Test probe underwater depth automatic positioning method and system

Abstract

The invention belongs to the technical field of underwater measurement, and discloses a test probe underwater depth automatic positioning method and system, and the method comprises the steps: collecting an absolute water pressure value of a current underwater environment, and carrying out the calculation of a hydrostatic pressure value through combining with water surface reference air pressure data; meanwhile, acoustic signals from the water surface base station are received, response is returned, and the round-trip propagation time of sound waves in the water body is measured and obtained; collecting water body temperature data and salinity change data, estimating density information of the current water body, and converting a hydrostatic pressure value into a pressure depth value; calculating an average sound wave propagation speed by adopting an empirical sound velocity model, and calculating an acoustic depth value of the probe in combination with back-and-forth propagation time of sound waves in the water body; the depth positioning precision and stability of the underwater probe in a complex environment are effectively improved, and high-reliability and high-precision underwater depth automatic positioning is realized.

Description

Technical Field

[0001] The present invention relates to the field of underwater measurement technology, and more particularly to a method and system for automatically positioning a test probe at underwater depth. Background Art

[0002] Patent publication number CN120009896A discloses a method and device for automatic underwater depth positioning of a test measuring rod, specifically relating to the field of underwater detection technology; by integrating a pressure sensor, a sonar ranging module and an inertial navigation unit on the measuring rod, combined with real-time acquired temperature, salinity and depth sensor data, the pressure-depth conversion result is dynamically corrected, and a high-precision target water depth value is generated through data fusion. At the same time, the system uses inertial navigation information and target depth change trends, and adopts a fuzzy logic control method to achieve real-time adaptive adjustment of the measuring rod posture and depth position. This method effectively improves the positioning accuracy and environmental adaptability of the underwater measuring rod in complex stratified water bodies, and has good practicality and innovation.

[0003] The existing test probe underwater depth automatic positioning method and system have the following main problems: In existing underwater detection systems, pressure sensors are prone to thermal drift errors under different water temperature conditions, which is particularly evident in deep water, high pressure, or environments with drastic temperature changes. This can cause systematic deviations in depth measurement data, making it difficult to ensure measurement accuracy and stability. In traditional technologies, pressure sounding and acoustic sounding are two independent methods, each affected by its own error sources, resulting in inconsistent measurement results. The lack of effective means to calibrate and integrate the two makes it difficult to support high-precision underwater positioning needs. Using only empirical sound velocity models to estimate underwater acoustic depth cannot adapt to complex water structures in real time, and can easily cause sound velocity mismatch, which in turn affects the accuracy of acoustic ranging.

[0004] Existing depth measurement methods based on pressure sensors are susceptible to factors such as water temperature changes, sensor aging, and structural stress in practical applications, resulting in thermal drift errors. This type of error manifests as a systematic offset in the measured values ​​under different temperature conditions, resulting in a lack of stability and reliability in the pressure depth values. Acoustic depth measurement relies on the propagation time of sound waves in water and the estimated sound velocity. However, the sound velocity in the actual underwater environment is affected by factors such as water temperature, salinity, and density changes, and has a distinct layered structure. In existing technologies, sound velocity estimates typically use average models or surface empirical values, which cannot fully reflect actual depth changes, resulting in problems with accuracy fluctuations and error accumulation in acoustic depth. Pressure depth and acoustic depth are often processed independently, lacking an effective joint constraint judgment and fusion mechanism, and are unable to dynamically exclude unreliable observations.

[0005] In view of this, the present invention proposes a method for automatically positioning a test probe underwater to solve the above problem. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: a method for automatically positioning a test probe underwater, comprising: S1. Collect the absolute water pressure value of the current underwater environment and calculate the hydrostatic pressure value by combining it with the reference air pressure data on the water surface. Simultaneously, receive the acoustic signal from the surface base station and return the response, and measure the round-trip propagation time of the sound wave in the water body. S2. Collect water temperature data and salinity change data, estimate the current water density information, and convert the hydrostatic pressure value into a pressure depth value. Use the empirical sound velocity model to calculate the average sound wave propagation velocity, and combine the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe. S3. Introduce a dynamic error compensation factor to correct the temperature drift error generated during pressure sounding, and perform a coordinated calibration of pressure depth and acoustic depth. Combine the corrected water temperature data and salinity change data to determine the sound wave propagation velocity at different water depths, and arrange them in ascending order by depth value to obtain a sound wave propagation velocity sequence. S4. Record the one-way sound wave propagation time, and infer the sound wave propagation path of each depth segment based on the sound wave propagation velocity sequence. Then infer the relative displacement of the probe during the sound wave propagation process. By introducing the time variable and the preset depth starting point, calculate the static depth value of the probe's current position; S5. Calculate the actual depth value of the probe's current position based on the sound wave propagation path and sound wave propagation time, establish an error constraint relationship between the static depth value and the actual depth value, and perform weighted fusion on the pressure depth value, acoustic depth value, and actual depth value to output the final target depth.

