Underwater ranging method and device based on motion state compensation, equipment and medium

Abstract

The application relates to an underwater ranging method and device based on motion state compensation, equipment and a storage medium. The method comprises the following steps: determining the position information of a transponder based on a pre-constructed motion state equation and an observation equation of the transponder; compensating the original slant range between the transponder and a base station to obtain a compensated slant range according to the position information of the transponder and the movement vector of the base station; extracting the sound speed gradient and the signal-to-noise ratio parameter; calculating the environmental confidence factor based on the sound speed gradient and the signal-to-noise ratio; calculating the first horizontal distance and the second horizontal distance between the transponder and the base station by using the depth difference and the vertical angle respectively; determining the first weight corresponding to the first horizontal distance and the second weight corresponding to the second horizontal distance according to the environmental confidence factor; and calculating the target horizontal distance between the transponder and the base station according to the first horizontal distance, the first weight, the second horizontal distance and the second weight.

Description

Technical Field

[0001] This application relates to the field of underwater ranging technology, and in particular to an underwater ranging method, apparatus, device and storage medium based on motion state compensation. Background Technology

[0002] Ultra-short baseline (USBL) positioning systems are widely used in marine engineering and underwater navigation, but their ranging accuracy is susceptible to various factors. In actual operations, the mother ship carrying the base station is constantly moving due to ocean waves, and the underwater transponder may also experience non-uniform motion due to ocean currents or its own propulsion, causing changes in the relative positions of the transmitter and receiver during sound wave propagation, resulting in ranging results deviating from the true geometric distance. Simultaneously, the speed of sound in the marine environment often varies non-uniformly with depth, causing sound ray bending and introducing systematic biases into distance calculations based on vertical geometry. Furthermore, long-distance propagation, multipath effects, or strong background noise can degrade echo signal quality, affecting the accuracy of angle parameter calculations. The coupling effect of these dynamic platform disturbances and complex acoustic environments means that existing USBL systems face technical challenges such as poor ranging stability and large horizontal position estimation errors in high sea states or deep-sea scenarios. Summary of the Invention

[0003] In view of the above, this application provides an underwater ranging method, apparatus, device and storage medium based on motion state compensation, the purpose of which is to solve the above-mentioned technical problems.

[0004] In a first aspect, this application provides an underwater ranging method based on motion state compensation, the method comprising: Based on the pre-constructed motion state equations and observation equations of the transponder, the position information of the transponder is determined; Based on the position information of the transponder and the movement vector of the base station, the original slant range between the transponder and the base station is compensated to obtain the compensated slant range. Extract sound velocity gradient and signal-to-noise ratio parameters, and calculate environmental confidence factor based on sound velocity gradient and signal-to-noise ratio; The first and second horizontal distances between the transponder and the base station are calculated using the depth difference and vertical angle, respectively. The first weight corresponding to the first horizontal distance is determined based on the environmental confidence factor, and the second weight corresponding to the second horizontal distance is determined. The target horizontal distance between the transponder and the base station is calculated based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight.

[0005] Secondly, this application provides an underwater ranging device based on motion state compensation, which includes a module that performs the underwater ranging method based on motion state compensation described in the first aspect.

[0006] Thirdly, this application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in a memory, it implements the steps of the underwater ranging method based on motion state compensation as described in any embodiment of the first aspect.

[0007] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the underwater ranging method based on motion state compensation as described in any embodiment of the first aspect.

[0008] The technical solutions provided in this application have the following advantages compared with the prior art: This application constructs the motion state equation and observation equation of the transponder, estimates its velocity and acceleration in real time, and combines the base station movement vector to dynamically compensate for the original slant range, effectively eliminating the ranging deviation caused by relative motion during signal propagation. By extracting the sound speed gradient and signal-to-noise ratio to calculate the environmental confidence factor, it adaptively adjusts the fusion weights of the first horizontal distance based on depth difference and the second horizontal distance based on vertical angle, realizing the priority use of high-reliability paths in different marine environments. The target horizontal distance is obtained through weighted fusion, improving the positioning robustness and accuracy of the USBL system in harsh sea conditions such as dynamic platforms, complex sound speed profiles, or low signal-to-noise ratios. Attached Figure Description

[0009] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a preferred embodiment of the underwater ranging method based on motion state compensation in this application; Figure 2 This is a schematic diagram of a preferred embodiment of the underwater ranging device based on motion state compensation in this application. Figure 3 This is a schematic diagram of a preferred embodiment of the electronic device of this application; The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0013] It should be noted that the use of terms such as "first" and "second" in this application is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of those features. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed in this application.

