Phase-retrieval-based multi-aperture high-frequency underwater acoustic imaging method, device and system

Abstract

The application discloses a multi-sub-aperture high-frequency underwater acoustic imaging method, device and system based on phase recovery. The method comprises the following steps: acquiring multi-sub-aperture echo signals of a target to be tested collected by an imaging sonar; performing two-dimensional Fourier transform on the echo signals, multiplying a reference function to perform matched filtering, and then performing Stolt interpolation operation to obtain preprocessed multi-sub-aperture spectra of the target to be tested; then, a window function is constructed in combination with each sub-aperture position, and inverse Fourier transform is performed on each sub-aperture spectrum to obtain a corresponding low-resolution image; finally, a phase recovery algorithm is used to synthesize high-resolution target reconstruction images from the low-resolution images corresponding to the multiple sub-apertures. According to the embodiment of the application, the reconstruction resolution of the underwater target can be improved, and the calculation accuracy can be improved through iterative optimization, so that the actual application requirements of high-frequency imaging in complex water areas can be met.

Description

Technical Field

[0001] This application belongs to the field of underwater acoustic imaging technology, and in particular relates to a multi-aperture underwater acoustic high-frequency imaging method, device and system based on phase retrieval. Background Technology

[0002] Underwater acoustic imaging is an important means of underwater target identification and detection. Currently, related technologies typically utilize multibeam sonar or synthetic aperture sonar to actively detect and obtain acoustic images containing both the background and the target through high-frequency sonar. However, for underwater targets with fine features and small-scale complex structures in actual lake and ocean scenarios, the measurement process struggles to dynamically adapt to complex underwater noise due to diverse sound field scattering mechanisms, complex and variable scattered sound fields, and severe acoustic channel distortion. This results in low target imaging resolution and slow convergence of reconstruction algorithms in practical applications, further increasing the difficulty of target identification and detection and failing to meet the current practical application requirements for high-resolution imaging of complex targets in key water areas. Summary of the Invention

[0003] This application provides a multi-aperture underwater high-frequency imaging method, apparatus, and system based on phase retrieval.

[0004] In a first aspect, embodiments of this application provide a multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval, comprising: Acquire the echo signal at the sub-aperture position of the target under test acquired by imaging sonar; The echo signal is subjected to a two-dimensional Fourier transform, filtered by a reference function multiplication filter, and then subjected to Stolt interpolation to obtain the preprocessed sub-aperture spectrum. Perform an inverse Fourier transform on the spectrum of each sub-aperture to obtain the corresponding low-resolution image; By combining the location of each sub-aperture, a window function is constructed, and a phase retrieval algorithm is used to synthesize the low-resolution images corresponding to multiple sub-apertures into a high-resolution target reconstruction image.

[0005] Secondly, embodiments of this application provide a multi-aperture underwater acoustic high-frequency imaging device based on phase retrieval, comprising: The acquisition module is used to acquire the multi-aperture echo signal of the target under test acquired by the imaging sonar; The preprocessing module is used to perform a two-dimensional Fourier transform on the echo signal, filter it through a reference function multiplication filter, and then perform a Stolt interpolation operation to obtain the preprocessed multi-aperture spectrum. The low-resolution processing module is used to sample each coordinate point in the sonar image spectrum according to a pre-constructed multi-aperture window function, and perform inverse Fourier transform on the sampled spectrum to obtain a low-resolution sonar signal estimation map corresponding to the coordinate point. The high-resolution processing module is used to synthesize a high-resolution target image from multiple low-resolution sonar signal images corresponding to multiple coordinate points using a phase retrieval algorithm.

[0006] Thirdly, embodiments of this application provide an electronic device, which includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the steps of the multi-aperture underwater acoustic high-frequency imaging method based on phase recovery as described in any embodiment of the first aspect.

[0007] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the steps of the multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval as described in any embodiment of the first aspect.

[0008] Fifthly, embodiments of this application provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the multi-aperture underwater acoustic high-frequency imaging method based on phase recovery as provided in the first aspect of embodiments of this application.

