Underwater sound signal positioning method and device and storage medium

Abstract

The invention relates to an underwater acoustic signal positioning method and device and a storage medium, and the method comprises the steps: obtaining an underwater acoustic signal, received by a hydrophone array, of a detected target, carrying out the signal processing of the underwater acoustic signal, and obtaining a time domain underwater acoustic signal image; determining the detection range of the hydrophone array, and generating a plurality of signal template images according to the position information of each template in the detection range; the signal template image is matched with the template position information; based on each signal template image, performing signal retrieval on the time domain underwater acoustic signal image to obtain a target signal image matched with at least one signal template image; and performing signal positioning according to the target signal image, and generating an underwater acoustic positioning result of the detected target. According to the invention, the problem of low underwater acoustic signal positioning precision is solved.

Description

Technical Field

[0001] The present application relates to the field of signal positioning, and in particular, to an underwater acoustic signal positioning method, apparatus, and storage medium. Background Art

[0002] Underwater acoustic positioning technology, as the core means of underwater non-line-of-sight detection, plays an irreplaceable role in fields such as seabed terrain mapping, underwater target tracking, and emergency rescue.

[0003] In related technologies, underwater acoustic target positioning technology mainly relies on frequency-domain analysis methods. This method extracts spectral features by performing Fourier transform on underwater acoustic signals, realizes signal-to-noise ratio gain through long-time integration, and determines the target azimuth angle. However, such methods have serious deficiencies in detecting short-time transient signals (such as the acoustic fingerprints of sudden failures of underwater equipment and the instantaneous radiation noise of fast-moving targets). Insufficient signal integration time will lead to the failure of energy accumulation, resulting in a significant increase in the missed detection rate, and further affecting the positioning accuracy of underwater acoustic signals.

[0004] Currently, no effective solution has been proposed for the problem of low positioning accuracy of underwater acoustic signals in related technologies. Summary of the Invention

[0005] Embodiments of the present application provide an underwater acoustic signal positioning method, apparatus, and storage medium to at least solve the problem of low positioning accuracy of underwater acoustic signals in related technologies.

[0006] In a first aspect, embodiments of the present application provide an underwater acoustic signal positioning method, the method including:

[0007] Obtain the underwater acoustic signal of the target to be measured received by a hydrophone array, perform signal processing on the underwater acoustic signal to obtain a time-domain underwater acoustic signal image;

[0008] Determine the detection range of the hydrophone array, and generate multiple signal template images according to the position information of each template located within the detection range; the signal template images match the template position information;

[0009] Based on each of the signal template images, perform signal retrieval on the time-domain underwater acoustic signal image to obtain a target signal image that matches at least one of the signal template images;

[0010] Perform signal positioning according to the target signal image to generate an underwater acoustic positioning result of the target to be measured.

[0011] In some of these embodiments, the determination process of the template position information includes:

[0012] Based on a preset position constraint condition, determine the position sparsity; the position constraint condition is used to indicate the constraint relationship between the template angle and the template distance;

[0013] Within the detection range, determine the template position information according to the position sparsity.

[0014] In some embodiments, generating multiple signal template images according to each template position information located within the detection range includes:

[0015] Calculate the propagation time of the sound signal according to the template position information and the element position information of the hydrophone array.

[0016] Based on the propagation time of the sound signal, calculate the time sampling point difference of the sound signals received between each element in the hydrophone array.

[0017] Generate the signal template image corresponding to the template position information according to the time sampling point difference.

[0018] In some embodiments, performing signal retrieval on the time-domain underwater acoustic signal image based on each signal template image to obtain a target signal image that matches at least one of the signal template images includes:

[0019] Slide each signal template image step by step within the time-domain underwater acoustic signal image for signal retrieval, and determine a first matching image from each signal template image based on the result of the signal retrieval.

[0020] Based on the first matching image, determine the target matching signal in the time-domain underwater acoustic signal image, and generate the target signal image according to the target matching signal.

[0021] In some embodiments, determining the target matching signal in the time-domain underwater acoustic signal image based on the first matching image includes:

[0022] Based on the first matching image, determine the matching signal region in the time-domain underwater acoustic signal image.

[0023] Perform spatial extension processing on the first matching image to obtain a second matching image.

[0024] Slide the second matching image step by step within the time-domain underwater acoustic signal image based on the matching signal region to determine the target matching signal.

[0025] In some embodiments, sliding each signal template image step by step within the time-domain underwater acoustic signal image for signal retrieval includes:

[0026] Detect the field characteristics of the measured target.

[0027] Read the field tags carried by each of the signal template images according to the field characteristics, and determine the field tags that match the field characteristics;

[0028] Sequentially slide the signal template images carrying the field tags that match the field characteristics step by step within the time-domain underwater acoustic signal image for signal retrieval.

[0029] In some embodiments, the performing signal positioning based on the target signal image to generate the underwater acoustic positioning result of the target to be measured includes:

[0030] Perform convolution processing on the target signal image, and determine the positions of multiple signal points based on the obtained convolution result;

[0031] Construct a hyperbolic positioning model according to the element position information of the hydrophone array; the hyperbolic positioning model is used to indicate the mapping relationship between the distances between signal points and each element in the hydrophone array and the sound signal propagation time;

[0032] Utilize the hyperbolic positioning model to fit the target signal position according to the signal point positions, and calculate the azimuth angle and distance of the target to be measured relative to the hydrophone array based on the target signal position; the underwater acoustic positioning result includes the azimuth angle and the distance.

[0033] In some embodiments, the performing convolution processing on the target signal image includes:

[0034] Obtain the signal distribution characteristic information of the signal template image that matches the target signal image;

[0035] Determine the corresponding convolution kernel based on the signal distribution characteristic information, and perform convolution processing on the target signal image based on the convolution kernel.