[0014] Reference Figure 1 The diagram shown is a flowchart illustrating an embodiment of the underwater ranging method based on motion state compensation according to this application. The method is executed by an electronic device, which can be implemented by a software system and / or a hardware system. This underwater ranging method based on motion state compensation includes: Step S10: Determine the position information of the transponder based on the pre-constructed motion state equation and observation equation of the transponder; Step S20: Based on the position information of the transponder and the movement vector of the base station, the original slant range between the transponder and the base station is compensated to obtain the compensated slant range; Step S30: Extract the sound velocity gradient and signal-to-noise ratio parameters, and calculate the environmental confidence factor based on the sound velocity gradient and signal-to-noise ratio; Step S40: Calculate the first horizontal distance and the second horizontal distance between the transponder and the base station using the depth difference and vertical angle, respectively; Step S50: Determine the first weight corresponding to the first horizontal distance based on the environmental confidence factor, and determine the second weight corresponding to the second horizontal distance; Step S60: Calculate the target horizontal distance between the transponder and the base station based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight.

[0015] In underwater ultra-short baseline (USBL) positioning systems, the positions of the base station and transponder continuously change during sound wave propagation due to the movement of the mother ship-borne base station with the waves and the potential autonomous movement of the underwater transponder. This results in significant dynamic errors in the directly measured raw slant range. Furthermore, variations in sound velocity gradients and low signal-to-noise ratios in the marine environment affect the accuracy of horizontal distance calculations based on depth difference and vertical angle, respectively. To address these issues, this embodiment proposes an underwater ranging method based on motion state compensation. The aim is to perform motion compensation on the raw ranging results by fusing the transponder dynamic model and environmental perception information, and adaptively fuse the horizontal distance estimates from two geometric paths, thereby obtaining a highly robust and accurate target horizontal distance.

[0016] Specifically, the position information of the transponder is determined based on the pre-constructed motion state equation and observation equation of the transponder. The motion state equation uses the three-dimensional position, three-dimensional velocity, and three-dimensional acceleration of the transponder as state variables, and the observation equation uses the slant range, azimuth angle, and pitch angle output by the USBL system as observations. The state is recursively estimated through a filtering algorithm to obtain the velocity, acceleration, and position information of the transponder at the current moment.

[0017] Based on the transponder's position information and the base station's movement vector, the original slant range between the transponder and the base station is compensated to obtain the compensated slant range. The one-way propagation time of the sound wave can be estimated using the original slant range and the average sound velocity. Combined with the transponder's trajectory (obtained by integrating velocity and acceleration) and the base station's movement vector during this propagation time, the relative displacement correction is calculated. Finally, the original slant range is dynamically compensated, and the compensated slant range is output.

[0018] The sound velocity gradient and signal-to-noise ratio (SNR) parameters are extracted, and an environmental confidence factor is calculated based on these parameters. The sound velocity gradient refers to the rate of change of sound velocity per unit depth along the water depth direction, reflecting the curvature of the sound wave propagation path, and is acquired in real time by a sound velocity profiler or CTD sensor in the marine environment monitoring module. The signal-to-noise ratio (SNR) is the ratio of the signal power of the USBL received signal to the background noise power, used to characterize the quality of the echo signal, and is directly output by the signal processing unit of the USBL receiver. After normalization, both parameters are combined according to preset weights to generate an environmental confidence factor with values ​​in the [0,1] interval, used to characterize the reliability of different ranging paths under the current marine environment.

