A scene-adaptive optimal preset sounding depth determination method for a sonar

Abstract

The present application belongs to the field of underwater acoustic engineering and sonar detection technology, and discloses a scene-adaptive sonar optimal preset listening depth determination method. According to the target quantity, the application scene is divided into three categories. For the no-target scene, the optimal preset listening depth is selected by calculating the full-azimuth propagation loss and counting the effective coverage rate. For the single-target scene, the optimal preset listening depth is selected by directly calculating the propagation loss of the target on the path to different depths. For the multi-target scene, the optimal preset listening depth is selected by comprehensively considering the propagation loss of multiple targets. The present application automatically identifies the no-target / single-target / multi-target scene based on the target quantity and switches the calculation strategy, eliminating the dependence on artificial experience and unified strategy. In the no-target scene, the present application introduces full-azimuth propagation loss calculation and effective coverage rate evaluation, and establishes the optimal preset listening depth selection on the global space coverage capability rather than single-azimuth evaluation.

Description

Technical Field

[0001] This invention belongs to the field of underwater acoustic engineering and sonar detection technology, and specifically relates to a scene-adaptive method for determining the optimal preset listening depth of sonar. Background Technology

[0002] In tasks such as monitoring marine environmental background noise, detecting underwater targets, and conducting marine communications, sonar listening equipment typically needs to be pre-positioned at a specific depth to obtain optimal signal quality or detection performance. When sound waves propagate in the ocean, they are affected by factors such as diffusion, absorption, seabed reflection, and refraction. The variation in sound intensity with distance and depth can be described by transmission loss (TL). The detectable range of a sonar system is usually measured by the figure of merit (FOM), which is the maximum allowable transmission loss for detecting a target. Because sound velocity profiles, seabed topography, and seabed composition vary significantly with different sea areas, sound propagation conditions differ markedly at different depths. Therefore, the selection of the pre-positioned listening depth directly determines the overall detection capability of the sonar.

[0003] There are two main types of existing methods for determining the preset listening depth of sonar. One type relies on the experience of the operators or a simplified lookup table method, directly assigning the preset listening depth based on the sea area type and mission nature. The other type, while introducing sound field propagation models (such as ray models and normal mode models) for auxiliary calculations, generally only calculates the propagation loss in a single azimuth or a few azimuth angles, and selects the optimal depth accordingly. Both of these methods are widely used in actual deployment.

[0004] However, the above two methods still have the following shortcomings in practical applications: (1) They rely on manual experience or fixed table lookup, lack objective and quantitative selection criteria, and different personnel or different sub-tasks may give inconsistent suggestions on the preset listening depth; (2) They only evaluate the sound propagation characteristics at a limited azimuth angle and do not consider the spatial differences in the entire range (affected by the sound velocity profile, seabed topography and seabed sediment with azimuth changes), and the selected depth may not be optimal in the overall coverage area; (3) They adopt a uniform calculation strategy for all tasks and do not distinguish the characteristics of different operation scenarios such as no target, single target and multiple targets, which leads to inaccurate selection of the optimal preset listening depth in a specific scenario, thereby affecting the detection performance of sonar.

[0005] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art. Summary of the Invention

[0006] To address the problems in existing technologies, such as the reliance on human experience in selecting the optimal preset listening depth for sonar, the limited assessment without considering the spatial variability of omnidirectional sound propagation, and the lack of adaptability to different mission scenarios, this invention proposes a scenario-adaptive method for determining the optimal preset listening depth for sonar. This method aims to objectively and quantitatively determine the optimal preset listening depth, thereby improving the detection performance of sonar systems in different marine environments and application scenarios.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A scene-adaptive method for determining the optimal preset listening depth of sonar includes the following steps: Step 1. Obtain the number of targets, target locations, depth list, and environmental parameters; Step 2. Determine the scene type based on the target quantity, and calculate the optimal preset listening depth using different strategies; When the number of targets is 0, proceed to step 3 to perform calculations for the no-target scenario; when the number of targets is 1, proceed to step 4 to perform calculations for the single-target scenario; when the number of targets is greater than 1, proceed to step 5 to perform calculations for the multi-target scenario. Step 3. Traverse the depth list, calculate the omnidirectional propagation loss for each depth within the approximate target range, convert it into a two-dimensional grid, truncate the propagation loss TL using the quality factor, and calculate the effective coverage. The depth with the highest effective coverage is selected as the optimal preset listening depth in the targetless scenario; Step 4. Traverse the depth list, calculate the propagation loss value from the target to each depth position, compare the propagation loss values ​​at each depth, and select the depth with the smallest propagation loss value as the optimal preset listening depth for a single target scene. Step 5. Traverse the depth list, calculate the propagation loss value from all targets at different depths to the sonar acquisition device, combine the propagation loss values ​​of multiple targets, and determine the optimal preset listening depth in a multi-target scenario.