[0036] In a second aspect, an embodiment of the present application provides an underwater acoustic signal positioning device, including:

[0037] A signal processing module, configured to obtain the underwater acoustic signal of the target to be measured received by the hydrophone array, perform signal processing on the underwater acoustic signal to obtain a time-domain underwater acoustic signal image;

[0038] A template generation module, configured to determine the detection range of the hydrophone array, and generate multiple signal template images according to the respective template position information located within the detection range; the signal template images match the template position information;

[0039] A signal retrieval module, configured to perform signal retrieval on the time-domain underwater acoustic signal image based on each of the signal template images, so as to obtain a target signal image that matches at least one of the signal template images;

[0040] A positioning module, configured to perform signal positioning according to the target signal image, and generate an underwater acoustic positioning result of the target to be measured.

[0041] In a third aspect, an embodiment of the present application provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the underwater acoustic signal positioning method as described in the first aspect above.

[0042] Compared with the related art, the underwater acoustic signal positioning method, device, and storage medium provided by the embodiments of the present application obtain the underwater acoustic signal of the target to be measured received by the hydrophone array, perform signal processing on the underwater acoustic signal to obtain a time-domain underwater acoustic signal image; determine the detection range of the hydrophone array, and generate multiple signal template images according to the position information of each template located within the detection range; the signal template image matches the template position information; based on each signal template image, perform signal retrieval on the time-domain underwater acoustic signal image to obtain a target signal image that matches at least one signal template image; perform signal positioning according to the target signal image to generate an underwater acoustic positioning result of the target to be measured. Based on this, the constructed signal template images are used for signal retrieval within the time-domain underwater acoustic signal image, so that it is possible to extract and analyze short-time or instantaneous underwater acoustic target signals using a single hydrophone array, improving the capture and analysis capabilities of instantaneous signals, and effectively solving the problem of low accuracy of underwater acoustic signal positioning.

[0043] Details of one or more embodiments of the present application are set forth in the following drawings and description, so that other features, objects, and advantages of the present application will become more clearly understood. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation to the present application. In the drawings:

[0045] Figure 1 is a hardware structure block diagram of a terminal for an underwater acoustic signal positioning method according to an embodiment of the present application;

[0046] Figure 2 is a flowchart of an underwater acoustic signal positioning method according to an embodiment of the present application;

[0047] Figure 3 is a schematic diagram of a time-domain underwater acoustic signal image according to an embodiment of the present application;

[0048] Figure 4Schematic diagram of the detection range of a hydrophone array according to an embodiment of the present application;

[0049] Figure 5A Schematic diagram of a signal template image according to an embodiment of the present application;

[0050] Figure 5B Schematic diagram of another signal template image according to an embodiment of the present application;

[0051] Figure 6 Schematic diagram of a signal retrieval process according to an embodiment of the present application;

[0052] Figure 7 Schematic diagram of a target signal image according to an embodiment of the present application;

[0053] Figure 8 Flow chart of another underwater acoustic signal positioning method according to an embodiment of the present application;

[0054] Figure 9A Schematic diagram of a near - field test signal according to an embodiment of the present application;

[0055] Figure 9B Schematic diagram of a far - field test signal according to an embodiment of the present application;

[0056] Figure 10 Block diagram of the structure of an underwater acoustic signal positioning device according to an embodiment of the present application. Detailed implementation manners

[0057] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be described and explained below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. Based on the embodiments provided by the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application. In addition, it can also be understood that although the efforts made in such a development process may be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present application, some designs, manufacturing or production changes made on the basis of the technical content disclosed in the present application are only conventional technical means and should not be understood as the content disclosed in the present application being insufficient.

[0058] Reference to "embodiment" in this application means that the specific features, structures, or characteristics described in connection with the embodiment may be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those of ordinary skill in the art will explicitly and implicitly understand that the embodiments described in this application may be combined with other embodiments without conflict.

[0059] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the ordinary meaning understood by those of ordinary skill in the technical field to which this application belongs. The words such as "a", "an", "one kind", "the" and the like involved in this application do not indicate a limitation in quantity and may represent a singular or plural number. The terms "include", "comprise", "have" and any variations thereof involved in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may further include unlisted steps or units, or may further include other steps or units inherent to these processes, methods, products or devices. The terms "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "plurality" involved in this application means greater than or equal to two. "And / or" describes the association relationship of associated objects and indicates that three relationships may exist. For example, "A and / or B" may represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0060] The method embodiment provided in this embodiment may be executed on a terminal, a computer, or a similar computing device. Taking running on a terminal as an example, Figure 1 is a hardware structure block diagram of a terminal for a method of underwater acoustic signal positioning according to an embodiment of this application. As Figure 1 shown, the terminal may include one or more ( Figure 1 only one is shown in the figure) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the above terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above terminal. For example, the terminal may further include more or fewer components than those Figure 1 shown in the figure, or may have a structure different from that Figure 1The different configurations shown.

[0061] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the underwater acoustic signal positioning method in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the terminal through a network. Examples of the above network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network, and combinations thereof.

[0062] The transmission device 106 is used to receive or send data via a network. Specific examples of the above network may include a wireless network provided by a communication provider of the terminal. In one instance, the transmission device 106 includes a network adapter (abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0063] This embodiment provides an underwater acoustic signal positioning method. Figure 2 It is a flowchart of an underwater acoustic signal positioning method according to an embodiment of the present application, as Figure 2 shown, and the process includes the following steps:

[0064] Step S210, obtain the underwater acoustic signal of the target to be measured received by the hydrophone array, perform signal processing on the underwater acoustic signal, and obtain a time-domain underwater acoustic signal image.

[0065] The above target to be measured refers to a moving target whose precise position needs to be surveyed in the sea area. In this step, the sound signals in the water are collected by the hydrophone array placed in the sea area, and after enhancing the collected multi-channel underwater acoustic signal data, a time-domain underwater acoustic signal image is obtained. It should be understood that the hydrophone array is a detection system composed of multiple hydrophones arranged according to a certain rule; a hydrophone is a sensor that can convert the acoustic signal (sound wave) in water into an electrical signal or other measurable signals.

