Research On Spread Spectrum Signal Detection, Classification And Parameter Estimation

With the rapid development of information science, information technology has been widely used in various fields. Especially in the field of military communications, information warfare has become one of the main forms of modern warfare. Spread spectrum communication has been widely used in military communications because of its good anti-interference and anti-interception capability and flexible network-construction. In military communication, owing to low SNR and lacking of priori knowledge, detection and identification of spread spectrum signal is very difficult, and it has become an important issue.This paper mainly studies the blind detection of the signal, the identification of direct sequence spread spectrum signal and the frequency hopping signal, and the estimation of the parameters of the frequency hopping signal.On the base of predecessors’studies, some improved methods were presented. Firstly, signal detection algorithms are discussed based on the spectrum sensing theory. Traditional and improved iteration algorithms are compared, an iteration algorithm based on moving average is proposed, and the simulations of these algorithms have been done. Secondly, the algorithm of time domain autocorrelation and partial Fourier transform are introduced, recognition algorithms of direct sequence spread spectrum signals and frequency-hopping signals are elaborated, and the entire recognition algorithm is given out. Simulation and comparison of these two algorithms have been accomplished as well. Finally, smoothing pesudo-wigner-ville distribution and circular autocorrelation algorithm are introduced, hopping period, moments, frequencies and symbol rate of frequency-hopping signals are estimated, and the simulations of these algorithms have been done.