Tilt Aberration Precorrection Method Based on Free-Space Optical Communication Receiver
By using a CCD camera and LSTM module to predict the speckle centroid position at the free-space optical communication receiver and driving the fiber end face offset, the problem of predicting and correcting dynamic aberrations at the receiver is solved, improving signal quality and coupling efficiency, and adapting to changes in atmospheric turbulence.
Patent Information
- Application Number
- CN202510045865.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-13
- Publication Date
- 2026-01-30
- Estimated Expiration
- 2045-01-13
AI Technical Summary
Existing technologies lack effective prediction and preventive correction of dynamic aberrations at the receiver in free-space optical communication, especially under atmospheric turbulence conditions, resulting in insufficient signal quality and coupling efficiency.
Six consecutive speckle images were captured by a CCD camera, converted into a centroid coordinate sequence using the Gray Scale Centroid module, and input into an LSTM module for time series analysis to predict the future centroid position. The result was then mapped to a control signal in the physical coordinate system through a fully connected layer to drive the fiber end face offset. A loop simulation system for the spatial optical modulator was built for testing.
It achieves high-precision prediction and fast response to receiver tilt aberration, improves coupling efficiency and signal quality, and ensures the stability and reliability of the communication system under complex atmospheric conditions.
Smart Images
Figure CN120017159B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of free space optical communication, and particularly relates to a tilt aberration pre-correction method based on a free space optical communication receiving end. BACKGROUND
[0002] As a high-bandwidth, low-latency wireless communication means, free space optical communication (FSO) has been widely used in point-to-point data transmission in recent years. However, the aberration phenomenon caused by atmospheric turbulence seriously limits the performance and reliability of FSO systems, especially in long-distance or severe weather conditions, this influence is particularly significant. In order to improve the communication quality and ensure the stability and efficiency of data transmission, it is necessary to develop a technical solution that can correct the aberration of the receiving end in real time.
[0003] Traditional technical solutions usually adopt static or semi-static optical compensation methods to resist the influence of atmospheric turbulence. These methods include using a deformable mirror or a liquid crystal spatial light modulator in an adaptive optical system to correct wavefront errors. Although this method can improve signal quality to some extent, it often requires a long response time and is difficult to respond in time to rapidly changing atmospheric conditions. In addition, the traditional solution relies on post-processing mechanism and cannot realize the pre-judgment and preventive correction of aberration, which makes it have certain limitations in practical application.
[0004] In the prior art, some advanced adaptive optical systems have begun to try to introduce machine learning algorithms to predict wavefront errors and correct them in advance. However, these systems mostly focus on the optimization of the transmitting end, and pay less attention to the dynamic aberration compensation of the receiving end. Moreover, the existing prediction methods lack sufficient mining of time series characteristics when processing speckle images, and fail to effectively capture the change rule of speckle centroid coordinates, resulting in insufficient prediction accuracy and being unable to meet the real-time correction requirements of high speed and high precision.
[0005] Therefore, the present application provides a tilt aberration pre-correction method based on a free space optical communication receiving end, which solves the above-mentioned technical problems. SUMMARY
[0006] The tilt aberration pre-correction method based on a free space optical communication receiving end of the present application comprises:
[0007] S1: converting the continuous 6 frames of speckle images captured by the CCD camera into a centroid coordinate sequence by using a Gray Scale Centroid module;
[0008] S2: inputting the centroid coordinate sequence into an LSTM module to obtain the change characteristics of the speckle centroid coordinate sequence in the continuous time domain;
[0009] S3: The centroid coordinate feature information predicted by the LSTM module is mapped back to the physical coordinate system through a fully connected layer to determine the exact position of the speckle centroid at the future time, generate a control signal to drive the fiber end face to shift, and realize the improvement of the coupling efficiency;
[0010] S4: Build a loop simulation system based on a spatial light modulator to test and verify the effective performance under simulated atmospheric turbulence conditions.
[0011] Preferably, the CCD camera in S1 captures speckle images, and the captured continuous 6 frames of speckle images are analyzed to obtain a sequence of speckle coordinates in the time domain.