[0066] More specifically, the underwater acoustic data collected by the hydrophone array is multi-channel; taking a hydrophone array with M channels as an example, when the number of sampling points of the hydrophone array reaches N, it can be visually displayed through Matlab software. After signal enhancement processing, the time-domain underwater acoustic signal image is obtained. The dimension size of this image is M×N, where M is the number of rows and N is the number of columns; both M and N are positive integers. The following describes the process of one type of signal enhancement processing:

[0067] Perform differential calculation on the current channel data and the previous channel data and take the absolute value, and the data of the first channel is not differentially processed; this differential processing process is shown in the following formula:

[0068] ;

[0069] In the above formula, F i is the underwater acoustic data received by the i-th channel of the hydrophone array. Through the above signal enhancement method, the signal-to-noise ratio of the received underwater acoustic signal of the target to be measured can be improved, which is convenient for subsequent matching processing and helps to improve the accuracy of matching. For the time-domain underwater acoustic signal image generated through the above steps, please refer to Figure 3 , where the abscissa in the figure represents the sound propagation time, and the ordinate represents the actual positions of the individual elements in the hydrophone array; an element refers to a single independent hydrophone unit that makes up the array and is the basic component unit of the array. It can be seen that most of the signals in the image are chaotic at this time, and it is difficult to identify and distinguish the effective signals and noise signals. Therefore, in order to ensure the accuracy of underwater acoustic signal positioning, effective signal extraction needs to be performed in the subsequent steps.

[0070] Step S220, determine the detection range of the hydrophone array, and generate multiple signal template images according to the position information of each template within the detection range; the signal template images match the template position information.

[0071] The types of various hydrophone arrays are different, and the detection ranges they can cover are also different. Among them, the detection range can be specifically determined by combining theoretical modeling, according to environmental parameter measurement and actual test verification. During the generation of the signal template image, first, based on the determined detection range of the hydrophone array, a series of template target points at different template positions are determined. The template positions of each target point can be determined randomly or according to a certain interval. It should be added that the template position has two parameters: template angle and template distance; in this embodiment, it should be ensured that for two template target points under adjacent template angles or adjacent template distances, the difference in the signal sampling points received by the hydrophone array is an integer and a non-zero value.

[0072] Taking the hydrophone array using a towed linear hydrophone array device as an example, please refer to Figure 4, the hydrophone array includes N array elements arranged linearly; when placed in a two-dimensional coordinate system, each array element in the hydrophone array is sequentially placed on the X-axis of the two-dimensional coordinate axis. Specifically, the angle between the line connecting the template target point and the coordinate origin and the X-axis is defined as the template angle, and the distance from the template target point to the array element is defined as the template distance; then within the detection range of the hydrophone array, the template distance and the template angle are changed to determine template target points at different positions. Still taking Figure 4 the linear hydrophone array shown as an example, since the results in the symmetric directions on both sides of the line array are consistent, only the template target points with the template angle in the range of 0° to 180° need to be processed and analyzed; while in other types of hydrophone arrays, the value range of the template angle is still 0° to 360°. Next, calculate the sound propagation signals of each template target point propagating to the hydrophone array at different template distances and template angles, and perform signal processing on the sound propagation signals, and convert them into signal template images.

[0073] Step S230, based on each signal template image, perform signal retrieval on the time-domain underwater acoustic signal image to obtain a target signal image that matches at least one signal template image.

[0074] Specifically, traverse each constructed signal template image, slide the currently traversed signal template image within the time-domain underwater acoustic signal image and perform signal matching; the matching method can adopt methods such as similarity calculation or matching based on a neural network. If a signal region matching the signal template image is found within the time-domain underwater acoustic signal image, the signal points within the matched region are correspondingly extracted. Then, repeat the above steps for the next traversed signal template image until all signal template images are traversed; at this time, the signal points extracted for all the matched signal regions within the time-domain underwater acoustic signal image are processed to generate a target signal image.

[0075] Step S240, perform signal positioning according to the target signal image to generate the underwater acoustic positioning result of the target to be measured.

[0076] It should be noted that through the above steps S210 to S230, the signals in the generated target signal image are effective signals in the time domain. Then in this step, image feature extraction is performed on the target signal image, and positioning is performed based on the positioning model; for example, the constructed hyperbolic positioning model is adopted, and calculations are performed according to the extracted multiple signal points, and finally the azimuth angle and distance of the target to be measured relative to the hydrophone array are obtained, that is, the above-mentioned underwater acoustic positioning result is obtained.

[0077] Optionally, in another embodiment, the signal positioning process can also be comprehensively analyzed in combination with the above template position information. For example, after calculating the azimuth and distance of the target to be measured, the calculated azimuth and / or distance values can be evaluated according to the template position information. If the difference between the calculated azimuth and the template angle of the current template target point is within the preset angle threshold range, and / or the difference between the calculated distance value and the template distance of the current template target point is within the preset distance threshold range, then it can be determined that the calculated azimuth and distance values are the underwater acoustic positioning results of the target to be measured; otherwise, recalculate and update.

[0078] In the related art, when using a frequency-domain-based method for target positioning, signal missed detection often occurs. In addition, traditional passive positioning methods include positioning based on matched field; however, due to the complexity of the underwater acoustic environment and the unknown nature of underwater acoustic target signals, it is difficult to make significant breakthroughs and progress in accurately positioning targets using the matched field method, resulting in low accuracy of underwater acoustic signal positioning.

[0079] In contrast, through the above steps, the embodiments of the present application retrieve signals in the time-domain underwater acoustic signal image for each constructed signal template image, thereby enabling the extraction and analysis of short-time or instantaneous underwater acoustic target signals using a single hydrophone array, improving the capture and analysis capabilities of instantaneous signals, and effectively solving the problem of low accuracy of underwater acoustic signal positioning.

