Downsampling Direct Sequence Spread Spectrum Signal Using Orthogonal Pretreatment

Abstract:

The Direct Sequence Spread Spectrum (DSSS) signal is widely used because of its good concealment and anti-jamming performance. The Compressive Sensing (CS) theory reduced the sampling rate of the DSSS signal effectively compared with the traditional Nyquist-rate sampling theory. While in the process of CS sampling the sensing matrix and the sparse basis generally have a strong correlation when the DSSS signal is decomposed with a complete dictionary. This paper presents a novel orthogonal pretreatment method with which the incoherence between sensing matrix and sparse basis can be improved. As a result, the reconstructed signal is more accurate. Simulation results demonstrate that this method is effective and efficient.

• Periodical: Applied Mechanics and Materials (Volume 610)
• Pages: 944-948
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.610.944
• Online since: August 2014
• Authors: Jin Bo Zhang*, Jian Cheng, Lei Yang
• Keywords: Compressive Sensing, Orthogonal Pretreatment, Reconstruction Algorithm, Sengsing Matrix

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