Adaptive refinement method of sound speed profile based on ranging error and in-chord effective area

Abstract

The application belongs to the technical field of sound velocity profile simplification, and discloses a sound velocity profile adaptive refinement method based on ranging error and chord inner effective area, which proposes a new measurement of chord inner area, quantifies the overall bending degree of the local curve by calculating the integral area between the curve segment and the chord, overcomes the defect that the existing method only reflects single-point deviation, and determines the effectiveness of the chord inner area by comparing the chord inner area with a threshold value to drive the adaptive refinement of the profile. On this basis, a closed-loop process driven by precision targets is established, the ranging error set by the user is taken as the input, the area difference threshold value is automatically calculated as the global constraint, the chord inner effective area criterion is used for iterative screening and feedback until the optimal simplified profile meeting the precision requirement is output, so that the leap from fuzzy empirical decision to quantitative target driving is realized, and the drawbacks of the traditional method, such as blind trial of parameters, poor shape preservation, and difficulty in balancing efficiency and precision, are fundamentally avoided.

Description

Technical Field

[0001] This invention belongs to the field of sound velocity profile simplification technology, specifically relating to an adaptive refinement method for sound velocity profiles based on ranging error and effective area within the string. Background Technology

[0002] High-precision underwater positioning is a core technology for marine surveying, resource exploration, and the construction of seabed benchmark networks. Sound waves are currently the only energy carrier capable of effectively propagating over long distances in seawater. Their propagation path strictly follows Snell's Law and is determined by the sound velocity profile (SVP). Therefore, the accuracy of the SVP is crucial to the accuracy of all underwater acoustic positioning systems.

[0003] To obtain high-resolution acoustic ray tracking (SVP), modern measurement equipment such as CTDs and MVPs can be used to collect large amounts of data. However, directly using high-density SVP for acoustic ray tracking calculations leads to a dramatic increase in computational load, severely impacting the real-time performance of positioning solutions. Therefore, efficiently simplifying the SVP while preserving key acoustic features has become a crucial technology for improving the practicality of underwater positioning systems.

[0004] In the field of sound velocity profile simplification, there are two different technical approaches: one based on local geometric judgment and the other based on global accuracy constraints. However, each has its limitations. The limitation of the method based on local geometric judgment is that the criteria are too localized, only reflecting the offset of a single point relative to its neighborhood, and failing to effectively characterize the overall curvature features of the curve segment. Therefore, it is insufficient in preserving the macroscopic gradient structure of the profile. The adaptive stratification method based on area difference constraints starts by controlling the overall simplification error. First, it transforms the maximum permissible ranging error into an allowable SVP area difference threshold. Then, based on experience or oceanographic knowledge, it performs subjective structuring pre-stratification of the profile, such as dividing it into surface layers, mezzanine layers, etc. Finally, it adaptively subdivides each layer using the aforementioned area as a constraint. The limitation of this method is that the stratification process heavily relies on the prior subjective stratification structure and is insufficient in simplifying areas such as the surface layer, exhibiting weak adaptability and environmental generalization. The two existing methods mentioned above provide ideas for SVP simplification from local and global perspectives, respectively, but they still have significant shortcomings in feature fidelity, adaptability, and decision-making basis.

[0005] Existing simplification algorithms for sound velocity profiles still have the following significant limitations: First, it is difficult to balance accuracy and simplification rate. Pursuing a high simplification rate often leads to over-smoothing of key gradient layers, resulting in significant deviations in ray calculations. Second, they lack adaptability; algorithm parameters largely rely on empirical presets, making it difficult to dynamically respond to complex and changing hydrological environments, thus limiting their applicability. Third, they lack decision-making basis; parameter selection lacks quantitative prediction, and the optimization process relies on trial and error, resulting in low efficiency. Summary of the Invention

[0006] The purpose of this invention is to propose an adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord. This method is based on the user's requirements for positioning accuracy. It transforms the maximum permissible ranging error into a calculable geometric constraint and uses the effective area within the chord as a criterion to drive automatic iterative simplification of the profile. Ultimately, it achieves high-efficiency data simplification while ensuring the accuracy of sound ray tracking.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] An adaptive refinement method for sound velocity profile based on ranging error and effective in-chord area includes the following steps:

[0009] Step 1. Calculate the threshold for the difference in sound velocity profile area allowed in the refinement process based on the preset maximum permissible ranging error. ;

[0010] Step 2. Calculate the effective area threshold within the chord based on the initial SVP data. ;

[0011] Step 3. Using the initial SVP data as the refined SVP, a sliding window is used to traverse all interior points except the start and end points. For each current point reached, the corresponding in-chord area is calculated. and judge Is it less than ;

[0012] like Then determine The area is considered invalid, and the current point is removed, while the starting point of the sliding window remains unchanged;

[0013] like Then determine To determine the effective area and retain the current point, update the starting point of the sliding window to the current point;

[0014] After the traversal is complete, the refined SVP is obtained;

[0015] Step 4. Calculate the area difference between the SVP before and after refinement. and judge Is it greater than ;

[0016] like Then reduce by the preset ratio. Then proceed to step 3;

[0017] like Then the refined SVP data will be output.

[0018] Furthermore, based on the adaptive refinement method of sound velocity profile based on ranging error and effective area within the string, this invention also proposes a corresponding adaptive refinement system of sound velocity profile based on ranging error and effective area within the string, the technical solution of which is as follows:

[0019] An adaptive refinement system for sound velocity profiles based on ranging error and effective in-chord area includes:

[0020] The sound velocity profile area difference threshold calculation module is used to calculate the allowable sound velocity profile area difference threshold for the refinement process based on the preset maximum permissible ranging error. ;

[0021] The in-chord effective area threshold calculation module is used to calculate the in-chord effective area threshold based on the initial SVP data. ;

[0022] The adaptive iterative refinement module uses the initial SVP data as the initial SVP before refinement. It employs a sliding window to traverse all interior points except the start and end points, and for each current point reached, it calculates the corresponding in-chord area. and judge Is it less than ;like Then determine This is considered an invalid area, and the current point is removed; the starting point of the sliding window remains unchanged. Then determine To determine the effective area and retain the current point, update the starting point of the sliding window to the current point; after traversal, obtain the refined SVP;

[0023] It also includes a verification feedback and optimal output module for calculating the area difference between the SVP before and after refinement. and judge Is it greater than ;like Then reduce by the preset ratio. And then proceed to the adaptive iterative refinement module; if Then the refined SVP data will be output.

[0024] Furthermore, based on the above-mentioned adaptive refinement method of sound velocity profile based on ranging error and effective area within the string, this invention also proposes a computer device, which includes a memory and one or more processors.

[0025] The memory stores executable code, and when the processor executes the executable code, it implements the steps of the adaptive refinement method for sound velocity profile based on ranging error and effective area within the string, as described above.

[0026] Furthermore, based on the aforementioned adaptive refinement method for sound velocity profile based on ranging error and effective area within the string, this invention also proposes a computer-readable storage medium storing a program thereon; when executed by a processor, this program is used to implement the steps of the aforementioned adaptive refinement method for sound velocity profile based on ranging error and effective area within the string.

[0027] The present invention has the following advantages:

[0028] As described above, this invention discloses an adaptive refinement method for sound velocity profiles based on ranging error and effective area within the chord. This method proposes a new metric, the area within the chord, to quantify the overall curvature of the local curves in the sound velocity profile. This is achieved by calculating the integral area between the curve segment and the chord, overcoming the limitation of existing methods that can only reflect single-point offsets. The method also establishes a closed-loop process driven by accuracy targets. Using the user-defined ranging error as input, it automatically calculates an area difference threshold as a global constraint and uses the effective area within the chord criterion for iterative filtering and feedback until the optimal simplified profile that meets the accuracy requirements is output. This results in a sound velocity profile with higher fidelity and a higher simplification rate under a preset positioning accuracy. Furthermore, this invention constitutes a complete adaptive refinement closed-loop system. Its final output is a highly simplified sound velocity profile optimized and filtered by the effective area within the chord criterion, under the premise of strictly meeting the user's preset positioning accuracy. This system achieves a leap from fuzzy empirical decision-making to quantitative target-driven approaches, fundamentally avoiding the drawbacks of traditional methods such as blind parameter testing, poor shape preservation, and difficulty in balancing efficiency and accuracy. Attached Figure Description

[0029] Figure 1 This is a flowchart of the adaptive refinement method for sound velocity profile based on ranging error and effective area within the string, as described in an embodiment of the present invention.