[0080] In some of these embodiments, the process of determining the above template position may further include the following steps:

[0081] Based on a preset position constraint condition, determine the position sparsity; the position constraint condition is used to indicate the constraint relationship between the template angle and the template distance; within the detection range, determine the template position information according to the position sparsity.

[0082] The above position constraint conditions are determined by polling the fixed template angle, changing different template distances, and fixing the template distance and changing different template angles. More specifically, during the generation of the signal template image, the template angle is fixed at a certain angle value, and two corresponding signal template images are generated at template distances R1 and R2 respectively; the similarity between the two signal template images is calculated. When the similarity is less than or equal to the preset template similarity threshold, it is considered that there is redundancy between the two signal template images. Therefore, the difference between R1 and R2 is increased accordingly. For example, the template distance R2 is adjusted to R3 with a larger distance difference, and the similarity between the signal template image generated at R1 and the signal template image generated at R3 is calculated until the similarity between the two signal template images is greater than the template similarity threshold, then the calculation is stopped, and the difference between the template distances corresponding to the two signal template images generated currently is used as the distance sparsity.

[0083] Similar to the determination process of the above distance sparsity, when determining the angle sparsity, the template distance is fixed at a certain distance value, and two signal template images are respectively generated at template angle θ1 and template angle θ2, and based on the judgment result of the similarity between the two signal template images with different template angles, the angle sparsity is calculated. Finally, according to the position sparsity including the distance sparsity and the angle sparsity, the template target points at different positions within the detection range are determined to generate a series of signal template images.

[0084] Through the above embodiments, the template positions of each template target point are determined according to the determined position sparsity, and the position sparsity is determined according to the position constraint conditions, so as to ensure the difference and non-redundancy between different signal template images.

[0085] In some of these embodiments, the above generation of multiple signal template images according to the template position information located within the detection range may further include the following steps:

[0086] According to the template position information and the element position information of the hydrophone array, calculate the sound signal propagation time; based on the sound signal propagation time, calculate the time sampling point difference of the sound signals received between each element in the hydrophone array; according to the time sampling point difference, generate a signal template image corresponding to the template position information.

[0087] Among them, since the template position information of each template target point located within the detection range has been determined, the time required for the sound signal to propagate to each element can be directly calculated according to the actual positions of each element of the hydrophone array and the sound propagation speed (i.e., the above sound signal transmission time). In another embodiment, in order to further reduce the number of signal template images, the template target points can be divided into near-field template targets and far-field template targets, and respectively at the near-field position and the far - field position Emit a sound signal downward. According to the sound propagation speed c, calculate the time required for the sound signal to propagate to each array element, as shown in the following formula:

[0088] ;

[0089] ;

[0090] In the above formula, t i is the time for the sound signal emitted by the near - field template target to propagate to the i - th array element in the array, and t j is the time for the sound signal emitted by the far - field template target to propagate to the j - th array element in the array.

[0091] Next, further calculate the time sampling point difference of the signals received between each array element of the hydrophone array, as shown in the following formula:

[0092] Δn i =(t i -t1)·f s ; i = 1, 2, ……, M;

[0093] Δn j =(t j -t1)·f s ; j = 1, 2, ……, M;

[0094] In the above formula, f s is the sampling frequency of the signal, Δn i is the time sampling point difference between the signal emitted by the near - field template target and the time when it propagates to the i - th array element and the first array element t1, and Δn j is the time sampling point difference between the signal emitted by the far - field template target and the time when it propagates to the j - th array element and the first array element.

[0095] According to the time sampling point differences Δn i and Δn j obtained above, in the two - dimensional plane, they respectively correspond to the curve of the near - field signal and the straight line of the far - field signal. Then, convert the above curve and straight line into binary images. After image dilation processing, the near - field signal template image and the far - field signal template image can be obtained. Among them, for the near - field signal template image, please refer to Figure 5A , the ordinate in the figure represents the actual positions of each array element in the hydrophone array, and the abscissa is used to represent the sound signal propagation time for the near - field template target to propagate the signal to the corresponding array element; the signal distribution feature in the near - field signal template image is a surface wave, which is shown as a curve on the received time - domain signal. For the far - field signal template image, please refer to Figure 5B, in the figure, the ordinate represents the actual positions of the elements in the hydrophone array, and the abscissa is used to represent the sound signal propagation time from the far-field template target propagation signal to the corresponding element; the signal distribution feature in the far-field signal template image is a plane wave, which appears as a straight line in the received time-domain signal. It should also be noted that in the actual application process, multiple variant signal image templates can also be obtained by adjusting the width-to-height ratio of the template image.

[0096] Through the above embodiments, by calculating the time sampling point differences between the template target point signals at different template positions propagating to each element in the hydrophone array, corresponding signal template images are generated, thus ensuring the accuracy of signal template image generation.

[0097] In some of these embodiments, for the above-mentioned signal retrieval of the time-domain underwater acoustic signal image based on each signal template image to obtain a target signal image that matches at least one signal template image, the following steps may further be included:

[0098] Each of the signal template images is slid step by step in the time-domain underwater acoustic signal image in sequence for signal retrieval, and based on the results of the signal retrieval, a matching signal region that matches at least one of the signal template images is determined from the time-domain underwater acoustic signal image; based on the matching signal region, the target matching signal in the time-domain underwater acoustic signal image is determined, and the target signal image is generated according to the target matching signal.

[0099] Specifically, each of the above signal template images can be stored in a pre-constructed template matching image library; during the underwater acoustic signal positioning process, each signal template image in the template matching image library is traversed. For the currently traversed signal template image, it is slid and matched in the time-domain underwater acoustic signal image according to a preset step size, and the correlation between the two is calculated. This preset step size can be set in advance in combination with the actual situation. For example, one process of calculating the correlation between the signal template image and the time-domain underwater acoustic signal image can be shown by the following formula:

[0100] ;

[0101] In the above formula, T m×n is the signal template image; X M×N is the time-domain underwater acoustic signal image. i is the starting position of the region to be matched in the current time-domain underwater acoustic signal image during the matching process, V i is the magnitude of the correlation between the signal template image and the image where the region to be matched is located, and (m, n) and (M, N) respectively represent the dimension sizes of the signal template image and the time-domain underwater acoustic signal image. s represents the preset step size.