[0007] Preferably, the method for obtaining the round-trip propagation time of the sound wave in the water body includes: The absolute water pressure value of the current underwater environment is acquired in real time by the pressure sensor deployed on the test probe. The absolute water pressure value includes the hydrostatic pressure generated by the water column and the water surface reference air pressure. At the same time, the water surface reference air pressure data is acquired in real time by the air pressure sensor deployed at the water surface. The water surface reference air pressure data is removed from the absolute water pressure value to eliminate the influence of the water surface reference air pressure on the underwater pressure measurement result, and the hydrostatic pressure value generated only by the water column is obtained. The surface base station sends an acoustic signal with a timestamp to the underwater test probe at a preset time point. The acoustic signal travels vertically in the water body to the underwater test probe. After receiving the acoustic signal, the test probe immediately triggers the response mechanism and sends a response signal back to the surface base station. The surface base station synchronously records the total time interval from the start time of transmitting the acoustic signal to the time point of receiving the probe response signal, which is recorded as the round-trip propagation time of the sound wave in the current water body.

[0008] Preferably, the method for obtaining the pressure depth value includes: The temperature sensor and salinity sensor installed on the underwater test probe respectively collect water temperature data and salinity change data at the test point in the water body; the salinity value of the water body at the test point collected by the salinity sensor is greater than or equal to the preset water salinity value threshold, and the UNESCO seawater state equation is used to estimate the current water density information; If the water salinity value is less than the preset water salinity threshold, the Tanaka formula is used to estimate the current water density information; based on the current water density information and gravitational acceleration, the hydrostatic pressure value obtained by removing the atmospheric pressure component from the absolute water pressure value is converted into a pressure depth value corresponding to the hydrostatic pressure value.

[0009] Preferably, the method for obtaining the acoustic depth value of the probe includes: Based on the real-time collected water temperature data and salinity change data, the Del Grosso model is used to calculate the average sound wave propagation velocity in the current water environment. The sound wave propagation path in the water is preset as a vertical straight line, and the product of the average sound wave propagation velocity and the round-trip propagation time of the sound wave is used to calculate the propagation distance of the sound wave in the one-way path, thereby obtaining the acoustic depth value of the test probe relative to the water surface reference.

[0010] Preferably, the method for performing collaborative calibration of pressure depth and acoustic depth comprises: Based on the acquired hydrostatic pressure value, a dynamic error compensation factor is introduced in real time according to the current water temperature. The temperature drift error caused by the change of water temperature is corrected by the dynamic error compensation function. By collecting the pressure-depth value and the corresponding acoustic depth value in continuous time periods, the difference deviation sequence between the two is calculated. Based on the statistical fitting method, an error mapping model between the two types of depth measurement values ​​is established, and the pressure-depth value and acoustic depth value after collaborative calibration are output.

[0011] Preferably, the method for acquiring the sound wave propagation velocity sequence includes: Based on the collaboratively calibrated pressure-depth and acoustic-depth values ​​and the corresponding water temperature and salinity data, a water body thermal-salinity profile dataset arranged in increasing order of depth is constructed. An appropriate empirical sound velocity calculation model is selected based on the target water area type. Using the empirical sound speed calculation model, the water temperature data, salinity change data and hydrostatic pressure value at each depth position are used as input parameters, and the sound wave propagation velocity value at the corresponding depth is calculated point by point; a mapping relationship is established between the sound wave propagation velocity value of each depth layer and the corresponding depth position, and the data are sorted in ascending order by depth value to form a sound wave propagation velocity sequence.

[0012] Preferably, the method for calculating the static depth value of the current position of the probe includes: The one-way sound wave propagation time is recorded. Based on the sound wave propagation velocity sequence, the sound wave propagation path is divided into n depth segments, which are considered as a layered medium propagation environment. By allocating the recorded one-way propagation time to each depth segment and combining it with the sound wave propagation velocity of each depth segment, the sound wave propagation path and the vertical displacement of the sound wave in each depth segment are sequentially calculated. The time variable is introduced as a control factor to dynamically evaluate the propagation displacement of sound waves in different depth segments per unit time. Taking the water surface as the starting reference point, the propagation distance corresponding to each time increment is integrated based on the sound wave propagation velocity sequence, and gradually superimposed to finally obtain the cumulative depth value corresponding to the sound wave propagation path as the static depth value of the probe at the current time point.

[0013] Preferably, the method for calculating the actual depth value of the current position of the probe includes: Compare the theoretical one-way acoustic wave propagation time estimated by the acoustic wave propagation velocity sequence and the acoustic wave propagation path with the actually measured one-way acoustic wave propagation time. If there is a propagation time difference between the two, it is determined that there is an offset in the static depth value estimation. According to the propagation time difference, the acoustic wave propagation path length of each depth segment in the acoustic wave propagation path is adjusted, and the acoustic wave propagation velocity of each depth segment in the acoustic wave propagation path is updated iteratively until the propagation time difference between the theoretical propagation time and the measured time is less than or equal to the preset propagation time difference threshold; The propagation distance integral is recalculated using the corrected sound wave propagation path, and the propagation distance of each depth segment is accumulated to obtain the vertical cumulative length of the actual sound wave propagation path, which is used as the actual depth value reached by the probe starting from the water surface reference point.

[0014] Preferably, the method for outputting the final target depth includes: An error constraint expression is introduced to establish the error constraint relationship between the static depth value and the actual depth value, and physical error boundaries are imposed on the pressure depth value and the acoustic depth value respectively. On the basis of satisfying the error constraint relationship, the pressure depth value, acoustic depth value and actual depth value are weightedly fused to calculate the target depth of the current position of the test probe.

