Digital Communication Signal Modulation Type Identification And Parameters Analysis Algorithm Research

Communication countermeasure is the earliest and most mature form of combat in the field of electronic warfare. Automatic identification and parameter estimation of modulation types of communication signals is a hot research topic in the field of communication. In non-cooperative communication, Frequency measurement is needed for the target signal without a priori knowledge. On this basis, the analysis of signal characteristics, the identification of the modulation types, the extraction of signal parameters and demodulation is the premise and key of the organization and implementation of communication confrontation, but also one of the important issues of communication electronic warfare. Based on the complex electromagnetic environment of digital communication signal analysis and processing of the new requirements, this paper organized the contents according to signal detection, parameter estimation, feature extraction and classifier design, etc.The research content of this paper is a sub task of communication reconnaissance system of the laboratory, mainly solved the problem of the modulation type identification of the prior information and the identification of the signal to noise ratio, the multipath fading and the insensitivity to the signal frequency,the defects of the existing methods are improved. Specific contents includes:(1)Aiming at the new situation of signal frequency measurement, this paper studies the principle of channel receiver, and presents a new method of signal frequency measurement based on multi-phase filtering technique. In this algorithm, the intermediate frequency sampling technique, orthogonal transformation, data extraction technique and multi-phase filtering technique are analyzed, digital communication signal detection and frequency measurement are realized, and the computer simulation is carried out by using Matlab software, which can reach the ideal state by continuous debugging.(2) Based on three methods of statistical characteristics, spectral correlation and high order, PSK, ASK, FSK and QAM four kinds of common digital signal modulation type identification are studied. The statistical characteristic analysis method can be used to determine the threshold value of the signal and realize the fast and accurate identification of digital communication signals by combining the identification parameters with the decision tree structure, but the threshold is not changed in advance, so the real-time performance is poor. The spectral correlation analysis method is characterized by the calculation of spectral correlation function and the structure of the characteristic parameters. The signal modulation types are distinguished and the anti disturbance ability is strong, but the parameters are complex and the efficiency is low. High order accumulation method can not only distinguish the signal of different modulation modes, but also distinguishes the different signals of the same modulation mode.(3) Finally the signal-to-noise ratio and symbol rate were estimated, based on the studied method for the blind demodulation of MPSK and MFSK, the formula derivation and simulation results verify the correctness of the algorithm.