[0102] After obtaining the above calculation results of the correlation, the signal template image that matches a partial signal region in the time-domain underwater acoustic signal image can be determined. For example, when the correlation value exceeds the set correlation threshold V th a signal template image for the current signal retrieval can be determined to match a partial signal region in the time-domain underwater acoustic signal image, and based on this, the corresponding position of the target signal in the time-domain underwater acoustic signal image can be determined; for the signal search results, please refer to Figure 6 , Figure 6 which shows the signal search results based on the signal template image in the time-domain underwater acoustic signal image. The regions where each rectangular box is located are the above-determined matching signal regions. Then, the signals in the determined matching signal regions are extracted as target matching signals, and the target matching signals are processed to generate a target signal image. The generated target signal image is as shown in Figure 7 .

[0103] Through the above embodiments, by sequentially sliding the signal template image step by step in the time-domain underwater acoustic signal image for matching to determine the target matching signal, it helps to improve the accuracy of signal retrieval and matching.

[0104] It should also be supplemented that if the target matching signal is directly extracted based on the signal region in the time-domain underwater acoustic signal image corresponding to the above first matching image and a target signal image is generated, it is likely to have problems such as matching errors and low accuracy of signal extraction. Based on this, in some embodiments, to determine the target matching signal in the time-domain underwater acoustic signal image for the above matching signal region, the following steps may further be included:

[0105] Perform spatial extension processing on the matching signal region to obtain an extended image; slide the signal template image step by step in the extended image to determine the target matching signal.

[0106] Specifically, when it is determined through the above steps that the correlation value of the first layer exceeds the set threshold V th the approximate position of the signal can be initially determined, that is, the above matching signal region is determined. Then, pixel expansion is performed at the edge of the matching signal region to obtain an extended image. Exemplarily, a preset pixel extension distance and a pixel extension direction are determined, and the boundary information is spatially extended to the pixel extension distance in the pixel extension direction. The pixel extension distance refers to the number of pixels that need to be extended outward for the current matching signal region; the pixel extension direction refers to the direction in which the current image frame extends outward; the pixel extension distance and the pixel extension direction can be set in advance according to actual situations. For example, the pixel extension direction is set to extend in the height direction and the width direction of the matching signal region, and the pixel extension distances in the two directions are respectively set to half of the height and width of the signal template image. Thus, an extended image X containing the target signal is obtained p, with a dimension size of (m + m / 2, n + n / 2); then in the extended image X p Perform a step-by-step pixel-by-pixel sliding search within it. At this time, the sliding search process can be based on each signal template image for the search, or directly slide the signal template image that matches the above-mentioned matching signal region within the extended image X p for the sliding search; finally, calculate the second-layer correlation between the signal template image and each region in the extended image during the sliding search. The position i of the signal at the maximum value of the second-layer correlation is calculated as follows:

[0107] i = argmax(Corr(X p | (i,1) , T m×n ));

[0108] Through the above embodiments, a hierarchical signal retrieval mechanism is realized, which can quickly filter out unmatched regions, and then perform fine-grained search for the region of interest after matching it, thereby further improving the accuracy of signal retrieval.

[0109] In some of these embodiments, the above-mentioned step-by-step sliding of each signal template image within the time-domain underwater acoustic signal image for signal retrieval may further include the following steps:

[0110] Detect the field characteristics of the target to be measured; according to the field characteristics, read the field labels carried by each signal template image, and determine the field label that matches the field characteristics; slide the signal template image carrying the field label that matches the field characteristics step by step within the time-domain underwater acoustic signal image for signal retrieval.

[0111] In the actual application process, the field characteristics of the above-mentioned target to be measured can be preliminarily detected to distinguish whether the target to be measured is a far-field target or a near-field target. Among them, a far-field target refers to a target whose distance from the hydrophone array satisfies the far-field condition, and a near-field target refers to a target whose distance from the hydrophone array satisfies the near-field condition; for example, assuming that the boundary point of the far-near field condition is 10 km, that is, a target less than 10 km is a near-field target, and vice versa is a far-field target. The preliminary detection method of the above-mentioned field characteristics can be to detect the focused beamforming of the target to be measured by comparing the response characteristics of far-field and near-field beamforming to distinguish the field of the target to be measured; for example, the main lobe of the beamforming of a far-field target is sharp, and the focusing gain is relatively lower, while the main lobe of the beamforming of a near-field target is broadened / shifted, and the focusing gain is relatively higher.

[0112] In addition, it should be understood that the field tags corresponding to each signal template image can be determined when the signal template image is generated. For example, the template target points used to generate the signal template image can be directly distinguished as near-field targets or far-field targets according to the template position information of the signal template image, and the corresponding field tags indicating near-field targets or far-field targets can be added to the signal template image according to the discrimination result.

[0113] Next, signal retrieval is performed based on the field characteristics of the measured target and the field tags of the signal template images. Specifically, determine the field tags of the same field type as the field characteristics of the measured target, and screen out the images carrying the determined field tags from each signal template image, and then sequentially slide the screened signal template images step by step in the time-domain underwater acoustic signal image for signal retrieval. Alternatively, when permitted by the embodiments, the signal template images can be stored in different template image libraries according to their respective field tags. For example, the signal template images with far-field tags are stored in the far-field template image library, and the signal template images with near-field tags are stored in the near-field template image library. In this way, during signal retrieval, the signal template images in the corresponding template image library can be directly extracted according to the detected field characteristics of the measured signal for retrieval and matching.