[0019] The first and second horizontal distances between the transponder and the base station are calculated using the depth difference and vertical angle, respectively. The depth difference refers to the absolute difference between the depth of the transponder and the depth of the base station. The transponder's depth is measured by its built-in pressure sensor and transmitted back via acoustic telemetry, while the base station's depth is provided by a depth sensor mounted on the mother ship. The vertical angle is the pitch angle relative to the local horizontal plane when the acoustic signal reaches the USBL array, calculated by the USBL system using multi-receiver phase difference. The first horizontal distance, given the depth difference between the transponder and the base station and the compensated slant range, is the horizontal projection distance derived using the Pythagorean theorem of a right triangle in three-dimensional space, and is used to characterize the horizontal distance under vertical geometric constraints. The second horizontal distance, given the vertical angle measured by the USBL system and the compensated slant range, is the horizontal distance obtained by cosine projection of the slant range onto the horizontal plane, and is used to characterize the horizontal distance under direction measurement constraints.

[0020] Based on the environmental confidence factor, a first weight corresponding to the first horizontal distance is determined, and a second weight corresponding to the second horizontal distance is determined. When the environmental confidence factor is low (indicating a large sound velocity gradient or low signal-to-noise ratio), the second horizontal distance based on the vertical angle is given priority. When the environmental confidence factor is high, the first horizontal distance based on the depth difference is given priority. In the intermediate range of the environmental confidence factor, the weights are dynamically allocated according to the estimated variances of the two horizontal distances to achieve a smooth transition.

[0021] By weighted fusion of horizontal distance estimates from two independent paths, the final target horizontal distance is output as the high-precision horizontal position output of the underwater positioning system. Introducing a transponder motion state compensation mechanism effectively eliminates slant range deviations caused by dynamic platforms. Furthermore, combining a fusion strategy that adaptively adjusts multi-source horizontal distances based on marine environmental parameters improves the ranging stability and accuracy of the USBL system under complex sea conditions, making it particularly suitable for deep-sea operations in environments with severe mother ship swaying and variable acoustic fields.

[0022] In one embodiment, determining the transponder's position information based on the pre-constructed motion state equation and observation equation of the transponder includes: Construct motion state equations with the three-dimensional position, three-dimensional velocity, and three-dimensional acceleration of the transponder as state variables; Construct an observation equation using the original slant range, azimuth angle, and elevation angle as the observation quantities; The motion state equation and the observation equation are jointly processed by the extended Kalman filter algorithm to obtain the predicted value of the transponder's state vector at the current moment. The location information of the transponder is extracted from the predicted value.

[0023] In underwater dynamic positioning scenarios, transponders may experience non-uniform motion due to ocean current disturbances, self-propulsion, or cable towing. Meanwhile, USBL observations are susceptible to multipath propulsion, reverberation, and low signal-to-noise ratio. Traditional filtering methods with fixed process noise covariance struggle to balance model constraints and observation reliability, leading to distorted velocity and acceleration estimates and consequently affecting the accuracy of subsequent slant range compensation. Therefore, this embodiment constructs a complete state-space model including position, velocity, and acceleration, and introduces an adaptive noise covariance adjustment mechanism based on environmental and dynamic characteristics to improve the robustness of state estimation.

[0024] Specifically, firstly, a motion state equation is constructed with the transponder's three-dimensional position, three-dimensional velocity, and three-dimensional acceleration as state variables. This motion state equation adopts a uniformly accelerated motion model, and its discrete form is as follows: ,in, It is a state vector (position, velocity, acceleration). Here is the state transition matrix. To control the input matrix, For control vectors, The process noise (following a time-varying Gaussian distribution) is denoted as . .

[0025] Secondly, an observation equation is constructed using the original slant range, azimuth angle, and elevation angle as the observation quantities. The original slant range refers to the straight-line spatial distance between the transponder and the base station calculated by the USBL system based on the round-trip time and average speed of sound. The azimuth angle is the horizontal angle between the transponder and the north direction of the base station. The elevation angle is the downward angle between the acoustic signal and the local horizontal plane when the sound signal arrives at the USBL array. The observation equation is expressed as a function... ,in, For INS and acoustic observation fusion data, For the observation matrix, The observation noise is denoted as . .

[0026] Based on residual sequence Dynamic update process noise covariance and observation noise covariance :

[0027]

[0028] in, , For adaptive adjustment factor, The observation residual at time k.

