Mode selection analysis method and system for satellite-ground laser communication mode diversity technology, product and element manufacturing method

Abstract

The invention discloses a mode selection analysis method and system for a satellite-ground laser communication mode diversity technology, a product and an element manufacturing method, belongs to the technical field of space laser communication, and solves the problem that the prior art directly selects first several modes as a group of fixed orthogonal mode bases due to experience; therefore, the technical problem that the stability of a communication link is reduced due to the fact that the optimal performance cannot be kept in a dynamically changing channel is solved. The method comprises the steps of 1, constructing a dynamic turbulence data set; 2, performing dynamic mode decomposition on complex amplitude distribution of the degraded light spots in the dynamic turbulence data set to obtain instantaneous power proportions of the degraded light spots in different modes; and 3, carrying out statistical analysis on the instantaneous power proportions of the degraded light spots in different modes, and screening out an optimal fixed mode combination in combination with the target turbulence intensity. The invention is used for realizing efficient optical signal transmission.

Description

Technical Field

[0001] This invention relates to the field of space laser communication technology, and more specifically to a mode selection analysis method, system, product, and component manufacturing method for satellite-to-ground laser communication mode diversity technology. Background Technology

[0002] Space-to-ground laser communication, with its advantages of high capacity and high speed, has become a core transmission technology for next-generation space information networks. However, high-sensitivity laser communication receivers typically rely on effectively coupling the incident light wavefront into a single-mode fiber (SMF) to achieve efficient optical signal transmission. In practice, this coupling process is affected by various factors, including the relative motion of the communication terminals, wavefront distortion caused by atmospheric turbulence, internal displacement of optical components due to thermal expansion, and system jitter caused by mechanical vibration. These factors work together to prevent the incident light field from perfectly matching the fundamental mode of the SMF, causing most of the optical power to be coupled to higher-order modes and unable to be received by the SMF, thus limiting link stability. To suppress the effects of turbulence, mode diversity reception technology has been extensively studied. Its core component is a multiplane optical converter (usually abbreviated as MPLC). Generally, it uses a series of fixed phase plates to spatially separate different spatial modes (such as Hermitian-Gaussian modes HGmn or Laguerre-Gaussian modes LPlm) in the incident distorted light field, and couples them separately into different single-mode optical fibers, thereby achieving diversity reception and compensating for signal fading.

[0003] Currently, the realization of MPLC phase screens is mainly based on two approaches: Spatial Light Modulator (SLM) and micro / nano fabrication technology. SLM is widely popular due to its ability to flexibly load arbitrary phase distributions. However, the linear polarization response characteristics and device size of SLM limit the application of MPLC devices. Therefore, MPLC design is usually based on micro / nano fabrication technology and still relies on a pre-selected set of fixed orthogonal mode bases. When MPLC is used as a spatial mode multiplexing / demultiplexing device, the first few modes are usually selected directly. For example, in the paper "Mode Selective 10-Mode Multiplexer based on Multi-Plane Light Conversion" published by Guillaume Labroille et al. at the OFC conference in 2016, the first 10 LP modes were directly selected. Later, Antonin Billaud et al. used this device to alleviate turbulence at the International Conference on Space Optical Systems and Applications (ICSOS) in 2022, without giving the specific reasons or analysis process for the selected mode combination.

[0004] Atmospheric turbulence is a stochastic and dynamic process, and the composition of the excited optical field modes evolves continuously over time. Directly selecting empirical combinations of the first few modes lacks theoretical support. Furthermore, a mode combination that seems reasonable under static or specific instantaneous conditions may not consistently maintain optimal performance in dynamically changing channels. Therefore, there is an urgent need in this field for an analytical method that can scientifically and quantitatively analyze the statistical characteristics of dynamic turbulent channels and select the optimal fixed mode combination for MPLC based on this analysis, in order to overcome the blind spots and static limitations of existing technologies.

[0005] In summary, existing technologies suffer from the problem of failing to maintain optimal performance in dynamically changing channels due to the reliance on experience to directly select the first few modes as a fixed set of orthogonal mode bases, which leads to reduced communication link stability. Summary of the Invention

[0006] This invention solves the technical problem in the prior art that, by relying on experience to directly select the first few modes as a fixed set of orthogonal mode bases, it is impossible to guarantee optimal performance in dynamically changing channels, resulting in reduced communication link stability.

