Delay Estimation Based on Compressed Sensing Subspace Pursuit Algorithm

DOI

10.2991/cnct-16.2017.21How to use a DOI?

Keywords

Sparse reconstruction, Delay estimation, Measurement matrix, Subspace pursuit

Abstract

In this paper, a novel method is constructed to estimate the time delay. The purpose of this article is to deal with the lack of measurement data in small sample (single snapshot) and low signal to noise ratio environment during wireless location. First, the sparse representation model of received signals is established. And then the measurement matrix is proofed to achieve the restricted isometry property. The idea of subspace pursuit is to find the subspace which consist of the received signal. Therefore, the delay estimation can be achieved using the corresponding relation between the time delay and the measurement matrix. Finally, simulations show that the subspace pursuit algorithm is suitable for small sample environment. The method can achieve a higher precision than greedy algorithms such as orthogonal matching pursuit and Regularized orthogonal matching pursuit algorithm. Furthermore, the subspace pursuit algorithm has a better performance in anti-multi channels.

Copyright

© 2017, 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  - Xue-dong LENG
AU  - Zi-lun ZHAO
AU  - Bin BA
PY  - 2016/12
DA  - 2016/12
TI  - Delay Estimation Based on Compressed Sensing Subspace Pursuit Algorithm
BT  - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
PB  - Atlantis Press
SP  - 155
EP  - 163
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnct-16.2017.21
DO  - 10.2991/cnct-16.2017.21
ID  - LENG2016/12
ER  -