[0008] Furthermore, based on the aforementioned scene-adaptive sonar optimal preset listening depth determination method, this invention also proposes a corresponding scene-adaptive sonar optimal preset listening depth determination system, which adopts the following technical solution: A scene-adaptive sonar optimal preset listening depth determination system includes the following modules: The preprocessing module is used to obtain the number of targets, target locations, depth list, and environmental parameters; The scene type determination module is used to determine the scene type based on the number of targets; When the number of targets is 0, enter the targetless scene calculation module; when the number of targets is 1, enter the single-target scene calculation module; when the number of targets is greater than 1, enter the multi-target scene calculation module. The targetless scene calculation module is used to traverse the depth list, calculate the omnidirectional propagation loss of each depth within the approximate range of the target, convert it into a two-dimensional grid, truncate the propagation loss TL with a quality factor, and calculate the effective coverage. The depth with the highest effective coverage is selected as the optimal preset listening depth in the targetless scenario; The single-target scene calculation module is used to traverse the depth list, calculate the propagation loss value from the target to each depth position, compare the propagation loss values ​​at each depth, and select the depth with the smallest propagation loss value as the optimal preset listening depth for the single-target scene. The multi-target scene calculation module is used to traverse the depth list, calculate the propagation loss value from all targets at different depths to the sonar acquisition device, and combine the propagation loss values ​​of multiple targets to determine the optimal preset listening depth in the multi-target scene.

[0009] Furthermore, based on the aforementioned scenario-adaptive sonar optimal preset listening depth determination method, this invention also proposes a computer device, which includes a memory and one or more processors.

[0010] The executable code is stored in memory. When the processor executes the executable code, it implements the steps of the above-described scenario-adaptive sonar optimal preset listening depth determination method.

[0011] Furthermore, based on the above-mentioned scenario-adaptive sonar optimal preset listening depth determination method, this invention also proposes a computer-readable storage medium storing a program that, when executed by a processor, implements the steps of the above-mentioned scenario-adaptive sonar optimal preset listening depth determination method.

[0012] The present invention has the following advantages: As described above, this invention discloses a scene-adaptive method for determining the optimal preset listening depth of sonar. This method categorizes application scenarios into three types (no target, single target, and multiple target) based on the number of targets, and designs differentiated optimal preset listening depth determination methods for each scenario. For no-target scenarios, the optimal preset listening depth is selected by calculating omnidirectional propagation loss and statistically analyzing effective coverage. For single-target scenarios, the optimal preset listening depth is selected by directly calculating the propagation loss along different depth paths from the target. For multiple-target scenarios, the optimal preset listening depth is selected by comprehensively considering the propagation loss of multiple targets. This method can adapt to different scenarios and improve the accuracy of sonar preset listening depth. This invention utilizes a scene-adaptive mechanism that automatically identifies no-target / single-target / multi-target scenarios and switches calculation strategies based on the number of targets, eliminating reliance on human experience and uniform strategies. In no-target scenarios, omnidirectional propagation loss calculation and effective coverage evaluation are introduced, establishing the selection of the optimal preset listening depth based on full-domain spatial coverage capability rather than a single-directional evaluation. Furthermore, two optimization modes are proposed for multi-target scenarios: overall optimal and key target optimal, balancing overall detection performance with the protection of critical targets. In addition, since the inputs to this invention are all conventional marine environmental parameters and equipment parameters, it can be directly integrated into existing sonar deployment assistance systems. Attached Figure Description

[0013] Figure 1 This is a flowchart of the scene-adaptive sonar optimal preset listening depth determination method in an embodiment of the present invention; Figure 2 This is a schematic diagram of the sound velocity profile; Figure 3 Diagram illustrating the propagation loss; Figure 4 A schematic diagram showing the detectable range of a specified FOM (FOM=90); Figure 5 This is a schematic diagram illustrating the various application scenarios targeted by the present invention; Figure 6 This is a calculation of the propagation loss of a single sector in an embodiment of the present invention; Figure 7 This is a schematic diagram of the sector propagation loss curve in an embodiment of the present invention; Figure 8 This is an omnidirectional propagation loss diagram in an embodiment of the present invention; Figure 9 This is a schematic diagram illustrating the calculation of single-target propagation loss in an embodiment of the present invention. Detailed Implementation

[0014] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: Glossary Sound Speed ​​Profile (SSP): A curve showing the distribution of sound speed with depth in seawater; it is a key environmental parameter for sonar performance calculations. For example... Figure 2 As shown, the horizontal axis represents the speed of sound, and the vertical axis represents depth.

