| The booming development of big data and high-speed communication service is requireing for transmission capacity and information transmission rate of satellite communication system.Satellite laser communication technology with the advantages of broadband width,high speed and high energy efficiency has made up for the deficiency of microwave communication in the application of satellite communication.With the deepening of the research on the key technologies of satellite laser communication,the establishment of laser communication link between satellite and ground for data transmission is the development trend of high-speed data transmission between satellite and ground in the future,research on the key technologies of high-speed transmission and reliable signal reception of laser has become a hot topic in the field of satellite laser communication.However,the high-speed transmission of satellite-to-ground laser communication system faces the following challenges:Deterioration of beam coherence caused by turbulence influence when the laser signal passes through the atmospheric channel section of satellite-ground link can adversely affect the communication quality;the complexity of modulation formats in satellite communication system is increasing in order to meet the needs of different users and services for make full use of channel capacity,lead to the receiver identify the modulation format of the signal to correct demodulation.Aiming at improving the coherence of laser signals and ensuring the reliability of laser signal recognition,the research on adaptive optics technology and signal identification technology of satellite laser communication system is carried out for the sake of to the above-mentioned problems.In order to correct the laser beam distortion and identify the laser signal without prior knowledge,this paper focuses on the adaptive optics technology,single carrier signal identification technology and multi-carrier signal identification technology involved in the satellite laser communication,to complete the real-time correction of the laser beam distortion and realize the reliable identification of the laser signal.The main research contents and innovations of this paper are as follows:(1)Modeling of atmospheric channel and analysis of optical transmission characteristicsIn researching the characteristics of atmospheric turbulence and kolmogorov turbulence theory,the random phase screen is constructed based on the power spectrum inversion method and the sub-harmonic compensation method,and the multi-phase screen model of atmospheric turbulence is completed,the beam coherence degradation is analyzed by simulating the light field of the laser beam after passing through the model,a method to measure the turbulence influence based on Intensity Variation Index is proposed.This method mainly obtains the distortion degree of the beam by comparing the difference in the light field intensity distribution between the beam propagating through the turbulent channel and free space.The feasibility of measuring the turbulence influence by the proposed method is studied by simulation.The simulation results show that the variation of light intensity index and scintillation index in the proposed method are basically consistent with the variation trend of light wavelength,and the variation index of light intensity increases with the increase of turbulence intensity.(2)Adaptive optics compensation method based on Hybrid Input-Output AlgorithmOn the basis of researching the principle of adaptive optics,an adaptive optics compensation method based on Hybrid Input-Output Algorithm(HIOA)is proposed.In this method,an adaptive optical compensation module based on Hybrid Input-Output Algorithm is designed to complete the distortion compensation of the distorted beam,the distortion compensation proformance of the proposed method on the distorted beam under different transmission distances and iteration times is simulated.Simulation results show that the proposed method can effectively compensate the phase distortion of the distorted laser beam caused by turbulence effect and improve the mode purity of beam;After 50 or more iterations,HIOA can reconstruct accurate wavefront distortion phase information,and recover the Gaussian distribution of distorted laser beam well by phase correction.(3)Single carrier signal recognition method based on Fractal Feature of Region and Support Vector MachineOn the basis of studying the characteristics of laser signal with single carrier in atmospheric time-varying channel,a single carrier signal recognition method based on Fractal Feature of Region and Support Vector Machine is proposed.This method designs a feature extraction algorithm based on Fractal Dimensions of Region(FDR)to obtain the fractal features of the single carrier signal constellation,the support vector machine learning algorithm is used to learn the processed training feature data and construct a modulation format recognition classifier to realize the modulation format recognition of single carrier signals,the recognition performance of the proposed method under the conditions of free space channel and atmospheric time-varying channel is simulated and studied.The simulation results show,the overall classification accuracy of the classifier based on the proposed method is over 89.8%in all signal-to-noise ratio ranges in free space channel,the classification accuracy performance of the classifier converges when the signal-to-noise ratio is greater than 7.5 dB,achieving 100%accurate identification of single carrier signal;Under the condition of weak turbulence in atmospheric time-varying channel,the overall classification accuracy reaches more than 86.7%in all turbulence intensity and signal-to-noise ratio ranges,the classification accuracy of the classifier increases with the increase of signal-to-noise ratio and then converges.Compared with other recognition methods,the proposed method can effectively improve the classification accuracy and convergence speed,and has high robustness to channel changes.(4)Multi-carrier signal recognition method based on multi-feature input and Hybrid Training Neural NetworkOn the basis of studying the signal characteristics of multi-carrier laser signal in time-varying channels,a multi-carrier signal recognition method based on multi-feature input and Hybrid Training Neural Network is proposed.This method designs a Hybrid Training Neural Network(HTNN)structure based on multi-feature input,the high-order statistics and constellation characteristics of orthogonal frequency division multiplexing(OFDM)subcarrier signals are used as inputs of the network,HTNN is trained to independently mine the high-order correlation features and obtain the model to realize automatic modulation format recognition among OFDM sub-carrier signals.The recognition performance of the proposed method in free space channel transmission and atmospheric time-varying channel transmission is studied by simulation.The simulation results show that the overall classification accuracy of the recognition model based on the proposed method is more than 93.37%in all Signal-to-Noise Ratio(SNR)ranges in the free space channel.When the SNR is greater than 7.5dB,the classification accuracy performance of the learning model converges,achieving 100%accurate identification of OFDM subcarrier signals.Under the condition of weak turbulent atmosphere time-varying channel the scope of the overall classification accuracy of 73.5%or more within all turbulence intensity and signal-to-noise ratio,the classification accuracy of classifiers as the SNR increases with the increasing convergence.Compared with the two comparison methods,the proposed method reduces the sensitivity to channel changes on the basis of ensuring the classification accuracy,improves the convergence speed,and realizes the reliability recognition of the OFDM subcarier signal under a wide range of signal-to-noise ratios. |
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