[0114] Through the above embodiments, signal retrieval based on the field characteristics of the measured target and the field characteristics of the signal template images helps to quickly screen out the qualified signal template images, avoiding the problem of excessive search time caused by traversing and signal retrieval for each signal template image stored in the image library, thereby effectively improving the signal retrieval efficiency.

[0115] In some of the embodiments, the above signal positioning based on the target signal image to generate the underwater acoustic positioning result of the measured target may further include the following steps:

[0116] Perform convolution processing on the target signal image, and determine multiple signal point positions based on the obtained convolution result; construct a hyperbolic positioning model according to the element position information of the hydrophone array; the hyperbolic positioning model is used to indicate the mapping relationship between the distances between the signal points and each element in the hydrophone array and the sound signal propagation time; use the hyperbolic positioning model to fit the target signal position according to the signal point positions, and calculate the azimuth angle and distance of the measured target relative to the hydrophone array based on the target signal position; the underwater acoustic positioning result includes the azimuth angle and the distance.

[0117] Specifically, the target signal image X is convolved in a certain row dimension y with a relatively small convolution kernel K sPerform convolution with a convolution kernel of size 2×2, and determine the ordinate y of the signal based on the peak position of the response curve of the convolution result. One calculation method is shown in the following formula:

[0118] ;

[0119] Through the above formula, the position (x, y) of the signal point can be calculated. Repeating the above calculation, the position coordinates of multiple signal points can be obtained. The position coordinates of the i-th signal point can be expressed as (x i , y i ). Next, by subtracting the x values of the coordinates of multiple signal points, the time delay difference can be calculated, and then using the speed of sound , the propagation distance difference Δx ij can be calculated as follows:

[0120] ;

[0121] Δx ij= ·C;

[0122] In the above formula, x i and x j are the time sampling point values of two signal points, is the time difference between signal point i and signal point j, Δx ij is the propagation distance difference of the signal to two array elements, and f s is the sampling frequency of the hydrophone array for collecting underwater acoustic data.

[0123] Next, the process of calculating the azimuth angle and distance of the target to be measured relative to the hydrophone array based on the positions of multiple signal points will be specifically described:

[0124] For any two array elements S i and S j in the hydrophone array, the hyperbolic positioning model for multiple signal points is:

[0125] ;

[0126] In the formula, (x i , y i ) and (x j , y j ) are the position coordinates of the i-th and j-th array elements in the hydrophone array, c is the speed of sound, and t ij is the time difference for the sound to propagate to the i-th and j-th array elements. The calculation process is as follows:

[0127] ;

[0128] In the formula, is the sampling frequency of the signal, and respectively represent the time sampling point values corresponding to the arrival of the target signal at the array element and respectively.

[0129] By solving the above hyperbolic positioning equation, the position coordinates of the underwater acoustic signal can be obtained , and the calculations of the azimuth angle A and the distance D are respectively:[[]]

[0130] ;

[0131] ;

[0132] More specifically, taking the example that the hydrophone array consists of three array elements, the coordinates of the three array elements are S1(x1, y1), S2(x2, y2), S3(x3, y3) respectively, and the constructed hyperbolic positioning model is shown in the following formula:[[]]

[0133] ;

[0134] ;

[0135] ;

[0136] In the formula, c is the speed of sound, is the time difference for the sound to propagate to the array element points S1 and S2, is the time difference for the sound to propagate to the array element points S1 and S3, is the time difference for the sound to propagate to the array element points S2 and S3, and they are respectively:[[]]

[0137] ;

[0138] ;

[0139] ;

[0140] In the formula, f s is the sampling frequency of the signal, x s1 , x s2 and x s3 respectively represent the time sampling point values of the signal points corresponding to the array elements S1, S2 and S3.

[0141] For the above hyperbolic positioning model, at least three signal point coordinates are required to solve for a result. If there are more than three signal point coordinates, non - linear fitting can be performed through the positioning model, and then the optimal result can be solved, that is, the position coordinates of the target signal are obtained , and the calculations of the azimuth angle A and the distance D are respectively:[[]]

[0142] ;

[0143] ;

[0144] Compared with the signal positioning method in the related art, which uses hydrophones placed at three different positions in water to measure the time difference of the received underwater acoustic target signal arriving between the three hydrophones, converts it into a distance difference according to the propagation sound speed, and finally calculates the azimuth and distance of the target through relevant positioning algorithms, resulting in the need for multiple hydrophones and difficulty in accurately positioning on a single ship. Through the above embodiments, the present application performs signal positioning on the target signal image through a hyperbolic positioning model, thereby realizing an underwater acoustic signal positioning method using a single hydrophone, and accurate signal positioning can be achieved without adding multiple hydrophones.

[0145] In some of these embodiments, the above-mentioned convolution processing of the target signal image may further include the following steps:

[0146] Obtain the signal distribution feature information of the signal template image that matches the target signal image; based on the signal distribution feature information, determine the corresponding convolution kernel, and based on the convolution kernel, perform convolution processing on the target signal image.

[0147] Specifically, in the process of extracting signal points from the target signal image, the corresponding convolution kernel can also be designed according to the shape characteristics of the signals in the signal template image (i.e., the above-mentioned signal distribution feature information) to quickly and accurately match the positions of the signal points. More specifically, in the signal template image, each small area belonging to the line shape is segmented, and the slope is calculated; for example, in line detection, there are corresponding oblique line detections of 45°, 60°, etc. Then, based on each slope angle, the weight distribution direction of the convolution kernel is determined correspondingly.

[0148] The process of determining the convolution kernel based on the signal template image is further described in detail below.

[0149] First, divide the line-shaped area in the matched signal template image into several small segments, for example, every 3 signal points or 5 signal points as a segment, or automatically segment according to the curvature change of the signal line in the image. For each segment of the divided line segment, methods such as differential calculation are used to calculate the slope of each line segment, and the slope of each calculated line segment is converted into an angle , as shown in the following formula:

[0150] ;

[0151] In the above formula, k i is used to represent the slope of the i-th line segment, Used to represent the angle corresponding to the i-th line segment obtained by slope conversion; i is a positive integer.

