Improving resolution of miniature spectrometers by exploiting sparse nature of signals | Zendy

J. Oliver | Zendy; Woong-Bi Lee | Zendy; Sangjun Park | Zendy; Heung-No Lee | Zendy

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Improving resolution of miniature spectrometers by exploiting sparse nature of signals

Author(s) -

J. Oliver,

Woong-Bi Lee,

Sangjun Park,

Heung-No Lee

Publication year - 2012

Publication title -

optics express

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.394

H-Index - 271

ISSN - 1094-4087

DOI - 10.1364/oe.20.002613

Subject(s) - underdetermined system , computer science , spectrometer , signal processing , algorithm , minification , signal (programming language) , optics , resolution (logic) , compressed sensing , limit (mathematics) , norm (philosophy) , sparse approximation , mathematics , physics , artificial intelligence , digital signal processing , mathematical analysis , law , political science , computer hardware , programming language

In this paper, we present a signal processing approach to improve the resolution of a spectrometer with a fixed number of low-cost, non-ideal filters. We aim to show that the resolution can be improved beyond the limit set by the number of filters by exploiting the sparse nature of a signal spectrum. We consider an underdetermined system of linear equations as a model for signal spectrum estimation. We design a non-negative L1 norm minimization algorithm for solving the system of equations. We demonstrate that the resolution can be improved multiple times by using the proposed algorithm.

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