A method, device, and medium for mode decomposition of atmospheric turbulence distorted speckle

Abstract

This invention relates to the field of optical communication, specifically providing a mode decomposition method, computer equipment, and medium for atmospheric turbulence-induced distortion of light spots. The method uses Singular Value Decomposition (SVD), sets a target similarity value between the reconstructed light spot and the original distorted light spot, determines the number of singular values ​​based on this similarity value, and thus determines the number of mode decompositions. This method is not limited to specific mode types and can directly decompose the distorted light spot into a certain number of sub-mode combinations, effectively decomposing the distorted light spot into a certain number of mode combinations. The reconstructed distorted light spot has a high similarity to the original distorted light spot, which is of great research significance for realizing atmospheric turbulence correction based on multi-plane optical conversion.

Description

Technical Field

[0001] This invention relates to the field of optical communication, and in particular to a method for mode decomposition of atmospheric turbulence-distorted light spots, a computer device, and a storage medium. Background Technology

[0002] Space laser communication plays an important role in the construction of 6G networks. However, atmospheric turbulence can affect the stability of coupling in space-to-ground laser communication links, so it is necessary to correct for it.

[0003] MPLC (Multi-Plane Light Conversion) devices are free-space devices that can achieve arbitrary mode conversion through multiple reflections on a continuous phase screen. Compared with traditional adaptive optics, they have the advantages of simple structure, small size, and passive operation. They also exhibit good robustness under different turbulent conditions and are conducive to the miniaturization of laser communication terminals. They have great development potential and application prospects in adaptive adjustment of laser communication. Therefore, the distorted light spot caused by atmospheric turbulence can be decomposed into a combination of modes, then converted into a fundamental mode optical array using MPLC, and finally coupled into a single-mode fiber, effectively improving the coupling efficiency of spatial light into single-mode fiber.

[0004] The aforementioned system for atmospheric turbulence correction based on MPLC first requires decomposing the mode composition of the distorted light spot affected by atmospheric turbulence. To address this mode decomposition, researchers proposed representing the distorted light spot using a combination of Hermite-Gaussian (HG) modes. However, the order of the HG modes required to compose the distorted light spot cannot be predicted in advance. Therefore, the reconstructed distorted light spot has low similarity to the original distorted light spot, resulting in unsatisfactory decomposition and impacting the mode conversion efficiency of the MPLC, ultimately affecting the coupling efficiency of the single-mode fiber.

[0005] For mode decomposition of turbulent distortion light spots, HG modes are currently commonly used as the basis, and the decomposition is represented by a combination of the fundamental mode and higher-order modes of the HG mode. However, when constructing turbulent distortion light spots using HG modes, algorithmic limitations necessitate a pre-defined multi-order HG mode library. Modes are selected from this library for decomposition. Since HG modes have infinitely many orders and constitute a maximally independent set of vectors, the required HG mode order cannot be predicted in advance. Modes not included in the pre-defined HG mode library cannot be represented using it. Consequently, the similarity between the decomposed and reconstructed light spot and the original light spot is low, resulting in unsatisfactory decomposition performance. This also affects the conversion efficiency when inputting the decomposed light spot into the MPLC for mode conversion, ultimately impacting the coupling efficiency. Summary of the Invention

[0006] In view of this, embodiments of the present invention provide a method for mode decomposition of atmospheric turbulence distortion light spots, a computer device, and a storage medium.

[0007] In a first aspect, the present invention provides a method for mode decomposition of atmospheric turbulence-distorted light spots, comprising:

[0008] By passing a Gaussian beam through a turbulent phase screen, the wavefront of the Gaussian beam spot is distorted, resulting in a distorted spot.

[0009] Singular value decomposition is performed on the distorted spot, and the number of singular values ​​selected is determined based on the target similarity value.

[0010] The number of patterns generated is equal to the number of singular values ​​selected, and the corresponding patterns are generated accordingly.

[0011] As an optional approach, the method of passing the Gaussian beam through a turbulent phase screen to distort the wavefront of the beam spot and generate a distorted beam spot includes:

[0012] Atmospheric turbulence was simulated using the multi-phase screen method, and the phase distribution of atmospheric disturbances was obtained using the power spectrum inversion method.

