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Radio Monitoring Signal Separation Study Based on Cyclic Statistics

Author: ZhangLiHui
Tutor: QiuTianShuang
School: Dalian University of Technology
Course: Signal and Information Processing
Keywords: Cyclostationary signals Cyclic Statistics Signal separation Blind Source Separation
CLC: TN911.7
Type: Master's thesis
Year: 2011
Downloads: 15
Quote: 0
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Abstract


Due to the variety of reasons, such as a signal of the wireless communication environment is intensive, a plurality of target echoes of the radar , the more general case is the presence of noise , etc. , which makes the received signal contains not only the signal of interest may also contain other unwanted signals , we called the interference signal or noise , the worse the situation is interference and noise at the same time . From noisy signals when the received mixed signal contains noise , how to recover a desired signal , when receiving a mixed signal containing the other interfering signals , how to suppress the interference signal is the signal of interest , which is the study of the several signal processing decades a major direction. Particularly consider the signal spectrum overlapping in this article , in this case, the deterioration of the general method of separating effect . And most of the communication signal can be regarded as the cyclostationary signal , its cyclic statistics case overlap in the frequency domain is still possible to separate the signal . Has some separation algorithm Firstly , to understand the signal model and the environment , and the simulation . Based on extensive literature , the combination of the symbol natural gradient algorithm and loop second-order statistics proposed natural gradient algorithm a fast convergence of the recycling symbol . The method utilizes cycle whitening the correlation between the cycle frequency domain removal signal so that the convergence speed . In addition, based on the fourth-order cyclic cumulants cyclostationary signal a simple blind source separation method . Two mixed signals , the method first cycle albino observation matrix , the cycle of the observation matrix is a unit matrix autocorrelation array , such separation matrix into a unitary , available single parameter . After the use of the cyclic nature of the statistic to find a judge function the best values ??of the parameters obtained in order to determine the separation matrix . The signal separation intuitive Figure crosstalk error analysis shows that the effectiveness of the method , qualitative discussion of the advantages of the algorithm and computation .

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Signal processing
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