Abstract: The data chain of ground to air communication plays an important role in the information transmission between the ground and the air. In order to analyze the information exchange of the data chain accurately, a new algorithm of data chain signal feature recognition based on particle swarm optimization and subtraction clustering is proposed. The envelope change is regarded as the basis of data chain signal division, and the basic features of signal carrier frequency, bandwidth and symbol speed are extracted using the strategy of square spectrum. The energy spectrum of signal is defined by wavelet transform, and the feature properties of signal are analyzed by the concept of energy fusion point. The frequency band with obvious energy spectrum difference is selected to create the feature quantity model of data chain signal. The particle swarm and subtraction fusion are integrated with Class method to search and reconstruct constellation. The best solution of particle and global population is defined. The fitness function of particle swarm is constructed, the cluster radius of the best subtraction method of constellationis calculated and the best cluster as the final signal feature recognition result is output. The experimental results show that the proposed method has high precision and strong ability of anti-interference, and can realize the real-time information interaction of VoIP ( Voice over Internet Protocol ) for ground to air communication data chain.

Key words: voice over internet protocol (VoIP) mode; , ground to air communication; , data link; , wavelet energy spectrum; , feature recognition