[0013] Passing a Gaussian light spot through an atmospheric turbulence phase screen yields a distorted light spot E, where E is an m A matrix of size n has a rank of r.

[0014] As an optional approach, the singular value decomposition of the distorted spot, and the determination of the number of selected singular values ​​based on the target similarity value, includes:

[0015] The distorted light spot E is first subjected to singular value decomposition to obtain the left singular matrix U, the right singular matrix V, and the singular value matrix S of the distorted light spot, wherein the left singular matrix U is m An m-order matrix, wherein the right singular matrix V is n The n-order matrix, the singular value matrix S is m An n-order diagonal matrix has singular values ​​δ1, δ2, ..., δr distributed along its diagonal, arranged in descending order. The singular value decomposition process is as follows (1):

[0016] (1)

[0017] Initialize the parameters of SVD pattern decomposition, set the order of singular value decomposition, set the number of singular values ​​K to 1, set the target similarity value ALFA, and calculate the similarity value α as follows (2):

[0018] (2)

[0019] Where E is the distorted spot, E' is the reconstructed spot, and the similarity value α represents the degree of similarity between the distorted spot and the reconstructed spot. The larger the value, the higher the degree of similarity.

[0020] Take the first K singular values ​​from the singular value matrix S to generate a new singular value matrix S. K Take the first K columns of the left singular matrix U to form a new left singular matrix U. K Take the first K rows of the right singular matrix V to form a new right singular matrix V. K , among which, U K For m A K-order matrix, S K For K A K-order matrix, V K For K n-order matrix;

[0021] The distorted spot E is reconstructed into E', and the reconstruction process is as follows (3):

[0022] (3)

[0023] The similarity value between the distorted spot E and the reconstructed spot E' is calculated using formula (3) and denoted as α.

[0024] Determine whether the similarity value α satisfies α≥ALFA;

[0025] If the similarity value α does not satisfy α≥ALFA, then increase the number of singular values ​​K by 1 until it satisfies the condition.

[0026] As an optional approach, the number of decomposition-based patterns is equal to the number of selected singular values, generating corresponding patterns, including:

[0027] The number of singular values ​​obtained from the singular value decomposition is K;

[0028] Singular value matrix S K For formula (4):

[0029] (4)

[0030] The singular value matrix S K In the matrix, except for the element at position coordinate (i, i), all other elements are set to 0, forming K submatrices S. i S i The expression is shown in the following formula (5):

[0031] (5)

[0032] According to the definition of matrix addition, the singular value matrix S K It is decomposed into the sum of K submatrices, and the decomposition process is shown in formula (6):

[0033] (6)

[0034] The reconstructed light spot E' is written as formula (7):

[0035] (7)

[0036] According to equation (7), K patterns E1~E1 are defined. K Reconstructing the light spot E', formula (8):

[0037] (8)

[0038] Various modes E i For formula (9):

[0039] (9).

[0040] In a second aspect, embodiments of the present invention provide a computer device, comprising:

[0041] At least one processor; and

[0042] A memory communicatively connected to the at least one processor; wherein,

[0043] The memory stores instructions that can be executed by the at least one processor, which, when executed, enable the at least one processor to perform the above-described method for mode decomposition of atmospheric turbulence-distorted light spots.

[0044] Thirdly, the present invention provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the above-described method for mode decomposition of atmospheric turbulence-distorted light spots.

[0045] This invention provides a mode decomposition method, computer equipment, and medium for atmospheric turbulence-induced distorted light spots. Using Singular Value Decomposition (SVD), a predefined similarity value between the reconstructed light spot and the original distorted light spot is set. Based on this similarity value, the number of singular values ​​is determined, thereby determining the number of mode decompositions. This method is not limited to specific mode types and can directly decompose distorted light spots into a certain number of sub-mode combinations. It effectively decomposes distorted light spots into a certain number of mode combinations, and the reconstructed distorted light spot has a high similarity to the original distorted light spot. This method has significant research value for realizing atmospheric turbulence correction based on multi-plane optical conversion. Attached Figure Description

[0046] Figure 1 The flowchart below shows a method for decomposing atmospheric turbulence-distorted light spots in an embodiment of the present invention.

