An automatic underwater depth positioning method and system for experimental probes

Abstract

This invention belongs to the field of underwater measurement technology. It discloses an automatic underwater depth positioning method and system for a test probe, including: collecting the absolute water pressure value of the current underwater environment; combining it with surface reference air pressure data to calculate the hydrostatic pressure value; simultaneously receiving acoustic signals from a surface base station and returning a response, measuring the round-trip propagation time of sound waves in the water; collecting water temperature and salinity change data, estimating the current water density information, and converting the hydrostatic pressure value into a pressure depth value; calculating the average sound wave propagation speed using an empirical sound velocity model, and combining it with the round-trip propagation time of sound waves in the water to calculate the acoustic depth value of the probe; effectively improving the depth positioning accuracy and stability of the underwater probe in complex environments, achieving highly reliable and high-precision automatic underwater depth positioning.

Description

Technical Field

[0001] This invention relates to the field of underwater measurement technology, and more specifically, to an automatic underwater depth positioning method and system for a test probe. Background Technology

[0002] Patent publication number CN120009896A discloses an automatic underwater depth positioning method and device for a test probe, specifically relating to the field of underwater detection technology. By integrating a pressure sensor, a sonar ranging module, and an inertial navigation unit onto the probe, and combining real-time acquired temperature, salinity, and depth sensor data, the system dynamically corrects the pressure-depth conversion results and generates a high-precision target water depth value through data fusion. Simultaneously, utilizing inertial navigation information and the target depth change trend, the system employs a fuzzy logic control method to achieve real-time adaptive adjustment of the probe's attitude and depth position. This method effectively improves the positioning accuracy and environmental adaptability of the underwater probe in complex stratified water bodies, demonstrating good practicality and innovation.

[0003] Existing methods and systems for automatic underwater depth positioning of experimental probes mainly suffer from the following problems:

[0004] In existing underwater detection systems, pressure sensors are prone to thermal drift errors under different water temperatures, especially in deep-water environments with high pressure or drastic temperature changes. This causes systematic deviations in depth measurement data, making it difficult to ensure measurement accuracy and stability. Traditional techniques treat pressure sounding and acoustic sounding as independent methods, each affected by its own error sources, resulting in inconsistent measurement results. The lack of effective methods for calibration and fusion of these two methods makes it difficult to support high-precision underwater positioning requirements. Using only empirical sound velocity models to calculate underwater acoustic depth cannot adapt to complex water structures in real time, easily leading to sound velocity mismatch and affecting the accuracy of acoustic ranging.

[0005] Existing depth measurement methods based on pressure sensors are susceptible to thermal drift errors in practical applications due to factors such as water temperature variations, sensor aging, and structural stress. These errors manifest as systematic shifts in measured values ​​under different temperature conditions, leading to a lack of stability and reliability in pressure depth values. Acoustic depth measurement relies on the estimated propagation time and velocity of sound waves in water. However, sound velocity in actual underwater environments is affected by factors such as water temperature, salinity, and density variations, exhibiting a distinct stratified structure. Current technologies typically use average models or surface empirical values ​​for sound velocity estimation, which cannot fully reflect true depth changes, resulting in accuracy fluctuations and error accumulation in acoustic depth measurements. Furthermore, pressure depth and acoustic depth are often processed independently, lacking effective joint constraint judgment and fusion mechanisms, and failing to dynamically eliminate unreliable observations.

[0006] In view of this, the present invention proposes an automatic underwater depth positioning method for experimental probes to solve the above problems. Summary of the Invention

[0007] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: an automatic underwater depth positioning method for a test probe, comprising:

[0008] S1. Collect the absolute water pressure value of the current underwater environment, combine it with the water surface reference air pressure data, and calculate the hydrostatic pressure value; at the same time, receive the acoustic signal from the water surface base station and return a response, and measure the round-trip propagation time of the sound wave in the water body.

[0009] S2. Collect water temperature and salinity change data, estimate the current water density information, and convert the hydrostatic pressure value into a pressure depth value; use an empirical sound velocity model to calculate the average sound wave propagation speed, and combine the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe.

[0010] S3. Introduce a dynamic error compensation factor to correct the temperature drift error generated during pressure depth sounding, and perform co-calibration of pressure depth and acoustic depth; combine the corrected water temperature data and salinity change data to determine the sound wave propagation speed at different water depths, and arrange them in ascending order of depth value to obtain a sound wave propagation speed sequence.

