Dsp Applied Research In The Automatic Modulation Recognition Of Communication Signals

Based on the development status and application value of the automatic classification of communication modulation signals, this dissertation presents a new method to classify the type of a signal using statistical parameters, and designs three automatic modulation recognizers, including analog, digital and synthesis modulation recognizer. The modulation signals generated by computer simulation is used as input signal in this dissertation, and its characteristic parameters is extracted. Simulation with Matlab gives the performance of these three modulation recognizers. This dissertation also does research on the application in estimation of communication signals' carrier offset and symbol rate with the parametric statistical method.Digital signal processing technique is leaded in to implement the recognition algorithm, which improves the real-time property of the system. A system soft-hardware implement plan based on TMS320VC5402 is presented in this dissertation, and 'C5402 is used as the main processor. And the independent digital signal processing circuit concluding data conversion from analog to digital, data processing, data display interface and other circuit necessary is designed and made. Meanwhile, software design cycle is given and main models of the programme is explained in detail. Hardware emulation is done with CCS, and it indicates that the parametric statistical method presented in this dissertation has smaller caculation, but good real-time property, and it is efficient.