[0029] The extended Kalman filter (EPF) algorithm is used to jointly process the motion state equation and the observation equation to obtain the predicted value of the transponder's state vector at the current time. The EPF is a recursive Bayesian estimation algorithm suitable for nonlinear systems, which updates the state by locally linearizing the nonlinear function. During the filtering process, the weights of the acceleration terms in the process noise covariance matrix are adaptively adjusted based on the current sound velocity profile, signal-to-noise ratio (SNR), and the transponder's dynamic characteristics. When the SNR is low or the sound velocity gradient is large, the process noise is increased to reduce model confidence; when the environment is stable, the process noise is decreased to enhance model constraints. This adaptive mechanism can improve the robustness of the filter in complex marine environments.

[0030] The velocity and acceleration of the transponder are extracted from the predicted values. The predicted values ​​are the optimal estimate of the transponder state vector output by the extended Kalman filter algorithm at the current moment, and the velocity and acceleration components can be directly separated from the predicted values.

[0031] In one embodiment, the step of compensating the original slant range between the transponder and the base station based on the transponder's location information and the base station's movement vector to obtain the compensated slant range includes: The displacement of the base station is calculated based on the base station's average velocity, average acceleration, and one-way propagation time of the sound wave. Based on the position vector of the transponder, the position vector of the base station, and the displacement of the base station, the geometric correction term for the signal propagation path is determined; Based on the aforementioned geometric correction term, effective sound velocity, and one-way sound wave propagation time, the compensated slant range is calculated by combining the direction cosine components of the azimuth and elevation angles.

[0032] The average velocity, average acceleration, and one-way propagation time of the sound wave are obtained. The average velocity and average acceleration of the base station are provided by the inertial navigation system (INS) carried by the mother ship, which reflects the motion state of the base station during signal propagation. The one-way propagation time of the sound wave, also known as the ranging time, refers to half of the round-trip propagation time of the sound wave from the USBL base station transmitting the interrogation signal to receiving the transponder reply signal.

[0033] The displacement of the base station (i.e., the movement vector of the base station) can be calculated according to the following formula (1). This value represents the geometric positional offset of the base station due to its movement: (1) in, Represents the movement vector of the base station. This represents the average speed of the base station. Indicates the distance measurement time. This represents the average acceleration of the base station.

[0034] Obtain the position vector of the beacon (responder) The location vector of the USBL base station and effective speed of sound c Substitute into the following formula (2): (2) This formula represents the ranging relationship without compensation for movement. This represents the slope distance after compensation, which is to be determined.

[0035] Equation (2) is algebraically transformed, and a relative displacement vector is introduced. L i (Defined as the difference between the base station displacement vector and the transponder displacement vector), resulting in formula (3): (3) in, x The cosine of the azimuth angle of the sound signal propagation direction in the horizontal plane relative to the x-axis (usually due north). y The cosine of the azimuth angle of the sound signal propagation direction in the horizontal plane relative to the y-axis (usually due east) is used to directly calculate the compensated slant distance. This allows for compensation.

[0036] In one embodiment, the extraction of sound velocity gradient and signal-to-noise ratio parameters, and the calculation of environmental confidence factors based on the sound velocity gradient and signal-to-noise ratio, includes: Acquire sound velocity gradient and signal-to-noise ratio from the marine environmental monitoring module; The first environmental influence component is obtained by taking the absolute value of the sound speed gradient and then inputting it into a preset monotonically decreasing nonlinear function. The signal-to-noise ratio is input into a preset monotonically increasing nonlinear function to obtain the second environmental influence component; The environmental confidence factor is calculated based on the first environmental impact component and the second environmental impact component.

[0037] The sound velocity gradient is measured in real time by a sound velocity profiler or CTD sensor, representing the rate of change of sound velocity per unit depth along the water depth direction. It is used to characterize the curvature of the sound wave propagation path. The signal-to-noise ratio is calculated by the signal processing unit of the USBL receiver, representing the ratio of echo signal power to background noise power. It is used to characterize the quality of the observed signal.