[0011] S4. Record the unidirectional sound wave propagation time, combine the sound wave propagation speed sequence to infer the sound wave propagation path of each depth segment, and inversely deduce the relative displacement of the probe during the sound wave propagation process. By introducing time variables and preset depth starting points, calculate the static depth value of the probe's current position.

[0012] S5. Based on the sound wave propagation path and propagation time, calculate the actual depth value of the probe's current position, establish the error constraint relationship between the static depth value and the actual depth value, and perform weighted fusion of the pressure depth value, acoustic depth value and actual depth value to output the final target depth.

[0013] Preferably, the method for obtaining the round-trip propagation time of the sound wave in the water body includes:

[0014] The absolute water pressure value of the current underwater environment is acquired in real time by a pressure sensor deployed on the test probe. The absolute water pressure value includes the hydrostatic pressure generated by the water column and the reference air pressure at the water surface. At the same time, the reference air pressure data of the water surface is acquired in real time by a pressure sensor deployed at the water surface. The reference air pressure data of the water surface is removed from the absolute water pressure value to eliminate the influence of the reference air pressure on the underwater pressure measurement result, so that only the hydrostatic pressure value generated by the water column is obtained.

[0015] At a preset time point, the surface base station sends an acoustic signal with a timestamp to the underwater test probe. The acoustic signal travels vertically through the water to the underwater test probe. Upon receiving the acoustic signal, the test probe immediately triggers a response mechanism and sends a response signal back to the surface base station. The surface base station synchronously records the total time interval between the start time of transmitting the acoustic signal and the time of receiving the probe's response signal, which is recorded as the round-trip propagation time of the sound wave in the current water body.

[0016] Preferably, the method for obtaining the pressure depth value includes:

[0017] Temperature and salinity data of the water body at the test point are collected by temperature and salinity sensors installed on the underwater test probe, respectively. If the salinity value of the water body at the test point is greater than or equal to the preset salinity value threshold, the density information of the current water body is estimated by the UNESCO seawater state equation.

[0018] If the salinity value of the water body is less than the preset salinity value threshold, the density information of the current water body is estimated using the Tanaka formula. Based on the density information of the current water body and the gravitational acceleration, the hydrostatic pressure value obtained by removing the atmospheric pressure component from the absolute water pressure value is converted into the pressure depth value corresponding to the hydrostatic pressure value.

[0019] Preferably, the method for obtaining the acoustic depth value of the probe includes:

[0020] Based on real-time collected water temperature and salinity change data, the Del Grosso model is used to calculate the average sound wave propagation speed in the current water environment. The propagation path of the sound wave in the water is preset to be a vertical straight line. The propagation distance of the sound wave in a one-way path is calculated by using the product of the average sound wave propagation speed and the round-trip propagation time of the sound wave, thereby obtaining the acoustic depth value of the test probe relative to the water surface reference.

[0021] Preferably, the method for co-calibrating the pressure depth and acoustic depth includes:

[0022] 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 influence of water temperature changes is corrected by the dynamic error compensation function. By collecting pressure depth values ​​and corresponding acoustic depth values ​​over a continuous time period, the difference deviation sequence between the two is calculated. An error mapping model between the two types of depth measurements is established based on a statistical fitting method, and the pressure depth value and acoustic depth value after collaborative calibration are output.

[0023] Preferably, the method for obtaining the sound wave propagation speed sequence includes:

[0024] Based on the pressure depth and acoustic depth values ​​after collaborative calibration, and the corresponding water temperature and salinity change data, a water thermohaline profile dataset is constructed in ascending order of depth; and an appropriate empirical sound velocity calculation model is selected according to the target water type.

[0025] Using an empirical sound velocity calculation model, water temperature data, salinity change data, and hydrostatic pressure values ​​at each depth location are used as input parameters to calculate the sound wave propagation velocity value at the corresponding depth point by point. A mapping relationship is established between the sound wave propagation velocity values ​​of each depth layer and the corresponding depth location, and the values ​​are sorted in ascending order of depth to form a sound wave propagation velocity sequence.

[0026] Preferably, the method for calculating the static depth value at the current position of the probe includes:

[0027] The unidirectional 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 regarded as a layered medium propagation environment. By distributing the recorded unidirectional propagation time to each depth segment and combining 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 calculated in turn.

[0028] A 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 speed sequence and gradually superimposed to obtain the cumulative depth value corresponding to the sound wave propagation path, which is used as the static depth value of the probe at the current time point.