[0009] In a sixth aspect, embodiments of this application provide a multi-aperture underwater acoustic high-frequency imaging system based on phase retrieval, including a first imaging sonar, a second imaging sonar, a third imaging sonar, a translational guide rail, and a multi-aperture underwater acoustic high-frequency imaging device based on phase retrieval as described in any embodiment of the second aspect. The translation guide rail is parallel to the echo receiving plane, and the multi-aperture underwater acoustic high-frequency imaging device based on phase recovery is communicatively connected to the first imaging sonar, the second imaging sonar, and the third imaging sonar respectively. The first imaging sonar is disposed on the side of the translation guide rail closer to the target under test, and is used to emit high-frequency sound waves to the target under test during the sound wave emission phase and receive echo signals during the echo reception phase. Both the second imaging sonar and the third imaging sonar are slidably mounted on the translation guide rail, and are used to move along a straight line on the translation guide rail during the echo reception phase to receive the echo signal.

[0010] The multi-aperture underwater acoustic high-frequency imaging method, apparatus, and system based on phase recovery of this application receive data transmitted back from imaging sonar, process it, and then display it in low-resolution graphics. The system runs graphics spectrum expansion and reconstruction algorithms to achieve super-resolution reconstruction of the sonar graphics and displays the final imaging results. This can improve the reconstruction resolution of underwater targets and improve the calculation accuracy through iterative optimization, so that it can meet the actual application requirements of high-frequency imaging in complex waters. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic flowchart of a multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval provided in an embodiment of this application; Figure 2 This is a schematic diagram of the underwater acoustic high-frequency imaging geometric model provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of a multi-aperture underwater acoustic high-frequency imaging device based on phase retrieval provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a multi-aperture underwater acoustic high-frequency imaging system based on phase retrieval provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0013] Figure label: A multi-aperture underwater acoustic high-frequency imaging device 300 based on phase retrieval includes an acquisition module 301, a preprocessing module 302, a low-resolution processing module 303, and a high-resolution processing module 304. Electronic device 500, processor 501, memory 502, communication interface 503, bus 510. Detailed Implementation

[0014] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0015] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0016] It should be noted that the acquisition, storage, use, and processing of data in this application embodiment all comply with the relevant provisions of national laws and regulations.

[0017] Underwater acoustic imaging is an important means of underwater target identification and detection. Currently, related technologies typically utilize multibeam sonar or synthetic aperture sonar to actively detect and obtain acoustic images containing both the background and the target through high-frequency sonar. However, for underwater targets with fine features and small-scale complex structures in actual lake and ocean scenarios, the measurement process struggles to dynamically adapt to complex underwater noise due to diverse sound field scattering mechanisms, complex and variable scattered sound fields, and severe acoustic channel distortion. This results in low target imaging resolution and slow convergence of reconstruction algorithms in practical applications, further increasing the difficulty of target identification and detection and failing to meet the current practical application requirements for high-resolution imaging of complex targets in key water areas.

[0018] To address the problems in the related technologies, this application provides a multi-aperture underwater acoustic high-frequency imaging method, apparatus, and system based on phase recovery.

[0019] The multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0020] Figure 1 A schematic flowchart of a multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval, according to an embodiment of this application, is shown. Figure 1 As shown, the multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval may specifically include the following steps: S101. Acquire the echo signal at the sub-aperture position of the target under test acquired by the imaging sonar; S102. Perform a two-dimensional Fourier transform on the echo signal, perform matched filtering by multiplying with a reference function, and then perform Stolt interpolation to obtain the preprocessed sub-aperture spectrum. S103. Perform an inverse Fourier transform on the spectrum of each sub-aperture to obtain the corresponding low-resolution image; S104. Combine the positions of each sub-aperture to construct a window function, and use the phase retrieval algorithm to synthesize the low-resolution images corresponding to multiple sub-apertures into a high-resolution target reconstruction image.

[0021] Therefore, the data received from the imaging sonar is processed and displayed in low-resolution graphics. Then, the graphics spectrum expansion and reconstruction algorithm is run to achieve super-resolution reconstruction of the sonar image and display the final imaging result. This can improve the reconstruction resolution of underwater targets. At the same time, the computational accuracy is improved through iterative optimization, so that it can meet the actual application requirements of high-frequency imaging in complex waters.

[0022] The specific implementation methods for each of the above steps are described below.

[0023] In some embodiments, a high-frequency underwater acoustic imaging geometric model is constructed, such as Figure 2 As shown, at time At that time, the imaging sonar was located at position The target P to be tested is located at coordinates The initial distance, or slant range, between the imaging sonar and the target P is denoted as... The speed of the sonar is .

