Paper Info
Title
A Novel Recovery Method of Soft X-ray Spectrum Unfolding Based on Compressive Sensing.
Abstract
In the experiment of inertial confinement fusion, soft X-ray spectrum unfolding can provide important information to optimize the design of the laser and target. As the laser beams increase, there are limited locations for installing detection channels to obtain measurements, and the soft X-ray spectrum can be difficult to recover. In this paper, a novel recovery method of soft X-ray spectrum unfolding based on compressive sensing is proposed, in which (1) the spectrum recovery is formulated as a problem of accurate signal recovery from very few measurements (i.e., compressive sensing), and (2) the proper basis atoms are selected adaptively over a Legendre orthogonal basis dictionary with a large size and Lasso regression in the sense of l1 norm, which enables the spectrum to be accurately recovered with little measured data from the limited detection channels. Finally, the presented approach is validated with experimental data. The results show that it can still achieve comparable accuracy from only 8 spectrometer detection channels as it has previously done from 14 detection channels. This means that the presented approach is capable of recovering spectrum from the data of limited detection channels, and it can be used to save more space for other detectors.
Year
DOI
Venue
2018
10.3390/s18113725
SENSORS
Keywords
Field
DocType
spectrum unfolding,compressive sensing,sparse representation,lasso regression,soft X-ray spectrometer,spectral measurement
Nanotechnology,X-ray,Electronic engineering,Engineering,Compressed sensing
Journal
Volume
Issue
ISSN
18
11.0
1424-8220
Citations 
PageRank 
References 
0
0.34
12
Authors
6
Name
Order
Citations
PageRank
Nan Xia1125.19
Yunbao Huang211.03
Haiyan Li386.32
Pu Li49615.13
Kefeng Wang500.34
Feng Wang631.06