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Sparsity Analysis of DS TT&C Signals via Basic Dictionary Building.
- Source :
- Journal of Signal Processing; May2015, Vol. 31 Issue 5, p594-601, 8p
- Publication Year :
- 2015
-
Abstract
- Compressed Sensing (CS) theory provides a new solution for lowering acquisition cost and synchronous demodulation processing pressure of DS TT&C signal, furthermore sparsity is an important prerequisite for CS application, but the research on sparsity of the signal is seldom reported. In this paper, the sparsity of DS TT&C signal is in depth analyzed by building the basic dictionary, and a dual-stage dictionary learning method is proposed, moreover the basic learned dictionary and delay-Doppler dictionary are built based on the dual-stage dictionary learning method and detailed analysis of the signal model. Lastly, the performances of the basic dictionaries are verified by simulation experiments. The results show that DS TT&C signals receive a strong sparsity both in the built basic dictionaries, which provides a foundation for signal processing on the basis of CS. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Chinese
- ISSN :
- 10030530
- Volume :
- 31
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Journal of Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 108286653