[0015] An underwater depth automatic positioning system for a test probe, comprising: The baseline depth perception module collects the absolute water pressure value of the current underwater environment and calculates the hydrostatic pressure value by combining it with the reference air pressure data on the surface. It also receives acoustic signals from the surface base station and returns a response, measuring the round-trip propagation time of the sound waves in the water. The initial depth estimation module collects water temperature data and salinity change data, estimates the current water density information, and converts the hydrostatic pressure value into a pressure depth value. It uses the empirical sound speed model to calculate the average sound wave propagation speed, and combines the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe. The sound velocity sequence construction module introduces a dynamic error compensation factor to correct the temperature drift error generated during pressure sounding and performs a coordinated calibration of pressure depth and acoustic depth. Combining the corrected water temperature data and salinity change data, the sound wave propagation velocity at different water depths is determined and arranged in ascending order by depth value to obtain a sound wave propagation velocity sequence. The motion interference decoupling module records the one-way sound wave propagation time, combines the sound wave propagation velocity sequence to infer the sound wave propagation path at each depth segment, and reversely infers the relative displacement of the probe during the sound wave propagation process. By introducing the time variable and the preset depth starting point, the static depth value of the probe's current position is calculated; The final depth positioning module calculates the actual depth value of the probe's current position based on the sound wave propagation path and sound wave propagation time, establishes an error constraint relationship between the static depth value and the actual depth value, and performs weighted fusion of the pressure depth value, acoustic depth value and actual depth value to output the final target depth.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention introduces a dynamic error compensation factor to construct a temperature drift correction function that includes temperature deviation, temperature change rate and historical compensation feedback. It can respond to water temperature changes in real time, effectively correct the pressure error caused by thermal drift, and make the corrected pressure depth value closer to the actual value. By continuously collecting two types of depth measurement data, the difference deviation sequence of pressure depth value and acoustic depth value is used for analysis, and the error mapping relationship between the two types of depth measurement methods is established through statistical fitting methods, so that the two depth measurement methods can achieve mutual compensation and adaptive correction in different environments, thereby significantly improving the overall reliability and consistency of depth measurement. By integrating water temperature, salinity, sound speed, pressure and error history data, an adaptive depth correction mechanism for dynamic water environment is realized, which is suitable for a variety of complex application scenarios and effectively overcomes the uncertainty caused by water parameter disturbances. The pressure depth and acoustic depth after collaborative calibration are more representative, laying a solid foundation for building higher-precision underwater depth positioning, and effectively improving the accuracy and stability of the overall underwater positioning system.

[0017] By establishing an error constraint relationship between static depth values ​​and pressure depth and acoustic depth values, a maximum allowable deviation threshold is set for the pressure depth value, and a dynamic tolerance limit based on the sound velocity change rate and propagation time interval is introduced for the acoustic depth value. This error constraint mechanism can effectively eliminate observations with excessive errors, ensuring the physical rationality of the data involved in the fusion, thereby improving the credibility and engineering practicality of the final target depth. The acoustic error constraint introduces the rate of change of the sound wave propagation velocity as a trade-off factor, which can reflect the actual dynamic characteristics of the sound velocity changes in the water body and make the error tolerance adaptive. This mechanism can still stably identify the credible boundary of the acoustic depth in the presence of obvious stratification and uneven sound velocity profiles in the water body, thereby improving the system's adaptability and robustness to complex hydrological environments. It does not rely on special hardware and can be achieved simply by integrating the depth estimation model and constraint logic into the existing probe system, which has good portability and engineering integration value. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a method for automatically positioning the underwater depth of a test probe according to the present invention; Figure 2 This is a schematic structural diagram of an automatic underwater depth positioning system for a test probe according to the present invention; Figure 3 This is a flow chart of the method for obtaining the sound wave propagation velocity sequence provided by the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] Example 1

[0021] See also Figure 1 and Figure 3 As shown, this embodiment 1 further illustrates a method for automatically locating the underwater depth of a test probe proposed by the present invention, including: Underwater detection and positioning are key technologies in a variety of fields, including ocean surveying and mapping, underwater communications, resource exploration, and environmental monitoring. Depth information, a fundamental parameter affecting underwater navigation and operational accuracy, is crucial for the performance of the entire system. Currently, mainstream underwater depth measurement methods include pressure sounding using pressure sensors and acoustic sounding based on the propagation time of sound waves.

[0022] Traditional pressure sounding methods rely on pressure sensors to collect the hydrostatic pressure in the water in real time and convert it based on water density information to obtain the corresponding depth value. However, in actual underwater applications, changes in water temperature, the high-pressure environment of deep water, and the temperature drift characteristics of the sensor itself can significantly affect the measurement results. For example, in deep-sea environments, changes in water temperature can cause systematic drift in the sensor output signal, known as thermal drift error. This error not only increases with depth but is also unpredictable in dynamic water environments. This results in a lack of consistency and repeatability in pressure sounding results under different environmental conditions, seriously restricting the accuracy and stability of the measurement.

[0023] Acoustic bathymetry measures the time it takes for sound waves to travel back and forth in the water and, combined with a preset sound velocity model, calculates the acoustic depth between the target and the reference point. Although the acoustic method can avoid temperature drift to a certain extent, its measurement accuracy is highly dependent on the accurate estimation of the sound velocity. The sound velocity in water is affected by factors such as temperature, salinity, and density, and exhibits a distinct layered structure at different depths. Existing systems often use average sound velocity or empirical models to estimate the sound velocity in water. However, due to the inability to perceive the actual profile changes of the water body in real time, it is easy to cause sound velocity mismatch, thereby causing systematic errors in the acoustic depth. In addition, the sound wave propagation path is curved in inhomogeneous media, further increasing the complexity of error analysis and compensation.