[0012] Preferably, the Gray Scale Centroid module in S1 converts the continuous 6 frames of speckle images into a sequence of centroid coordinates, specifically including: the Gray Scale Centroid module reads the gray value of each pixel point in each frame of speckle image, calculates the centroid position of the light spot in the speckle image according to the gray value, and adds the gray values of each row and each column of pixels in each frame of image by calculating the weighted coordinate average value of x dimension and y dimension, and then divides by the total gray value, the formula is: where I ij represents the gray value of (i,j) position, N and M are the row and column pixel numbers of the two-dimensional image of the CCD camera, and the centroid coordinates (x,y) corresponding to the image are obtained.
[0013] Preferably, the centroid coordinate sequence in S2 is input into the LSTM module to obtain the change feature of the speckle centroid coordinate sequence in the continuous time domain, including the following steps:
[0014] S2.1: The centroid coordinates (x,y) corresponding to the 6 frames of speckle images generated by the Gray Scale Centroid module are arranged into a two-dimensional time series data set;
[0015] S2.2: The time series data set is input into the LSTM module, which is processed through a multi-layer neuron structure, and each time step in the LSTM module receives the state from the previous time sequence and the centroid coordinate input at the current time;
[0016] S2.3: The LSTM module processes the centroid coordinates step by step, calculates a new state value according to the memory state of the previous time and the current input, and passes it to the next time step;
[0017] S2.4: After the iteration processing of all time steps, the LSTM module outputs the future centroid coordinate feature information.
[0018] Preferably, each pair of centroid coordinates in the two-dimensional time series data set in S2.1 represents the position information of a speckle image at a specific time point, arranged in time sequence to form an input sequence.
[0019] Preferably, in S2.4, the future centroid coordinate position is predicted by the LSTM module to obtain the speckle centroid coordinate sequence change feature in the continuous time domain; the speckle centroid coordinate sequence change feature includes but is not limited to the displacement, velocity and acceleration dynamic properties of the centroid coordinate in the time sequence; the speckle centroid coordinate sequence change feature covers how the centroid position moves between consecutive frames, the rate of change of the centroid position per unit time, and the change of the centroid movement rate; the speckle centroid coordinate sequence change feature also includes the time correlation, periodicity or random fluctuation of the centroid coordinate; the dynamic behavior of the speckle in the receiving plane is captured by analyzing the change of the centroid coordinate with time, and the future centroid coordinate position is predicted.
[0020] Preferably, in S3, the future centroid coordinate feature information output by the LSTM module is input to the fully connected layer, and the fully connected layer receives the future centroid coordinate prediction value and performs nonlinear transformation to obtain higher-level features; the nonlinear transformation includes weighted summation combined with an activation function, and the future centroid coordinate prediction value is mapped to the physical coordinate system through the activation function sTanh of the last layer of the fully connected layer, and the formula is: sTanh(l) = 20*tanh(0.3*l), where l is the input centroid coordinate value.
[0021] Preferably, the fully connected layer maps the future centroid coordinate feature information predicted by the LSTM module to a specific numerical value in the physical coordinate system, converts the specific numerical value into a control signal, calculates the required offset according to the mapped physical coordinate value, and converts the offset into an electrical signal or a digital instruction; the electrical signal or the digital instruction is transmitted to the actuator to adjust the position of the fiber end face.
[0022] Preferably, in S4, the loop simulation system is built by using the AOtools tool package of Python to generate a random phase screen to simulate atmospheric turbulence, and the continuous change of the dynamic phase screen is realized by the extrapolation method; the generated phase screen is loaded onto a spatial light modulator to modulate the incident laser beam; the laser beam modulated by the spatial light modulator is focused by a lens, and the light beam is guided to a CCD camera to capture speckle images and calculate centroid coordinates.
[0023] Preferably, the loop simulation system includes an Optisystem free space optical communication simulation platform, which includes signal encoding and modulation at the transmitting end, atmospheric turbulence simulation of the transmission channel, and photoelectric conversion and signal analysis modules at the receiving end, forming a complete communication link simulation environment.
[0024] Compared with the prior art, the technical scheme of the application has the following technical effects:
[0025] The application provides a solid foundation for subsequent aberration prediction by capturing 6 continuous speckle images by using a CCD camera and converting the 6 continuous speckle images into a centroid coordinate sequence by using a Gray Scale Centroid module, is conducive to rapid completion of time domain feature extraction of tilt aberration by a subsequent module, and enables the system to maintain stable and efficient performance under complex and changeable atmospheric conditions.
