes. , ; No. The time-series data of the pressure wave under test were collected from each of the measured sub-nodes. The timing data of the three-axis attitude to be tested , , Depth time series data to be measured ; If the accuracy and completeness of the data acquisition do not meet the sampling criteria, all data will be re-synchronized and acquired.

[0027] In the formula It is a sampling time series. For roll angle, For pitch angle, Yaw angle This represents the absolute vertical depth of the measuring point from the still water surface.

[0028] Step S3: Wave pressure data preprocessing and wave spectrum signal inversion The core objective of this step is to eliminate noise interference and water depth attenuation effects in the raw data, convert the underwater wave pressure data into an equivalent sea surface wave height time series, and provide a standardized and effective signal for subsequent wave parameter calculation and correlation analysis.

[0029] First, the raw wave pressure time series data of all nodes are preprocessed by performing three operations in sequence: First, the DC component is eliminated to remove the fixed bias caused by the hydrostatic pressure at the measuring point. Second, a 5th-order Butterworth bandpass filter with a passband range of 0.05Hz to 0.5Hz is used to cover the main frequency range of shallow sea waves and filter out ultra-low frequency drift and high frequency environmental noise. Third, the least squares method is used to remove trend terms, eliminating trend interference caused by hull vibration and long-period tidal level changes. After preprocessing, the effective wave pressure time series of each node is obtained. ( ), sampling interval .

[0030] Based on this, and using linear micro-amplitude wave theory, the underwater wave pressure time series is inverted into the equivalent sea surface wave height time series at the corresponding measuring points through the water depth transfer function. Since the wave pressure signal decays exponentially with increasing water depth, the wave pressure signal amplitude at different water depth measuring points inherently differs. This difference must be eliminated through inversion to ensure the comparability of wave height time series at different measuring points. The frequency domain transfer function for wave pressure and sea surface wave height is: In the formula, The density of seawater, It is the acceleration due to gravity. The wave angular frequency, Wave number The total water depth of the measurement area (vertical distance from the still water surface to the seabed). The vertical depth of the measuring point from the still water surface. The frequency domain sequence of sea surface wave height, This is the frequency domain sequence of the preprocessed post-wave pressure time series.

[0031] Among them, wave number With angular frequency Satisfies the linear wave dispersion relation: The wavenumber of the corresponding angular frequency is obtained by iteratively solving the dispersion relation. Then, the equivalent sea surface wave height time series of the measurement point can be obtained by inversion using inverse fast Fourier transform (IFFT). This serves as the foundational signal for subsequent wave parameter calculations and time-series correlation analysis.

[0032] Step S4: Array-based wave parameter and wave number vector calculation The core objective of this step is to accurately calculate the propagation characteristics of ocean waves within the measurement area using a pre-calibrated ternary array, establish a spatial measurement coordinate system based on wave propagation, and provide a stable directional reference for subsequent positioning calculations.

[0033] First, based on the equivalent sea surface wave height time series of the main measurement node... The core characteristic parameter for calculating ocean waves: significant wave height. With zero-crossing cycle Among them, significant wave height , for Standard deviation; zero-crossing period , for In duration The number of zero-crossings within the measurement area and the number of zero-crossings are used to characterize the basic features of ocean waves within the measurement area.

[0034] Subsequently, the wave height timing of the three-element array nodes was analyzed. , , Perform Fast Fourier Transform (FFT) on each signal to obtain the complex signal in the frequency domain: In the formula Frequency index, corresponding to frequency .

[0035] Selecting effective frequency bands For each effective frequency point The phase difference between the auxiliary solution node and the main measurement node is calculated using complex division: Phase difference is extracted using the arctangent function: In the formula , These represent taking the imaginary part and the real part, respectively.

[0036] Based on linear wave propagation theory, the wave height phase difference between two points in space and the wave number vector satisfy a dot product relationship: in The difference between the horizontal coordinates of the two points. The wavenumber vector to be solved is denoted as .

[0037] Establish a system of linear equations for the ternary matrix: Solving this system of equations using Cramer's rule yields the determinant of the coefficient matrix as follows: like This indicates that the three-element arrays are approximately collinear, and there is no unique solution; therefore, this frequency point is skipped. Otherwise, the solution for the wavenumber vector is: For all effective frequency points , Spectral energy at corresponding frequency points The final wavenumber vector is obtained by weighting the weights. The main propagation direction of the wave was calculated: The modulus of the wavenumber is Corresponding wavelength .

[0038] The wave field within a small area of ​​shallow sea exhibits strong spatial coherence. The three-element array formed by the main measurement node and two auxiliary wave parameter calculation nodes has been weighted and averaged to lock the two-dimensional wavenumber vector characterizing the overall wave characteristics of the current sea area. Based on this, two sets of independent wave propagation directions with an angle ≥30° to the main wave direction were obtained. , The angle between the two sets of directions must satisfy the rank condition to ensure that the subsequent horizontal coordinate calculation has a unique solution. The two sets of directions can be obtained by rotating the main wave direction or separating the multi-frequency band wave direction, without relying on the random changes of the natural wave direction of the ocean waves, thus ensuring the stability of the measurement reference.