[0015] The sound velocity profiles vary significantly across different sea areas.

[0016] Transmission Loss (TL): The attenuation of sound intensity as a sound wave propagates in water due to diffusion, absorption, and other factors, measured in dB. Figure 3 As shown, the sound intensity gradually decreases as the distance increases from the sound source.

[0017] Figure of Merit (FOM): A metric that measures the overall performance of a sonar system, representing the maximum permissible propagation loss at which the sonar can detect a target. A higher FOM value indicates better sonar detection performance.

[0018] like Figure 4 As shown, the FOM (Form of Memory) determines the detectable range of a sonar (within...). Figure 4 In the diagram, FOM is 90, and areas with values ​​less than FOM are filled in yellow, representing the audible area.

[0019] Bathymetry (BTY): Data on how seabed depth varies with geographical location, used to describe the undulating shape of the seabed. Bathymetry affects the reflection and refraction of sound waves and is an important environmental parameter for sound propagation calculations.

[0020] Seabed Type (BRC): The physical properties of the seabed substrate, such as sand, mud, and rock. Different substrate types have different absorption and reflection characteristics for sound waves, affecting the calculation of sound propagation loss.

[0021] Example 1 To address the problems of existing methods for selecting the optimal preset listening depth of sonar, which rely on manual experience or fixed table lookups, only evaluate in a limited azimuth without fully considering the spatial variability of sound propagation in all directions, and lack adaptability to different task scenarios, this invention provides an objective, quantitative method for calculating the optimal preset listening depth of sonar that can automatically adapt to the scenario.

[0022] Before introducing the method of this invention, the various application scenarios targeted by this invention will be described first, such as... Figure 5 As shown: No-goal scenario: No clear (specific) goal, such as Figure 5 As shown in (a); Single-target scenario: There is only one target in the environment, such as Figure 5As shown in (b); Multi-object scenario: There are multiple objects in the environment, such as Figure 5 As shown in (c).

[0023] In the appendix Figure 5 In the diagram, the small circle in the center represents the sonar acquisition device, and the triangle represents the surface vessel, i.e., the target. For the aforementioned multiple application scenarios, this invention designs an optimal preset sonar listening depth calculation method adapted to different scenarios.

[0024] like Figure 1 As shown, the scene-adaptive sonar optimal preset listening depth determination method in this embodiment includes the following steps: Step 1. Obtain target parameters, equipment parameters, environmental parameters, and calculation parameters; Step 1.1. Obtain the target parameters.

[0025] In single-target or multi-target scenarios, the number of targets is provided. Used to determine the scene type; single target. When there are multiple targets Target location ,in , indicating the first The three-dimensional coordinates of the target.

[0026] No target scenario Provides the approximate location of the target, i.e., the approximate location to be covered: including distance. Unit: m.

[0027] Step 1.2. Obtain device parameters.

[0028] Coordinates of the sonar listening equipment location: ,in To determine the preset listening depth for the current hypothesis, select from the list of preset listening depths for the hypothesis. Selected from, i.e. , , This assumes a preset number of listening depths.

[0029] High-quality factors: , in dB, represents the maximum permissible propagation loss that sonar can detect a target.

[0030] Step 1.3. Obtain environmental parameters.

[0031] sound speed profile , is used to describe the distribution of sound speed as a function of depth.

[0032] Seabed topography This is data used to describe how seabed depth varies with location.

[0033] Substrate type It is used to describe the physical properties of seabed sediment.

[0034] Step 1.4. Obtain the calculation parameters.

[0035] Receive distance array : The minimum value is The maximum value is Step size is Number of sampling points for: .

[0036] Angular resolution: , unit: degrees, used to determine the precision of azimuth calculation.

[0037] Grid spacing: , Unit: m, usually taken as The resolution is determined by a preset value and is used for the Cartesian grid division in step 3.5 below. In this embodiment... m.

[0038] Step 2. Determine the scene type based on the target quantity, and use different strategies to calculate the optimal preset listening depth.