[0026] The application solves the problem of compensation delay caused by calculation and response device delay by inputting the centroid coordinate sequence into an LSTM module to obtain a speckle centroid coordinate sequence time domain variation feature in a continuous time domain, utilizes the powerful time sequence processing capability of the LSTM module to process the centroid coordinates in each time step, calculates a new state value according to a memory state at a previous moment and a current input, improves the prediction accuracy, enables the system to quickly respond to changes in environmental factors such as atmospheric turbulence, realizes high-precision prediction of the speckle centroid position, and improves the coupling efficiency and signal quality of the free space optical communication receiving end.
[0027] The application solves the problem of being unable to realize predictive correction by mapping the future centroid coordinate feature information output by the LSTM module back to specific numerical values in a physical coordinate system to generate a control signal to drive fiber end face deflection, adopts a fully connected layer to perform nonlinear transformation on the received future centroid feature information, accurately maps the future centroid feature information to the physical coordinate system, and then calculates the required deflection and converts the deflection into an electrical signal or a digital instruction to be transmitted to an execution mechanism. Seamless connection from prediction to actual correction is realized, the fiber end face can be quickly adjusted accordingly, the tilt aberration that will occur is corrected in advance, and the response speed and correction accuracy of the device are improved.
[0028] The application solves the problem that complex atmospheric conditions are difficult to reproduce in an experimental environment by building a loop simulation system based on a spatial light modulator, including generating a random phase screen by using an AOtools tool package of Python to simulate atmospheric turbulence. The continuous change of the dynamic phase screen is realized by an extrapolation method, and the generated phase screen is loaded onto the spatial light modulator to modulate the incident laser beam, thereby simulating a communication scene close to reality. In this way, the effectiveness of the algorithm can be tested and verified, and the performance of the system can be evaluated under different environments to ensure its reliability in actual application. In combination with a free space optical communication simulation platform of Optisystem, a complete communication link simulation environment is formed.
[0029] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the contents of the description can be implemented, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following will be described in detail with the preferred embodiments of the present application and with the help of the accompanying drawings.
[0030] The above and other purposes, advantages and characteristics of the present application will be more apparent to those skilled in the art from the following detailed description of specific embodiments of the present application in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS
[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings described below are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual proportions.
[0032] Figure 1 Flow chart of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0033] Figure 2 Future centroid coordinate position flow chart of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0034] Figure 3 Structure principle diagram of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0035] Figure 4 Hardware system diagram of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0036] Figure 5 Loss value curve diagram of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0037] Figure 6 Simulation comparison diagram of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0038] Figure 7 Convergence speed comparison diagram of the present application based on the tilt aberration pre-correction method of the free space optical communication receiving end;
[0039] Figure 8Coupling efficiency probability distribution diagram of open loop and closed loop under different turbulence for the tilt aberration pre-correction method based on free space optical communication receiving end of the application;
[0040] Figure 9 Network structure framework diagram of the tilt aberration pre-correction method based on free space optical communication receiving end of the application;
[0041] Figure 10 Communication eye diagram of the tilt aberration pre-correction method based on free space optical communication receiving end of the application;
[0042] Figure 11 Bit error rate comparison diagram of the tilt aberration pre-correction method based on free space optical communication receiving end of the application. DETAILED DESCRIPTION
[0043] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. In the following description, specific details such as specific configurations and components are provided only to help a comprehensive understanding of the embodiments of the present application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, in order to be clear and concise, the description of known functions and structures is omitted in the embodiments.
[0044] It should be understood that the "one embodiment" or "the embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "one embodiment" or "the embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner.
[0045] In addition, reference numerals and / or letters can be repeated in different examples in the present application. Such repetition is for the purpose of simplification and clarity, and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.
[0046] The term "and / or" herein is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can mean that there are three cases of A alone, B alone and A and B together. The term "and" herein is a description of another association relationship of the associated objects, which means that there can be two relationships, for example, A and B can mean that there are two cases of A alone and A and B together. In addition, the character " / " herein generally represents that the associated objects before and after the character " / " are in an "or" relationship.
[0047] The term "at least one" herein is only used to describe associated objects, which means that three relationships can exist, for example, at least one of A and B, which can mean that A exists alone, A and B exist together, and B exists alone.
[0048] It should also be noted that the relationship terms such as first and second in this text are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion.