[0024] but, At time t, the distance between the imaging sonar and the target P can be written as: .

[0025] When a sonar, acting as a sound wave source, emits a linear frequency modulated signal during the sound wave emission phase, the echo signal received by the sonar during the echo reception phase can be expressed as: ; in, It is a complex constant. The speed at which sound signals propagate. Off-center For distance envelope, For directional envelope, The frequency modulation rate of the acoustic signal. Indicates the center frequency of the sonar carrier. Represents the imaginary unit. Indicates distance in time.

[0026] Furthermore, in some embodiments, the echo signal of the target under test acquired by the imaging sonar is... Then, in S102, the echo signal is converted to the two-dimensional frequency domain through a two-dimensional Fourier transform, that is: ; in, It is a complex constant. The center frequency of the azimuth Doppler is... For the range envelope spectrum, This is the azimuth envelope spectrum. The frequency domain phase obtained after Fourier transform can be expressed as: .

[0027] Furthermore, the phase of the reference function multiplication filter is defined as: .

[0028] After reference function multiplication filtering (RFM), the residual phase of the echo signal can be approximated as: .

[0029] It is understandable, based on the factors in the above formula. The phase is zero at the reference distance, but still exists at other distances.

[0030] Furthermore, in some embodiments, the phase data in the two-dimensional frequency domain is changed by using a distance-frequency axis transformation through a Stolt interpolation operation.

[0031] The radical factor in the above formula is derived from the distance frequency after translation and transformation. Replacement, i.e.: .

[0032] After Stolt mapping, the residual phase of the signal becomes: .

[0033] The above equation shows that the residual phase is related to the range frequency. The linear relationship means that the Stolt mapping can effectively remove the higher-order phase terms of the signal and complete residual range compression. At this point, the azimuth envelope can be written as: .

[0034] The signal after Stolt mapping can be written as: .

[0035] Thus, the preprocessing of the echo signal was completed through two-dimensional Fourier transform, reference function multiplication, and Stolt interpolation, resulting in the preprocessed sonar image spectrum.

[0036] Furthermore, in some embodiments, in S103, an aperture window function is defined. for: ; in, The pre-defined pixel distance radius.

[0037] The first in the sonar image spectrum line, number Taking the center coordinate position as an example, according to the set aperture window function... First, analyze the spectrum of the sonar image. Window sampling is performed, followed by inverse Fourier transform of the sampled spectrum to obtain a low-resolution intensity image of the corresponding location. This refers to a low-resolution sonar signal map.

[0038] Specifically, a low-resolution sonar signal map can be represented as: ; in, The Cartesian coordinate system representing the two-dimensional image plane. It is the imaginary unit.

[0039] Therefore, for coordinates at different locations By repeating the above steps, multiple low-resolution sonar images of the corresponding locations can be generated.

[0040] Furthermore, in S104, high-resolution reconstruction is performed using a phase retrieval algorithm based on the obtained multiple low-resolution sonar signal images. It should be noted that the core of the phase retrieval algorithm in this embodiment is to utilize the Fourier transform relationship between the spatial and frequency domains. By adding constraints in the spatial and frequency domains and performing alternating iterations, not only can phase information be recovered, but also high-frequency image information implied in the low-frequency images at different locations can be moved to their original correct positions. This allows for the synthesis of a high-resolution image from a series of low-resolution images, continuously approximating and converging to the true value of the target image. This process can be considered a non-convex optimization problem. .

[0041] Specifically, the following steps A to D are executed iteratively until a preset termination condition is met to obtain the high-resolution spectrum of the target image: Step A: For the low-resolution sonar signal map of each sub-aperture, the high-resolution target image is initially guessed to obtain the initial guessed image. and its corresponding initial guessed image spectrum Step B: Calculate the corresponding low-resolution estimated image based on the initial guessed image and its corresponding initial guessed image spectrum; Step C: Update the amplitude information of the low-resolution estimated image based on the low-resolution sonar signal map that matches the sub-aperture position of the low-resolution estimated image to obtain the updated low-resolution estimated image; Step D: Fourier transform the updated low-resolution estimated image to the frequency domain and update the corresponding initial guessed image spectrum.

[0042] In specific implementation, based on the initial guessed image and its corresponding initial guessed image spectrum, the initial guessed image is windowed using an aperture window function according to the following formula, and then subjected to inverse Fourier transform to obtain the corresponding low-resolution estimated image: ; in, Indicates the first line, number Initial guess of the image spectrum for column coordinates; This represents the aperture window function.