[0030] Figure 2 This is a schematic diagram of the initial SVP in the geometric definition and iterative screening process of the effective area within the chord in this embodiment of the invention.

[0031] Figure 3 This is a schematic diagram illustrating the geometric definition of the effective area within a chord and the process of retaining internal points in the iterative screening process, as described in this embodiment of the invention.

[0032] Figure 4 This is a schematic diagram illustrating the geometric definition of the effective area within a chord and the process of removing internal points during the iterative screening in this embodiment of the invention.

[0033] Figure 5 This is a schematic diagram of the geometric definition of the effective area within a chord and the refinement of the SVP in the iterative screening process in an embodiment of the present invention. Detailed Implementation

[0034] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0035] Example 1

[0036] Existing methods for simplifying sound velocity profiles generally suffer from three core problems: First, in pursuing a high simplification rate, it is difficult to maintain the structure of the key sound velocity gradient layer, resulting in a decrease in the accuracy of sound field reconstruction; second, the algorithm parameters rely on human experience and cannot adapt to the complex hydrological environment of different sea areas, resulting in weak generalization ability; and third, the simplification process lacks prior performance prediction and quantitative guidance, leading to blind and inefficient parameter tuning.

[0037] To address the aforementioned issues, this invention aims to provide an adaptive refinement method. Its purpose is to offer a method that can adaptively generate the optimal simplified profile directly based on the accuracy requirements of the application. This method establishes an accuracy-geometric constraint mapping and employs innovative local feature criteria to fundamentally solve the challenges of fidelity, adaptability, and decision-making basis during the simplification process, achieving a controllable balance between accuracy and efficiency. Testing shows that this invention can achieve a profile simplification rate of over 87% while accurately depicting the key acoustic channel structure, and improves the computational efficiency of ray tracking by approximately 8 times, effectively solving the problem of balancing accuracy and efficiency in existing technologies.

[0038] To clearly illustrate the method of this invention, the core concepts and models used in this invention will first be introduced.

[0039] Area difference : refers to the area difference between the original sound velocity profile and the simplified sound velocity profile in the depth-sound velocity coordinate system. It is used to measure the overall geometric error caused by simplification.

[0040] Inner surface area : refers to the velocity of sound profile curve, which is formed by any three adjacent points , , A defined local curve segment, connecting the beginning and end points. , The area of ​​the closed region enclosed by a straight line (called a chord). This area value Used to quantify the degree of continuous curvature of a local curve segment.

[0041] Effective area and ineffective area: During the screening process, the area within the chord is compared. With threshold To determine its validity. If The area within the chord is called the effective area, and its corresponding data points are... These are key points characterizing the profile features; if The area within the chord is called the invalid area, and its corresponding point is... These are redundant points.

[0042] The following describes the model for the sound velocity profile. To establish the accuracy mapping relationship, the following model is introduced:

[0043] Background sound velocity profile : refers to the stable sound speed profile in a specific sea area over a short period of time, among which For depth, Indicates depth The background sound velocity value at a given location reflects the basic vertical structure of the sound velocity in the water body in that area.

[0044] Disturbance term : Refers to the instantaneous change in sound velocity superimposed on the background sound velocity profile, caused by ocean dynamic processes (such as internal waves and turbulence) and measurement noise.

[0045] Instantaneous sound speed profile : Refers to the actual observed or calculated sound speed profile at a certain moment, expressed as the sum of the background sound speed profile and the disturbance term. .

[0046] Set of sound velocity profiles of the same cluster : From the same background sound velocity profile A set of instantaneous sound velocity profiles, consisting of different perturbation terms, typically derived from multiple observations within the same sea area and time period, sharing a consistent background structure but exhibiting random or systematic differences; denoted as the set: ,in This represents the total number of sound velocity profiles in the same cluster.