[0039] When the number of targets is 0, proceed to step 3 to enter the calculation of the no-target scenario; when the number of targets is 1, proceed to step 4 to enter the calculation of the single-target scenario; when the number of targets is greater than 1, proceed to step 5 to enter the calculation of the multi-target scenario.

[0040] Automatic branching based on the target number eliminates the need for manual depth setting, reducing reliance on experience and providing strong adaptability.

[0041] Step 3. Calculation of the targetless scenario ( ).

[0042] Traverse the depth list, calculate the omnidirectional propagation loss for each depth within the target approximation range, convert it into a two-dimensional grid, truncate the propagation loss TL using a quality factor, and calculate the effective coverage.

[0043] The depth with the highest effective coverage is selected as the optimal preset listening depth (i.e., the optimal depth) in the targetless scenario.

[0044] Step 3.1. Azimuth initialization; According to angular resolution Determine the number of azimuth angles and their values ​​for calculation; sector azimuth angle sequence. for: ; in, , .

[0045] Step 3.2. Calculation of propagation loss on a single sector.

[0046] Define a function to calculate propagation loss, such as Figure 6 The diagram illustrates the calculation of propagation loss on a single sector. The calculation of propagation loss on a single sector uses a sound field propagation model (generally a ray calculation model).

[0047] The input parameters for the sound field propagation model are: Sound source depth: That is, the current assumption is the preset listening depth; Receive depth: The receiving depth is equal to the sound source depth; Receive distance array: ; Azimuth: From the sector azimuth sequence Selected from; Sound velocity profile: ; Seabed topography: ; Substrate type: ; The output of the sound field propagation model is at a specified depth. Azimuth The propagation loss curve below , for the receiving distance array One-dimensional arrays of equal length : .

[0048] in Horizontal distance The propagation loss value at the location, For example, the propagation loss curve of a certain sector is shown below (distance unit: m, propagation loss unit: dB). Table 1 and Figure 7 As shown.

[0049] Table 1. Propagation loss curve values

[0050] Step 3.3. Calculation of all-round propagation loss.

[0051] Traversing the sector azimuth sequence The function for calculating the propagation loss of a single sector is called for each azimuth angle.

[0052] Seabed topography According to azimuth The direction is obtained by reading the corresponding topographic profile data from the digital nautical chart to determine the sound source depth. The multi-sector propagation loss matrix, expressed in polar coordinates, is as follows: ; in Represent each depth in polar coordinates. Multi-sector propagation loss.

[0053] in Horizontal distance, unit: meters. The azimuth angle is expressed in degrees. Both are continuous independent variables and can take any value within the calculation range. For distance from sampling point, The azimuth angle of the sector. This represents the number of sampling points. This represents the number of sectors.

[0054] Step 3.4. Depth-first traversal calculation.

[0055] For the hypothetical pre-set listening depth list Each depth in Repeat steps 3.2 and 3.3 to obtain the multi-sector propagation loss set at all depths. : .

[0056] Step 3.5. Convert polar coordinates to Cartesian grid.

[0057] For each depth output in step 3.4 Multi-sector propagation loss From polar coordinates Convert to Cartesian coordinates The uniform mesh below, i.e., the three-dimensional propagation loss mesh .

[0058] The purpose of this is to visualize the sonar coverage as a flat map, making it easier to calculate the effective coverage rate.

[0059] The specific process of step 3.5 is as follows: Step 3.5.1. Establish a Cartesian uniform grid.

[0060] A two-dimensional uniform grid is established within the target coverage area, with the sound source location as the origin.

[0061] Let the grid spacing be , (Determined by the preset resolution, usually taken as...) Then the grid coverage area is The number of grid points is , .

[0062] Grid points The coordinates are: .

[0063] in , .

[0064] Step 3.5.2. Polar coordinate transformation.

[0065] For each grid point Calculate its corresponding polar coordinates That is, the distance of that point relative to the sound source. and azimuth The formula is expressed as follows: ; ; The mod operation converts the return value of atan2 to... The range is consistent with the sector azimuth sequence.

[0066] like This means that the grid point is outside the calculation range of the propagation loss data, and the received distance array... The upper limit does not exceed If so, it will be directly judged as unaudible, and... Take greater than The value is determined and subsequent interpolation calculations are skipped; Otherwise, continue with the following steps.

[0067] Step 3.5.3. Azimuth interpolation; Since the calculations are performed at discrete azimuth angles, and grid points may be located between two calculated azimuth angles, it is necessary to obtain the propagation loss curve at that azimuth angle through interpolation.

[0068] according to In the sector azimuth sequence The azimuth angles of two adjacent sectors are located in the center.