[0152] Next, based on the calculated angle value above, determine the gradient direction α perpendicular to the edge of the i-th line segment i , as shown in the following formula:

[0153] ;

[0154] Subsequently, design a convolution kernel according to the above gradient direction, making its weights sensitive in the gradient direction α i , Exemplarily, a convolution kernel in any direction can be constructed first. For example, the horizontal direction gradient kernel G is obtained by decomposing the Sobel operator x and the vertical direction gradient kernel G y , and project G x and G y in the gradient direction α i to obtain the convolution kernel K i :

[0155] ;

[0156] Finally, normalize the weights of K i to ensure that their sum is 0, avoid offset, and thus complete the design of the convolution kernel.

[0157] Through the above embodiments, a signal extraction method for determining a convolution kernel by providing a reference signal template image is provided, which can effectively improve the accuracy and efficiency of extracting multiple signal points in the target signal image, and thus improve the accuracy and efficiency of underwater acoustic signal positioning.

[0158] The following describes and illustrates the present application through specific embodiments. Figure 8 is a flowchart of another underwater acoustic signal positioning method according to an embodiment of the present application, as Figure 8 shown, and this process includes the following steps:

[0159] Step S801, collect the sound signals in the water through a hydrophone array placed in the water, and after performing signal enhancement processing on the collected multi-channel time-domain underwater acoustic signal data, convert it into a time-domain underwater acoustic signal image for output.

[0160] Step S802, according to the propagation characteristics of the near-field template underwater acoustic target and the far-field template underwater acoustic target, fit the signals received by the hydrophone array, and respectively obtain a surface wave and a plane wave. After performing image processing on them, obtain a signal template image.

[0161] Step S803: Search by sliding and matching the signal template image on the time-domain underwater acoustic signal image, calculate the correlation, and the position with high correlation is the position area of the signal. Then, perform more accurate matching in the position area containing the signal.

[0162] Step S804: Output the target signal image according to the result of matching the signal template image, extract multiple signal points from the target signal image, and calculate the time delay difference and distance difference of the signals received by each array element.

[0163] Step S805: According to the time delay difference and distance difference of the signal points received at the actual positions of each array element of the hydrophone array, calculate the azimuth angle and distance of the measured target through the hyperbolic positioning model of multiple signal points.

[0164] Through the above steps S801 to S805, verify the time-domain data of the target signal received in the test. Please refer to Figure 9A , the figure shows the effect of the near-field test signal. Among them, Figure 9A the azimuth angle of the test signal 1 in the left half is 45°, and the distance is 100 m. Figure 9A The azimuth angle of the test signal 2 in the right half is 81.85°, the azimuth error is 0.85°, the distance is 1.086 km, and the distance error is 86 m.

[0165] To verify the effect of the far-field signal, please refer to the simulated time-domain data of the far-field signal Figure 9B . Among them, Figure 9B the azimuth angle of the test signal 3 in the left half is 89°, and the distance is 10 km; Figure 9B the azimuth angle of the test signal 4 in the middle part is 89°, and the distance is 20 km; Figure 9B the azimuth angle of the test signal 5 in the right half is 89°, and the distance is 40 km. The calculation results are as follows: the azimuth angle of the test signal 3 is 90.01°, the azimuth error is 1.01°, the distance is 9.08 km, and the distance error is 0.92 km; the azimuth angle of the test signal 4 is 95.01°, the azimuth error is 6.01°, the distance is 25.82 km, and the distance error is 5.82 km; the azimuth angle of the test signal 5 is 96.52°, the azimuth error is 7.52°, the distance is 52.99 km, and the distance error is 12.99 km.

[0166] Based on the analysis of the above test data results, the above underwater acoustic signal positioning method calculates the azimuth of the measured target accurately, and as the target distance decreases, the distance calculation error of the measured target also decreases.

[0167] It should be noted that the steps shown in the above process or the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0168] This embodiment also provides an underwater acoustic signal positioning device, which is used to implement the above-mentioned embodiment and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, terms such as "module", "unit", "sub-unit", etc. can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0169] Figure 10 is a structural block diagram of an underwater acoustic signal positioning device according to an embodiment of the present application, as Figure 10 shown, the device includes: a signal processing module 10, a template generation module 20, a signal retrieval module 30, and a positioning module 40; wherein:

[0170] The signal processing module 10 is used to obtain the underwater acoustic signal of the target to be measured received by the hydrophone array, perform signal processing on the underwater acoustic signal, and obtain a time-domain underwater acoustic signal image; the template generation module 20 is used to determine the detection range of the hydrophone array, and generate multiple signal template images according to the respective template position information located within the detection range; the signal template images are matched with the template position information; the signal retrieval module 30 is used to perform signal retrieval on the time-domain underwater acoustic signal image based on each signal template image, and obtain a target signal image that matches at least one signal template image; the positioning module 40 is used to perform signal positioning according to the target signal image, and generate an underwater acoustic positioning result of the target to be measured.

[0171] In some of these embodiments, the above-mentioned underwater acoustic signal positioning device further includes a template position determination module; the template position determination module is used to determine the position sparsity based on a preset position constraint condition; the position constraint condition is used to indicate the constraint relationship between the template angle and the template distance; the template position determination module is further used to determine the template position information within the detection range according to the position sparsity.

[0172] It should be noted that the above-mentioned each module can be a functional module or a program module, and can be implemented either by software or by hardware. For the modules implemented by hardware, the above-mentioned each module can be located in the same processor; or the above-mentioned each module can also be located in different processors in any combination form. Specific examples in this embodiment can refer to the examples described in the above-mentioned embodiment and optional implementation manners, and will not be repeated in this embodiment.