[0047] The method of the present invention is summarized below.

[0048] This invention proposes an adaptive refinement method for sound velocity profile based on ranging error and effective area within the string. Its core lies in constructing an adaptive system driven by task accuracy, with innovative geometric criteria as the execution engine and a closed-loop feedback mechanism. This aims to fundamentally solve the shortcomings of existing methods in terms of fidelity, adaptability, and decision-making basis.

[0049] The specific process is as follows: Figure 1 As shown, the method of this invention consists of three core components, forming a logical closed loop:

[0050] Step 1: Quantitative Mapping of Accuracy Constraints. The user-defined positioning accuracy requirement, i.e., the maximum permissible ranging error, is transformed into a calculable and monitorable global geometric constraint, i.e., the maximum permissible area difference.

[0051] Step 2: Adaptive Iterative Refinement Based on Effective Intrachord Area. Using the global constraints generated in Step 1 as the target, the effective intrachord area proposed in this invention is used as a local feature criterion to dynamically filter and iteratively simplify the original profile.

[0052] Step 3: Verification Feedback and Optimal Output. The simplified result is verified in real time to ensure it meets global constraints. If not, parameters are automatically adjusted and the process iterates again until the optimal profile that simultaneously meets the preset accuracy and high simplification rate requirements is output.

[0053] The entire process achieves intelligent processing from setting accuracy targets to automatically outputting the optimal simplified results.

[0054] The method proposed in this invention will be described in detail below. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the string includes the following steps:

[0055] Step 1. Quantitative mapping from ranging error to area difference constraint: Based on the preset maximum permissible ranging error, calculate the allowable sound velocity profile area difference threshold for the refinement process. .

[0056] The core of step 1 is to determine the maximum permissible ranging error set by the user. The threshold for the difference in sound velocity profile area allowed during the refinement process is calculated in reverse. . Figure 1 The maximum allowable value of the ranging error input is... After calculating the proportionality coefficient The maximum allowable area difference obtained by reverse calculation is... . The specific calculation process is as follows:

[0057] First, it is necessary to determine the linear scaling factor. The process is as follows:

[0058] Data preparation: Obtain a set of sound velocity profiles from the same cluster in the target sea area. Calculate the set of sound velocity profiles within the same cluster for the target sea area. The average profile was used as the background sound velocity profile. The estimated value.

[0059] Calculate the area difference: Calculate the area difference between each sound velocity profile in the same cluster and the background sound velocity profile. .

[0060] Calculate the propagation time difference: Under fixed acoustic transceiver geometry, use a ray tracing algorithm to calculate the sound wave propagation time difference between each sound velocity profile in the same cluster and the background sound velocity profile. .

[0061] Linear fitting: for multiple groups ( , The data is subjected to least-squares linear fitting, and the resulting slope is the scaling factor under the current fixed acoustic transceiver geometry. , Related to the initial glancing angle.

[0062] Then, the reference speed of sound needs to be determined. .

[0063] Specifically, refer to the speed of sound Typically, the weighted average sound velocity of the background sound velocity profile within the relevant water layer range is taken, or a representative sound velocity value is specified according to the specific application scenario.

[0064] Finally, the threshold for the difference in sound velocity profile area is calculated inversely. The process is as follows:

[0065] Based on sound wave propagation time Relationship with distance measurement value and linear relationship Establish ranging error Area difference Direct contact:

[0066] .

[0067] Therefore, the user-preset maximum permissible ranging error can be... Converted to the maximum allowable value of area difference That is, the global constraint threshold:

[0068] .

[0069] Will The threshold for the difference in sound velocity profile area allowed in the refinement process. This is the rigid accuracy constraint target that drives and verifies the entire subsequent adaptive refinement process.

[0070] Step 2. Calculate the effective area threshold within the chord based on the initial SVP data. .

[0071] In step 2, the effective area threshold within the chord is initialized. The process is as follows:

[0072] Based on the initial SVP data, calculate the set of in-chord areas of all points within the original sound velocity profile except for the starting and ending points. }

[0073] Take the set of interior areas of chords { The maximum value in} As the initial internal screening threshold, the initial internal screening threshold is the effective area threshold within the chord. The initial value.

