Individual Character Research Of Communication Transmitter

Identification of individual communication transmitters is one of the hotspots in the field of communication countermeasure now. Since some subtle individual difference exists on the hardware of each transmitter. The individual character of communication transmitters are usually extracted by distinguishing each transmitter signal, so as to achieve the analysis, identification and monitoring of transmitters. Using the technology of individual transmitters identification, we could monitoring the activities of the enemy's communication transmitters in complex electromagnetic environment of battlefield. Analyzing which are the key enemy's communication transmitters, and then receiving, electronic jamming and military attack to them. Identification of individual communication transmitters has becoming a key task to the communication countermeasure in recent years.The individual transmitter character analysis is vital for communication transmitter identification. Aimed at the identification of individual communication transmitters of the same type and working mode, the stable working characters analysis and research are taken in this dissertation. Based on generating mechanism, the characteristics of carrier deviation, modulation parameters and stray output resulting from individual transmitter are researched under stable conditions. And the high order spectrum fetures especially integrated bispectra are researched. All the proposed algorithms are verified by simulation experiments with the measured radio data. The radio feature of STFT trispectrum is derived from this paper. And the good performance is verified by simulation experiments with real data.The primary work included in this paper can be described as followed.1) The subtle characters extraction based on the characteristics of frequency and stray output from individual transmitter are researched. The result of estimated carrier deviation and symbol rate show that frequency characteristic can be used as part of the characters of individual communication transmitters. The method of high order J and spectrum symmetry features are used to extract stray output from individual transmitter. Experimental results show that the extraction features have good performance of clustering.2) The bispectrum is used to extract the individual features of transmitters. The extract methods of four integrated bispectra are analyzed and compared. They are all verified by simulation experiments with the measured radio data. Experiment show that integrated bispectra can be used to identify transmitters as the signal subtle features, but the recognition rate is not good.3) Aimed at the low recognition rate of common bispectra feature, a method using STFT trispectrum is proposed. The algorithm is verified by simulation experiment with measured data. Experimental results show that the STFT trispectrum feature is more stable and have higher recognition rate than integrated bispectra feature.