[0024] Current technologies often use pressure depth and acoustic depth as independent measurement channels, each subject to its own inherent error sources. These channels lack effective calibration, joint constraints, or fusion mechanisms, leading to inconsistent measurement results and making it difficult to calibrate and assess the credibility of the final depth output. Complex water environments and variable error sources make it even more difficult for the system to identify and eliminate anomalous data, limiting the practicality of existing technologies for high-precision underwater positioning tasks.

[0025] In view of this, the present invention proposes a method for automatically positioning a test probe underwater, comprising: S1. Collect the absolute water pressure value of the current underwater environment and calculate the hydrostatic pressure value by combining it with the reference air pressure data on the water surface. Simultaneously, receive the acoustic signal from the surface base station and return the response, and measure the round-trip propagation time of the sound wave in the water body. S2. Collect water temperature data and salinity change data, estimate the current water density information, and convert the hydrostatic pressure value into a pressure depth value. Use the empirical sound velocity model to calculate the average sound wave propagation velocity, and combine the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe. S3. Introduce a dynamic error compensation factor to correct the temperature drift error generated during pressure sounding, and perform a coordinated calibration of pressure depth and acoustic depth. Combine the corrected water temperature data and salinity change data to determine the sound wave propagation velocity at different water depths, and arrange them in ascending order by depth value to obtain a sound wave propagation velocity sequence. S4. Record the one-way sound wave propagation time, and infer the sound wave propagation path of each depth segment based on the sound wave propagation velocity sequence. Then infer the relative displacement of the probe during the sound wave propagation process. By introducing the time variable and the preset depth starting point, calculate the static depth value of the probe's current position; S5. Calculate the actual depth value of the probe's current position based on the sound wave propagation path and sound wave propagation time, establish an error constraint relationship between the static depth value and the actual depth value, and perform weighted fusion on the pressure depth value, acoustic depth value, and actual depth value to output the final target depth.

[0026] Methods for obtaining the round-trip propagation time of sound waves in water include: The absolute water pressure value of the current underwater environment is acquired in real time by the pressure sensor deployed on the test probe. The absolute water pressure value includes the hydrostatic pressure generated by the water column and the water surface reference air pressure (atmospheric pressure). At the same time, the water surface reference air pressure data is acquired in real time by the air pressure sensor deployed at the water surface. The water surface reference air pressure data is removed from the absolute water pressure value to eliminate the influence of the water surface reference air pressure on the underwater pressure measurement results, and the hydrostatic pressure value generated solely by the water column is obtained. The surface base station sends an acoustic signal with a timestamp to the underwater test probe at a preset time point. The acoustic signal travels vertically in the water body to the underwater test probe. After receiving the acoustic signal, the test probe immediately triggers the response mechanism and sends a response signal back to the surface base station. The surface base station synchronously records the total time interval from the start time of transmitting the acoustic signal to the time point of receiving the probe response signal, which is recorded as the round-trip propagation time of the sound wave in the current water body.

[0027] Methods for obtaining pressure depth values ​​include: The temperature sensor and salinity sensor installed on the underwater test probe respectively collect water temperature data and salinity change data at the test point in the water body. The water temperature data includes the real-time water temperature value at the location of the test probe, the gradient of water temperature change with depth, and temperature distribution data at different depths. The salinity change data includes the concentration of dissolved salts in the water, the change of salinity with depth, and salinity distribution data at different depths. The salinity value of the water body at the test point collected by the salinity sensor is greater than or equal to the preset water salinity value threshold, and the UNESCO seawater state equation is used to estimate the current water density information. If the water salinity value is less than the preset water salinity threshold, the Tanaka formula is used to estimate the current water density information; based on the current water density information and gravitational acceleration, the hydrostatic pressure value obtained by removing the atmospheric pressure component from the absolute water pressure value is converted into a pressure depth value corresponding to the hydrostatic pressure value.

[0028] The pressure depth values ​​are: ;in, Indicates the pressure depth value calculated from the hydrostatic pressure value; Indicates the hydrostatic pressure value after removing the influence of the water surface reference pressure; Indicates the water density at the corresponding depth; represents the acceleration due to gravity; Methods for obtaining the acoustic depth value of the probe include: Based on the real-time collected water temperature data and salinity change data, the Del Grosso model is used to calculate the average sound wave propagation velocity in the current water environment. The sound wave propagation path in the water is preset as a vertical straight line, and the product of the average sound wave propagation velocity and the round-trip propagation time of the sound wave is used to calculate the propagation distance of the sound wave in the one-way path, thereby obtaining the acoustic depth value of the test probe relative to the water surface reference.

[0029] Methods for performing co-calibration of pressure depth and acoustic depth include: In practical underwater applications, the pressure sensors used in underwater probes are susceptible to changes in water temperature, resulting in thermal drift errors. These errors typically manifest as a systematic shift in measured values ​​as water temperature increases or decreases. These errors are more pronounced under high pressure (deep water) conditions. Furthermore, sensor temperature drift characteristics vary between different batches or models, requiring dynamic compensation.