[0074] Step 3. Using the initial SVP data as the refined SVP, a sliding window is used to traverse all interior points except the start and end points. For each current point reached, the corresponding in-chord area is calculated. and judge Is it less than Based on the area inside the string With the threshold of the area inside the chord The comparison results will be used to determine the outcome.

[0075] like Then determine This is considered an invalid area, and the current point is removed; the starting point of the sliding window remains unchanged. Then determine To obtain the effective area, and retaining the current point, update the starting point of the sliding window to the current point; after traversal, obtain the refined SVP.

[0076] This invention proposes a new criterion—the effective area within the chord—and designs an iterative process centered on this criterion. The following is an introduction to the definition and calculation of the core metric of this invention: the area within the chord.

[0077] The area within a string is a continuous, global, local characteristic measure proposed for a sound velocity profile curve. Its geometric definition is: the area between any three adjacent points on the curve. , , The determined local curve segment, and the connection between the beginning and end points. , The area of ​​the closed region enclosed by a straight line (called a chord) is the curve segment's overall curvature, rather than the discrete offset of a single point.

[0078] For the i-th point in the sound speed profile curve Its corresponding depth is The speed of sound is ,in The range of values ​​is , The total number of points on the sound velocity profile curve, i.e., the starting point. and the finish line It is not included in the calculation.

[0079] With point The adjacent data points are the first two data points in the sound speed profile curve. Points and the Points .point The corresponding depth is The speed of sound is .point The corresponding depth is The speed of sound is .

[0080] point Corresponding in-chord area The calculation process is as follows:

[0081] String connection: Connection point With point Get the string ,in For depth:

[0082] .

[0083] Interpolation of local curves: using points Based on the data points before and after it (usually two points before and after, for a total of five points), a smooth local interpolation curve is constructed using cubic spline interpolation. To approximate the original cross-sectional shape with high precision. When When approaching the endpoints of the profile, interpolation is performed using all available neighboring points.

[0084] Calculating area through integration: Calculating local interpolation curves using numerical integration. With string The area of ​​the region between them is used to obtain the point. Corresponding in-chord area :

[0085] .

[0086] The in-chord area used in this invention is an integral measure of the continuous bending shape of a curve, which can more comprehensively and accurately identify and preserve the key gradient structure in the profile, thus solving the limitation of seeing points but not lines.

[0087] This embodiment also includes an adaptive iterative refinement process in step 3, which is a process of dynamically adjusting internal thresholds and gradually approaching global constraints.

[0088] Specifically, for the unrefined SVP, a sliding window is used to traverse all internal points except the start and end points.

[0089] Then, the iteration point selection is performed. For each current point encountered, its corresponding in-chord area is calculated. And based on the area inside the chord With the effective area threshold within the chord The comparison results will be used to determine the outcome.

[0090] The specific elimination condition is: if the area inside the chord corresponding to the current point is... Less than the effective area threshold within the chord ,Right now Then the point is considered The curve segment is close to a straight line; determine the area inside the chord. The area is considered invalid; the current point is a redundant point and is removed, while the starting point of the sliding window remains unchanged.

[0091] The specific retention condition is: if the area inside the chord corresponding to the current point is... Not less than the effective area threshold within the chord ,Right now Then the point is considered The curve segment is significantly curved; determine the area inside the chord. To determine the effective area, the current point is designated as the key point and retained. The starting point of the sliding window is then shifted downwards, meaning the starting point of the sliding window is updated to the current point.

[0092] After traversing all internal points except the starting and ending points, the refined SVP is obtained.

[0093] The above rules ensure that the sliding window always starts from the most recently retained key point, thus coherently traversing and filtering the entire profile, such as... Figures 2 to 5 As shown, the initial SVP is the SVP before refinement, the refined SVP is the SVP after refinement, and the interpolation curve is the local interpolation curve. The baseline is the chord. .