[0049] Embodiment 1
[0050] This embodiment mainly describes a tilt aberration pre-correction method based on a free space optical communication receiving end, as shown in Figure 1 The method comprises the following steps:
[0051] S1: Through the continuous 6 frames of speckle images captured by the CCD camera, the Gray Scale Centroid module is used to convert the continuous 6 frames of speckle images into a centroid coordinate sequence;
[0052] Further, the Gray Scale Centroid module converts the continuous 6 frames of speckle images into a centroid coordinate sequence, which specifically includes that the Gray Scale Centroid module reads the gray value of each pixel point in each frame of speckle image, calculates the centroid position of the light spot in the speckle image according to the gray value, and adds the gray value of each row and each column of pixels in each frame of image by calculating the weighted coordinate average value of the x-dimension and y-dimension pixel points, and then divides by the total gray value. The formula is: Where I ij represents the gray value of the (i,j) position, N and M are the row and column pixel numbers of the two-dimensional image of the CCD camera, and the centroid coordinates (x,y) corresponding to the image are obtained.
[0053] S2: The centroid coordinate sequence is input into the LSTM module to obtain the change characteristics of the speckle centroid coordinate sequence in the continuous time domain;
[0054] Further, the centroid coordinate sequence is input into the LSTM module to obtain the change characteristics of the speckle centroid coordinate sequence in the continuous time domain, as shown in Figure 2 The method comprises the following steps:
[0055] S2.1: The centroid coordinates (x,y) corresponding to the 6 frames of speckle images generated by the Gray Scale Centroid module are arranged into a two-dimensional time sequence data set;
[0056] S2.2: The LSTM module is input through the time series data set, processed through a multi-layer neural structure, and receives the state from the previous time sequence and the centroid coordinate input at the current time through each time step in the LSTM module;
[0057] S2.3: The LSTM module processes the centroid coordinates step by step, calculates a new state value according to the memory state of the previous time and the current input, and passes it to the next time step;
[0058] S2.4: After the iterative processing of all time steps, the LSTM module outputs the predicted future centroid coordinate feature information.
[0059] Further, each pair of centroid coordinates in the two-dimensional time series data set in S2.1 represents the position information of a speckle image at a specific time point, and is arranged in time sequence to form an input sequence.
[0060] Further, in S2.4, the future centroid coordinate position is predicted by the LSTM module to obtain the speckle centroid coordinate sequence change feature in the continuous time domain; the speckle centroid coordinate sequence change feature includes but is not limited to the displacement, velocity and acceleration dynamic properties of the centroid coordinate in the time sequence; the speckle centroid coordinate sequence change feature covers how the centroid position moves between consecutive frames, the rate of change of the centroid position per unit time, and the change of the centroid movement rate; the speckle centroid coordinate sequence change feature also includes the time correlation, periodicity or random fluctuation of the centroid coordinate; by analyzing the change of the centroid coordinate with time, the dynamic behavior of the speckle in the receiving plane is captured, and the future centroid coordinate position is predicted.
[0061] S3: The centroid coordinate feature information predicted by the LSTM module is mapped back to the physical coordinate system through the fully connected layer to determine the exact position of the speckle centroid at the future time, generate a control signal to drive the fiber end face to shift, and realize the improvement of the coupling efficiency;
[0062] Further, the future centroid coordinate feature information output by the LSTM module is input to the fully connected layer, and the fully connected layer receives the future centroid coordinate feature information and transforms it into higher-level features through nonlinear transformation; the nonlinear transformation includes weighted summation combined with an activation function; through the activation function sTanh of the last layer of the fully connected layer, the future centroid coordinate prediction value is mapped to the physical coordinate system, and the formula is: sTanh(l) = 20*tanh(0.3*l), where l is the input centroid coordinate value.
[0063] Further, the full connection layer maps the future centroid coordinate feature information predicted by the LSTM module into specific numerical values in the physical coordinate system, converts the specific numerical values into control signals, calculates the required offset according to the mapped physical coordinate values, and converts the offset into electrical signals or digital instructions; the electrical signals or digital instructions are transmitted to the actuator to adjust the position of the fiber end face.
[0064] S4: Build a loop simulation system based on a spatial light modulator to test and verify the effective performance under simulated atmospheric turbulence conditions.