[0029] Preferably, the method for calculating the actual depth value of the probe's current position includes:

[0030] By comparing the theoretical one-way sound wave propagation time estimated through the sound wave propagation velocity sequence and sound wave propagation path with the actual measured one-way sound wave propagation time, if there is a difference in propagation time between the two, it is determined that there is an offset in the estimation of the static depth value.

[0031] Based on the propagation time difference, the length of the sound wave propagation path at each depth segment in the sound wave propagation path is adjusted, and the sound wave propagation speed at each depth segment in the sound 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.

[0032] The propagation distance is recalculated using the corrected sound wave propagation path, and the propagation distances at each depth segment are 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 from the water surface reference point.

[0033] Preferably, the method for outputting the final target depth includes:

[0034] An error constraint expression is introduced to establish an error constraint relationship between the static depth value and the actual depth value. Physical error boundaries are applied to the pressure depth value and the acoustic depth value respectively. Based on satisfying the error constraint relationship, the pressure depth value, acoustic depth value and actual depth value are weighted and fused to calculate the target depth of the current position of the test probe.

[0035] An automatic underwater depth positioning system for a test probe, comprising:

[0036] The reference depth sensing module collects the absolute water pressure value of the current underwater environment, combines it with the reference air pressure data at the water surface, and calculates the hydrostatic pressure value; at the same time, it receives acoustic signals from the water surface base station and returns a response, and measures the round-trip propagation time of sound waves in the water.

[0037] The initial depth estimation module collects water temperature and salinity change data, estimates the current water density information, and converts the hydrostatic pressure value into a pressure depth value. It uses an empirical sound velocity model to calculate the average sound wave propagation speed and, combined with the round-trip propagation time of the sound wave in the water, calculates the acoustic depth value of the probe.

[0038] The sound velocity sequence construction module introduces a dynamic error compensation factor to correct the temperature drift error generated during pressure depth sounding and performs co-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 of depth value to obtain the sound wave propagation velocity sequence.

[0039] The motion interference decoupling module records the unidirectional sound wave propagation time, infers the sound wave propagation path at each depth segment by combining the sound wave propagation velocity sequence, and reverses the relative displacement of the probe during the sound wave propagation process. By introducing time variables and preset depth starting points, it calculates the static depth value of the probe's current position.

[0040] The final depth positioning module calculates the actual depth value of the probe's current position based on the sound wave propagation path and 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.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] This 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. This function can respond in real-time to changes in water temperature, effectively correcting pressure errors caused by thermal drift and making the corrected pressure-depth value closer to the actual value. By continuously collecting two types of depth measurement data, the difference deviation sequence between pressure-depth and acoustic depth values ​​is analyzed. An error mapping relationship between the two depth measurement methods is established through statistical fitting, enabling mutual compensation and adaptive correction between the two methods under different environments, thereby 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, applicable to various complex application scenarios, 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.

[0043] By constructing error constraint relationships between static depth values, pressure depth values, and acoustic depth values, a maximum permissible deviation threshold is set for pressure depth values, while a dynamic tolerance limit based on the rate of change of sound velocity and the propagation time interval is introduced for acoustic depth values. This error constraint mechanism effectively eliminates 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 rate of change of sound wave propagation velocity is introduced as a trade-off factor in the acoustic error constraint, which can reflect the actual dynamic characteristics of sound velocity changes in water bodies, enabling the error tolerance to have adaptive adjustment capabilities. This mechanism can still stably identify the credible boundary of acoustic depth even in water bodies with obvious stratification and uneven sound velocity profiles, thereby improving the system's adaptability and robustness to complex hydrological environments. It does not rely on special hardware and can be implemented simply by integrating the depth estimation model and constraint logic into existing probe systems, possessing good portability and engineering integration value. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the process for an automatic underwater depth positioning method for a test probe according to the present invention;

[0045] Figure 2 This is a schematic diagram of the underwater depth automatic positioning system for a test probe according to the present invention;

[0046] Figure 3 This is a schematic diagram of the method for obtaining the sound wave propagation speed sequence provided by the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1

[0049] Please see Figure 1 and Figure 3 As shown, this embodiment further illustrates the automatic underwater depth positioning method for a test probe proposed in this invention, including:

[0050] Underwater detection and positioning are key technologies in multiple fields such as marine surveying, underwater communication, resource exploration, and environmental monitoring. Depth information, as a fundamental parameter affecting the accuracy of underwater navigation and operations, directly impacts the performance of the entire system through its accuracy and stability. Currently, the mainstream underwater depth measurement methods mainly include pressure sounding based on pressure sensors and acoustic sounding based on sound wave propagation time.