[0038] The absolute value of the extracted sound velocity gradient is taken, and the first environmental influence component is obtained by mapping the absolute value through a preset monotonically decreasing nonlinear function. The first environmental influence component decreases as the sound velocity gradient increases, reflecting the influence of sound field stability on the horizontal distance estimation based on depth difference.

[0039] The extracted signal-to-noise ratio (SNR) is input to a preset monotonically increasing nonlinear function for mapping, resulting in a second environmental influence component. This second environmental influence component increases with the SNR, reflecting the impact of signal quality on the reliability of angle calculation. The first and second environmental influence components are then linearly combined with equal weights to generate an environmental confidence factor. β The value ranges from 0 to 1, and the larger the value, the more stable the current marine environment.

[0040] Among them, environmental confidence factors β The calculation formula is as follows:

[0041] in, G c Represents the sound speed gradient. SNR This represents the signal-to-noise ratio. By introducing a nonlinear combination function based on sound velocity gradient and signal-to-noise ratio, an environmental confidence factor was constructed, enabling precise quantification of the dynamic characteristics of the marine environment. Compared to simple linear weighting or threshold judgment, this method can respond more sensitively to sound field distortion and signal degradation, distinguish the reliability of ranging paths under different operating conditions, provide a scientific basis for adaptive fusion of multi-source horizontal distances, and improve the positioning robustness and accuracy of the USBL system in complex marine environments.

[0042] In one embodiment, calculating the first horizontal distance and the second horizontal distance between the transponder and the base station using the depth difference and the vertical angle respectively includes: The depth difference between the transponder and the base station is calculated based on the depth of the transponder and the depth of the base station. The depth difference and the compensated slant distance are then substituted into the Pythagorean theorem formula to calculate the first horizontal distance. Obtain the vertical angle output by the USBL system, wherein the vertical angle is the pitch angle relative to the horizontal plane when the acoustic signal reaches the USBL array; Substituting the vertical angle and the compensated slant distance into the cosine projection formula, the second horizontal distance is calculated.

[0043] The transponder's depth can be measured in real time by its built-in sensors and transmitted back to the mother ship on the surface via acoustic telemetry. The base station's depth is provided by a high-precision depth sensor mounted on the mother ship. The absolute value of the difference between the two is the depth difference, representing the relative distance between the transponder and the base station in the vertical direction. The compensated slant range is the spatial straight-line distance after motion state compensation, eliminating dynamic errors caused by the movement of both parties during signal propagation. Assuming that the sound wave propagates in a straight line, the transponder, the base station, and their projections on the horizontal plane form a right triangle, and its horizontal side is the first horizontal distance. The formula for calculating the first horizontal distance is: ,in, Indicates the first horizontal distance. This represents the compensated slope distance. H i This indicates the depth difference.

[0044] The vertical angle output by the USBL system is obtained, where the vertical angle is the pitch angle relative to the local horizontal plane when the acoustic signal arrives at the USBL array. This vertical angle is calculated by the phase difference of the acoustic signals received by the USBL receiver array through multiple hydrophone units, and then output after attitude data compensation from the mother ship's inertial navigation system (INS) to eliminate the influence of hull sway on the angle measurement. The vertical angle and the compensated slant distance are substituted into the cosine projection formula to calculate the second horizontal distance. Specifically, the compensated slant distance is taken as the hypotenuse, and the vertical angle is taken as the angle with the horizontal plane; its projected length on the horizontal plane is the second horizontal distance. The formula for calculating the second horizontal distance is: , The second horizontal distance is indicated by the vertical angle of the underwater acoustic direction finding.

[0045] In one embodiment, determining the first weight corresponding to the first horizontal distance and the second weight corresponding to the second horizontal distance based on the environmental confidence factor includes: If the environmental confidence factor is less than the first threshold, the first weight is set to 0 and the second weight is set to 1. If the environmental confidence factor is not less than the first threshold and not greater than the second threshold, then calculate the first estimated variance corresponding to the first horizontal distance and the second estimated variance corresponding to the second horizontal distance, and calculate the first weight and the second weight respectively using the inverse variance weighting method based on the first estimated variance and the second estimated variance. If the environmental confidence factor is greater than the second threshold, set the first weight to 1 and the second weight to 0.