[0007] The mode selection analysis method for satellite-to-ground laser communication mode diversity technology, as described in this invention, includes the following steps: Step 1: Construct a dynamic turbulence dataset; Step 2: Perform dynamic mode decomposition on the complex amplitude distribution of the degraded spot in the dynamic turbulence dataset to obtain the instantaneous power ratio of the degraded spot in different modes. Step 3: Statistically analyze the instantaneous power ratio of the degraded light spot in different modes, and select the optimal fixed mode combination based on the target turbulence intensity.

[0008] Furthermore, in one embodiment of the present invention, the construction of the dynamic turbulence dataset in step 1 includes the following steps: Step 11: Generate a dynamic turbulent phase screen sequence; Step 12: Construct a light wave propagation model to simulate how multiple degraded light spots are formed at the receiving end after the laser beam is transmitted through a dynamic turbulent phase screen sequence, and these spots change over time. Step 13: Classify and store multiple degraded light spots according to different turbulence intensity levels to obtain a dynamic turbulence dataset.

[0009] Furthermore, in one embodiment of the present invention, the dynamic mode decomposition in step 2 specifically includes: The complex amplitude distribution of the degraded light spot is tilted and corrected. The tilted and corrected complex amplitude distribution is then projected onto a set of pre-selected complete orthogonal mode bases to obtain the instantaneous power ratio of the degraded light spot in different modes.

[0010] Furthermore, in one embodiment of the present invention, the tilt correction specifically includes: By subtracting the overall tilt aberration in the complex amplitude distribution of the degraded spot, increasing the tracking system error of the simulated receiving surface, constructing a compensation phase, and obtaining the tilt-corrected complex amplitude distribution based on the complex amplitude distribution of the degraded spot and the compensation phase.

[0011] Furthermore, in one embodiment of the present invention, the tilt-corrected complex amplitude distribution is projected onto a set of pre-selected complete orthogonal mode bases, and the instantaneous power ratio of the degraded spot in different modes is obtained by calculating the inner product and taking the square of its modulus.

[0012] Furthermore, in one embodiment of the present invention, in step 3, the instantaneous power ratio of the degraded spot in different modes is statistically analyzed according to the mode group, the comprehensive score of different mode groups is calculated respectively, and the top K modes with the highest comprehensive scores are taken as the optimal fixed mode combination under the target turbulence intensity.

[0013] Furthermore, in one embodiment of the present invention, the step of calculating the comprehensive score for different mode groups specifically involves: Calculate the average power percentage of different model groups over the entire observation period under the target turbulence intensity, as well as the standard deviation of the average power percentage of each model group over the entire time series. Based on the average power percentage and standard deviation, obtain the comprehensive score of different model groups.

[0014] The present invention discloses a mode selection analysis system for satellite-to-ground laser communication mode diversity technology. The system is constructed based on the aforementioned method and includes the following modules: Module 1: Constructing a dynamic turbulence dataset; Module 2 performs dynamic mode decomposition on the complex amplitude distribution of the degraded light spot in the dynamic turbulence dataset to obtain the instantaneous power ratio of the degraded light spot in different modes. Module 3 performs statistical analysis on the instantaneous power ratio of the degraded light spot in different modes, and selects the optimal fixed mode combination based on the target turbulence intensity.

[0015] The computer program product of the present invention includes a computer program or instructions, which, when executed by a processor, implement any of the above-described mode selection analysis methods for satellite-to-ground laser communication mode diversity technology.

[0016] The present invention discloses a method for manufacturing a fixed phase mask element for an MPLC. The manufacturing method is based on any of the above-described mode selection analysis methods. The optimal fixed mode combination selected is used as the input of the design objective and substituted into the numerical optimization algorithm. After iterative optimization, the distribution function of multiple phase masks required to achieve the mode conversion is calculated. Based on the distribution function of the phase masks, the fixed phase mask element of the MPLC is manufactured through micro-nano fabrication technology.