[0065] Further, the loop simulation system is built by using the AOtools toolkit of Python to generate a random phase screen to simulate atmospheric turbulence, and the continuous change of the dynamic phase screen is realized by the extrapolation method. The generated phase screen is loaded onto the spatial light modulator to modulate the incident laser beam; the laser beam modulated by the spatial light modulator is focused by a lens to guide the light beam to a CCD camera, capture the speckle image and calculate the centroid coordinates.
[0066] Further, the loop simulation system includes an Optisystem free space optical communication simulation platform, which includes signal encoding and modulation at the transmitting end, atmospheric turbulence simulation of the transmission channel, and photoelectric conversion and signal analysis modules at the receiving end, forming a complete communication link simulation environment.
[0067] The embodiment realizes accurate prediction of the centroid position of the speckle at the future time by combining the continuous speckle images captured by the CCD camera with the time series analysis of the LSTM module, and maps the prediction results back to the physical coordinate system through the full connection layer to generate control signals to drive the fiber end face offset, thereby improving the coupling efficiency. By introducing the time series alignment mechanism and deep learning algorithm, the accuracy and timeliness of the prediction are improved, and ultimately a more stable and reliable communication performance is brought.
[0068] Embodiment 2
[0069] This embodiment describes in detail the structure model of the tilt aberration pre-correction method based on the free space optical communication receiving end, as shown in Figure 3 , specifically including:
[0070] The structure model includes a beam splitter, a coupling lens, a CCD camera, and a PC end; the CCD camera is used to detect the received speckle information, and a control system with prediction ability is used to output control signals to drive the fiber end face offset, thereby realizing the improvement of the coupling efficiency;
[0071] For the overall offset of the speckle centroid coordinates in the structure model, rmse is used as an evaluation index, and the formula is: Where (x p ,y p) is the predicted value of the spot centroid coordinate at time t, (x t ,y t ) is the true value of the spot centroid coordinate at time t, m is the number of spot centroid coordinates, and i is the i-th spot centroid coordinate.
[0072] This embodiment describes in detail the structure model of the tilt aberration pre-correction method based on the free space optical communication receiving end, and gives the evaluation index formula, which can more objectively judge the overall offset of the speckle centroid coordinate and realize accurate measurement.
[0073] Embodiment 3
[0074] Based on embodiment 1, this embodiment describes in detail the data generation and performance test of the tilt aberration pre-correction method based on the free space optical communication receiving end, which specifically includes:
[0075] Based on the atmospheric frozen flow hypothesis, the von Karman turbulence power spectrum inversion method built-in python AOtools toolkit is used to generate a random phase screen, and the wavefront distortion of atmospheric turbulence is measured; the fixed size atmospheric turbulence phase screen is slidingly intercepted, and the extrapolation method is selected to calculate the new phase information repeatedly by using the phase covariance function, and then the dynamic simulation of the atmospheric turbulence phase screen is realized; a 1 kilometer laser atmospheric horizontal transmission is simulated, in which the receiving aperture is 0.1 m, the spatial sampling is 1920x1200, the beam wavelength is 1550 nm, and the sampling frequency is 500 Hz; the detailed parameters of the atmospheric turbulence simulation are shown in Table 1, and D / r0 is used to describe the influence of turbulence on the light beam, wherein D is the diameter of the telescope, and r0 is the Freid parameter;
[0076] Table 1 Atmospheric turbulence simulation parameter setting
[0077]
[0078] On the optical platform, a laser atmospheric transmission part hardware loop system based on a spatial light modulator is built, the phase screen is loaded to the spatial light modulator, the incident laser is modulated to realize the wavefront distortion effect of atmospheric turbulence; the spatial light modulator has a resolution of 1920x1200 and a frame rate of 60hz, and finally a lens with a focal length of 300mm is used for focusing, and a CCD camera is used for completing the speckle data acquisition, as shown in Figure 4 , wherein a is the system diagram, b is the phase screen loaded to the spatial light modulator, and c is the speckle received by the CCD; the speckle data set and the verification set used in this paper are generated by the laser atmospheric transmission part hardware loop system.