[0069] when or At this time, azimuth angle wrapping is required (because) and (They are in the same direction), take , Otherwise, the positioning is satisfied. Adjacent sector azimuth angles and ;

[0070] The azimuth angle is obtained through linear interpolation. Propagation loss curve at the location : ; in , They represent the azimuth angles respectively. and The propagation loss curve at the location.

[0071] Step 3.5.4. Distance dimension interpolation.

[0072] The propagation loss curve obtained by interpolation Above, according to Find two adjacent distance sampling points and ,satisfy The final propagation loss value is obtained through linear interpolation. : ; in , These represent the distances from the sampling points. and The propagation loss value at the location.

[0073] Step 3.5.5. Traverse all depths Repeat the above process to obtain the three-dimensional propagation loss mesh. .

[0074] like Figure 8 The diagram shows the omnidirectional propagation loss calculated by this invention.

[0075] Step 3.6. Calculate the effective coverage area.

[0076] Use high-quality factors For propagation loss grid Filter: Preservation propagation loss less than or equal to Remove grid points larger than The grid points are selected; the proportion of remaining grid points after filtering to the total number of grid points is the effective coverage at that depth. : ; in To meet The number of grid points, This represents the total number of grid points.

[0077] Of course, in this embodiment, in addition to using the FOM threshold to truncate the detectable range, the coverage capability criterion can also use the detection probability or signal-to-noise ratio distribution as the coverage evaluation standard to adapt to different performance evaluation needs.

[0078] Step 3.7. Select the depth with the highest effective coverage as the optimal preset listening depth. The formula is as follows: .

[0079] This invention uses a quantitative approach to select the optimal coverage area based on omnidirectional propagation loss and effective coverage rate, avoiding biases in unidirectional assessments and ensuring objective and accurate selection. Furthermore, the use of Cartesian gridding makes coverage visible, statistically verifiable, intuitive, and easy to interpret, facilitating review and decision-making.

[0080] Step 4. Single-target scene calculation ( ).

[0081] Traverse the depth list, calculate the propagation loss value from the target to each depth position, compare the propagation loss values ​​at each depth, and select the depth with the smallest propagation loss value as the optimal preset listening depth for a single target scene. In this single-objective scenario It is calculated directly from the target location coordinates and the sonar location coordinates, without the need for separate specification.

[0082] Distance in this scene It is directly calculated from the target's location coordinates and the sonar's location coordinates; Step 4.1. Define the single-point propagation loss calculation function, and its calculation process is as follows: Figure 9 As shown, the single-point propagation loss calculation function is a sound field propagation model (generally a ray propagation model), and the input parameters of the sound field propagation model are: Target location coordinates: (Consistent with the definition in step 1,) hour, ).

[0083] Coordinates of the sonar listening equipment location: ; Sound velocity profile: ; Seabed topography: ; Substrate type: ; The function for calculating single-point propagation loss outputs the single-point propagation loss value. .

[0084] Step 4.2. Traverse the hypothetical pre-defined listening depth list Each depth in The propagation loss calculation function at each single point is called to obtain the propagation loss value at each depth. .

[0085] Step 4.3. Select the depth with the minimum propagation loss as the optimal preset listening depth. : .

[0086] Step 5. Multi-objective scene calculation ( ).

[0087] Traverse the depth list, calculate the propagation loss value from all targets at different depths to the sonar acquisition device, and combine the propagation loss values ​​of multiple targets to determine the optimal preset listening depth in a multi-target scenario.

[0088] In this multi-target scenario, distance Take the maximum distance among all targets, that is: This is used to determine the range of propagation loss calculation.

[0089] Step 5.1. Construct the propagation loss matrix.

[0090] Traverse the hypothetical pre-defined listening depth list Each depth in For each target , The single-point propagation loss calculation function defined in step 4 is called to calculate the propagation loss value of each target at that depth, thus obtaining the propagation loss matrix. : ; in, Indicates depth Next goal The propagation loss value.

[0091] Step 5.2. Optimal preset listening depth selection. This embodiment supports two calculation modes.

[0092] The first method uses a row-based calculation model (overall optimal) to determine the optimal preset listening depth.

[0093] Propagation loss matrix For each row, representing each depth, calculate the sum of the propagation loss for all targets at that depth: ; Choose the sum of propagation losses The minimum depth is used as the optimal preset listening depth. : .

[0094] Of course, this embodiment can also use column calculation mode (optimal for key targets) to determine the optimal preset listening depth.