[0094] Step 4. Verification Feedback and Optimal Output: Calculate the area difference between the SVP before and after refinement. and judge Is it greater than .like Then the effective area threshold within the chord is reduced by a preset ratio. Then proceed to step 3. If Then the refined SVP data will be output.

[0095] Step 4 is the core feedback mechanism of the closed-loop system, used to ensure that the simplified results meet the preset global accuracy constraints.

[0096] In this embodiment, step 4 specifically includes:

[0097] First, verify the simplification results. After completing one round of point filtering, a simplified profile (i.e., the refined SVP) is generated, and the overall area difference between it and the original profile (i.e., the unrefined SVP) is calculated. .

[0098] Then, determine whether the constraints are satisfied. If If the global accuracy constraint is met, the process ends, and the final profile, i.e., the refined SVP data, is output. If If the current simplification is excessive and does not meet the accuracy requirements, parameter adjustments are necessary.

[0099] when Feedback and adjustments will be made as needed. The internal filtering threshold will be adjusted accordingly. Reduce by a preset percentage (e.g., 2%), then return to step 3 to perform iterative filtering again. The preferred preset percentage is 2%, i.e., to determine... At that time, the effective area threshold within the chord is set. The reduction of 2% is based on the algorithm's convergence and numerous simulation experiments, ensuring stable approximation of the optimal solution and avoiding iterative oscillations or inefficiency.

[0100] when When the optimal output is obtained, the above process is repeated until the simplified profile of the output satisfies the condition. The final output is a sound velocity profile with a high simplification rate while strictly meeting the accuracy constraints.

[0101] Key points of the method of this invention:

[0102] First, the core criterion proposes a new metric, the area within the chord, to quantify the overall curvature of a local curve in the sound velocity profile. This is achieved by calculating the integral area between the curve segment and the chord, overcoming the limitation of existing methods that can only reflect single-point offsets.

[0103] Second, an adaptive process was established, creating a closed-loop process driven by accuracy targets. Using the user-defined ranging error as input, the system automatically calculates an area difference threshold as a global constraint, and uses the effective area criterion within the chord for iterative filtering and feedback until the optimal simplified profile that meets the accuracy requirements is output.

[0104] The core of this invention lies in a holistic method for adaptively refining the sound velocity profile using the effective area within the chord as a criterion. Its core steps include converting ranging errors into area difference constraints; filtering data points using the effective area within the chord; and using iterative feedback to ensure the simplified result satisfies the constraints.

[0105] In this invention, the criterion calculation adopts a specific method for calculating the effective area within the chord, that is, for points on the curve... Connect its front and back points and Get the string ;use and its neighboring points (As shown in the examples of two points before and two points after) Interpolate the local curve; calculate and The integral area of ​​the region between them.

[0106] The technical advantage of this invention is that, under a given positioning accuracy, a sound velocity profile with higher fidelity and higher simplification is obtained.

[0107] Existing technologies in the field of sound velocity profile simplification suffer from core limitations such as subjective hierarchical frameworks and discrete point criteria, making it difficult to achieve fully automated, closed-loop adaptive optimization directly driven by user accuracy targets without human intervention and while maintaining high fidelity in preserving the macroscopic gradient characteristics of the profile. The effective area criterion within the chord proposed in this invention, along with its closed-loop iterative process aimed at accuracy constraints, fundamentally solves these problems.

[0108] Example 2

[0109] This embodiment 2 describes an adaptive refinement system for sound velocity profile based on ranging error and effective area within the string. This system is based on the same inventive concept as the adaptive refinement method for sound velocity profile based on ranging error and effective area within the string in embodiment 1.

[0110] Specifically, the adaptive refinement system for sound velocity profile based on ranging error and effective area within the string includes the following modules:

[0111] The sound velocity profile area difference threshold calculation module is used to calculate the allowable sound velocity profile area difference threshold for the refinement process based on the preset maximum permissible ranging error. .

[0112] The in-chord effective area threshold calculation module is used to calculate the in-chord effective area threshold based on the initial SVP data. .