[0046] The system determines whether the environmental confidence factor is less than a first threshold, which can be 0.3. If the environmental confidence factor is less than 0.3, it indicates that the current sound velocity gradient is large or the signal-to-noise ratio is low, the sound field is severely distorted or the observation quality is poor. In this case, the first horizontal distance based on the depth difference is unreliable. Therefore, the first weight is set to 0 and the second weight is set to 1, meaning the second horizontal distance is fully trusted.

[0047] If the environmental confidence factor is greater than the second threshold (which can be 0.7), it indicates that the current sound field is stable, the signal-to-noise ratio is high, and the depth measurement is reliable. In this case, the first horizontal distance based on the depth difference is more accurate. Therefore, the first weight is set to 1 and the second weight is set to 0, which means that the first horizontal distance is fully trusted.

[0048] If the environmental confidence factor is not less than the first threshold and not greater than the second threshold, then the system enters the intermediate transition zone. Within this zone, both horizontal distances have a certain degree of reliability and need to be weighted and fused based on their estimation accuracy. The first estimation variance is calculated by the joint propagation of depth measurement error, compensated slant range error, and residual sound velocity profile error. The second estimation variance is calculated by the joint propagation of vertical angle calculation error, compensated slant range error, and USBL array calibration residual. The first weight = second estimation variance / (first estimation variance + second estimation variance), and the second weight = first estimation variance / (first estimation variance + second estimation variance). The specific calculation formula is as follows: ,

[0049] in, Indicates the first weight. Indicates the second weight. This represents the first estimated variance. This represents the variance of the second estimate. The error variance of the real-time estimate is dynamically weighted. When the incident angle is shallow, the depth difference dominates, using its high signal-to-noise ratio to suppress random errors. When the incident angle becomes steeper, the weight of the vertical angle is gradually increased, using its good geometric stability to suppress divergence caused by depth perturbations.

[0050] Further, the step of calculating the target horizontal distance between the transponder and the base station based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight includes: Multiply the first horizontal distance by the first weight to obtain the first weighted horizontal distance; Multiply the second horizontal distance by the second weight to obtain the second weighted horizontal distance; The first weighted horizontal distance and the second weighted horizontal distance are added together to obtain the target horizontal distance between the transponder and the base station.

[0051] The formula for expressing the horizontal distance to the target is:

[0052] in, r i Indicates the horizontal distance to the target. Indicates the first weight. Indicates the second weight. Indicates the first horizontal distance. This indicates the second horizontal distance.

[0053] Reference Figure 2 The diagram shown is a functional module schematic of the underwater ranging device 100 based on motion state compensation according to this application.

[0054] The underwater ranging device 100 based on motion state compensation described in this application is installed in an electronic device. Depending on the functions implemented, the underwater ranging device 100 based on motion state compensation includes a construction module 110, a compensation module 120, a first calculation module 130, a second calculation module 140, a determination module 150, and a third calculation module 160. These modules can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0055] In this embodiment, the functions of each module / unit are as follows: Module 110: Used to determine the position information of the transponder based on the pre-built motion state equation and observation equation of the transponder; Compensation module 120: used to compensate the original slant range between the transponder and the base station based on the transponder's position information and the base station's movement vector to obtain the compensated slant range; First calculation module 130: used to extract sound velocity gradient and signal-to-noise ratio parameters, and calculate environmental confidence factor based on sound velocity gradient and signal-to-noise ratio; Second calculation module 140: used to calculate the first horizontal distance and the second horizontal distance between the transponder and the base station using the depth difference and the vertical angle, respectively; Determining module 150: used to determine the first weight corresponding to the first horizontal distance based on the environmental confidence factor, and to determine the second weight corresponding to the second horizontal distance; The third calculation module 160 is used to calculate the target horizontal distance between the transponder and the base station based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight.

[0056] The specific implementation of the underwater ranging device based on motion state compensation in this application is largely the same as the specific implementation of the underwater ranging method based on motion state compensation described above, and will not be repeated here.

[0057] Reference Figure 3 The diagram shown is a schematic representation of a preferred embodiment of the electronic device of this application.

