Research On Key Technologies Of Sky Wave For Remote Reliable Propagation And Communication

Shortwave communication is an important component of remote communication systems and plays a crucial role in military and emergency communication.As the main means of shortwave communication,skywaves have the advantage of high survivability in modern warfare environments,as they are less vulnerable to destruction in nuclear war and can quickly establish communication links to facilitate the effective transmission of information and ensure the command and control of military forces.However,skywave communication is susceptible to instability,low passage rates,and unreliability due to the dynamic changes in the physical properties of the ionospheric reflection zone.On the one hand,the ionosphere can only reflect skywaves of specific frequencies,which may cause communication to be interrupted as higher frequency skywaves penetrate the ionosphere but lower frequency ones are absorbed.In particular,the geomagnetic storms caused by solar activity can greatly diminish the reliability of skywave propagation.On the other hand,due to the influence of the distance between communication links,existing multi-carrier shortwave communication systems require high transmission power,resulting in high peak-to-average ratios.Furthermore,the ionospheric channel of skywave communication is complex,and in adverse environments,the signal-to-noise ratio of the link is low,making the complete recovery and reliable transmission of information a research challenge and a key point.Therefore,ensuring the reliability of skywave communication is of great theoretical and practical significance.In response to the insufficient reliability of skywave communication mentioned above,this paper conducts research from two aspects: reliable propagation of skywave ionosphere and reliable transmission of communication information.Specifically,concerning the different latitude characteristics of skywave propagation in the ionosphere,this paper plans the transmission path of remote skywaves,constructs a global empirical ionospheric F2 layer critical frequency prediction framework,which is used to support skywave selection frequency and ensure the reliable propagation of skywave signals.On this basis,by utilizing the characteristics of LT codes,a skywave multi-carrier communication system based on LT codes is constructed to ensure the reliable transmission of communication information.The following research achievements have been mainly obtained:Ⅰ.Construction of a low-latitude ionospheric skywave propagation prediction model To study the variation of critical frequency of the F2 layer in the low-latitude ionosphere,this paper first analyzed the impact of space weather on the low-latitude ionosphere.Then a time-space two-dimensional hybrid neural network framework was proposed for predicting the fo F2 of the low-latitude ionosphere,which combined convolutional neural networks and bidirectional long short-term memory models to extract the spatial and temporal characteristics of the changes in the low-latitude ionosphere.On this basis,combining with the quantile regression algorithm,the asymmetric distribution characteristics of fo F2 in the low-latitude ionosphere were analyzed to improve the prediction accuracy of the model.Finally,by analyzing the performance of the model using the fo F2 data collected by the digital ionosonde in Brisbane,Australia(27°53’S,152°92’E)during high-and low-solar activity years and two geomagnetic storm events in the 24 th solar activity cycle.The relationship between the input and output lengths of the fo F2 time series was also analyzed to obtain the optimal input and output lengths for the prediction model of the low-latitude ionosphere.Simulation results show that the proposed model has improved the prediction accuracy of low-latitude ionospheric fo F2 significantly by more than 20.1% compared with the IRI model,effectively improving the accuracy of the fo F2 prediction model in the lowlatitude ionosphere,ensuring reliable communication of skywaves in low-latitude regions,and providing effective support for frequency selection.Ⅱ.Construction of a mid-latitude ionospheric skywave propagation prediction model This study investigates the variations of critical frequency of the F2 layer in the mid-latitude ionosphere,based on analysis of space weather parameters.Firstly,a mid-latitude ionospheric fo F2 prediction model based on intelligent optimization algorithm search and deep neural network is proposed.The Sparrow Search algorithm is adopted to optimize the hyperparameters of the deep neural network,obtaining the best predictive performance for the mid-latitude ionospheric fo F2 prediction model based on deep neural network.Secondly,to further improve the prediction accuracy of the fo F2 sequence,the Informer-fo F2 framework based on encoder-decoder and self-attention mechanism is proposed,utilizing unique attention mechanisms to capture temporal characteristics of the mid-latitude ionospheric fo F2 and achieve high-precision prediction.Finally,the collected ionospheric fo F2 data from the Advanced Digital Ionosonde located in Beijing,China(40.3°N,116.2°E)are used to conduct testing and validation during periods of calm space weather,and the predictive performance of the proposed models are discussed and analyzed under different seasons of geomagnetic storms.Simulation results indicate that the two models perform better than the international reference ionospheric model in predicting mid-latitude ionospheric fo F2 values with 9.8% and 19.6% prediction accuracy improvment.Ⅲ.Construction of High-Latitude Ionospheric Skywave Propagation Prediction Model This study investigates the variations of critical frequency of the F2 layer in the high-latitude ionosphere,and due to the special characteristics of the polar ionosphere,the fo F2 observation sequence is incomplete and lacks continuity in the time dimension,which cannot be applied to large-scale deep learning frameworks.Therefore,a differential integration sliding average auto-regressive neural network hybrid time series prediction framework is proposed to construct a data-driven high-latitude ionospheric fo F2 prediction model,which aims to improve the predictive performance of ionospheric models under conditions of sparse fo F2 observation samples and incomplete time dimension.Secondly,using ionospheric fo F2 measurement data collected from the Mawson Observatory(67.60°S,62.88°E)in Antarctica,tests and validations are conducted during periods of quiet space weather and polar day/night conditions.Simulation results show that the proposed model significantly improves the prediction accuracy with 12.7% compared to international reference ionospheric model.Ⅳ.Design of Reliable Information Transmission Encoding for Skywave Communication Based on the reliable propagation of skywaves,further research is conducted on the reliable transmission of communication information.Firstly,a skywave multicarrier communication system based on LT codes is designed to control the peak-to-average power ratio(PAPR)and reliably transmit information utilizing the advantages of LT codes in skywave OFDM systems.Secondly,an optimized robust soliton distribution for LT codes is proposed to address the issue of high decoding cost at low PAPR thresholds,by improving the probability of occurrence of small degree values using statistical characteristics of PAPR.Furthermore,a new statistical degree distribution function is constructed by combining the binaryexponential degree distribution with a high initial decoding success rate,using a particle swarm optimization algorithm with a target function of minimizing the average degree value.Finally,simulation tests and analysis are carried out under different PAPR thresholds and original packet numbers.The results show that the performance of the statistical degree distribution is better than the classic robust soliton distribution,effectively reducing decoding cost with 12.8% at the receiver and improving the performance of the communication system to ensure reliable transmission of information.