[0017] This invention solves the technical problem in existing technologies where relying on experience to directly select the first few modes as a fixed set of orthogonal mode bases fails to guarantee optimal performance in dynamically changing channels, leading to reduced communication link stability. Specific beneficial effects include: 1. This invention proposes a mode selection analysis method for satellite-to-ground laser communication mode diversity technology. It provides a complete and quantitative analysis process, which guides MPLC design by analyzing the real mode distribution characteristics of dynamic turbulence, so that the mode combination and the time-averaged statistical characteristics of the channel can be optimally matched. This can improve the performance of MPLC devices, avoid relying on experience to directly select the first few modes as a fixed set of orthogonal mode bases, and transform MPLC mode selection from "empirical selection" to "statistical science", making the design process more reliable and optimizable. 2. This invention proposes a mode selection analysis method for satellite-to-ground laser communication mode diversity technology, enhancing system robustness and ensuring link stability. Because the selected mode has a high average proportion and is more stable during dynamic processes, the system is less sensitive to instantaneous changes in turbulence, exhibits smaller performance fluctuations, and improves link reliability. 3. This invention proposes a mode selection analysis method for satellite-to-ground laser communication mode diversity technology, balancing high performance and low cost. This invention optimizes MPLC with a fixed phase mask, ensuring performance while avoiding the drawbacks of using SLM, reducing system complexity, cost, and power consumption, and making it easier to implement and deploy in engineering. Attached Figure Description

[0018] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of the pattern selection analysis method described in Implementation Method 1; Figure 2 This is a schematic diagram of the light field propagation simulation described in Implementation Method 2; Figure 3 This is a schematic diagram of the dynamic turbulent phase screen sequence described in Embodiment 2; Figure 4This is a schematic diagram of the average power ratio, standard deviation, and evaluation index under a specific comprehensive selection function for the first 6 HG mode groups under specific strong turbulence as described in Implementation Method 4. Detailed Implementation

[0019] Various embodiments of the present invention will now be clearly and completely described with reference to the accompanying drawings. The embodiments described with reference to the drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0020] Implementation Method 1: A mode selection analysis method for satellite-to-ground laser communication mode diversity technology, comprising the following steps: Step 1: Construct a dynamic turbulence dataset; Step 2: Perform dynamic mode decomposition on the complex amplitude distribution of the degraded spot in the dynamic turbulence dataset to obtain the instantaneous power ratio of the degraded spot in different modes. Step 3: Statistically analyze the instantaneous power ratio of the degraded light spot in different modes, and select the optimal fixed mode combination based on the target turbulence intensity.

[0021] Atmospheric turbulence, as a typical stochastic dynamic process, exhibits physical characteristics of spatiotemporal irregularity and unpredictability. This turbulent disturbance continuously excites complex mode evolution in the optical field. The composition of these optical field modes dynamically adjusts with real-time changes in turbulence parameters. This evolution is non-stationary and cannot be accurately characterized statistically by instantaneous snapshots. Traditional methods that directly extract empirical combinations of the first few low-order modes are essentially simplified approximations of complex systems. This approach may not consistently maintain optimal performance in dynamically changing channels.

[0022] To address the aforementioned issues, this embodiment proposes a mode selection analysis method for satellite-to-ground laser communication mode diversity technology, such as... Figure 1 As shown, these are the four core steps of this implementation: Step 1: Construct a dynamic turbulent spot dataset; Step 2: Perform temporal orthogonal mode decomposition; Step 3: Extract dominant mode optimization combination; Step 4: Guide MPLC phase mask design.

[0023] This implementation method reveals the statistical distribution law of light spot patterns under dynamic turbulence through numerical simulation, and uses this law to guide MPLC in selecting the optimal fixed mode combination. This solves the technical problem in the prior art that the existing technology relies on experience to directly select the first few modes as a fixed set of orthogonal mode bases, which cannot guarantee the optimal performance in dynamically changing channels and leads to a decrease in communication link stability.

[0024] Implementation Method Two: This implementation method further defines the mode selection analysis method for satellite-to-ground laser communication mode diversity technology described in Implementation Method One. Step 1, which involves constructing a dynamic turbulence dataset, includes the following steps: Step 11: Generate a dynamic turbulent phase screen sequence; Step 12: Construct a light wave propagation model to simulate how multiple degraded light spots are formed at the receiving end after the laser beam is transmitted through a dynamic turbulent phase screen sequence, and these spots change over time. Step 13: Classify and store multiple degraded light spots according to different turbulence intensity levels to obtain a dynamic turbulence dataset.

[0025] This implementation method generates a dynamic turbulent phase screen sequence that evolves over time, based on atmospheric turbulence phase screen models (such as the Kolmogorov spectrum and the Von Kármán spectrum) and the Taylor frozen turbulence assumption. Using a light wave propagation model, it simulates a series of time-varying degraded light spot images (complex amplitude distributions) formed at the receiving end after the laser beam passes through this phase screen sequence. These images are then classified and stored according to different turbulence intensity levels (using the ratio of atmospheric coherence length r0 to the receiving aperture diameter D, D / r0, as an indicator), constructing a dynamic dataset for analysis.