[0047] Figure 2 This is a flowchart illustrating the method for determining the number of singular values ​​in a mode decomposition method for atmospheric turbulence distortion spot, as provided in this embodiment of the invention.

[0048] Figure 3 This is a schematic diagram of the process of solving each mode in a mode decomposition method for atmospheric turbulence distortion spot provided in an embodiment of the present invention;

[0049] Figure 4 This is an example schematic diagram of the turbulent distortion spot and the various model diagrams obtained after decomposition in the method for mode decomposition of atmospheric turbulent distortion spot provided in an embodiment of the present invention.

[0050] Figure 5 This invention provides a structural block diagram of a computer device in an embodiment of the invention. Detailed Implementation

[0051] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0052] The terms "first," "second," "third," "fourth," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0053] Combination Figure 1 As shown, this embodiment of the invention provides a mode decomposition method for atmospheric turbulence-distorted light spots, comprising:

[0054] S101. Pass the Gaussian beam through the turbulent phase screen to distort the wavefront of the Gaussian beam spot, thus producing a distorted spot.

[0055] S102. Perform singular value decomposition on the distorted spot and determine the number of singular values ​​to be selected based on the target similarity value.

[0056] S103. The number of decomposition-based patterns is equal to the number of selected singular values, and the corresponding patterns are generated.

[0057] This invention provides a mode decomposition method for atmospheric turbulence distortion spot. It uses Singular Value Decomposition (SVD), sets a target similarity value between the reconstructed spot and the original distorted spot, determines the number of singular values ​​based on this similarity value, and then determines the number of mode decompositions. This method is not limited to specific mode types and can directly decompose the distorted spot into a certain number of sub-mode combinations. It effectively decomposes the distorted spot into a certain number of mode combinations, and the reconstructed distorted spot has a high similarity to the original distorted spot. This method has significant research value for realizing atmospheric turbulence correction based on multi-plane optical conversion.

[0058] In S101, the process of passing the Gaussian beam through the turbulent phase screen to distort the wavefront of the beam spot and generate a distorted beam spot includes:

[0059] Atmospheric turbulence was simulated using the multi-phase screen method, and the phase distribution of atmospheric disturbances was obtained using the power spectrum inversion method.

[0060] Passing a Gaussian light spot through an atmospheric turbulence phase screen yields a distorted light spot E, where E is an m A matrix of size n has a rank of r.

[0061] Combination Figure 2 As shown, in S102, the singular value decomposition of the distorted spot and the determination of the number of selected singular values ​​based on the target similarity value include:

[0062] S1021. First, perform singular value decomposition on the distorted light spot E to obtain the left singular matrix U, the right singular matrix V, and the singular value matrix S of the distorted light spot, wherein the left singular matrix U is m An m-order matrix, wherein the right singular matrix V is n The n-order matrix, the singular value matrix S is m An n-order diagonal matrix has singular values ​​δ1, δ2, ..., δr distributed along its diagonal, arranged in descending order. The singular value decomposition process is as follows (1):

[0063] (1)

[0064] S1022. Initialize the parameters of SVD pattern decomposition, set the order of singular value decomposition, the number of singular values ​​K selected to 1, set the target similarity value ALFA, and calculate the similarity value α as follows (2):

[0065] (2)

[0066] Where E is the distorted spot, E' is the reconstructed spot, and the similarity value α represents the degree of similarity between the distorted spot and the reconstructed spot. The larger the value, the higher the degree of similarity.

[0067] S1023. Take the first K singular values ​​from the singular value matrix S to generate a new singular value matrix S. K Take the first K columns of the left singular matrix U to form a new left singular matrix U. K Take the first K rows of the right singular matrix V to form a new right singular matrix V. K , among which, U K For m A K-order matrix, S K For K A K-order matrix, V K For K n-order matrix;

[0068] S1024. Reconstruct the distorted spot E into E'. The reconstruction process is as follows (3):

[0069] (3)

[0070] S1025. Calculate the similarity value between the distorted spot E and the reconstructed spot E' using formula (3), denoted as α.

