Abstract:

Automatic modulation classification of communication signals is very important for both military and civilian purposes. In order to automatically recognize the conventional analogue communication signals, a new method for extracting the signal feature parameters is proposed. When the carrier has been synchronized, the received signals are transformed to zero intermediate frequency and the complex base band signal vector is then rotated anticlockwise around the origin for 90 degrees. Thus, it avoids the disadvantages caused by the discontinued phase during the processing of the DSB signal. Following that, five feature parameters based on the first statistical moments of the received signals are proposed. The calculation of all those feature parameters is less complicated and more robust. Next, an automatic modulation recognition algorithm based on the decisiontheoretic approach is developed and its realization is also presented in the form of a flowchart. Finally, computer simulation results show that all the aforementioned types of analogue communication signals can be recognized with average success rate greater than 97% at an SNR above -7dB. It is suitable for the practical application of signal detection and fast recognition in noncooperation communication systems.

Key words: automatic analogue modulation classification;signal vector rotation;feature parameter