[0051] Traditional pressure sounding methods rely on pressure sensors to collect 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 sensors themselves can significantly affect the measurement results. For example, in the deep-sea environment, changes in water temperature can cause a 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, resulting in a lack of consistency and repeatability of pressure sounding results under different environmental conditions, severely limiting the accuracy and stability of the measurement.

[0052] Acoustic depth sounding methods calculate the acoustic depth between a target and a reference point by measuring the round-trip time of sound waves in water and combining this with a pre-defined sound velocity model. While acoustic methods can avoid temperature drift to some extent, their measurement accuracy is highly dependent on the accurate estimation of sound velocity. The sound velocity in water is influenced by factors such as temperature, salinity, and density, exhibiting a distinct stratified structure at different depths. Existing systems often use average sound velocity or empirical models to estimate the sound velocity in water, but because they cannot detect real-time changes in the actual water profile, sound velocity mismatch is easily caused, leading to systematic errors in acoustic depth. Furthermore, the curved propagation path of sound waves in non-homogeneous media further increases the complexity of error analysis and compensation.

[0053] In current technologies, pressure depth and acoustic depth are often used as independent measurement channels, each limited by its inherent error sources. Furthermore, the lack of effective calibration, joint constraints, or fusion mechanisms leads to inconsistencies in the measurement results, making it difficult to correct and assess the reliability of the final depth output. When the aquatic environment is complex and error sources are varied, the system struggles to identify and eliminate abnormal data, limiting the practicality of existing technologies in high-precision underwater positioning tasks.

[0054] In view of this, the present invention proposes an automatic underwater depth positioning method for a test probe, comprising:

[0055] S1. Collect the absolute water pressure value of the current underwater environment, combine it with the water surface reference air pressure data, and calculate the hydrostatic pressure value; at the same time, receive the acoustic signal from the water surface base station and return a response, and measure the round-trip propagation time of the sound wave in the water body.

[0056] S2. Collect water temperature and salinity change data, estimate the current water density information, and convert the hydrostatic pressure value into a pressure depth value; use an empirical sound velocity model to calculate the average sound wave propagation speed, and combine the round-trip propagation time of the sound wave in the water to calculate the acoustic depth value of the probe.

[0057] S3. Introduce a dynamic error compensation factor to correct the temperature drift error generated during pressure depth sounding, and perform co-calibration of pressure depth and acoustic depth; combine the corrected water temperature data and salinity change data to determine the sound wave propagation speed at different water depths, and arrange them in ascending order of depth value to obtain a sound wave propagation speed sequence.

[0058] S4. Record the unidirectional sound wave propagation time, combine the sound wave propagation speed sequence to infer the sound wave propagation path of each depth segment, and inversely deduce the relative displacement of the probe during the sound wave propagation process. By introducing time variables and preset depth starting points, calculate the static depth value of the probe's current position.

[0059] S5. Based on the sound wave propagation path and propagation time, calculate the actual depth value of the probe's current position, establish the error constraint relationship between the static depth value and the actual depth value, and perform weighted fusion of the pressure depth value, acoustic depth value and actual depth value to output the final target depth.

[0060] Methods for obtaining the round-trip propagation time of sound waves in water include:

[0061] The absolute water pressure value of the current underwater environment is acquired in real time by a pressure sensor deployed on the test probe. The absolute water pressure value includes the hydrostatic pressure generated by the water column and the reference air pressure (atmospheric pressure) at the water surface. At the same time, the reference air pressure data of the water surface is acquired in real time by a pressure sensor deployed at the water surface. The reference air pressure data of the water surface is removed from the absolute water pressure value to eliminate the influence of the reference air pressure on the underwater pressure measurement results, so that only the hydrostatic pressure value generated by the water column is obtained.

[0062] At a preset time point, the surface base station sends an acoustic signal with a timestamp to the underwater test probe. The acoustic signal travels vertically through the water to the underwater test probe. Upon receiving the acoustic signal, the test probe immediately triggers a response mechanism and sends a response signal back to the surface base station. The surface base station synchronously records the total time interval between the start time of transmitting the acoustic signal and the time of receiving the probe's response signal, which is recorded as the round-trip propagation time of the sound wave in the current water body.