[0095] The optimal preset listening depth is determined using a column-based calculation method, as shown in the following formula: Propagation loss matrix For each column representing each target, calculate the sum of the propagation loss for that target across all depths: ; Choose the sum of propagation losses The smallest target is the key target. : ; Then, among the propagation loss values ​​at various depths for the target, the depth corresponding to the minimum value is selected as the optimal preset listening depth. : ; in Indicate key objectives In depth The propagation loss value at the location.

[0096] It supports overall optimization or optimization of key objectives in multi-objective scenarios, adapts to different task focuses, and is flexibly configurable.

[0097] Of course, the sound field propagation model can also be replaced by any calculation model such as normal wave or parabolic equation. Different models have their own advantages in accuracy and efficiency under different marine environments (shallow / deep sea, low frequency / high frequency), and can be selected according to actual conditions.

[0098] Example 2 This embodiment 2 describes a scene-adaptive sonar optimal preset listening depth determination system, which is based on the same inventive concept as the scene-adaptive sonar optimal preset listening depth determination method in embodiment 1 above.

[0099] The scene-adaptive sonar optimal preset listening depth determination system described in Embodiment 2 includes the following modules: The preprocessing module is used to obtain target parameters, equipment parameters, environmental parameters, and calculation parameters; The scene type determination module is used to determine the scene type based on the number of targets; When the number of targets is 0, enter the targetless scene calculation module; when the number of targets is 1, enter the single-target scene calculation module; when the number of targets is greater than 1, enter the multi-target scene calculation module. The targetless scene calculation module is used to traverse the depth list, calculate the omnidirectional propagation loss of each depth within the approximate range of the target, convert it into a two-dimensional grid, truncate the propagation loss TL with a quality factor, and calculate the effective coverage. The depth with the highest effective coverage is selected as the optimal preset listening depth in the targetless scenario; The single-target scene calculation module is used to traverse the depth list, calculate the propagation loss value from the target to each depth position, compare the propagation loss values ​​at each depth, and select the depth with the smallest propagation loss value as the optimal preset listening depth for the single-target scene. The multi-target scene calculation module is used to traverse the depth list, calculate the propagation loss value from all targets at different depths to the sonar acquisition device, and combine the propagation loss values ​​of multiple targets to determine the optimal preset listening depth in the multi-target scene.

[0100] It should be noted that any content not mentioned in the above-described functional modules of the system described in Embodiment 2 can be referred to the step description of the corresponding method in Embodiment 1 above, and will not be repeated in detail here.

[0101] Example 3 This embodiment 3 describes a computer device including a memory and one or more processors. Executable code is stored in the memory. When the processor executes the executable code, it implements the steps of the scene-adaptive sonar optimal preset listening depth determination method described in embodiment 1 above.

[0102] In this embodiment, the computer device can be any device or apparatus with data processing capabilities, and will not be described in detail here.

[0103] Example 4 This embodiment 4 describes a computer-readable storage medium storing a program that, when executed by a processor, implements the steps of the scene-adaptive sonar optimal preset listening depth determination method in embodiment 1 above.

[0104] 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.

[0105] 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. A scene-adaptive method for determining the optimal preset listening depth of sonar, characterized in that, Includes the following steps: Step 1. Obtain the number of targets, target locations, depth list, and environmental parameters; Step 2. Determine the scene type based on the target quantity, and calculate the optimal preset listening depth using different strategies; When the number of targets is 0, proceed to step 3 to enter the calculation of the no-target scenario; when the number of targets is 1, proceed to step 4 to enter the calculation of the single-target scenario; when the number of targets is greater than 1, proceed to step 5 to enter the calculation of the multi-target scenario. Step 3. Traverse the depth list, calculate the omnidirectional propagation loss for each depth within the approximate target range, convert it into a two-dimensional grid, truncate the propagation loss TL using the quality factor, and calculate the effective coverage. The depth with the highest effective coverage is selected as the optimal preset listening depth in the targetless scenario; Step 4. Traverse the depth list, calculate the propagation loss value from the target to each depth position, compare the propagation loss values ​​at each depth, and select the depth with the smallest propagation loss value as the optimal preset listening depth for a single target scene. Step 5. Traverse the depth list, calculate the propagation loss value from all targets at different depths to the sonar acquisition device, combine the propagation loss values ​​of multiple targets, and determine the optimal preset listening depth in a multi-target scenario.

2. The scene-adaptive sonar optimal preset listening depth determination method according to claim 1, characterized in that, Step 1 specifically involves: Step 1.