[0058] The electronic device includes a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114. The memory 113 is used to store computer programs, such as underwater ranging programs based on motion state compensation; In some embodiments, the processor 111 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 111 is typically used to control the overall operation of the electronic device, such as performing data interaction or communication-related control and processing. In this embodiment, the processor 111 is used to run program code stored in the memory 113 or process data.

[0059] The communication interface 112 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The communication interface 112 may also be used to establish a communication connection between the electronic device and other electronic devices.

[0060] The memory 113 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 113 may be an internal storage unit of the electronic device, such as the hard disk or memory of the electronic device. In other embodiments, the memory 113 may also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. of the electronic device. Of course, the memory 113 may include both internal storage units and external storage devices of the electronic device. In this embodiment, the memory 113 is typically used to store the operating system and various computer programs installed on the electronic device, such as the program code of an underwater ranging program based on motion state compensation. In addition, the memory 113 can also be used to temporarily store various types of data that have been output or will be output.

[0061] Figure 3 Only an electronic device with components 111-114 is shown; however, it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0062] In one embodiment of this application, when the processor 111 executes the program stored in the memory 113, it implements the underwater ranging method based on motion state compensation provided in any of the foregoing method embodiments, including: Based on the pre-constructed motion state equations and observation equations of the transponder, the position information of the transponder is determined; Based on the position information of the transponder and the movement vector of the base station, the original slant range between the transponder and the base station is compensated to obtain the compensated slant range. Extract sound velocity gradient and signal-to-noise ratio parameters, and calculate environmental confidence factor based on sound velocity gradient and signal-to-noise ratio; The first and second horizontal distances between the transponder and the base station are calculated using the depth difference and vertical angle, respectively. The first weight corresponding to the first horizontal distance is determined based on the environmental confidence factor, and the second weight corresponding to the second horizontal distance is determined. The target horizontal distance between the transponder and the base station is calculated based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight.

[0063] For a detailed explanation of the above steps, please refer to the above. Figure 1 Description of the flowchart of an embodiment of an underwater ranging method based on motion state compensation.

[0064] Furthermore, this application also proposes a computer-readable storage medium that is both non-volatile and volatile. This computer-readable storage medium is any one or any combination of several of the following: hard disk, multimedia card, SD card, flash memory card, SMC, read-only memory (ROM), erasable programmable read-only memory (EPROM), portable compact disc read-only memory (CD-ROM), USB memory, etc. The computer-readable storage medium includes a data storage area and a program storage area. The program storage area stores an underwater ranging program based on motion state compensation. When executed by a processor, the underwater ranging program based on motion state compensation performs the following operations: Based on the pre-constructed motion state equations and observation equations of the transponder, the position information of the transponder is determined; Based on the position information of the transponder and the movement vector of the base station, the original slant range between the transponder and the base station is compensated to obtain the compensated slant range. Extract sound velocity gradient and signal-to-noise ratio parameters, and calculate environmental confidence factor based on sound velocity gradient and signal-to-noise ratio; The first and second horizontal distances between the transponder and the base station are calculated using the depth difference and vertical angle, respectively. The first weight corresponding to the first horizontal distance is determined based on the environmental confidence factor, and the second weight corresponding to the second horizontal distance is determined. The target horizontal distance between the transponder and the base station is calculated based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight.

[0065] The specific implementation of the computer-readable storage medium in this application is largely the same as the specific implementation of the underwater ranging method based on motion state compensation described above, and will not be repeated here.

[0066] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, apparatus, article, or method. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware simulation platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0068] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. An underwater ranging method based on motion state compensation, characterized in that, The method includes: Based on the pre-constructed motion state equations and observation equations of the transponder, the position information of the transponder is determined; Based on the position information of the transponder and the movement vector of the base station, the original slant range between the transponder and the base station is compensated to obtain the compensated slant range. Extract sound velocity gradient and signal-to-noise ratio parameters, and calculate environmental confidence factor based on sound velocity gradient and signal-to-noise ratio; The first and second horizontal distances between the transponder and the base station are calculated using the depth difference and vertical angle, respectively. The first weight corresponding to the first horizontal distance is determined based on the environmental confidence factor, and the second weight corresponding to the second horizontal distance is determined. The target horizontal distance between the transponder and the base station is calculated based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight.