[0030] Based on the obtained hydrostatic pressure value, a dynamic error compensation factor is introduced in real time according to the current water temperature. The temperature drift error caused by the change of water temperature is corrected by the dynamic error compensation function. The corrected hydrostatic pressure value is: ;in, Indicates the corrected hydrostatic pressure value; Indicates the dynamic error compensation value caused by temperature drift. It should be noted that although Indicates that it is a dynamic error compensation function composed of temperature function, time function and historical compensation value; The dynamic error compensation function is: ;in, Indicates the static sensitivity coefficient of temperature deviation to error; Indicates the preset reference temperature (the temperature at which the sensor is calibrated); Indicates the temperature change rate, reflecting the impact of dynamic temperature changes on the error; Indicates the dynamic sensitivity coefficient corresponding to the temperature change rate; Indicates the water temperature at the current time; Indicates the dynamic error compensation value at the previous time point; Represents the historical error attenuation factor, based on expert experience, The value range is between 0 and 1; By collecting pressure depth values ​​and corresponding acoustic depth values ​​in continuous time periods, calculating the difference deviation sequence between the two, and establishing an error mapping model between the two types of depth measurement values ​​based on the statistical fitting method, the pressure depth values ​​and acoustic depth values ​​after collaborative calibration are output.

[0031] The following problems existing in the existing technology are solved: In existing underwater detection systems, pressure sensors are prone to thermal drift errors under different water temperature conditions, which are particularly obvious in deep water, high pressure or environments with drastic temperature changes. This causes systematic deviations in depth measurement data, making it difficult to ensure measurement accuracy and stability. In traditional technologies, pressure sounding and acoustic sounding are two independent methods. They are affected by their own error sources, resulting in inconsistent measurement results. There is a lack of effective means to calibrate and integrate the two, making it difficult to support high-precision underwater positioning needs. The sole use of empirical sound speed models to infer underwater acoustic depth cannot adapt to complex water structures (such as stratification and salt jump layers) in real time, which can easily cause sound speed mismatch, thereby affecting the accuracy of acoustic ranging.

[0032] Advantages compared to existing technologies: By introducing a dynamic error compensation factor, a temperature drift correction function is constructed that includes temperature deviation, temperature change rate, and historical compensation feedback. This function can respond to water temperature changes in real time, effectively correcting pressure errors caused by thermal drift, and making the corrected pressure-depth values ​​closer to the actual values. By continuously collecting two types of depth measurement data, the difference deviation sequence between pressure depth values ​​and acoustic depth values ​​is analyzed, and an error mapping relationship between the two types of depth measurement methods is established through statistical fitting methods. This enables mutual compensation and adaptive correction of the two depth measurement methods in different environments, significantly improving the overall reliability and consistency of depth measurement. By integrating water temperature, salinity, sound velocity, pressure, and historical error data, an adaptive depth correction mechanism for dynamic water environments is implemented. This mechanism is suitable for a variety of complex application scenarios, including seawater, freshwater, reservoirs, and fisheries, effectively overcoming the uncertainty caused by water parameter disturbances. The collaboratively calibrated pressure depth and acoustic depth are more representative, laying a solid foundation for building higher-precision underwater depth positioning and effectively improving the accuracy and stability of the overall underwater positioning system.

[0033] The methods for obtaining the sound wave propagation velocity series include: Based on the collaboratively calibrated pressure-depth and acoustic-depth values ​​and the corresponding water temperature and salinity data, a water body thermosalinity profile dataset arranged in ascending order of depth was constructed. An appropriate empirical sound velocity calculation model was selected based on the target water type: the Mackenzie model was used in seawater environments, and the Wilson model was used in freshwater or low-salinity environments. Using the empirical sound speed calculation model, the water temperature data, salinity change data and hydrostatic pressure value at each depth position are used as input parameters, and the sound wave propagation velocity value at the corresponding depth is calculated point by point; a mapping relationship is established between the sound wave propagation velocity value of each depth layer and the corresponding depth position, and the data are sorted in ascending order by depth value to form a sound wave propagation velocity sequence.

[0034] Methods for calculating the static depth value of the probe's current position include: The one-way sound wave propagation time is recorded. Based on the sound wave propagation velocity sequence, the sound wave propagation path is divided into n depth segments, which are considered as a layered medium propagation environment. By allocating the recorded one-way propagation time to each depth segment and combining it with the sound wave propagation velocity of each depth segment, the sound wave propagation path and the vertical displacement of the sound wave in each depth segment are sequentially calculated. The time variable is introduced as a control factor to dynamically evaluate the propagation displacement of sound waves in different depth segments per unit time. Taking the water surface as the starting reference point (the preset depth is zero), the propagation distance corresponding to each time increment is integrated based on the sound wave propagation velocity sequence, and gradually superimposed to finally obtain the cumulative depth value corresponding to the sound wave propagation path as the static depth value of the probe at the current time point.

[0035] The methods for calculating the actual depth value of the probe's current position include: Compare the theoretical one-way acoustic wave propagation time estimated by the acoustic wave propagation velocity sequence and the acoustic wave propagation path with the actually measured one-way acoustic wave propagation time. If there is a propagation time difference between the two, it is determined that there is an offset in the static depth value estimation. According to the propagation time difference, the acoustic wave propagation path length of each depth segment in the acoustic wave propagation path is adjusted, and the acoustic wave propagation velocity of each depth segment in the acoustic wave propagation path is updated iteratively until the propagation time difference between the theoretical propagation time and the measured time is less than or equal to the preset propagation time difference threshold; The propagation distance integral is recalculated using the corrected sound wave propagation path, and the propagation distance of each depth segment is accumulated to obtain the vertical cumulative length of the actual sound wave propagation path, which is used as the actual depth value reached by the probe starting from the water surface reference point.

