Research On Parameters Recognition Algorithm For Continuous Phase Modulation In Non-cooperative Shortwave Communication

Non-cooperative communication refers to the use of a small amount of information or even no information to complete the estimation and identification of the received signal through signal processing technology without affecting the normal communication of both parties.Shortwave communication has the advantages of long communication distance,strong mobility,and strong survivability.It is an important long-range military communication method.Continuous Phase Modulation(CPM)is used in shortwave communications due to its high spectral efficiency,low out-of-band power and strong anti-interference ability.The parameters of the CPM signal identified in non-cooperative shortwave communication can interfere with the enemy's military communication equipment,help decipher the enemy's information,and facilitate reconnaissance and counter-reconnaissance activities.Therefore,this paper mainly studies the CPM signal parameter identification algorithm in Rayleigh fading channel non-cooperative shortwave communication.The main tasks completed in this paper are as follows:First,study the mathematical model and basic characteristics of the CPM signal.Analyze the relationship between its power spectrum characteristics and the carrier frequency of the CPM signal,study the decomposition of pulse amplitude modulation(PAM)and derive the cyclostationarity of the CPM signal from this,analyze the relationship between cyclostationarity and symbol rate,modulation index and modulation order.Second,the CPM parameter recognition algorithm based on feature is studied.The power spectrum density is used to estimate the CPM carrier frequency,and the signal is down-converted to a baseband signal according to the estimated value of the carrier frequency.The joint identification algorithm of symbol period,modulation index and modulation order based on cyclostationarity and the modulation parameter identification algorithm based on approximate entropy feature are studied.The CPM modulation range and recognition effect applicable to these two algorithms are evaluated.Finally,study the CPM parameter recognition algorithm based on likelihood.Explain the basic principle of modulation parameter recognition algorithm based on likelihood.Analyze the flow of the hidden Markov model likelihood modulation parameter recognition algorithm,valuate the recognition effect of the algorithm.Analyze the basic principles of the hybrid maximum likelihood modulation parameter recognition algorithm and simulate and analyze the recognition effect of the algorithm.Aiming at the problem of the slow convergence of the expectation maximization algorithm,an improved hybrid maximum likelihood CPM parameter identification algorithm is proposed.This algorithm decomposes all modulation waveforms of the signal to be identified into two parts: mapping symbol and waveform representation by CPM,the improved expectation maximization algorithm is used to calculate the maximum value of the likelihood function and obtain the estimated value of the unknown parameter,determine the modulation type of the signal to be identified.Simulation and comparative analysis of the average correct recognition probability and algorithm execution time of the CPM parameter recognition algorithm involved in the paper.