[0063] Methods for obtaining pressure depth values ​​include:

[0064] Temperature and salinity data of the water body at the test point are collected by temperature and salinity sensors installed on an underwater test probe, respectively. The water temperature data includes the real-time water temperature value at the test probe location, the gradient of water temperature with depth, and the temperature distribution data at different depths. The salinity data includes the concentration of dissolved salts in the water, the salinity change data with depth, and the salinity distribution data at different depths. If the water salinity value collected by the salinity sensor at the test point is greater than or equal to a preset water salinity threshold, the density information of the current water body is estimated using the UNESCO seawater state equation.

[0065] If the salinity value of the water body is less than the preset salinity value threshold, the density information of the current water body is estimated using the Tanaka formula. Based on the density information of the current water body and the gravitational acceleration, the hydrostatic pressure value obtained by removing the atmospheric pressure component from the absolute water pressure value is converted into the pressure depth value corresponding to the hydrostatic pressure value.

[0066] Pressure depth value: ;in, This represents the pressure depth value calculated from the hydrostatic pressure value; This represents the hydrostatic pressure value after removing the influence of the reference air pressure at the water surface; This indicates the water density at the corresponding depth; Represents gravitational acceleration;

[0067] Methods for obtaining the acoustic depth value of the probe include:

[0068] Based on real-time collected water temperature and salinity change data, the Del Grosso model is used to calculate the average sound wave propagation speed in the current water environment. The propagation path of the sound wave in the water is preset to be a vertical straight line. The propagation distance of the sound wave in a one-way path is calculated by using the product of the average sound wave propagation speed and the round-trip propagation time of the sound wave, thereby obtaining the acoustic depth value of the test probe relative to the water surface reference.

[0069] Methods for co-calibrating pressure depth and acoustic depth include:

[0070] In practical underwater applications, the pressure sensors configured on underwater probes are susceptible to changes in water temperature, resulting in thermal drift errors (temperature drift). These errors typically manifest as: a systematic shift in measured values ​​as water temperature increases or decreases; errors are more pronounced under high-pressure (deep water) conditions; and different batches or models of sensors exhibit varying temperature drift characteristics, requiring dynamic compensation.

[0071] 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 changes in water temperature is corrected through the dynamic error compensation function. The corrected hydrostatic pressure value is: ;in, This indicates the corrected hydrostatic pressure value; This represents the dynamic error compensation value caused by temperature drift. It should be noted that although this is expressed using... It is represented as a dynamic error compensation function composed of a temperature function, a time function, and historical compensation values;

[0072] The dynamic error compensation function is: ;in, This represents the static sensitivity coefficient of temperature deviation to error. This indicates the preset reference temperature (the temperature during sensor calibration). It represents the rate of temperature change, reflecting the impact of dynamic temperature changes on the error; The dynamic sensitivity coefficient represents the rate of temperature change. Indicates the water temperature at the current time; This represents the dynamic error compensation value at the previous time point; This represents the historical error attenuation factor, based on expert experience. The value ranges from 0 to 1;

[0073] By collecting pressure depth values ​​and corresponding acoustic depth values ​​over a continuous time period, calculating the difference deviation sequence between the two, establishing an error mapping model between the two types of depth measurements based on a statistical fitting method, and outputting the pressure depth values ​​and acoustic depth values ​​after collaborative calibration.

[0074] This solution addresses the following problems in existing technologies: In current underwater detection systems, pressure sensors are prone to thermal drift (temperature drift) errors under different water temperatures, especially in deep-water, high-pressure, or drastically temperature-changing environments. This causes systematic deviations in depth measurement data, making it difficult to ensure measurement accuracy and stability. Traditional technologies treat pressure sounding and acoustic sounding as independent methods, each affected by its own error sources, resulting in inconsistent measurement results. There is a lack of effective means to calibrate and fuse these two methods, making it difficult to support high-precision underwater positioning requirements. Using only empirical sound velocity models to calculate underwater acoustic depth cannot adapt to complex water structures (such as stratification and haloclines) in real time, easily leading to sound velocity mismatch and affecting the accuracy of acoustic ranging.

[0075] Compared to existing technologies, the advantages are as follows: By introducing a dynamic error compensation factor, a temperature drift correction function incorporating temperature deviation, temperature change rate, and historical compensation feedback is constructed. 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 value closer to the actual value. By continuously collecting two types of depth measurement data, the difference deviation sequence between pressure depth and acoustic depth values ​​is analyzed. An error mapping relationship between the two depth measurement methods is established through statistical fitting, enabling mutual compensation and adaptive correction between the two methods under different environments, thus 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, applicable to various complex application scenarios, including seawater, freshwater, reservoirs, and fishing grounds, 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.

