A reconstruction method based on AL0FGD for compressed sensing in border monitoring WSN system

In this paper, to monitor the border in real-time with high efficiency and accuracy, we applied the compressed sensing (CS) technology on the border monitoring wireless sensor network (WSN) system and proposed a reconstruction method based on approximately l0 norm and fast gradient descent (AL0FGD)...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2014-12, Vol.9 (12), p.e112932-e112932
Main Authors: Wang, Yan, Wu, Xi, Li, Wenzao, Zhang, Yi, Li, Zhi, Zhou, Jiliu
Format: Article
Language:English
Subjects:
Acoustics
Algorithms
Analysis
Architectural engineering
Computer and Information Sciences
Computer science
Computer simulation
Decomposition
Emigration and Immigration
Energy consumption
Engineering
Engineering and Technology
Helicopter performance
Humans
Image Processing, Computer-Assisted
Information technology
International conferences
Internet
Methods
Monitoring
Monitoring systems
Problems
Reconstruction
Remote sensors
Satellite Communications
Sensors
Shrinkage
Signal processing
Theory
Wavelet transforms
Wireless networks
Wireless sensor networks
Wireless Technology
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, to monitor the border in real-time with high efficiency and accuracy, we applied the compressed sensing (CS) technology on the border monitoring wireless sensor network (WSN) system and proposed a reconstruction method based on approximately l0 norm and fast gradient descent (AL0FGD) for CS. In the frontend of the system, the measurement matrix was used to sense the border information in a compressed manner, and then the proposed reconstruction method was applied to recover the border information at the monitoring terminal. To evaluate the performance of the proposed method, the helicopter sound signal was used as an example in the experimental simulation, and three other typical reconstruction algorithms 1)split Bregman algorithm, 2)iterative shrinkage algorithm, and 3)smoothed approximate l0 norm (SL0), were employed for comparison. The experimental results showed that the proposed method has a better performance in recovering the helicopter sound signal in most cases, which could be used as a basis for further study of the border monitoring WSN system.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0112932