[0113] The adaptive iterative refinement module uses the initial SVP data as the initial SVP before refinement. It employs a sliding window to traverse all interior points except the start and end points, and for each current point reached, it calculates the corresponding in-chord area. and judge Is it less than ;like Then determine This is considered an invalid area, and the current point is removed; the starting point of the sliding window remains unchanged. Then determine To obtain the effective area, and retaining the current point, update the starting point of the sliding window to the current point; after traversal, obtain the refined SVP.

[0114] It also includes a verification feedback and optimal output module for calculating the area difference between the SVP before and after refinement. and judge Is it greater than ;like Then reduce by the preset ratio. And then proceed to the adaptive iterative refinement module; if Then the refined SVP data will be output.

[0115] The method of this invention forms a complete adaptive refinement closed-loop system through the series connection of three stages. Its final output is a positioning accuracy that strictly meets the user's preset positioning accuracy (determined by...). Under the premise of ensuring safety, the system achieves a leap from fuzzy empirical decision-making to quantitative target-driven decision-making by optimizing and screening the high-simplification rate sound velocity profile through the effective area criterion within the string. This fundamentally avoids the drawbacks of traditional methods, such as blind parameter testing, poor shape preservation, and difficulty in balancing efficiency and accuracy.

[0116] Tests show that the present invention can achieve a profile simplification rate of over 87% while ensuring the accuracy of ray tracking and positioning, and improves the ray tracking calculation efficiency by more than 8 times, which is significantly better than existing simplification methods.

[0117] It should be noted that, in the adaptive refinement system of sound velocity profile based on ranging error and effective area within the string, the implementation process of the functions and roles of each functional module is detailed in the implementation process of the corresponding steps in the method of Example 1, and will not be repeated here.

[0118] Example 3

[0119] This embodiment 3 describes a computer device that includes a memory and one or more processors.

[0120] The memory stores executable code, which, when executed by the processor, is used to implement the steps of the adaptive refinement method for sound velocity profile based on ranging error and effective area within the string in Embodiment 1 above.

[0121] In this embodiment, the computer device can be any device or apparatus with data processing capabilities, and will not be described in detail here.

[0122] Example 4

[0123] This embodiment 4 describes a computer-readable storage medium storing a program that, when executed by a processor, implements the steps of an adaptive refinement method for sound velocity profiles based on ranging error and effective area within the string.

[0124] The computer-readable storage medium can be an internal storage unit of any device or apparatus with data processing capabilities, such as a hard disk or memory, or an external storage device of any device with data processing capabilities, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc.

[0125] Of course, the above description is only a preferred embodiment of the present invention. The present invention is not limited to the above-described embodiments. It should be noted that any equivalent substitutions or obvious modifications made by those skilled in the art under the guidance of this specification fall within the scope of this specification and should be protected by the present invention.

Claims

1. An adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, characterized in that, Includes the following steps: Step 1. Calculate the threshold for the difference in sound velocity profile area allowed in the refinement process based on the preset maximum permissible ranging error. ; Step 2. Calculate the effective area threshold within the chord based on the initial SVP data. ; Step 3. Using the initial SVP data as the refined SVP, a sliding window is used to traverse all interior points except the start and end points. For each current point reached, the corresponding in-chord area is calculated. and judge Is it less than ; like Then determine The area is considered invalid, and the current point is removed, while the starting point of the sliding window remains unchanged; like Then determine To determine the effective area and retain the current point, update the starting point of the sliding window to the current point; After the traversal is complete, the refined SVP is obtained; Step 4. Calculate the area difference between the SVP before and after refinement. and judge Is it greater than ; like Then reduce by the preset ratio. Then proceed to step 3; like Then the refined SVP data will be output.

2. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, as described in claim 1, is characterized in that... In step 1, the process of determining the linear scaling factor is as follows: Obtain the set of sound velocity profiles of the same cluster in the target sea area. ; Compute set The average profile was used as the background sound velocity profile. The estimated value, of which Indicates depth; Calculate the area difference between each sound velocity profile in the same cluster and the background sound velocity profile. ; With fixed acoustic transceiver geometry, the sound wave propagation time difference between each sound velocity profile in the same cluster and the background sound velocity profile is calculated using a ray tracing algorithm. ; For multiple groups ( , The slope obtained by performing a least-squares linear fit on the data is the linear proportionality coefficient. .

3. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, as described in claim 2, is characterized in that... In step 1, the process of back-calculating the threshold of the sound velocity profile area difference is as follows: Based on sound wave propagation time Relationship with distance measurement value and linear relationship Establish ranging error With area difference The direct connection is: ； in, Indicates the reference speed of sound; The user-preset maximum allowable ranging error Converted to the maximum allowable value of area difference : ； This refers to the threshold of sound velocity profile area difference allowed during the refinement process.

4. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, as described in claim 1, is characterized in that... In step 3, the area inside the chord The calculation process is as follows: For the first in the sound velocity profile curve Points Its corresponding depth is The speed of sound is ;in, The range of values ​​is , This represents the total number of points on the sound velocity profile curve. With point The adjacent data points are the first two data points in the sound speed profile curve. Points and the Points ;point The corresponding depth is The speed of sound is ;point The corresponding depth is The speed of sound is ; Connection point With point Get the string : ； in, For depth; for points Based on the data points before and after it, and multiple adjacent data points, a smooth local interpolation curve is constructed using cubic spline interpolation. ; Calculate the local interpolation curve using numerical integration. With string The area of ​​the region between them is used to obtain the point. Corresponding in-chord area : 。 5. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, as described in claim 1, is characterized in that... In step 2, the effective area threshold within the chord is initialized. The process is as follows: Based on the initial SVP data, calculate the set of in-chord areas of all points within the original sound velocity profile except for the starting and ending points. }; Take the set of interior areas of chords { The maximum value in} As the initial internal screening threshold; The initial internal screening threshold is the effective area threshold within the chord. The initial value.

6. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, as described in claim 1, is characterized in that... In step 3, a sliding window is used to traverse all internal points except the start and end points of the SVP before refinement. For each current point encountered during the traversal, calculate its corresponding area within the chord. And based on the area inside the chord With the effective area threshold within the chord The comparison results will be used to determine the outcome. If the area inside the chord corresponding to the current point Less than the effective area threshold within the chord ,Right now Then determine the area inside the chord. The current point is considered an invalid area and is therefore discarded as a redundant point. The starting point of the sliding window remains unchanged. If the area inside the chord corresponding to the current point Not less than the effective area threshold within the chord ,Right now Then determine the area inside the chord. To determine the effective area, the current point is designated as a key point and retained, and the starting point of the sliding window is updated to the current point. After traversing all internal points except the starting and ending points, the refined SVP is obtained.

7. The adaptive refinement method for sound velocity profile based on ranging error and effective area within the chord, as described in claim 1, is characterized in that... In step 4, the preset ratio is 2%; That is, to judge At that time, the effective area threshold within the chord is set. Reduce by 2% and proceed to step 3.

8. An adaptive refinement system for sound velocity profiles based on ranging error and effective area within a chord, characterized in that, include: The sound velocity profile area difference threshold calculation module is used to calculate the allowable sound velocity profile area difference threshold for the refinement process based on the preset maximum permissible ranging error. ; The in-chord effective area threshold calculation module is used to calculate the in-chord effective area threshold based on the initial SVP data. ; The adaptive iterative refinement module uses the initial SVP data as the initial SVP before refinement. It employs a sliding window to traverse all interior points except the start and end points, and for each current point reached, it calculates the corresponding in-chord area. and judge Is it less than ;like Then determine This is considered an invalid area, and the current point is removed; the starting point of the sliding window remains unchanged. Then determine To determine the effective area and retain the current point, update the starting point of the sliding window to the current point; after traversal, obtain the refined SVP; It also includes a verification feedback and optimal output module for calculating the area difference between the SVP before and after refinement. and judge Is it greater than ;like Then reduce by the preset ratio. And then proceed to the adaptive iterative refinement module; if Then the refined SVP data will be output.

9. A computer device comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that, When the processor executes the executable code, it implements the steps of the adaptive refinement method for sound velocity profile based on ranging error and effective area within the string as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the adaptive refinement method for sound velocity profile based on ranging error and effective area within the string as described in any one of claims 1 to 7.

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