[0026] The core of this implementation is to generate a dynamic atmospheric turbulence phase screen and simulate light field transmission. The degraded light spot over time can be calculated using a dynamic phase screen model and light field transmission theory. Besides the power spectrum inversion method based on Fourier transform, this implementation can also use the Zernike polynomial method to generate a high-precision phase screen. A modified Von Kármán turbulence spectrum model is used, with its three-dimensional refractive index power spectrum... As shown in the following formula:

[0027] in, Let be the refractive index structure constant, with The unit is altitude h, which is a function of altitude. Typical values ​​in Between these, atmospheric turbulence is generally stronger closer to the ground. The larger. , where is the space wavenumber. The wavelength is [wavelength]. Atmospheric turbulence can generally be considered as consisting of eddies of varying sizes. and These represent the internal and external scales of turbulence, corresponding to the sizes of small and large eddies on the turbulent structure, respectively. Here, we select... = 0.01m, .

[0028] The Zernike polynomial method uses continuously orthogonal Zernike polynomials within the unit circle. As a basis function, it addresses wavefront phase distortion caused by turbulence. To expand upon.

[0029] in, For the order index of the polynomial, Normalized extreme radius ( (Relative to the phase screen aperture radius). It is the polar angle.

[0030] To simulate dynamic turbulence, the Zernike coefficient was compared with time. Correlation, thereby constructing time-varying wavefronts: ; in, It is the total order of the Zernike polynomials used. It is the first The Zernike polynomial of order at time The coefficients. These coefficients It is a stochastic process that evolves over time, with a theoretical mean of 0 and a variance that conforms to the time power spectral density. To ensure that the generated phase screen has correct temporal statistical properties, the temporal power spectral density is based on the Taylor frozen turbulence assumption and can be expressed in the following form: ; in, It is the total length of the turbulent path of the beam propagation. Along the path The lateral wind speed profile, , and These represent the refractive index structure constant, outer scale, and inner scale profiles along the path, respectively. Function Defined the first The filtered response of the Zernike model to the turbulent spatial spectrum is as follows: ; in, For the first Zernike polynomial of order Fourier transform, and For spatial frequency components, , Through simulation As time changes, a continuously evolving dynamic turbulent phase screen sequence can be generated, such as... Figure 3As shown, t represents time. The effect of the phase screen on the light field is manifested in changing the phase distribution of the complex amplitude of the light field. The effect of the i-th phase screen on the light field is as follows: ; in, Let be the phase distribution of the i-th phase screen.

[0031] The time-varying degradation of the light spot can be calculated using a dynamic phase screen model and optical field transmission theory. The optical field transmission model is as follows: Figure 2 As shown, the point light source passes through a series of dynamic phase screens placed along the propagation path to simulate dynamic atmospheric turbulence, forming a degraded light spot at the receiving end that varies with time.

[0032] This embodiment can divide a continuous random medium into a series of parallel plates of different thicknesses. The light field located on the front surface of the plate propagates to the rear surface of the plate according to the formula for propagation in a vacuum. Then, it is phase-modulated by the plate to form the final light field. This field then propagates to the rear surface of the next plate through the same vacuum propagation and phase modulation, and so on, until it reaches the receiving end.

[0033] For each time t, the initial Gaussian beam is calculated according to the step-by-step propagation model described above. Passing through all dynamic phase screens in sequence , , ...., The light field after that. Finally, at the receiving end (i.e., after the last phase screen), the complex amplitude distribution of the degraded light spot at that moment is obtained. Repeat this process to construct the entire dynamic time series of light spot dataset.

[0034] Implementation Method 3: This implementation method further defines the mode selection analysis method for satellite-to-ground laser communication mode diversity technology described in Implementation Method 1. The dynamic mode decomposition in step 2 specifically includes: The complex amplitude distribution of the degraded light spot is tilted and corrected. The tilted and corrected complex amplitude distribution is then projected onto a set of pre-selected complete orthogonal mode bases to obtain the instantaneous power ratio of the degraded light spot in different modes.