[0036] Methods for outputting the final target depth include: The error constraint expression is introduced to establish the error constraint relationship between the static depth value and the actual depth value, and the physical error boundaries are imposed on the pressure depth value and the acoustic depth value respectively. The error constraint expression is introduced as ;in, represents the error constraint set; Indicates the acoustic depth value of the current position of the test probe; Indicates the static depth value of the current position of the test probe; Indicates the preset maximum allowable pressure depth deviation threshold; represents the acoustic error sensitivity adjustment coefficient; It represents the rate of change of the speed of sound waves in water; Indicates the time interval for sound wave propagation; On the basis of satisfying the error constraint relationship, the pressure depth value, acoustic depth value and actual depth value are weightedly fused to calculate the target depth of the current position of the test probe.

[0037] The following problems existing in the prior art are solved: the existing depth measurement method based on pressure sensors is easily affected by factors such as water temperature changes, sensor aging and structural stress in actual applications, resulting in thermal drift errors. This type of error manifests itself as a systematic offset of the measured values ​​under different temperature conditions, resulting in a lack of stability and credibility in the pressure depth values. Acoustic depth measurement relies on the propagation time of sound waves in water bodies and the estimated value of the speed of sound. However, the speed of sound in the actual underwater environment is affected by factors such as water temperature, salinity, and density changes, and has obvious layered structural characteristics. In the prior art, the sound speed estimation usually adopts an average model or surface empirical value, which cannot fully reflect the actual depth changes, resulting in the problems of accuracy fluctuation and error accumulation in the acoustic depth; the pressure depth and acoustic depth are often processed independently, lacking an effective joint constraint judgment and fusion mechanism, and cannot dynamically exclude unreliable observations; Compared with existing technologies, the system has the following advantages: by constructing an error constraint relationship between static depth values ​​and pressure depth values ​​and acoustic depth values, setting a maximum allowable deviation threshold for pressure depth values, and introducing a dynamic tolerance limit based on the sound velocity change rate and propagation time interval for acoustic depth values; this error constraint mechanism can effectively eliminate observations with excessive errors, ensuring that the data involved in the fusion are physically reasonable, thereby improving the credibility and engineering practicality of the final target depth; the acoustic error constraint introduces the rate of change of the sound wave propagation velocity as a trade-off factor, which can reflect the actual dynamic characteristics of the sound velocity changes in the water body and make the error tolerance adaptively adjustable. This mechanism can still stably identify the credible boundary of the acoustic depth even when there is obvious stratification in the water body and uneven sound velocity profile, thereby improving the system's adaptability and robustness to complex hydrological environments; it does not rely on special hardware and can be achieved simply by integrating the depth estimation model and constraint logic into the existing probe system, which has good portability and engineering integration value.

[0038] The preset water salinity value threshold is set by the staff based on the results of historical data analysis. The historical analysis process includes the system collecting multiple water salinity values ​​and calculating their average value as a reference to obtain the preset water salinity value threshold; similarly, the preset propagation time difference threshold is also set by the staff based on the system's historical operation data and specific application scenario requirements, and can be adjusted by the staff according to actual conditions during the system operation process.

[0039] In this embodiment, by introducing a dynamic error compensation factor, a temperature drift correction function is constructed that includes temperature deviation, temperature change rate, and historical compensation feedback. This function can respond to changes in water temperature in real time, effectively correct the pressure error caused by thermal drift, and make the corrected pressure depth value closer to the actual value. By continuously collecting two types of depth measurement data, the difference deviation sequence between the pressure depth value and the acoustic depth value is used for analysis, and the error mapping relationship between the two types of depth measurement methods is established through statistical fitting methods. The two depth measurement methods can achieve mutual compensation and adaptive correction in different environments, thereby significantly improving the overall reliability and consistency of depth measurement. By integrating water temperature, salinity, sound speed, pressure, and error history data, an adaptive depth correction mechanism for dynamic water environments is implemented, which is suitable for a variety of complex application scenarios and effectively overcomes the uncertainty caused by water parameter disturbances. The pressure depth and acoustic depth after collaborative calibration are more representative, laying a solid foundation for building higher-precision underwater depth positioning and effectively improving the accuracy and stability of the overall underwater positioning system.

[0040] By establishing an error constraint relationship between static depth values ​​and pressure depth and acoustic depth values, a maximum allowable deviation threshold is set for the pressure depth value, and a dynamic tolerance limit based on the sound velocity change rate and propagation time interval is introduced for the acoustic depth value. This error constraint mechanism can effectively eliminate observations with excessive errors, ensuring the physical rationality of the data involved in the fusion, thereby improving the credibility and engineering practicality of the final target depth. The acoustic error constraint introduces the rate of change of the sound wave propagation velocity as a trade-off factor, which can reflect the actual dynamic characteristics of the sound velocity changes in the water body and make the error tolerance adaptive. This mechanism can still stably identify the credible boundary of the acoustic depth in the presence of obvious stratification and uneven sound velocity profiles in the water body, thereby improving the system's adaptability and robustness to complex hydrological environments. It does not rely on special hardware and can be achieved simply by integrating the depth estimation model and constraint logic into the existing probe system, which has good portability and engineering integration value.