[0071] S1026. Determine whether the similarity value α satisfies α≥ALFA;

[0072] If the similarity value α does not satisfy α≥ALFA, then increase the number of singular values ​​K by 1 and repeat S1023 to S1026 until it is satisfied. If the similarity value α satisfies α≥ALFA, then start executing S103.

[0073] Combination Figure 3 As shown, in S103, the number of decomposition-based patterns is equal to the number of selected singular values, generating corresponding patterns, including:

[0074] S1031. The number of singular values ​​obtained from the singular value decomposition is K;

[0075] Singular value matrix S K For formula (4):

[0076] (4)

[0077] S1032, the singular value matrix S K In the matrix, except for the element at position coordinate (i, i), all other elements are set to 0, forming K submatrices S. i S i The expression is shown in the following formula (5):

[0078] (5)

[0079] According to the definition of matrix addition, the singular value matrix S K It is decomposed into the sum of K submatrices, and the decomposition process is shown in formula (6):

[0080] (6)

[0081] S1033, Reconstruct the light spot E' and write it as formula (7):

[0082] (7)

[0083] According to equation (7), K patterns E1~E1 are defined. K Reconstructing the light spot E', formula (8):

[0084] (8)

[0085] S1034, various modes E i For formula (9):

[0086] (9).

[0087] Combination Figure 4 As shown in the figure, the simulation results demonstrate that the method provided by this invention is practical and effective. Specifically, when a Gaussian beam passes through a turbulent phase screen obtained using the power spectrum inversion method, a distorted beam spot E is obtained, with a size of 512. The light spot distribution of 512,E is as follows Figure 4 As shown in section a. Then, singular value decomposition (SVD) was performed on the distorted spot, yielding the left singular matrix U, right singular matrix V, and singular value matrix S. Next, the parameters for initializing the SVD mode decomposition were determined: first, the order of the singular value decomposition, i.e., the number of selected singular values ​​K, was set to 1, and the target similarity value ALFA was set to 0.9995. After... Figure 2 The process of calculating the number of singular values ​​shown yields a required number of singular values, K, of 2. Based on the required number of singular values, K, obtained in the second step, the number of decomposition patterns is also determined to be 2. This is followed by... Figure 3 The steps shown generate various patterns, and the distribution of the patterns is as follows: Figure 4 As shown in parts b and c.

[0088] The mode decomposition method for atmospheric turbulence distortion spot provided by this invention has the following advantages:

[0089] (1) The singular value matrix obtained by SVD singular value decomposition is a diagonal matrix, with singular values ​​distributed from large to small on the diagonal. The magnitude of the singular value represents the contribution rate to the matrix. Therefore, this invention uses this method to delete smaller singular values, that is, modes with a smaller proportion, and retain larger singular values, thereby filtering out modes with a larger proportion, so that the reconstructed spot meets the target similarity value;

[0090] (2) Compared with traditional turbulent mode decomposition methods, the present invention can overcome the defect of not being able to accurately predict the required HG mode order and directly decompose the distorted spot into a certain number of mode combinations.

[0091] Compared with traditional mode decomposition methods based on HG mode, this method can effectively improve the similarity between the decomposed and reconstructed spot and the original spot, improve the mode conversion efficiency of MPLC, and ultimately improve the coupling efficiency of the turbulent spot to the single-mode fiber.

[0092] Accordingly, according to embodiments of the present invention, the present invention also provides a computer device, a readable storage medium, and a computer program product.

[0093] Figure 5 This is a schematic diagram of the structure of a computer device 12 provided in an embodiment of the present invention. Figure 5 A block diagram of an exemplary computer device 12 suitable for implementing embodiments of the present invention is shown. Figure 5 The computer device 12 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0094] like Figure 5 As shown, computer device 12 is represented in the form of a general-purpose computing device. Computer device 12 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0095] The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0096] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0097] Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0098] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 5 Not shown; usually referred to as a "hard drive"). Although Figure 5 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0099] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0100] Computer device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with computer device 12, and / or with any device that enables computer device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, computer device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0101] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the mode decomposition method for atmospheric turbulence distortion spot provided in the embodiments of the present invention.