[0043] In other words, the initial guessed image is sampled using the aperture window function at the corresponding location, and then subjected to an inverse Fourier transform to obtain the corresponding low-resolution estimated image. .

[0044] In practice, the updated low-resolution estimated image is calculated according to the following formula: .

[0045] In other words, while keeping the phase information of the low-resolution estimated image unchanged, the corresponding low-resolution sonar signal map is used. Update its amplitude information to obtain an updated low-resolution estimated image. .

[0046] In practice, the updated low-resolution estimated image is Fourier transformed into the frequency domain, and the initial guessed image spectrum of the aperture window at the corresponding location is updated, while other regions remain unchanged. .

[0047] Repeating the above steps until all low-resolution images are traversed, i.e., until all low-resolution images are completely updated, can be considered as completing one iteration. Repeating this process i times continues until the reconstruction algorithm converges, thus obtaining the high-resolution spectrum of the target image.

[0048] As an optional embodiment, the preset termination condition includes: the error is less than a preset threshold; The error is: ; in, Indicates the first line, number The low-resolution image corresponding to the aperture window region centered at coordinates; The Cartesian coordinate system representing the two-dimensional image plane; Indicates the first The low-resolution estimated image of the next iteration.

[0049] That is, error If the value is less than the set threshold, the loop will exit and the reconstruction process will be completed.

[0050] Furthermore, in some embodiments, an inverse Fourier transform is performed on the high-resolution spectrum of the target image to obtain a high-resolution target image. That is, the image is then transformed back to the spatial domain using an inverse Fourier transform to obtain a high-resolution target image.

[0051] As can be seen, the embodiments of this application have the following beneficial technical effects: Firstly, it has strong robustness: by employing an aperture window function and assigning overlapping window regions, the coherence of the signal is increased, thereby improving noise resistance and avoiding the deviation problem caused by noise in traditional methods. Secondly, it has high resolution: it uses phase retrieval method for iterative optimization to continuously correct the details of the target image, improve imaging accuracy, and avoid the problem of traditional methods getting trapped in local optima; Third, it can be applied to complex underwater environments: it can be used in scenarios such as marine exploration, port monitoring, underwater communication and navigation, and target identification and tracking.

[0052] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] Based on the same technical concept, and corresponding to any of the above embodiments, this application also provides a multi-aperture underwater acoustic high-frequency imaging device 300 based on phase recovery.

[0054] like Figure 3 As shown, the phase retrieval-based multi-aperture underwater acoustic high-frequency imaging device 300 may include: The acquisition module 301 is used to acquire the multi-aperture echo signal of the target under test collected by the imaging sonar; The preprocessing module 302 is used to perform a two-dimensional Fourier transform on the echo signal, filter it through a reference function multiplication filter, and then perform a Stolt interpolation operation to obtain the preprocessed multi-aperture spectrum. The low-resolution processing module 303 is used to sample each coordinate point in the sonar image spectrum according to a pre-constructed multi-aperture window function, and perform inverse Fourier transform on the sampled spectrum to obtain a low-resolution sonar signal estimation map corresponding to the coordinate point. The high-resolution processing module 304 is used to synthesize a high-resolution target image from multiple low-resolution sonar signal images corresponding to multiple coordinate points using a phase recovery algorithm.

[0055] It should be noted that, for ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0056] The apparatus of the above embodiments is used to implement the corresponding multi-aperture underwater acoustic high-frequency imaging method based on phase recovery in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0057] Furthermore, this application also provides a multi-aperture underwater acoustic high-frequency imaging system based on phase retrieval.

[0058] Figure 4 A schematic diagram of the structure of a phase retrieval-based multi-aperture underwater acoustic high-frequency imaging system according to an embodiment of this application is shown. Figure 4 As shown, the phase-recovery-based multi-aperture underwater acoustic high-frequency imaging system includes: a first imaging sonar, a second imaging sonar, a third imaging sonar, a translation guide rail, and a corresponding phase-recovery-based multi-aperture underwater acoustic high-frequency imaging device as described in any of the foregoing embodiments.

[0059] The translation guide rail is parallel to the echo receiving plane, and the multi-aperture underwater acoustic high-frequency imaging device based on phase recovery is communicatively connected to the first imaging sonar, the second imaging sonar, and the third imaging sonar.

