Complex Communication Signal Analysis And Recognition

With the rapid development of communication technology and the way of communication, the modulation type of communication signal and communication system become more and more complex, the technology of modulation recognition and signal analysis attract more and more attention in the field of communication reconnaissance, spectrum monitoring, cognitive radio and other non-cooperative signal processing. The following is studied in this thesis:Considering modulation recognition of CPFSK, an algorithm of CPFSK recognition is studied by extracting statistical distribution differences of instantaneous phase’s linear fit slope. An algorithm of CPFSK recognition is studied by extracting statistical character differences of smooth instantaneous frequency. An algorithm of CPFSK recognition is proposed based on difference of CPFSK signal Lyapunov index. The feasibility of the above studies is theoretically proved. The performance is simulated by modulation recognition rate curve with SNR.Considering parameters estimation of CPFSK, an algorithm of CPFSK symbol rate estimation is studied based on partial related function of instantaneous frequency, with theoretical prove, simulation results show that peak in symbol rate value exist in power spectrum of partial related function of instantaneous frequency, symbol rate can be estimated by searching the peak position. With low complexity, this algorithm can be applied in CPFSK and common FSK signal. With the mathematical relationship between Lyapunov index and modulation index, modulation index is estimated by extracting Lyapunov index, the performance is simulated by symbol rate MSE curve with SNR.Combine algorithms introduced in this thesis and commonly used in engineer, a complex communication signal recognition and analysis system with six kinds of signal is modeled and simulated. Covered with a wide range of parameters, the simulation results show low complexity and reasonable modeling.