[0035] The tilt correction specifically includes: By subtracting the overall tilt aberration in the complex amplitude distribution of the degraded spot, increasing the tracking system error of the simulated receiving surface, constructing a compensation phase, and obtaining the tilt-corrected complex amplitude distribution based on the complex amplitude distribution of the degraded spot and the compensation phase.

[0036] The tilt-corrected complex amplitude distribution is projected onto a set of pre-selected complete orthogonal mode bases. By calculating the inner product and taking the square of its modulus, the instantaneous power ratio of the degraded spot in different modes is obtained.

[0037] This implementation performs high-precision HG mode decomposition on the dynamic spot dataset constructed in step 1 to obtain the instantaneous power distribution of the light field on the orthogonal mode basis. The specific implementation process is as follows: (1) Read the dynamic spot dataset output in step 1. This dataset contains a series of time sampling points. ( The corresponding complex amplitude distribution of the optical field at the receiving surface ,in, These represent the x and y coordinates in a rectangular coordinate system, respectively. It is a time coordinate.

[0038] (2) Tilt correction. The overall tilt (Tip-Tilt) aberration is subtracted from the complex amplitude of the light field, and the tracking system residual is added randomly to simulate the higher-order modes of turbulence and the overall excitation of the tracking system.

[0039] For the light field of the light spot dataset for each frame This can be achieved by calculating its phase gradient or by fitting a Zernike polynomial (extracting the coefficients of its second and third terms). , To accurately estimate its overall tilt, the coefficients of the second and third terms of random Gaussian noise are added after removing the entire value. , This is used to simulate the tracking system error of the receiving surface. Specifically, it constructs a compensated phase with random error that is opposite to the overall tilt. ; in, and It is a standard Zernike tilted polynomial.

[0040] Then, the original optical field is multiplied by the complex exponent of the compensated phase to obtain the corrected optical field: ; (3) Pattern projection. The tilt-corrected light field... To a pre-selected set of complete orthogonal model bases (For example, the pre-M order Hermitian-Gaussian mode) Or Laguerre-Gaussian model Projecting is performed by calculating the inner product and then onto the projection. By squaring the modulus, we can obtain the instantaneous power percentage of the optical field in each mode.

[0041] The selected basis vectors satisfy orthogonal normalization within the region defined by the receiving aperture D: ; by Taking the mode as an example, the complex projection coefficients of the light field on the (m,n)th mode We obtain the following by calculating the inner product: ; in, Let be the complex conjugate of the (m,n)th order mode in this orthogonal mode basis. This inner product operation can be numerically implemented through discrete summation. The mode at time […]. instantaneous power ratio It is determined by the ratio of the square of the modulus of its coefficient to the sum of the squares of the modulus of all model coefficients: ; The tilt correction and mode projection operations are repeated for each frame of the light field in the dataset, and finally the power proportion time series data of all modes at all time points are output. .

[0042] Implementation Method 4: This implementation method further defines the mode selection analysis method for satellite-to-ground laser communication mode diversity technology described in Implementation Method 1. In step 3, the instantaneous power ratio of the degraded spot in different modes is statistically analyzed according to the mode group, and the comprehensive score of different mode groups is calculated. The top K modes with the highest comprehensive scores are taken as the optimal fixed mode combination under the target turbulence intensity.

[0043] The calculation of the comprehensive score for different mode groups is as follows: Calculate the average power percentage of different model groups over the entire observation period under the target turbulence intensity, as well as the standard deviation of the average power percentage of each model group over the entire time series. Based on the average power percentage and standard deviation, obtain the comprehensive score of different model groups.

[0044] This embodiment uses the mode power timing data obtained in step 2. Perform statistical analysis. Calculate the mean power percentage (Mean) of each model over the entire time period at a specific turbulence intensity level. ).

[0045] At the same time, the standard deviation Std( of the power share of each mode) is calculated. This is used as an evaluation index for power stability. Given the total number K of modes required for MPLC design, based on the above statistical results, a comprehensive selection function F is constructed for each turbulence intensity level. This function is the average power percentage Mean( ) and the time series stability index Std( The weighted or combined function of ), i.e.: ; According to each mode The top K modes with the highest comprehensive scores are sorted and selected to form the optimal fixed mode combination for MPLC design under this turbulence intensity.

[0046] The following describes this embodiment in detail with reference to a specific turbulence intensity level (e.g., D / r0 = 7, strong turbulence).

[0047] This implementation method performs statistical analysis on the mode power time series data output in step 2, and selects the optimal fixed mode combination for MPLC under a specific turbulence intensity level based on the comprehensive score.