[0102] This invention also provides a non-transitory computer-readable storage medium storing computer instructions, on which a computer program is stored, wherein the program, when executed by a processor, is the mode decomposition method for atmospheric turbulence distortion light spots provided in all embodiments of this application.

[0103] The computer storage medium of this invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0104] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0105] The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof. The computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0106] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for decomposing atmospheric turbulence-distorted light spots.

[0107] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0108] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for decomposing atmospheric turbulence-distorted light spots using a model, characterized in that, include: Passing a Gaussian beam through a turbulent phase screen distorts the wavefront of the beam's spot, producing a distorted spot, including: Atmospheric turbulence was simulated using the multi-phase screen method, and the phase distribution of atmospheric disturbances was obtained using the power spectrum inversion method. A Gaussian spot was passed through an atmospheric turbulence phase screen to obtain a distorted spot E, where E is an m... A matrix of size n has a rank of r. Singular value decomposition is performed on the distorted spot, and the number of selected singular values ​​is determined based on the target similarity value, including: The distorted light spot E is first subjected to singular value decomposition to obtain the left singular matrix U, the right singular matrix V, and the singular value matrix S of the distorted light spot, wherein the left singular matrix U is m An m-order matrix, wherein the right singular matrix V is n An n-order matrix, wherein the singular value matrix S is m An n-order diagonal matrix has singular values ​​δ1, δ2, ..., δr distributed along its diagonal, arranged in descending order. The singular value decomposition process is as follows (1): （1） Initialize the parameters of SVD pattern decomposition, set the order of singular value decomposition, set the number of singular values ​​K to 1, set the target similarity value ALFA, and calculate the similarity value α as follows (2): （2） Where E is the distorted spot, E' is the reconstructed spot, and the similarity value α represents the degree of similarity between the distorted spot and the reconstructed spot. The larger the value, the higher the degree of similarity. Take the first K singular values ​​from the singular value matrix S to generate a new singular value matrix S. K Take the first K columns of the left singular matrix U to form a new left singular matrix U. K Take the first K rows of the right singular matrix V to form a new right singular matrix V. K , among which, U K For m A K-order matrix, S K For K A K-order matrix, V K For K n-order matrix; The distorted spot E is reconstructed into E', and the reconstruction process is as follows (3): （3） The similarity value between the distorted spot E and the reconstructed spot E' is calculated using formula (3) and denoted as α; Determine whether the similarity value α satisfies α≥ALFA; If the similarity value α does not satisfy α≥ALFA, then increase the number of singular values ​​K by 1 until it satisfies the condition. Based on the fact that the number of decomposed patterns is equal to the number of selected singular values, corresponding patterns are generated, and the distorted spot is decomposed into multiple pattern combinations to reconstruct a distorted spot with high similarity to the original distorted spot.

2. The method for mode decomposition of atmospheric turbulence-distorted light spots according to claim 1, characterized in that, The number of decomposition-based patterns is equal to the number of selected singular values, generating corresponding patterns, including: The number of singular values ​​obtained from the singular value decomposition is K; Singular value matrix S K For formula (4): （4） The singular value matrix S K In the matrix, except for the element at position coordinate (i, i), all other elements are set to 0, forming K submatrices S. i S i The expression is shown in the following formula (5): （5） According to the definition of matrix addition, the singular value matrix S K It is decomposed into the sum of K submatrices, and the decomposition process is shown in formula (6): （6） The reconstructed light spot E' is written as formula (7): （7） According to equation (7), K patterns E1~E1 are defined. K Reconstructing the light spot E', formula (8): （8） Various modes E i Formula (9): （9）。 3. A computer device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the mode decomposition method for atmospheric turbulence distortion spot as described in any one of claims 1 to 2.

4. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the mode decomposition method for atmospheric turbulence distortion spot as described in any one of claims 1 to 2.

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