title: Improving resolution of miniature spectrometers by exploiting sparse nature of signals.
abstract: 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.
authors.affiliation: School of Information and Communications, Gwangju Institute of Science and Technology, South Korea.
authors.forename: J
authors.initials: J
authors.lastname: Oliver
authors.forename: Woongbi
authors.initials: W
authors.lastname: Lee
authors.forename: Sangjun
authors.initials: S
authors.lastname: Park
authors.forename: Heung-No
authors.initials: HN
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016014:Linear Models; D008904:Miniaturization; D012815:Signal Processing, Computer-Assisted; D013057:Spectrum Analysis / Q000295:instrumentation* / Q000379:methods*