[0173] This embodiment also provides an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0174] Optionally, the above electronic device may further include a transmission device and an input / output device. Among them, the transmission device is connected to the above processor, and the input / output device is connected to the above processor.

[0175] Optionally, in this embodiment, the above processor may be configured to execute the following steps through a computer program:

[0176] S1. Obtain the underwater acoustic signal of the target to be measured received by the hydrophone array, perform signal processing on the underwater acoustic signal to obtain a time-domain underwater acoustic signal image.

[0177] S2. Determine the detection range of the hydrophone array, and generate multiple signal template images according to the position information of each template located within the detection range; the signal template images match the template position information.

[0178] S3. Based on each signal template image, perform signal retrieval on the time-domain underwater acoustic signal image to obtain a target signal image that matches at least one signal template image.

[0179] S4. Perform signal positioning according to the target signal image to generate an underwater acoustic positioning result of the target to be measured.

[0180] It should be noted that the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and will not be repeated here.

[0181] In addition, in combination with the underwater acoustic signal positioning method in the above embodiments, an embodiment of the present application can be implemented by providing a storage medium. A computer program is stored on the storage medium; when the computer program is executed by a processor, any one of the underwater acoustic signal positioning methods in the above embodiments is implemented.

[0182] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data that have been authorized by the user or fully authorized by all parties.

[0183] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0184] Those skilled in the art should understand that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0185] The above embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. An underwater acoustic signal positioning method, characterized in that, The method includes: Obtaining an underwater acoustic signal of a target to be measured received by a hydrophone array, performing signal processing on the underwater acoustic signal to obtain a time-domain underwater acoustic signal image; Determining a detection range of the hydrophone array, and generating a plurality of signal template images according to respective template position information located within the detection range; the signal template images match the template position information; Based on each of the signal template images, performing signal retrieval on the time-domain underwater acoustic signal image to obtain a target signal image that matches at least one of the signal template images; Performing signal positioning according to the target signal image to generate an underwater acoustic positioning result of the target to be measured.

2. The underwater acoustic signal positioning method according to claim 1, characterized in that, The determination process of the template position information includes: Determining a position sparsity based on a preset position constraint condition; the position constraint condition is used to indicate a constraint relationship between a template angle and a template distance; Within the detection range, determining the template position information according to the position sparsity.

3. The underwater acoustic signal positioning method according to claim 1, characterized in that, The generating a plurality of signal template images according to respective template position information located within the detection range includes: Calculating a sound signal propagation time according to the template position information and element position information of the hydrophone array; Based on the sound signal propagation time, calculating a time sampling point difference of sound signals received between each element in the hydrophone array; Generating the signal template image corresponding to the template position information according to the time sampling point difference.

4. The underwater acoustic signal positioning method according to claim 1, characterized in that, The performing signal retrieval on the time-domain underwater acoustic signal image based on each of the signal template images to obtain a target signal image that matches at least one of the signal template images includes: Sequentially sliding each of the signal template images step by step within the time-domain underwater acoustic signal image for signal retrieval, and based on the signal retrieval result, determining a matching signal region in the time-domain underwater acoustic signal image that matches at least one of the signal template images; Based on the matching signal region, determining a target matching signal in the time-domain underwater acoustic signal image, and generating the target signal image according to the target matching signal.

5. The underwater acoustic signal positioning method according to claim 4, wherein The determining a target matching signal in the time-domain underwater acoustic signal image based on the matching signal region includes: Performing spatial extension processing on the matching signal region to obtain an extended image; sliding the signal template image step by step within the extended image to determine the target matching signal.

6. The underwater acoustic signal positioning method according to claim 4, characterized in that, The sequentially sliding each of the signal template images step by step within the time-domain underwater acoustic signal image for signal retrieval includes: Detecting a field feature of the target to be measured; According to the field feature, reading a field label carried by each of the signal template images, and determining a field label that matches the field feature; Sequentially sliding the signal template image carrying the field label that matches the field feature step by step within the time-domain underwater acoustic signal image for signal retrieval.

7. The underwater acoustic signal positioning method according to any one of claims 1 to 6, characterized in that, The performing signal positioning according to the target signal image to generate an underwater acoustic positioning result of the target to be measured includes: Performing convolution processing on the target signal image, and determining a plurality of signal point positions based on a convolution result obtained by the processing; Construct a hyperbolic positioning model according to the element position information of the hydrophone array; the hyperbolic positioning model is used to indicate the mapping relationship between the distances between a signal point and each element in the hydrophone array and the sound signal propagation time; Utilize the hyperbolic positioning model to fit the target signal position according to the signal point position, and calculate the azimuth angle and distance of the measured target relative to the hydrophone array according to the target signal position; the underwater acoustic positioning result includes the azimuth angle and the distance.

8. The underwater acoustic signal positioning method according to claim 7, characterized in that, The performing convolution processing on the target signal image includes: Obtain the signal distribution feature information of a signal template image that matches the target signal image; Based on the signal distribution feature information, determine a corresponding convolution kernel, and perform convolution processing on the target signal image based on the convolution kernel.

9. An underwater acoustic signal positioning device, characterized in that, Includes: A signal processing module, configured to obtain the underwater acoustic signal of the measured target received by the hydrophone array, perform signal processing on the underwater acoustic signal, and obtain a time-domain underwater acoustic signal image; A template generation module, configured to determine the detection range of the hydrophone array, and generate multiple signal template images according to the respective template position information located within the detection range; The signal template image matches the template position information; A signal retrieval module, configured to perform signal retrieval on the time-domain underwater acoustic signal image based on each of the signal template images, and obtain a target signal image that matches at least one of the signal template images; A positioning module, configured to perform signal positioning according to the target signal image, and generate an underwater acoustic positioning result of the measured target.

10. A storage medium, characterized in that, A computer program is stored in the storage medium, wherein the computer program is configured to execute the underwater acoustic signal positioning method according to any one of claims 1 to 8 when running.

Images