@inproceedings{85687531480541e2b81c6e145adfb283,
title = "Compressive sensing of direct sequence spread spectrum signals",
abstract = "In this paper, Compressive Sensing (CS) methods for Direct Sequence Spread Spectrum (DSSS) signals are introduced. DSSS signals are formed by modulating the original signal by a Pseudo-Noise sequence. This modulation spreads the spectra over a large bandwidth and makes interception of DSSS signals challenging. Interception of DSSS signals using traditional methods require Analog-to-Digital Converters sampling at very high rates to capture the full bandwidth. In this work, we propose CS methods that can intercept DSSS signals from compressive measurements. The proposed methods are evaluated with DSSS signals generated using Maximum-length Sequences and Binary Phase-Shift-Keying modulation at varying signal-to-noise and compression ratios.",
keywords = "Compressive Matched Filtering, Compressive Sensing, DSSS, Sensing Matrix Design",
author = "Feng Liu and Marcellin, {Michael W.} and Goodman, {Nathan A.} and Ali Bilgin",
note = "Publisher Copyright: {\textcopyright} 2014 SPIE.; Compressive Sensing III ; Conference date: 07-05-2014 Through 09-05-2014",
year = "2014",
doi = "10.1117/12.2053370",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Fauzia Ahmad",
booktitle = "Compressive Sensing III",
}