[0041] Example 2

[0042] See also Figure 2 As shown, for parts not described in detail in this embodiment, please refer to the description of Example 1. A test probe underwater depth automatic positioning system is provided, comprising: The baseline depth perception module collects the absolute water pressure value of the current underwater environment and calculates the hydrostatic pressure value by combining it with the reference air pressure data on the surface. It also receives acoustic signals from the surface base station and returns a response, measuring the round-trip propagation time of the sound waves in the water. The initial depth estimation module collects water temperature data and salinity change data, estimates the current water density information, and converts the hydrostatic pressure value into a pressure depth value. It uses the empirical sound speed model to calculate the average sound wave propagation speed, and combines the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe. The sound velocity sequence construction module introduces a dynamic error compensation factor to correct the temperature drift error generated during pressure sounding and performs a coordinated calibration of pressure depth and acoustic depth. Combining the corrected water temperature data and salinity change data, the sound wave propagation velocity at different water depths is determined and arranged in ascending order by depth value to obtain a sound wave propagation velocity sequence. The motion interference decoupling module records the one-way sound wave propagation time, combines the sound wave propagation velocity sequence to infer the sound wave propagation path at each depth segment, and reversely infers the relative displacement of the probe during the sound wave propagation process. By introducing the time variable and the preset depth starting point, the static depth value of the probe's current position is calculated; The final depth positioning module calculates the actual depth value of the probe's current position based on the sound wave propagation path and sound wave propagation time, establishes an error constraint relationship between the static depth value and the actual depth value, and performs weighted fusion of the pressure depth value, acoustic depth value and actual depth value to output the final target depth.

[0043] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0044] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for automatically positioning a test probe underwater, characterized in that: include: S1. Collect the absolute water pressure value of the current underwater environment and calculate the hydrostatic pressure value by combining it with the reference air pressure data on the water surface. Simultaneously, receive the acoustic signal from the surface base station and return the response, and measure the round-trip propagation time of the sound wave in the water body. S2. Collect water temperature data and salinity change data, estimate the current water density information, and convert the hydrostatic pressure value into a pressure depth value. Use the empirical sound velocity model to calculate the average sound wave propagation velocity, and combine the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe. S3. Introduce a dynamic error compensation factor to correct the temperature drift error generated during pressure sounding and perform a coordinated calibration of pressure depth and acoustic depth; Combined with the corrected water temperature data and salinity change data, the sound wave propagation speed at different water depths is determined and arranged in ascending order of depth value to obtain a sound wave propagation speed sequence; S4. Record the one-way sound wave propagation time, and infer the sound wave propagation path of each depth segment based on the sound wave propagation velocity sequence. Then infer the relative displacement of the probe during the sound wave propagation process. By introducing the time variable and the preset depth starting point, calculate the static depth value of the probe's current position; S5. Calculate the actual depth value of the probe's current position based on the sound wave propagation path and sound wave propagation time, establish an error constraint relationship between the static depth value and the actual depth value, and perform weighted fusion on the pressure depth value, acoustic depth value, and actual depth value to output the final target depth.

2. The method for automatically positioning the underwater depth of a test probe according to claim 1, characterized in that: The method for obtaining the round-trip propagation time of the sound wave in the water body includes: The absolute water pressure value of the current underwater environment is acquired in real time by the pressure sensor deployed on the test probe. The absolute water pressure value includes the hydrostatic pressure generated by the water column and the water surface reference air pressure. At the same time, the water surface reference air pressure data is acquired in real time by the air pressure sensor deployed at the water surface. The water surface reference air pressure data is removed from the absolute water pressure value to eliminate the influence of the water surface reference air pressure on the underwater pressure measurement result, and the hydrostatic pressure value generated only by the water column is obtained. The surface base station sends an acoustic signal with a timestamp to the underwater test probe at a preset time point. The acoustic signal travels vertically in the water body to the underwater test probe. After receiving the acoustic signal, the test probe immediately triggers the response mechanism and sends a response signal back to the surface base station. The surface base station synchronously records the total time interval from the start time of transmitting the acoustic signal to the time point of receiving the probe response signal, which is recorded as the round-trip propagation time of the sound wave in the current water body.

3. The method for automatically positioning the underwater depth of a test probe according to claim 2, characterized in that: The method for obtaining the pressure depth value includes: The temperature sensor and salinity sensor installed on the underwater test probe respectively collect water temperature data and salinity change data at the test point in the water body; the salinity value of the water body at the test point collected by the salinity sensor is greater than or equal to the preset water salinity value threshold, and the UNESCO seawater state equation is used to estimate the current water density information; If the water salinity value is less than the preset water salinity threshold, the Tanaka formula is used to estimate the current water density information; based on the current water density information and gravitational acceleration, the hydrostatic pressure value obtained by removing the atmospheric pressure component from the absolute water pressure value is converted into a pressure depth value corresponding to the hydrostatic pressure value.

4. The method for automatically positioning the underwater depth of a test probe according to claim 3, characterized in that: The method for obtaining the acoustic depth value of the probe includes: Based on the real-time collected water temperature data and salinity change data, the Del Grosso model is used to calculate the average sound wave propagation velocity in the current water environment. The sound wave propagation path in the water is preset as a vertical straight line, and the product of the average sound wave propagation velocity and the round-trip propagation time of the sound wave is used to calculate the propagation distance of the sound wave in the one-way path, thereby obtaining the acoustic depth value of the test probe relative to the water surface reference.

