Blind and Sparsity Level Adaptive Reconstruction of Wideband Time-frequency-varying Signals with Sub-Nyquist Sampling

DOI

10.2991/iccmcee-15.2015.90How to use a DOI?

Keywords

Compressed sensing, sub-Nyquist sampling, sparsity level adaptive, modulated wideband converter, iterative adaptive approach.

Abstract

This paper addresses the problem of wideband time-frequency-varying signal sub-Nyquist sampling and reconstruction based on compressed sensing (CS) framework. We propose a system of blind and sparsity level adaptive signal reconstruction for wideband signals with sub-Nyquist sampling. We utilize modulated wideband converter (MWC) that deals well with multi-band signals to acquire sub-Nyquist samples, change the signal sensing and reconstruction model to parameters estimation model in the array signal processing, and apply iterative adaptive approach (IAA) to recover spectral support and reconstruct signals simultaneously without any prior knowledge. Simulation results show that the proposed method outperforms the continue to finite (CTF) following MWC in low signal-to-noise ratio (SNR).

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weichao Sun
AU  - Zhichao Sha
AU  - Xiang Wang
AU  - FengHua Wang
AU  - Zhitao Huang
PY  - 2015/11
DA  - 2015/11
TI  - Blind and Sparsity Level Adaptive Reconstruction of Wideband Time-frequency-varying Signals with Sub-Nyquist Sampling
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 483
EP  - 488
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.90
DO  - 10.2991/iccmcee-15.2015.90
ID  - Sun2015/11
ER  -