Individual Identification In Communication Signals

During the individual identification in communication signals, parameter estimation and character sorting are two kinds of important problems. Precisely estimating target parameters and selecting the right characters will guarantee the actualizing for the communication countermeasure and communication counter -countermeasure.In order to construct system to sense and recognize the enemy transceivers in this dissertation, we proposed many algorithms to emulate signal extraction.After we received the mixed signals of transceivers more than one, we estimate the directions of arrival (DOA), from the beams of the transceiver formed, and focus the partition points between the transient signal and the balanced communication signal using the wavelet transform.For the separated and balanced communication signal, it is to estimate the parameters (such as symbol rate), and then identify the simulant and digital signal. Detecting the frequency warp of the communication signal wave carried is a method of being as the inherent characters.The transients and the fine features of communication signals are regarded as the fingerprints of a transceiver. For transients, it is processed by STFT, WT and SPWD to gain the fine characters. It is a good method of using high-order accumulating for non-gauss signal to pick up the fine characters.