5. The method for automatically positioning the underwater depth of a test probe according to claim 4, characterized in that: The method for performing collaborative calibration of pressure depth and acoustic depth includes: Based on the acquired hydrostatic pressure value, a dynamic error compensation factor is introduced in real time according to the current water temperature. The temperature drift error caused by the change of water temperature is corrected by the dynamic error compensation function. By collecting the pressure-depth value and the corresponding acoustic depth value in continuous time periods, the difference deviation sequence between the two is calculated. Based on the statistical fitting method, an error mapping model between the two types of depth measurement values ​​is established, and the pressure-depth value and acoustic depth value after collaborative calibration are output.

6. The method for automatically positioning the underwater depth of a test probe according to claim 5, characterized in that: The method for obtaining the sound wave propagation velocity sequence includes: Based on the collaboratively calibrated pressure-depth and acoustic-depth values ​​and the corresponding water temperature and salinity data, a water body thermal-salinity profile dataset arranged in increasing order of depth is constructed. An appropriate empirical sound velocity calculation model is selected based on the target water area type. Using the empirical sound speed calculation model, the water temperature data, salinity change data and hydrostatic pressure value at each depth position are used as input parameters, and the sound wave propagation velocity value at the corresponding depth is calculated point by point; a mapping relationship is established between the sound wave propagation velocity value of each depth layer and the corresponding depth position, and the data are sorted in ascending order by depth value to form a sound wave propagation velocity sequence.

7. The method for automatically positioning the underwater depth of a test probe according to claim 6, characterized in that: Methods for calculating the static depth value of the probe's current position include: The one-way sound wave propagation time is recorded. Based on the sound wave propagation velocity sequence, the sound wave propagation path is divided into n depth segments, which are considered as a layered medium propagation environment. By allocating the recorded one-way propagation time to each depth segment and combining it with the sound wave propagation velocity of each depth segment, the sound wave propagation path and the vertical displacement of the sound wave in each depth segment are sequentially calculated. The time variable is introduced as a control factor to dynamically evaluate the propagation displacement of sound waves in different depth segments per unit time. Taking the water surface as the starting reference point, the propagation distance corresponding to each time increment is integrated based on the sound wave propagation velocity sequence, and gradually superimposed to finally obtain the cumulative depth value corresponding to the sound wave propagation path as the static depth value of the probe at the current time point.

8. The method for automatically positioning the underwater depth of a test probe according to claim 7, characterized in that: The method for calculating the actual depth value of the current position of the probe includes: Compare the theoretical one-way acoustic wave propagation time estimated by the acoustic wave propagation velocity sequence and the acoustic wave propagation path with the actually measured one-way acoustic wave propagation time. If there is a propagation time difference between the two, it is determined that there is an offset in the static depth value estimation. According to the propagation time difference, the acoustic wave propagation path length of each depth segment in the acoustic wave propagation path is adjusted, and the acoustic wave propagation velocity of each depth segment in the acoustic wave propagation path is updated iteratively until the propagation time difference between the theoretical propagation time and the measured time is less than or equal to the preset propagation time difference threshold; The propagation distance integral is recalculated using the corrected sound wave propagation path, and the propagation distance of each depth segment is accumulated to obtain the vertical cumulative length of the actual sound wave propagation path, which is used as the actual depth value reached by the probe starting from the water surface reference point.

9. The method for automatically positioning the underwater depth of a test probe according to claim 8, characterized in that: The method for outputting the final target depth includes: An error constraint expression is introduced to establish the error constraint relationship between the static depth value and the actual depth value, and physical error boundaries are imposed on the pressure depth value and the acoustic depth value respectively. On the basis of satisfying the error constraint relationship, the pressure depth value, acoustic depth value and actual depth value are weightedly fused to calculate the target depth of the current position of the test probe.

10. An automatic underwater depth positioning system for a test probe, used to implement the automatic underwater depth positioning method for a test probe according to any one of claims 1 to 9, characterized in that: include: The baseline depth perception module collects the absolute water pressure value of the current underwater environment and calculates the hydrostatic pressure value by combining it with the reference air pressure data on the surface. It also receives acoustic signals from the surface base station and returns a response, measuring the round-trip propagation time of the sound waves in the water. The initial depth estimation module collects water temperature data and salinity change data, estimates the current water density information, and converts the hydrostatic pressure value into a pressure depth value. It uses the empirical sound speed model to calculate the average sound wave propagation speed, and combines the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe. The sound velocity sequence construction module introduces a dynamic error compensation factor to correct the temperature drift error generated during pressure sounding and performs a coordinated calibration of pressure depth and acoustic depth. Combining the corrected water temperature data and salinity change data, the sound wave propagation velocity at different water depths is determined and arranged in ascending order by depth value to obtain a sound wave propagation velocity sequence. The motion interference decoupling module records the one-way sound wave propagation time, combines the sound wave propagation velocity sequence to infer the sound wave propagation path at each depth segment, and reversely infers the relative displacement of the probe during the sound wave propagation process. By introducing the time variable and the preset depth starting point, the static depth value of the probe's current position is calculated; The final depth positioning module calculates the actual depth value of the probe's current position based on the sound wave propagation path and sound wave propagation time, establishes an error constraint relationship between the static depth value and the actual depth value, and performs weighted fusion of the pressure depth value, acoustic depth value and actual depth value to output the final target depth.

Images