Research On Communication Signals Modulation Identification And Detection Of Parameters

Modulation classification is an important feature of communication signals. Thus, detection of characteristic parameters of communication signals and modulation classification and identification is one of the important issues of electronic warfare in a complex electromagnetic environment. The detection of modulation characteristics and identification technology of the analog and digital modulation communication signals are studied based on pattern recognition theory.First in this paper, various kinds of communication signals are analyzed on theories, and a variety of analog and digital modulation signal models are established, based on which, aimming at analog and digital modulations, the arithmetic for modulation signals identification is used based on decision-theoretic. After that, the whole modulation identification process is studied by using Matlab. The simulation results show that when the SNR is larger than10dB, the probability of success in the modulation signals identification is higher. Meanwhile, the decision-theoretic has some advantages as computational advantage and good identification effect. In the end, the carrier frequency of communication signals is estimates in the time domain and frequency domain respectively; the amplitude and frequency modulation coefficient for analog signals are detected using Fourier transform; the code speed for digital modulation signals is estimated using the methods of associated with delays and wavelet transform respectively, and the feasibility of the methods is well verdicted by computer simulations.The researches of paper have been used in a communication countermeasure equipment. The analyzing of measured data also proved the effectiveness of the methods.