[0039] The pressure data collected by the auxiliary measurement node is a one-dimensional time series. To pinpoint its two-dimensional spatial coordinates without relying on multi-directional mixed sea states, this embodiment uses the two-dimensional wavenumber vector as a two-dimensional spatial reference function. Within a Cartesian coordinate system formed by the main measurement node and two auxiliary measurement nodes, the spatial position coordinates of the auxiliary measurement node are determined. Perform spatial phase scanning matching analysis.

[0040] Step S5: Bidirectional projection distance calculation based on temporal correlation The core objective of this step is to calculate the projected distance of the secondary node to be measured in two independent wave propagation directions by analyzing the correlation between the wave height time series of the main and secondary measuring points, and to establish the core equation for the horizontal coordinate calculation.

[0041] For the two independent wave propagation directions , Extract the wave height time sequence of the corresponding frequency bands (based on the wave propagation direction determined in step S4). , and two-dimensional wavenumber vector The Pearson correlation coefficient was used to calculate the relationship between the main measurement node and the first... Cross-correlation function of the wave height time series of the sub-measurement nodes to be measured: In the formula, For relative time delay, , These are the mean values ​​of the wave height time series of the main and secondary nodes, respectively.

[0042] Because the wave field in a small area of ​​shallow sea has spatial uniformity, the wave train will pass through the main node and the secondary node sequentially along the propagation direction, therefore the cross-correlation function... The time delay corresponding to the maximum value This refers to the relative time delay of the wave train propagating from the main node to the secondary node.

[0043] Combined with the wave phase velocity in the corresponding direction , ( , (where ω is the dominant angular frequency in the corresponding direction), the projected distances of the secondary node relative to the primary node in the two propagation directions can be obtained: Step S6: Solving the three-axis relative spatial coordinates The core purpose of this step is to calculate the horizontal two-dimensional coordinates by calculating the two-way projection distance, and to obtain the vertical coordinates by combining the depth data, so as to finally obtain the complete three-axis spatial coordinates of the sub-node to be tested relative to the main node.

[0044] The projected distance and the horizontal relative coordinate satisfy a system of linear equations. The projected distance is essentially the projection of the horizontal coordinate vector onto the direction of wave propagation. Therefore: because and The included angle is ≥30°, the coefficient matrix of the system of equations is of full rank, there exists a unique solution, and the solution yields the th... The horizontal two-dimensional relative coordinates of each secondary node: The relative coordinates in the vertical direction do not need to be calculated using wavefield analysis; they are directly obtained from the depth sensor data of the main and secondary nodes, eliminating the vertical direction error caused by wavefield analysis and ensuring the measurement accuracy of the vertical dimension. In the formula, The absolute depth of the master node. For the first The absolute depth of each secondary node.

[0045] Thus, the first step is complete. The complete three-axis relative spatial coordinates of each secondary node relative to the primary node The solution.

[0046] Step S7: Global coordinate system construction and unified calibration of pose of all array points The core objective of this step is to unify the coordinates and orientations of all nodes to be measured into the same engineering coordinate system, complete the global spatial pose calibration of the entire array of measurement points, and provide standardized, multi-dimensional data for engineering construction.

[0047] First, attitude data normalization is performed based on the reference three-axis attitude data from the master measurement node. , will the The attitude data to be measured at each sub-measurement node Transform to the global coordinate system to obtain the normalized attitude parameters: Then, the main measurement node is taken as the origin. Defined in step 1 - The right-hand rectangular coordinate system is a unified local coordinate system, which sets the relative coordinates of the three axes of all secondary measurement nodes. Normalized attitude parameters The coordinates are uniformly mapped to this global coordinate system to complete the global unified calibration of the spatial pose of all measurement points in the entire measurement array.

[0048] The core advantages of this method are: using the natural ocean wave field as a unified spatial reference benchmark across the entire domain, eliminating the need for manual deployment of benchmark targets and underwater manual measurement operations, thus completely solving the problems of low efficiency, high risk, and large errors due to ocean currents in traditional string-based methods. It also avoids the inherent defects of acoustic methods such as multipath interference and optical methods such as water attenuation. Through three-element array frequency domain phase difference analysis, the wave propagation direction and wave number vector can be stably calculated with small wave direction estimation errors, ensuring a stable and controllable measurement benchmark. By calculating the horizontal coordinates through bidirectional projection distances and combining them with high-precision depth sensors to obtain vertical coordinates, the complete three-axis relative position and attitude parameters of the measurement point can be calculated in one go, providing complete measurement dimensions without blind spots, and achieving stable centimeter-level measurement accuracy even in complex shallow sea conditions.