[0079] Five different D / r0 simulation continuous-time coordinate data were simultaneously input into the coordinate pre-correction model to improve the robustness of the model; in order to adapt to the time delay in most systems while avoiding excessive calculation and overfitting problems, 6 consecutive frames of data were selected as the input of the model, i.e. the centroid position coordinates from time t to t+5 were used as the model input, and the centroid position at time t+8 was set as the data label, effectively avoiding the problem of excessive data processing by the model, and solving the problem of compensation delay caused by device running time delay, 12000 groups of data were generated under each D / r0 condition, the first 10800 groups of data were used as the training set, and the last 1200 groups were used as the verification data, a total of 54000 groups of data were used to constitute the training set, and 6000 groups of verification data were used as the verification set.
[0080] The training process of the model was carried out by a desktop workstation, which included AMD Ryzen 97950X, NVIDIA GeForce RTX 4090 and other devices, the code was realized by using the keras framework, the Adam optimizer mechanism was used to adaptively adjust the learning rate according to the momentum and second moment matrix, the initial learning rate was 0.001, the Dropout mechanism was introduced in the training process to randomly discard 20% of the neurons to prevent overfitting of the model training, as shown in Figure 5 The loss value curve of the model training set and test set is shown in the figure, the training set basically completes the convergence fitting in 20 rounds, at the same time the loss value curve of the model in the test set is basically coincided with the training set, which shows that the model completes the convergence and does not appear overfitting problem.
[0081] We tested the prediction ability of the trained model under different conditions, from the continuous 6 frames of data from time t to t+5 in the simulation to get the centroid position at time t+8, and compared it with the ideal value prepared in advance, the overall offset of the ideal and predicted results was used to compare the RMS to measure the prediction effect, the formula is: Where m is the number of spot centroid coordinates, i is the i-th spot centroid coordinate;
[0082] As shown in Figure 6The RME values of the predicted values and the true values of the test data set are shown in (a), and the residual RMS of the predicted values and the true values of the test data set is shown in (b); the RMS values of the original beam centroid position offset (Truth RMS), the predicted centroid position offset (Prediction RMS), and the residual RMS of the two are plotted for each turbulence in the variation curve of 600 consecutive frames. It can be seen from the curves in the figure that the greater the atmospheric turbulence D / r0, the greater the RMS, and the greater the Residual RMS, but the value of the Residual RMS is stable below 0.04λ, which indicates that the pre-correction method has good prediction ability for tilt aberration under different turbulence intensities, and good generalization performance in different environments.
[0083] To test the closed-loop rate advantage of the pre-correction model under different atmospheric turbulence, the performance of the classic SPGD algorithm is compared to verify the advancement of the model in the technical level. The model and the traditional SPGD algorithm are used to correct and compensate the received end speckle centroid offset under different D / r0, and the performances of the two algorithm models in the closed loop are as follows Figure 7 The results are the mean values of 20 groups of independent data iteration times, and the SPGD needs 5 to 7 iterations to complete the closed loop in the face of different turbulence, but the prediction model proposed in the application only needs one prediction to make the system complete the closed loop control, and the one-time prediction time is 0.04 ms, which is two orders of magnitude higher than the SPGD algorithm in closed loop efficiency.
[0084] For the test of coupling efficiency, the coupling efficiency of spatial light into a single-mode optical fiber is a widely used indicator in free space optical communication. However, the bit error rate and the coupling efficiency are nonlinearly related, and even if there is a higher coupling efficiency, the signal will still have a large jitter. Therefore, the probability distribution of the coupling efficiency at the open loop and closed loop time of the pre-correction network, and the corresponding variance are tested and analyzed, and the results are as follows Figure 8 As shown in the figure, under different turbulence, the coupling efficiency at the closed loop time is greatly improved, and the probability distribution of the coupling efficiency greater than 0.7 of the weak turbulence is more than 90%, and even under D / r0=3, the coupling efficiency can be improved to more than 0.6; in the field of laser transmission, D / r0 is usually used to describe the influence of turbulence on the light beam, where D is the diameter of the telescope, and r0 is the Freid parameter.
[0085] In the simulation test, we calculate the coupling efficiency variance at the open-loop and closed-loop time. From small to large turbulence, the open-loop time variance is 0.03359, 0.047829, 0.044962, 0.040021, 0.036353 respectively. After the closed-loop is implemented, these values are reduced to 0.000553, 0.001817, 0.002181, 0.002538, 0.002552 respectively. The higher coupling efficiency and lower variance after closed-loop control show lower bit error rate.