[0076] Methods for obtaining sound wave propagation speed sequences include:

[0077] Based on the pressure depth and acoustic depth values ​​after collaborative calibration, and the corresponding water temperature and salinity change data, a water thermohaline profile dataset is constructed in ascending order of depth; an appropriate empirical sound velocity calculation model is selected according to the target water type, with the Mackenzie model used in seawater environment and the Wilson model used in freshwater or low-salinity environment.

[0078] Using an empirical sound velocity calculation model, water temperature data, salinity change data, and hydrostatic pressure values ​​at each depth location are used as input parameters to calculate the sound wave propagation velocity value at the corresponding depth point by point. A mapping relationship is established between the sound wave propagation velocity values ​​of each depth layer and the corresponding depth location, and the values ​​are sorted in ascending order of depth to form a sound wave propagation velocity sequence.

[0079] Methods for calculating the static depth value at the current position of the probe include:

[0080] The unidirectional 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 regarded as a layered medium propagation environment. By distributing the recorded unidirectional propagation time to each depth segment and combining 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 calculated in turn.

[0081] A 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 (preset depth is zero), the propagation distance corresponding to each time increment is integrated based on the sound wave propagation speed sequence, and the results are gradually superimposed to obtain the cumulative depth value corresponding to the sound wave propagation path, which is used as the static depth value of the probe at the current time point.

[0082] Methods for calculating the actual depth value at the current position of the probe include:

[0083] By comparing the theoretical one-way sound wave propagation time estimated through the sound wave propagation velocity sequence and sound wave propagation path with the actual measured one-way sound wave propagation time, if there is a difference in propagation time between the two, it is determined that there is an offset in the estimation of the static depth value.

[0084] Based on the propagation time difference, the length of the sound wave propagation path at each depth segment in the sound wave propagation path is adjusted, and the sound wave propagation speed at each depth segment in the sound 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.

[0085] The propagation distance is recalculated using the corrected sound wave propagation path, and the propagation distances at each depth segment are 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 from the water surface reference point.

[0086] Methods for outputting the final target depth include:

[0087] An error constraint condition expression is introduced to establish the error constraint relationship between the static depth value and the actual depth value, and physical error boundaries are applied to the pressure depth value and the acoustic depth value respectively.

[0088] The expression for introducing error constraint conditions is as follows: ;in, Represents the set of error constraints; This indicates the acoustic depth value at the current position of the test probe; This indicates the static depth value at the current position of the test probe; This indicates the preset maximum allowable pressure depth deviation threshold; This represents the acoustic error sensitivity adjustment coefficient; This represents the rate of change of the speed of sound propagation in water. Indicates the time interval of sound wave propagation;

[0089] Based on the error constraint relationship, the pressure depth value, acoustic depth value and actual depth value are weighted and fused to calculate the target depth of the current position of the test probe.

[0090] This paper addresses the following problems in existing technologies: Existing depth measurement methods based on pressure sensors are susceptible to thermal drift errors due to factors such as water temperature variations, sensor aging, and structural stress in practical applications. These errors manifest as systematic shifts in measured values ​​under different temperature conditions, leading to a lack of stability and reliability in pressure depth values. Acoustic depth measurement relies on the propagation time and estimated sound velocity in water. However, sound velocity in actual underwater environments is affected by factors such as water temperature, salinity, and density variations, exhibiting a distinct stratified structure. In existing technologies, sound velocity estimates typically use average models or surface empirical values, which cannot fully reflect true depth changes, resulting in accuracy fluctuations and error accumulation in acoustic depth measurements. Furthermore, pressure depth and acoustic depth are often processed independently, lacking effective joint constraint judgment and fusion mechanisms, and failing to dynamically eliminate unreliable observations.

[0091] Compared to existing technologies, the advantages are as follows: By constructing error constraint relationships between static depth values, pressure depth values, and acoustic depth values, a maximum permissible deviation threshold is set for pressure depth values, and a dynamic tolerance limit based on the rate of change of sound velocity and the propagation time interval is introduced for acoustic depth values. 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 rate of change of sound wave propagation velocity is introduced as a trade-off factor in the acoustic error constraint, which can reflect the actual dynamic characteristics of sound velocity changes in water bodies, enabling the error tolerance to have adaptive adjustment capabilities. This mechanism can still stably identify the credible boundary of acoustic depth even in water bodies with obvious stratification and uneven sound velocity profiles, thereby improving the system's adaptability and robustness to complex hydrological environments. It does not rely on special hardware and can be implemented simply by integrating the depth estimation model and constraint logic into existing probe systems, possessing good portability and engineering integration value.