1. Obtain the target parameters; No target scenario, i.e., number of targets Provides approximate location of the target: including distance ; In single-target or multi-target scenarios, the number of targets is provided. Used to determine the scene type; single target. When there are multiple targets Target location ,in , indicating the first The three-dimensional coordinates of the target; Step 1.

2. Obtain device parameters; Coordinates of the sonar listening device location: ,in To determine the preset listening depth for the current hypothesis, select from the list of preset listening depths for the hypothesis. Selected from, i.e. , , Assuming a preset number of listening depths; High-quality factors: The unit is dB, which represents the maximum permissible propagation loss that sonar can detect. Step 1.

3. Obtain environmental parameters; sound speed profile , used to describe the distribution of sound speed with depth; Seabed topography , used to describe the variation of seabed depth with location; Substrate type Used to describe the physical properties of seabed sediment; Step 1.

4. Obtain the calculation parameters; Receive distance array : The minimum value is The maximum value is Step size is Number of sampling points for: ; Angular resolution: Unit: degrees; used to determine the precision of azimuth calculation. Grid spacing: , , unit: m, used for dividing Cartesian grids.

3. The scene-adaptive sonar optimal preset listening depth determination method according to claim 2, characterized in that, Step 3 specifically involves: Step 3.

1. Azimuth initialization; According to angular resolution Determine the number of azimuth angles and their values ​​for calculation; sector azimuth angle sequence. for: ； in, , ; Step 3.

2. Calculation of propagation loss on a single sector; Prepare the propagation loss calculation function, with the following input parameters: Sound source depth: That is, the current assumption is the preset listening depth; Receive depth: The receiving depth is equal to the sound source depth; Receive distance array: ; Azimuth: From the sector azimuth sequence Selected from; Sound velocity profile: ; Seabed topography: ; Substrate type: ; The output of the propagation loss calculation function is at a specified depth. Azimuth The propagation loss curve below , for the receiving distance array One-dimensional arrays of equal length : ; in Horizontal distance The propagation loss value at the location, ; Step 3.

3. Calculation of all-around propagation loss; Traversing the sector azimuth sequence Call the single-sector propagation loss calculation function for each azimuth angle; Seabed topography According to azimuth The direction is obtained by reading the corresponding topographic profile data from the digital nautical chart to determine the sound source depth. The multi-sector propagation loss matrix, expressed in polar coordinates, is as follows: ； in Represent each depth in polar coordinates. Multi-sector propagation loss; in Horizontal distance, unit: meters. Azimuth, unit: degrees. , It is a continuous independent variable, taking any value within the calculation range; For distance from sampling point, The azimuth angle of the sector. This represents the number of sampling points. Number of sectors; Step 3.

4. Depth-first traversal calculation; For the hypothetical pre-set listening depth list Each depth in Repeat steps 3.2 and 3.3 to obtain the multi-sector propagation loss set at all depths. : ； Step 3.

5. Convert polar coordinates to Cartesian grid; For each depth output in step 3.4 Multi-sector propagation loss From polar coordinates Convert to Cartesian coordinates The uniform mesh below, i.e., the three-dimensional propagation loss mesh ; Step 3.

6. Calculate the effective coverage area; Use high-quality factors For propagation loss grid Filter: Preservation propagation loss less than or equal to Remove grid points larger than The grid points are selected; the proportion of remaining grid points after filtering to the total number of grid points is the effective coverage at that depth. : ； in To meet The number of grid points, This represents the total number of grid points; Step 3.

7. Select the depth with the highest effective coverage as the optimal preset listening depth. The formula is as follows: 。 4. The scene-adaptive sonar optimal preset listening depth determination method according to claim 3, characterized in that, Step 3.5 specifically involves: Step 3.5.

1. Establish a Cartesian uniform grid; A two-dimensional uniform grid is established within the target coverage area, with the sound source location as the origin; the grid spacing is set to . , The grid coverage area is The number of grid points is , ; Grid points The coordinates are: ; in , ; Step 3.5.

2. Polar coordinate transformation; For each grid point Calculate its corresponding polar coordinates That is, the distance of that point relative to the sound source. and azimuth The formula is expressed as follows: ； ； The mod operation converts the return value of atan2 to... The range is consistent with the sector azimuth sequence; like If so, it will be directly judged as unaudible, and... Take greater than If the value is not found, skip the subsequent interpolation calculations; otherwise, continue with the following steps. Step 3.5.

