Title :
Basis Mismatch in a Compressively Sampled Photonic Link
Author :
McLaughlin, Colin ; Nichols, Jonathan M. ; Bucholtz, Frank
Author_Institution :
Naval Res. Lab., Washington, DC, USA
Abstract :
To accurately reproduce an incoming signal, compressive sampling requires that the signal have a sparse representation from within a finite basis or dictionary of vectors. If the incoming signal cannot be sparsely represented by vectors within the given basis or dictionary-a situation sometimes termed basis mismatch-then reconstruction error or failure is likely. In this letter, we present both simulated and experimental results showing the influence of basis mismatch on the ability of a photonic compressive sampling system to accurately reconstruct harmonic signals. Our reconstruction algorithm utilizes gradient projection for sparse reconstruction coupled with a discrete Fourier basis.
Keywords :
Fourier transform optics; compressed sensing; optical information processing; optical links; signal reconstruction; signal representation; signal sampling; basis mismatch; compressively sampled photonic link; discrete Fourier basis; finite basis; gradient projection; harmonic signals; reconstruction algorithm; reconstruction error; reconstruction failure; signal sampling; sparse reconstruction; sparse representation; vector dictionary; Compressed sensing; Frequency modulation; Government; Image reconstruction; Mathematical model; Photonics; Vectors; Compressive sampling; analog-to-digital conversion; basis mismatch; photonics; sparse recovery;
Journal_Title :
Photonics Technology Letters, IEEE
DOI :
10.1109/LPT.2013.2285309