[0092] The preset water salinity threshold is set by staff based on historical data analysis results. This historical analysis process includes the system collecting salinity values ​​from multiple water bodies and calculating their average value as a reference to obtain the preset water salinity threshold. Similarly, the preset propagation time difference threshold is also set by staff based on the system's historical operating data and the specific application scenario requirements, and can be adjusted by staff during system operation according to the actual situation.

[0093] In this embodiment, a temperature drift correction function is constructed by introducing a dynamic error compensation factor, which includes temperature deviation, temperature change rate, and historical compensation feedback. This function can respond to changes in water temperature in real time, effectively correcting pressure errors caused by thermal drift, and making the corrected pressure depth value closer to the actual value. By continuously collecting two types of depth measurement data, the difference deviation sequence between pressure depth and acoustic depth values ​​is analyzed. An error mapping relationship between the two depth measurement methods is established through statistical fitting methods, realizing mutual compensation and adaptive correction between the two depth measurement methods under different environments, thereby 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 realized, applicable to various complex application scenarios, and effectively overcoming the uncertainty caused by water parameter disturbances. The co-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.

[0094] By constructing error constraint relationships between static depth values, pressure depth values, and acoustic depth values, a maximum permissible deviation threshold is set for pressure depth values, while a dynamic tolerance limit based on the rate of change of sound velocity and the propagation time interval is introduced for acoustic depth values. This error constraint mechanism effectively eliminates 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 rate of change of sound wave propagation velocity is introduced as a trade-off factor in the acoustic error constraint, which can reflect the actual dynamic characteristics of sound velocity changes in water bodies, enabling the error tolerance to have adaptive adjustment capabilities. This mechanism can still stably identify the credible boundary of acoustic depth even in water bodies with obvious stratification and uneven sound velocity profiles, thereby improving the system's adaptability and robustness to complex hydrological environments. It does not rely on special hardware and can be implemented simply by integrating the depth estimation model and constraint logic into existing probe systems, possessing good portability and engineering integration value.

[0095] Example 2

[0096] Please see Figure 2 As shown, parts not described in detail in this embodiment are described in Embodiment 1. An automatic underwater depth positioning system for a test probe is provided, comprising:

[0097] The reference depth sensing module collects the absolute water pressure value of the current underwater environment, combines it with the reference air pressure data at the water surface, and calculates the hydrostatic pressure value; at the same time, it receives acoustic signals from the water surface base station and returns a response, and measures the round-trip propagation time of sound waves in the water.

[0098] The initial depth estimation module collects water temperature and salinity change data, estimates the current water density information, and converts the hydrostatic pressure value into a pressure depth value. It uses an empirical sound velocity model to calculate the average sound wave propagation speed and, combined with the round-trip propagation time of the sound wave in the water, calculates the acoustic depth value of the probe.

[0099] The sound velocity sequence construction module introduces a dynamic error compensation factor to correct the temperature drift error generated during pressure depth sounding and performs co-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 of depth value to obtain the sound wave propagation velocity sequence.

[0100] The motion interference decoupling module records the unidirectional sound wave propagation time, infers the sound wave propagation path at each depth segment by combining the sound wave propagation velocity sequence, and reverses the relative displacement of the probe during the sound wave propagation process. By introducing time variables and preset depth starting points, it calculates the static depth value of the probe's current position.

[0101] The final depth positioning module calculates the actual depth value of the probe's current position based on the sound wave propagation path and 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.

[0102] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0103] 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 embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing 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 locating the underwater depth of a test probe, characterized in that, include: S1. Collect the absolute water pressure value of the current underwater environment, combine it with the water surface reference air pressure data, and calculate the hydrostatic pressure value; at the same time, receive the acoustic signal from the water surface base station and return a response, and measure the round-trip propagation time of the sound wave in the water body. S2. Collect water temperature and salinity change data, estimate the current water density information, and convert the hydrostatic pressure value into a pressure depth value; use an empirical sound velocity model to calculate the average sound wave propagation speed, 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 depth measurement, and perform joint calibration of pressure depth and acoustic depth. By combining the corrected water temperature and salinity change data, the sound wave propagation speed at different water depths was determined and sorted in ascending order of depth value to obtain a sound wave propagation speed sequence. S4. Record the unidirectional sound wave propagation time, combine the sound wave propagation speed sequence to infer the sound wave propagation path of each depth segment, and inversely deduce the relative displacement of the probe during the sound wave propagation process. By introducing time variables and preset depth starting points, calculate the static depth value of the probe's current position. S5. Based on the sound wave propagation path and propagation time, calculate the actual depth value of the probe's current position, establish the error constraint relationship between the static depth value and the actual depth value, and perform weighted fusion of the pressure depth value, acoustic depth value and actual depth value to output the final target depth.