2. The underwater ranging method based on motion state compensation as described in claim 1, characterized in that, The determination of the transponder's position information based on the pre-constructed motion state equations and observation equations includes: Construct motion state equations with the three-dimensional position, three-dimensional velocity, and three-dimensional acceleration of the transponder as state variables; Construct an observation equation using the original slant range, azimuth angle, and elevation angle as the observation quantities; The motion state equation and the observation equation are jointly processed by the extended Kalman filter algorithm to obtain the predicted value of the transponder's state vector at the current moment. The location information of the transponder is extracted from the predicted value.

3. The underwater ranging method based on motion state compensation as described in claim 1, characterized in that, The step of compensating the original slant range between the transponder and the base station based on the transponder's position information and the base station's movement vector to obtain the compensated slant range includes: The displacement of the base station is calculated based on the base station's average velocity, average acceleration, and one-way propagation time of the sound wave. Based on the position vector of the transponder, the position vector of the base station, and the displacement of the base station, the geometric correction term for the signal propagation path is determined; Based on the aforementioned geometric correction term, effective sound velocity, and one-way sound wave propagation time, the compensated slant range is calculated by combining the direction cosine components of the azimuth and elevation angles.

4. The underwater ranging method based on motion state compensation as described in claim 1, characterized in that, The extraction of sound velocity gradient and signal-to-noise ratio parameters, and the calculation of environmental confidence factors based on sound velocity gradient and signal-to-noise ratio, include: Obtain the sound velocity gradient and signal-to-noise ratio; The first environmental influence component is obtained by taking the absolute value of the sound speed gradient and then inputting it into a preset monotonically decreasing nonlinear function. The signal-to-noise ratio is input into a preset monotonically increasing nonlinear function to obtain the second environmental influence component; The environmental confidence factor is calculated based on the first environmental impact component and the second environmental impact component.

5. The underwater ranging method based on motion state compensation as described in claim 1, characterized in that, The calculation of the first horizontal distance and the second horizontal distance between the transponder and the base station using depth difference and vertical angle respectively includes: The depth difference between the transponder and the base station is calculated based on the depth of the transponder and the depth of the base station. The depth difference and the compensated slant distance are then substituted into the Pythagorean theorem formula to calculate the first horizontal distance. Obtain the vertical angle output by the USBL system, wherein the vertical angle is the pitch angle relative to the horizontal plane when the acoustic signal reaches the USBL array; Substituting the vertical angle and the compensated slant distance into the cosine projection formula, the second horizontal distance is calculated.

6. The underwater ranging method based on motion state compensation as described in claim 1, characterized in that, The step of determining the first weight corresponding to the first horizontal distance based on the environmental confidence factor, and determining the second weight corresponding to the second horizontal distance, includes: If the environmental confidence factor is less than the first threshold, the first weight is set to 0 and the second weight is set to 1. If the environmental confidence factor is not less than the first threshold and not greater than the second threshold, then calculate the first estimated variance corresponding to the first horizontal distance and the second estimated variance corresponding to the second horizontal distance, and calculate the first weight and the second weight respectively using the inverse variance weighting method based on the first estimated variance and the second estimated variance. If the environmental confidence factor is greater than the second threshold, set the first weight to 1 and the second weight to 0.

7. The underwater ranging method based on motion state compensation as described in claim 1, characterized in that, The step of calculating the target horizontal distance between the transponder and the base station based on the first horizontal distance, the first weight, the second horizontal distance, and the second weight includes: Multiply the first horizontal distance by the first weight to obtain the first weighted horizontal distance; Multiply the second horizontal distance by the second weight to obtain the second weighted horizontal distance; The first weighted horizontal distance and the second weighted horizontal distance are added together to obtain the target horizontal distance between the transponder and the base station.

8. An underwater ranging device based on motion state compensation, characterized in that, The device includes: The device includes a module that performs the underwater ranging method based on motion state compensation as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor, when executing a program stored in memory, implements the underwater ranging method based on motion state compensation as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the underwater ranging method based on motion state compensation as described in any one of claims 1 to 7.

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