[0048] Assuming that the average power share and standard deviation of the first 21 modes have been calculated for the target turbulence intensity (i.e., D / r0 = 7), the specific implementation process is as follows: (1) Obtain the power proportion time series data of the first 21 modes within the same observation time from step 2. (m, n) is the HG pattern index. .

[0049] (2) Since energy conversion occurs within the same mode group during practical applications of MPLC, statistical analysis needs to be performed according to the mode group. For the HG mode, the mode group is defined as the set of all modes that satisfy m + n = M (M is a constant). For example: Pattern group M=0:{HG00}; Pattern group M=1:{HG01, HG10}; Pattern group M=2:{HG02, HG11, HG20}; ......; And so on.

[0050] For each pattern group M, there are (M+1) patterns, at time... power percentage The average instantaneous power of all modes within this group: ; Calculate the average power percentage of each model group throughout the entire observation period: ; This indicator reflects the average energy level of the model group during dynamic processes.

[0051] Calculate the power percentage of each mode group Standard deviation Std over the entire time series This indicator quantifies the degree of fluctuation in the total power of the entire model group over time. For example... Figure 4 The following is an example, showing the average power and standard deviation of the first 6 mode groups (out of 21 modes).

[0052] (3) Comprehensive scoring and determination of dominant mode. The weight parameters of average power and standard deviation in the comprehensive selection function are set according to the application scenario.

[0053] For example, according to Calculations were performed for each pattern group, with α=1.5 and β=0.5, for all 6 pattern groups. And sort them according to their scores from highest to lowest. Based on the number of mode groups designed for the MPLC, such as... The first three mode groups are directly selected from the above sorting table to form the dominant mode combination under this turbulence intensity and tracking error. Figure 4 The examples are groups 1, 2, and 3, and the corresponding pattern combinations are {HG00, HG01, HG10, HG11, HG02, HG20}.

[0054] Implementation Method 5: The present implementation method describes a method for manufacturing a fixed phase mask element for an MPLC. The manufacturing method is based on any of the above-described mode selection analysis methods. The optimal fixed mode combination selected is used as the input of the design objective and substituted into the numerical optimization algorithm. After iterative optimization, the distribution function of multiple phase masks required to achieve the mode conversion is calculated. Based on the distribution function of the phase masks, the fixed phase mask element for the MPLC is manufactured using micro-nano fabrication technology.

[0055] In this implementation, the optimal fixed mode combination obtained in step 3 is used as the input to the design objective. This input is then substituted into a numerical optimization algorithm (such as simulated annealing, particle swarm optimization, or wavefront matching). Through iterative optimization, the distribution function of the K phase masks (or the number determined according to the system design) required to achieve the mode conversion is calculated. Based on this phase distribution function, fixed phase mask elements for the MPLC are fabricated using micro / nano fabrication processes such as photolithography or laser direct writing.

[0056] In this embodiment, the wavefront matching algorithm was first proposed by Hashimoto et al., and its theoretical basis is the principle of reversibility of optical systems. The core idea of ​​this algorithm is that if the input light field mode can be perfectly converted into the target output mode, then at any cross-section on the optical propagation path, the phase distribution of the forward-propagating input beam should be consistent with the phase distribution of the reverse-derived target output beam.

[0057] The mode combination obtained in step 3 is used as the input optical field mode. The target output mode is determined according to application requirements; here, it is set to the HG00 mode. Given other design parameters, such as the beam waist of the target output optical field mode, the wavefront matching algorithm can be used to complete the design of the MPLC device.

[0058] Implementation Method Six: A mode selection analysis system for satellite-to-ground laser communication mode diversity technology, as described in this implementation method, is constructed based on the method described in Implementation Method One, and includes the following modules: Module 1: Constructing a dynamic turbulence dataset; Module 2 performs dynamic mode decomposition on the complex amplitude distribution of the degraded light spot in the dynamic turbulence dataset to obtain the instantaneous power ratio of the degraded light spot in different modes. Module 3 performs statistical analysis on the instantaneous power ratio of the degraded light spot in different modes, and selects the optimal fixed mode combination based on the target turbulence intensity.

[0059] Implementation Method Seven: A computer program product according to this implementation method includes a computer program or instructions, characterized in that, when the computer program or instructions are executed by a processor, they implement any of the above-described mode selection analysis methods for satellite-to-ground laser communication mode diversity technology.