[0049] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A high-precision underwater relative spatial ranging method based on pressure signals in shallow sea environments, comprising the following steps: S1: Defines the spatial coordinate system including the main measurement node, auxiliary wave parameter calculation node, and the sub-measurement node to be measured; S2: Synchronously acquire wave pressure time series data, attitude time series data and depth time series data of each node; S3: The equivalent sea surface wave height time series of each node is obtained by inverting the wave pressure time series data through the water depth transfer function; S4: Based on the equivalent sea surface wave height time series of the main measurement node and the auxiliary wave parameter calculation node, calculate the wave number vector of the sea waves in the measurement area and obtain two sets of independent wave propagation directions; S5: Calculate the wave height time-series cross-correlation function of the main measurement node and the sub-measurement node under test in the two sets of wave propagation directions respectively, obtain the time delay, and then calculate the projected distance of the sub-measurement node under test in the two sets of wave propagation directions; S6: Calculate the horizontal two-dimensional relative coordinates of the sub-measurement node to be measured based on the projection distance, and obtain the vertical relative coordinates by combining the depth time series data of each node, so as to obtain the complete three-axis relative spatial coordinates of the sub-measurement node to be measured.

2. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 1, characterized in that: The main measurement node and the two auxiliary wave parameter calculation nodes together constitute a three-element array wave parameter sensing subsystem. The three are rigidly fixed on the same reference structure, arranged non-collinearly, and their geometric positions have been pre-calibrated with high precision.

3. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 1, characterized in that: The main measurement node, the auxiliary wave parameter calculation node, and the sub-measurement node under test are all equipped with a pressure sensor, a three-axis attitude sensor, a depth sensor, a synchronization clock module, and a data storage and transmission module.

4. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 1, characterized in that: Step S3 includes preprocessing the wave pressure time series data of each node. The preprocessing process includes: Eliminate the DC component and remove the fixed bias caused by the hydrostatic pressure at the measuring point; A bandpass filter covering the dominant frequency range of shallow sea waves was used to filter the wave pressure time series data; The filtered wave pressure time series data were processed using the least squares method to remove the trend term, in order to eliminate the trend interference caused by ship vibration and long-period tidal level changes.

5. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 4, characterized in that: In step S3, the expression for the water depth transfer function is: ； In the formula, The density of seawater, It is the acceleration due to gravity. The wave angular frequency, Wave number To measure the total water depth of the area, The vertical depth of the measuring point from the still water surface. The frequency domain sequence of sea surface wave height, The frequency domain sequence for preprocessing the post-wave pressure time series; Among them, wave number With angular frequency Satisfies the linear wave dispersion relation: ； The corresponding wave angular frequency is obtained by iteratively solving the linear wave dispersion relation. wavenumber The equivalent sea surface wave height time series of the measurement points was obtained by inversion using inverse fast Fourier transform. .

6. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 1, characterized in that, Step S4 specifically includes: S41: Perform fast Fourier transform on the equivalent sea surface wave height time series of the main measurement node and the two auxiliary wave parameter calculation nodes to obtain the frequency domain complex signal; S42: For frequency points within the effective frequency band, calculate the phase difference between the two auxiliary wave parameter solution nodes and the main measurement node; S43: Based on the linear wave propagation theory, establish a system of linear equations relating the wave height phase difference between two points to the dot product of the wave number vector, and solve for the wave number vector components corresponding to each effective frequency point. S44: Weighted average is performed using the spectral energy of the frequency points as weights to obtain the final wave number vector, and the propagation direction of the main wave is calculated. S45: Obtain two sets of independent wave propagation directions with an angle ≥30° to the main wave direction. , .

7. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 6, characterized in that, In step S41: Obtain the independent wave propagation direction. , The methods include: main wave rotation and multi-band wave separation.

8. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 6, characterized in that, Step S5 includes: The Pearson correlation coefficient was used to calculate the main measurement node and the sub-measurement node under test in two independent wave propagation directions. , The cross-correlation function of wave height time series; Extract the relative time delay corresponding to the maximum value of the cross-correlation function, multiply it by the wave phase velocity in the corresponding propagation direction, and obtain the projected distance of the sub-measurement node relative to the main measurement node in the two propagation directions.

9. The high-precision underwater relative spatial ranging method for shallow sea environments based on pressure signals according to claim 8, characterized in that, Step S6 includes: The expression for the horizontal two-dimensional relative coordinates of the sub-measuring node to be measured is: ； in: The coordinates of the sub-measuring node to be measured; These represent the angles of the two sets of wave propagation directions; These are the projected distances from the measured sub-measuring node to the two independent wave propagation directions, respectively; Depth of the sub-measuring node to be measured The expression is: ； in: The absolute depth of the sub-measuring node to be measured. The absolute depth of the primary measurement node.

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