[0060] Specifically, the first imaging sonar is positioned on the side of the translation guide rail closer to the target under test, and is used to emit high-frequency sound waves to the target under test during the sound wave emission phase and receive echo signals during the echo reception phase.

[0061] Specifically, both the second imaging sonar and the third imaging sonar are slidably mounted on the translation guide rail, and are used to move linearly along the translation guide rail during the echo reception phase to receive echo signals.

[0062] In other words, the multi-aperture underwater acoustic high-frequency imaging system based on phase retrieval in this application mainly consists of three imaging sonars, a translation guide rail, a data processing terminal (i.e., a multi-aperture underwater acoustic high-frequency imaging device based on phase retrieval), connecting lines, etc. Among them, the first imaging sonar 1 is the acoustic wave emission source of the system, during the acoustic wave emission phase ( Figure 4 (a) Imaging sonar 1 emits high-frequency sound waves toward the target to achieve active imaging; during the echo reception phase ( Figure 4 (b) Imaging sonar 1 also participates in receiving the echo signal from the center position. Imaging sonar 2 and imaging sonar 3 are the echo signal receivers of the system, during the echo reception phase ( Figure 4 (b) The two sonars sequentially receive echo signals at different locations. Both sonars disable their acoustic transmission function, retaining only their reception function. A translation guide is used to move imaging sonar 2 and imaging sonar 3 along a straight line on the echo reception plane, thereby achieving scanning echo reception. The data processing terminal receives data from each imaging sonar, processes it, and then performs low-resolution graphical display. It then runs a graphic spectrum expansion and reconstruction algorithm to achieve super-resolution reconstruction of the sonar images and displays the final imaging results. The low-resolution imaging results can be displayed in real time, while the high-resolution processing results require iterative reconstruction over a period of time.

[0063] Based on the same technical concept, corresponding to any of the above embodiments, this application also provides an electronic device.

[0064] Figure 5 A schematic diagram of a more specific electronic device hardware structure provided in this embodiment is shown.

[0065] The electronic device 500 may include a processor 501 and a memory 502 storing computer program instructions.

[0066] Specifically, the processor 501 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0067] Memory 502 may include mass storage for data or instructions. For example, and not limitingly, memory 502 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 502 may include removable or non-removable (or fixed) media. Where appropriate, memory 502 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 502 is non-volatile solid-state memory.

[0068] In certain embodiments, the memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.

[0069] The processor 501 reads and executes computer program instructions stored in the memory 502 to implement any of the phase recovery-based multi-aperture underwater acoustic high-frequency imaging methods in the above embodiments.

[0070] In some examples, the electronic device 500 may also include a communication interface 503 and a bus 510. For example, Figure 5 As shown, the processor 501, memory 502, and communication interface 503 are connected through bus 510 and complete communication with each other.

[0071] The communication interface 503 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0072] Bus 510 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not as a limitation, bus 510 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 510 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0073] For example, the electronic device 500 can be a mobile phone, tablet computer, laptop computer, handheld computer, in-vehicle electronic device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc.

[0074] Based on the same technical concept, corresponding to any of the methods in the above embodiments, this application also provides a non-transitory computer-readable storage medium. This computer-readable storage medium stores computer program instructions; when executed by a processor, these computer program instructions implement any of the phase retrieval-based multi-aperture underwater acoustic high-frequency imaging methods in the above embodiments. Examples of computer-readable storage media include non-transitory computer-readable storage media such as portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, etc.

[0075] Based on the same technical concept, corresponding to any of the above embodiments, this application also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer to cause the computer and / or the processor to perform the phase retrieval-based multi-aperture underwater acoustic high-frequency imaging method. Corresponding to the execution entity for each step in each embodiment of the phase retrieval-based multi-aperture underwater acoustic high-frequency imaging method, the processor executing the corresponding step can belong to the corresponding execution entity.

[0076] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0077] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0078] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0079] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0080] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval, characterized in that, include: Acquire the echo signal at the sub-aperture location of the target under test acquired by imaging sonar; The echo signal is subjected to a two-dimensional Fourier transform, and matched filtering is performed by multiplying with a reference function. Then, the Stolt interpolation operation is performed to obtain the preprocessed sub-aperture spectrum. Perform an inverse Fourier transform on the spectrum of each sub-aperture to obtain the corresponding low-resolution image; By combining the location of each sub-aperture, a window function is constructed, and a phase retrieval algorithm is used to synthesize the low-resolution images corresponding to multiple sub-apertures into a high-resolution target reconstruction image.