[0086] For the test of communication performance, a single-aperture transmitting and single-aperture receiving system of free space optical communication is built in the OptiSystem simulation system to verify the performance of the test pre-correction model in the communication system. The non-return-to-zero (NRZ) coding is used at the transmitting end. The pseudo-random sequence electrical signal is loaded onto the 1550nm laser carrier by the Mach-Zehnder modulator (MZ Modulator). The laser transmitting power is -4dBm, the system code rate is 10G bit / s, and the coupling efficiency is loaded as multiplicative noise on the receiving end beam signal after propagation on the free space optical link (FSO Channel). Then, the photoelectric conversion is used to receive the signal, and the low-pass Gaussian filter (LPG Filter) is used to analyze the signal bit error rate (BER) after the signal. Figure 9 The network framework diagram of the OptiSystem simulation system is shown in
[0087] As shown in Figure 10 , (a) is the open-loop, and (b) is the closed-loop. Figure 10 The eye diagram comparison of the communication system at the open-loop and closed-loop time is shown. After the closed-loop, the system eye diagram signal line is narrowed, the eye height is increased, and the line trace definition is improved, which indicates that the signal voltage noise is reduced, the time domain jitter is weakened, the inter-symbol interference is improved, and the signal quality is obviously improved.
[0088] To explore the influence of turbulence intensity on the correction of the pre-correction model, the bit error rate of the pre-correction model at the open-loop and closed-loop time is tested under different D / r0 environments. 15 groups of comparison data are tested in each turbulence environment, and the results are shown in Figure 11 At the open-loop time, the bit error rate under each turbulence is higher than 0.001, and the average value reaches 0.02191. After the pre-correction model completes the closed-loop, the link bit error rate is significantly reduced to 1.1e -9 Below, the communication system reaches the telecommunication level; the system bit error rate under D / r0=1 is basically reduced to 0, and the effect is the most significant.
[0089] The embodiment describes the data generation and performance test of the tilt aberration pre-correction method of the free space optical communication receiving end in detail, simulates under five turbulence intensities, and it can be seen from the above that the method has good generalization under different turbulence, and can complete convergence more quickly compared with the traditional SPGD algorithm. Meanwhile, the method significantly improves the coupling efficiency and greatly reduces the variance of the coupling efficiency. An optical communication system is simulated and built by using Optisystem, and the bit error rate and communication stability are greatly improved, which verifies the effectiveness of the method. Meanwhile, the closed loop bandwidth is effectively improved without increasing the equipment, which is a key advantage for the deployment of the free space optical communication network equipment, can realize autonomous operation, and avoids the parameter optimization process.
[0090] The above merely describes the preferred embodiments of the present application, and is not intended to limit the protection scope of the present application. The present application can have various changes and modifications for those skilled in the art; any changes, modifications, replacements, integrations and parameter changes of the embodiments within the spirit and principles of the present application, which can realize the same functions without departing from the principles and spirit of the present application, fall within the protection scope of the present application.
Claims
1. A method for pre-correcting tilt aberration based on free space optical communication receiving end, characterized in that, The application relates to a method for improving the coupling efficiency of a fiber end face, and a device for improving the coupling efficiency of a fiber end face. S1: six continuous speckle images captured by a CCD camera are converted into a centroid coordinate sequence by a Gray Scale Centroid module; S2: the centroid coordinate sequence is input into an LSTM module to obtain the speckle centroid coordinate sequence variation characteristics in the continuous time domain; S3: the centroid coordinate feature information predicted by the LSTM module is mapped back to the physical coordinate system through a full connection layer to determine the exact position of the speckle centroid at the future time, generate a control signal to drive the fiber end face to deviate, and realize the improvement of the coupling efficiency; S4: a loop simulation system based on a spatial light modulator is built to test and verify the effective performance under simulated atmospheric turbulence conditions; In the S1, six continuous speckle images are captured by a CCD camera, and the centroid coordinates of the captured six continuous speckle images are analyzed to obtain the centroid coordinate sequence in the continuous time domain; In the S2, the centroid coordinate sequence is input into an LSTM module to obtain the speckle centroid coordinate sequence variation characteristics in the continuous time domain, including the following steps: S2.1: the centroid coordinates (x, y) corresponding to the six speckle images generated by the Gray Scale Centroid module are arranged into a two-dimensional time sequence data set; S2.2: the time sequence data set is fed into the LSTM module, and is processed through a multi-layer neuron structure; each time step in the LSTM module receives the state from the previous time sequence and the centroid coordinate input at the current time; S2.3: the centroid coordinates are processed by the LSTM module one time step at a time; the new state value is calculated according to the memory state of the previous time and the current input, and is transmitted to the next time step; S2.4: after the iteration processing of all time steps, the LSTM module outputs the predicted future centroid coordinate feature information; In the S2.1, each pair of centroid coordinates in the two-dimensional time sequence data set represents the position information of a speckle image at a specific time point, and the input sequence is formed in time sequence. 2.The method of pre-correcting tilt aberration based on free space optical communication receiving end according to claim 1, characterized in that, The Gray Scale Centroid module in the S1 converts the continuous 6 speckle images into a centroid coordinate sequence, specifically including: the Gray Scale Centroid module reads the gray value of each pixel point in each frame of speckle image, calculates the centroid position of the light spot in the speckle image according to the gray value, and adds the gray value of each row and column pixel of each frame of image by calculating the weighted coordinate average value of the x dimension and the y dimension pixel points, and then divides by the total gray value, the formula is: Wherein I ij represents the gray value of the (i,j) position, N and M are the row and column pixel numbers of the two-dimensional image of the CCD camera, and the centroid coordinate (x,y) corresponding to the image is obtained. 3.The method of pre-correcting tilt aberration based on free space optical communication receiving end according to claim 1, characterized in that, In the S2.4, the future centroid coordinate position is predicted by the LSTM module to obtain the speckle centroid coordinate sequence variation characteristics in the continuous time domain; the speckle centroid coordinate sequence variation characteristics include the displacement, speed and acceleration dynamic attributes of the centroid coordinates in the time sequence; the speckle centroid coordinate sequence variation characteristics cover how the centroid position moves between continuous frames, the rate of change of the centroid position in unit time, and the change of the centroid movement rate; the speckle centroid coordinate sequence variation characteristics also include the time correlation, periodicity or random fluctuation of the centroid coordinates; the dynamic behavior of the speckle in the receiving plane is captured by analyzing the change of the centroid coordinates with time, and the future centroid coordinate position is predicted.
4. The method for pre-correcting tilt aberration of a free-space optical communication receiving end according to claim 1, wherein, The future centroid coordinate feature information output by the LSTM module in S3 is transmitted as input to a fully connected layer, which receives the future centroid coordinate feature information and transforms it into physical information, i.e., coordinate prediction values, through a nonlinear transformation; the nonlinear transformation includes weighted summation combined with an activation function, and the future centroid coordinate feature information is mapped into a physical coordinate system through the activation function sTanh of the last layer of the fully connected layer, according to the formula: sTanh(l) = 20*tanh(0.3*l), where l is the input centroid coordinate feature information.
5. The method for pre-correcting tilt aberration based on free space optical communication receiving end according to claim 1 or 4, characterized in that, The fully connected layer maps the future centroid coordinates predicted by the LSTM module into specific numerical values in the physical coordinate system, converts the specific numerical values into control signals, calculates the required offset according to the mapped physical coordinate values, and converts the offset into an electrical signal or a digital instruction; the electrical signal or the digital instruction is transmitted to an actuator to adjust the position of the fiber end face.
6. The method for pre-correcting tilt aberration of a free-space optical communication receiving end based on the tilt aberration, as claimed in claim 1, wherein The loop simulation system in S4 is built by using the AOtools toolkit of Python to generate a random phase screen to simulate atmospheric turbulence, and the continuous change of the dynamic phase screen is realized by extrapolation; the generated phase screen is loaded onto a spatial light modulator to modulate the incident laser beam; the laser beam modulated by the spatial light modulator is focused by a lens to guide the light beam to a CCD camera, capture the speckle image and calculate the centroid coordinates.
7. The method for pre-correcting tilt aberration based on free space optical communication receiving end according to claim 1 or 6, characterized in that, The loop simulation system includes an Optisystem free-space optical communication simulation platform, which includes signal encoding and modulation at the transmitting end, atmospheric turbulence simulation of the transmission channel, and photoelectric conversion and signal analysis modules at the receiving end, forming a complete communication link simulation environment.