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

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

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

5. The method for automatic underwater depth positioning of a test probe according to claim 4, characterized in that, The method for co-calibrating the 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 influence of water temperature changes is corrected by the dynamic error compensation function. By collecting pressure depth values ​​and corresponding acoustic depth values ​​over a continuous time period, the difference deviation sequence between the two is calculated. An error mapping model between the two types of depth measurements is established based on a statistical fitting method, and the pressure depth value and acoustic depth value after collaborative calibration are output.

6. The method for automatic underwater depth positioning of a test probe according to claim 5, characterized in that, The method for obtaining the sound wave propagation speed sequence includes: Based on the pressure depth and acoustic depth values ​​after collaborative calibration, and the corresponding water temperature and salinity change data, a water thermohaline profile dataset is constructed in ascending order of depth; and an appropriate empirical sound velocity calculation model is selected according to the target water type. Using an empirical sound velocity calculation model, water temperature data, salinity change data, and hydrostatic pressure values ​​at each depth location are used as input parameters to calculate the sound wave propagation velocity value at the corresponding depth point by point. A mapping relationship is established between the sound wave propagation velocity values ​​of each depth layer and the corresponding depth location, and the values ​​are sorted in ascending order of depth to form a sound wave propagation velocity sequence.

7. The automatic underwater depth positioning method for a test probe according to claim 6, characterized in that, Methods for calculating the static depth value at the current position of the probe include: The unidirectional 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 regarded as a layered medium propagation environment. By distributing the recorded unidirectional propagation time to each depth segment and combining 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 calculated in turn. A 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 speed sequence and gradually superimposed to obtain the cumulative depth value corresponding to the sound wave propagation path, which is used as the static depth value of the probe at the current time point.

8. The automatic underwater depth positioning method for a test probe according to claim 7, characterized in that, The method for calculating the actual depth value of the probe's current position includes: By comparing the theoretical one-way sound wave propagation time estimated through the sound wave propagation velocity sequence and sound wave propagation path with the actual measured one-way sound wave propagation time, if there is a difference in propagation time between the two, it is determined that there is an offset in the estimation of the static depth value. Based on the propagation time difference, the length of the sound wave propagation path at each depth segment in the sound wave propagation path is adjusted, and the sound wave propagation speed at each depth segment in the sound 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 is recalculated using the corrected sound wave propagation path, and the propagation distances at each depth segment are 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 from the water surface reference point.

9. The automatic underwater depth positioning method for 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 an error constraint relationship between the static depth value and the actual depth value. Physical error boundaries are applied to the pressure depth value and the acoustic depth value respectively. Based on satisfying the error constraint relationship, the pressure depth value, acoustic depth value and actual depth value are weighted and 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 as described in any one of claims 1 to 9, characterized in that, include: The reference depth sensing module collects the absolute water pressure value of the current underwater environment, combines it with the reference air pressure data at the water surface, and calculates the hydrostatic pressure value; at the same time, it receives acoustic signals from the water surface base station and returns a response, and measures the round-trip propagation time of sound waves in the water. The initial depth estimation module collects water temperature and salinity change data, estimates the current water density information, and converts the hydrostatic pressure value into a pressure depth value. It uses an empirical sound velocity model to calculate the average sound wave propagation speed and, combined with the round-trip propagation time of the sound wave in the water, calculates 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 depth sounding and performs co-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 of depth value to obtain the sound wave propagation velocity sequence. The motion interference decoupling module records the unidirectional sound wave propagation time, infers the sound wave propagation path at each depth segment by combining the sound wave propagation velocity sequence, and reverses the relative displacement of the probe during the sound wave propagation process. By introducing time variables and preset depth starting points, it calculates the static depth value of the probe's current position. The final depth positioning module calculates the actual depth value of the probe's current position based on the sound wave propagation path and 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.

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