2. The method according to claim 1, characterized in that, The step of using a phase retrieval algorithm to synthesize a high-resolution target image from low-resolution images corresponding to multiple sub-apertures includes: Iteratively execute steps A to D until a preset termination condition is met to obtain the high-resolution spectrum of the target image: Step A: For the low-resolution images corresponding to each sub-aperture, guess the initial high-resolution target image and obtain the spectrum of the initial guessed image corresponding to it; Step B: Calculate the corresponding low-resolution estimated image based on the spectrum of the initial guessed image and the corresponding aperture window function; Step C: Update the amplitude information of the low-resolution estimated image based on the image that matches the sub-aperture position of the low-resolution estimated image to obtain the updated low-resolution estimated image; Step D: Fourier transform the updated low-resolution estimated image to the frequency domain and update the image spectrum of the aperture window at the corresponding location; An inverse Fourier transform is performed on the high-resolution spectrum of the target image to obtain a high-resolution reconstructed target image.

3. The method according to claim 2, characterized in that, The preset termination condition includes: the error is less than a preset threshold; The error is: ； in, Indicates the first line, number The low-resolution image corresponding to the aperture window region centered at coordinates; The Cartesian coordinate system representing the two-dimensional image plane; Indicates the first The low-resolution estimated image of the next iteration.

4. The method according to claim 3, characterized in that, The step of calculating the corresponding low-resolution estimated image based on the initial guessed image and its corresponding initial guessed image spectrum includes: Based on the initial guessed image and its corresponding spectrum, the initial guessed image is sampled using an aperture window function according to the following formula, and then subjected to inverse Fourier transform to obtain the corresponding low-resolution estimated image: ； in, Indicates the first line, number The initial guessed image spectrum is listed with the center coordinates as the column; This represents the aperture window function.

5. The method according to claim 4, characterized in that, The step of updating the amplitude information of the low-resolution estimated image based on the low-resolution sonar signal map that matches the coordinate points of the low-resolution estimated image to obtain the updated low-resolution estimated image includes: The updated low-resolution estimated image is calculated using the following formula: 。 6. A multi-aperture underwater acoustic high-frequency imaging device based on phase retrieval, characterized in that, include: The acquisition module is used to acquire the multi-aperture echo signal of the target under test acquired by the imaging sonar; The preprocessing module is used to perform a two-dimensional Fourier transform on the echo signal, filter it through a reference function multiplication filter, and then perform a Stolt interpolation operation to obtain the preprocessed multi-aperture spectrum. The low-resolution processing module is used to sample each coordinate point in the sonar image spectrum according to a pre-constructed multi-aperture window function, and perform inverse Fourier transform on the sampled spectrum to obtain a low-resolution sonar signal estimation map corresponding to the coordinate point. The high-resolution processing module is used to synthesize a high-resolution target image from low-resolution sonar signal images corresponding to multiple coordinate points using a phase retrieval algorithm.

7. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; when the processor invokes the computer program instructions, it implements the multi-aperture underwater acoustic high-frequency imaging method based on phase recovery as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when invoked by a processor, implement the multi-aperture underwater acoustic high-frequency imaging method based on phase recovery as described in any one of claims 1-5.

9. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the multi-aperture underwater acoustic high-frequency imaging method based on phase retrieval as described in any one of claims 1-5.

10. A multi-aperture underwater acoustic high-frequency imaging system based on phase retrieval, characterized in that, It includes a first imaging sonar, a second imaging sonar, a third imaging sonar, a translation guide rail, and a multi-aperture underwater acoustic high-frequency imaging device based on phase recovery as described in claim 6; The translation guide rail is parallel to the echo receiving plane, and the multi-aperture underwater acoustic high-frequency imaging device based on phase recovery is communicatively connected to the first imaging sonar, the second imaging sonar, and the third imaging sonar respectively. The first imaging sonar is disposed on the side of the translation guide rail closer to the target under test, and is used to emit high-frequency sound waves to the target under test during the sound wave emission phase and receive echo signals during the echo reception phase. Both the second imaging sonar and the third imaging sonar are slidably mounted on the translation guide rail, and are used to move along a straight line on the translation guide rail during the echo reception phase to receive the echo signal.

Images