[0060] The foregoing has provided a detailed description of the mode selection analysis method, system, product, and component manufacturing method for satellite-to-ground laser communication mode diversity technology proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for mode selection analysis for satellite-to-ground laser communication mode diversity technique, characterized in that, The method comprises the following steps: Step 1, constructing a dynamic turbulence data set; Step 2, performing dynamic mode decomposition on the complex amplitude distribution of the degraded spots in the dynamic turbulence data set to obtain the instantaneous power proportion of the degraded spots in different modes; Step 3, performing statistical analysis on the instantaneous power proportion of the degraded spots in different modes, and screening out an optimal fixed mode combination under a target turbulence intensity.

2. The method for mode selection analysis of satellite-to-ground laser communication mode diversity technique according to claim 1, wherein, The step 1 of constructing the dynamic turbulence data set comprises the following steps: Step 11, generating a dynamic turbulence phase screen sequence; Step 12, constructing a light wave propagation model to simulate that a laser beam transmits through the dynamic turbulence phase screen sequence and forms a plurality of degraded spots changing with time at a receiving end; Step 13, classifying and storing the plurality of degraded spots according to different turbulence intensity levels to obtain the dynamic turbulence data set.

3. The method for mode selection analysis of satellite-to-ground laser communication mode diversity technique according to claim 1, wherein, The dynamic mode decomposition in the step 2 is specifically as follows: The complex amplitude distribution of the degraded spots is subjected to tilt correction, the tilt-corrected complex amplitude distribution is projected onto a group of preselected complete orthogonal mode bases to obtain the instantaneous power proportion of the degraded spots in different modes.

4. The method for mode selection analysis of satellite-to-ground laser communication mode diversity technique according to claim 3, wherein, The tilt correction is specifically as follows: The overall tilt aberration in the complex amplitude distribution of the degraded spots is deducted, a tracking system error of a simulation receiving surface is added, a compensation phase is constructed, and the tilt-corrected complex amplitude distribution is obtained based on the complex amplitude distribution of the degraded spots and the compensation phase.

5. The method for mode selection analysis of satellite-to-ground laser communication mode diversity technique according to claim 3, wherein, The tilt-corrected complex amplitude distribution is projected onto a group of preselected complete orthogonal mode bases, the inner product is calculated and the modulus square is obtained to obtain the instantaneous power proportion of the degraded spots in different modes.

6. The method for mode selection analysis of satellite-to-ground laser communication mode diversity technique according to claim 1, wherein, In the step 3, the instantaneous power proportion of the degraded spots in different modes is statistically analyzed according to mode groups, the comprehensive scores of different mode groups are calculated, and the first K modes with the highest comprehensive scores are taken as the optimal fixed mode combination under the target turbulence intensity.

7. The method for mode selection analysis of satellite-to-ground laser communication mode diversity technique according to claim 6, wherein, The calculation of the comprehensive scores of different mode groups is specifically as follows: The average power proportion of different mode groups in the entire observation time under the target turbulence intensity and the standard deviation of the average power proportion of each mode group in the entire time sequence are calculated, and the comprehensive scores of different mode groups are obtained based on the average power proportion and the standard deviation.

8. A mode selection analysis system for satellite-to-ground laser communication mode diversity technique, the system is constructed based on the method of claim 1, characterized in that, The method comprises the following modules: Module 1, constructing a dynamic turbulence data set; Module 2, performing dynamic mode decomposition on the complex amplitude distribution of the degraded spots in the dynamic turbulence data set to obtain the instantaneous power proportion of the degraded spots in different modes; Module 3, performing statistical analysis on the instantaneous power proportion of the degraded spots in different modes, and screening out an optimal fixed mode combination under a target turbulence intensity.

9. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions are executed by a processor to realize the mode selection analysis method for the mode diversity technology of the star-ground laser communication according to any one of claims 1-7.

10. A method for manufacturing a fixed phase mask element of an MPLC, which is based on the mode selection analysis method according to any one of claims 1 to 6, characterized in that, The optimal fixed mode combination screened out is taken as an input of a design target, is substituted into a numerical optimization algorithm, and is iteratively optimized to calculate distribution functions of a plurality of phase masks required for realizing the mode conversion. According to the distribution functions of the phase masks, a fixed phase mask element of the MPLC is manufactured through a micro-nano processing process.

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