Research On Analytical Method Of Non-stationary Signals Based On FRFT

The wireless communication system brings convenient data transmission service to people. However, the open channel property results in secure risks, the signal can be easily monitored and deciphered by the third party. If the wireless communication signal which has non-stationary characteristics can be designed, the signal characteristics will get more and more unpredicted as the number of observation data increasing, this means that statistical characteristics of the non-stationary signal cannot be estimated by long-term observation and analysis, thus achieving anti-reconnaissance and anti-interception capabilities. The time-frequency analysis tools provide a function which can describe the energy density of the signal in time and frequency domain concurrently. This function can reflect the distribution of energy at a certain time and frequency. Therefore, the time-frequency analysis tools usually be used for analysis of time-varying signals and the Fractional Fourier Transform is one of the most effective tools for analysis of non-stationary signals.Based on the parameter estimation of chirp signal will be effected by sampling frequency and frequency overlapping and other factors, a system for parameter estimating based on Fractional Fourier Transform(FRFT) be designed. The non-stationary signals also be analysised by Fractional Fourier Transform. The time-limited chirp signal will take on energy concentration by Fractional Fourier Transform and the non-stationary signals will also does in the special condition.Based on these property, these following research works are completed.(1) Based on the intensive study of the FRFT and its discrete computing algorithm, an appropriate decomposition algorithm for Chirp signal analysis was designed and a parameter estimation model based on the discrete algorithm was constructed.(2) Based on the parameter estimation model, the impact of the Gaussian white noise on the detection performance of the single/multi component Chirp signal was analyzed. The simulation results show that the FRFT has a strong noise suppressing ability.(3) Based on this parameter estimation model, the influence of sampling frecquency, parameter differences, different sampling rate and the frequency overlap on the detection performance of the Chirp signal was studied and some conclusions were drawn.(4) The FRFT-based analysis for the proposed non-stationary communication signals was investigated in some special cases. The simulation results show that the non-stationary communication signals with a few time-varying frequency point can be detected by the FRFT under the condition of noiseless.