3. Azimuth interpolation; The propagation loss curve at this azimuth angle is obtained by interpolation, and the specific process is as follows: according to In the sector azimuth sequence The azimuth angles of two adjacent sectors are located in the center; when or At this time, azimuth angle wrapping processing is required, and the following steps are taken: , ; Otherwise, the positioning is satisfied. Adjacent sector azimuth angles and ; The azimuth angle is obtained through linear interpolation. Propagation loss curve at the location : ； in , They represent the azimuth angles respectively. and The propagation loss curve at the location; Step 3.5.

4. Distance dimension interpolation; The propagation loss curve obtained by interpolation Above, according to Find two adjacent distance sampling points and ,satisfy The final propagation loss value is obtained through linear interpolation. : ； in , These represent the distances from the sampling points. and The propagation loss value at the location; Step 3.5.

5. Traverse all depths Repeat the above process to obtain the three-dimensional propagation loss mesh. .

5. The scene-adaptive sonar optimal preset listening depth determination method according to claim 2, characterized in that, Step 4 specifically involves: Distance in this scene It is directly calculated from the target's location coordinates and the sonar's location coordinates; Step 4.

1. Prepare the single-point propagation loss calculation function, whose input parameters are: Target location coordinates: ; Coordinates of the sonar listening device location: ; Sound velocity profile: ; Seabed topography: ; Substrate type: ; The output of the single-point propagation loss calculation function is the single-point propagation loss value. ; Step 4.

2. Traverse the hypothetical pre-defined listening depth list Each depth in The propagation loss calculation function at each single point is called to obtain the propagation loss value at each depth. ; Step 4.

3. Select the depth with the minimum propagation loss as the optimal preset listening depth. : 。 6. The scene-adaptive sonar optimal preset listening depth determination method according to claim 2, characterized in that, Step 5 specifically involves: In this multi-target scenario, distance Take the maximum distance among all targets, that is: ； Step 5.

1. Construct the propagation loss matrix; Traverse the hypothetical pre-defined listening depth list Each depth in For each target , Using the single-point propagation loss calculation function, the propagation loss value of each target at that depth is calculated, and the propagation loss matrix is ​​obtained. : ； in, Indicates depth Next goal The propagation loss value; Step 5.

2. Determine the optimal preset listening depth using the row calculation mode; Propagation loss matrix For each row, representing each depth, calculate the sum of the propagation loss for all targets at that depth: ； Choose the sum of propagation losses The minimum depth is used as the optimal preset listening depth. : 。 7. The scene-adaptive sonar optimal preset listening depth determination method according to claim 5, characterized in that, Step 5.2 is replaced by determining the optimal preset listening depth using a column calculation mode, as shown in the following formula: Propagation loss matrix For each column representing each target, calculate the sum of the propagation loss for that target across all depths: ； Choose the sum of propagation losses The smallest target as the key target : ； Then, among the propagation loss values ​​at various depths for the target, the depth corresponding to the minimum value is selected as the optimal preset listening depth. : ； in Indicate key objectives In depth The propagation loss value at the location.

8. A scene-adaptive sonar optimal preset listening depth determination system, characterized in that, Includes the following modules: The preprocessing module is used to obtain the number of targets, target locations, depth lists, and environmental parameters. The scene type determination module is used to determine the scene type based on the number of targets; When the number of targets is 0, enter the targetless scene calculation module; when the number of targets is 1, enter the single-target scene calculation module; when the number of targets is greater than 1, enter the multi-target scene calculation module. The targetless scene calculation module is used to traverse the depth list, calculate the omnidirectional propagation loss of each depth within the approximate range of the target, convert it into a two-dimensional grid, truncate the propagation loss TL with a quality factor, and calculate the effective coverage. The depth with the highest effective coverage is selected as the optimal preset listening depth in the targetless scenario; The single-target scene calculation module is used to traverse the depth list, calculate the propagation loss value from the target to each depth position, compare the propagation loss values ​​at each depth, and select the depth with the smallest propagation loss value as the optimal preset listening depth for the single-target scene. The multi-target scene calculation module is used to traverse the depth list, calculate the propagation loss value from all targets at different depths to the sonar acquisition device, and combine the propagation loss values ​​of multiple targets to determine the optimal preset listening depth in the multi-target scene.

9. A computer device, comprising a memory and one or more processors; characterized in that, The memory stores executable code, which, when executed by the processor, is used to implement the scene-adaptive sonar optimal preset listening depth determination method 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 executed by the processor, the program is used to implement the scene-adaptive sonar optimal preset listening depth determination method as described in any one of claims 1 to 7.

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