Title
Model-Based Calibration of Filter Imperfections in the Random Demodulator for Compressive Sensing
Abstract
The random demodulator is a recent compressive sensing architecture providing efficient sub-Nyquist sampling of sparse band-limited signals. The compressive sensing paradigm requires an accurate model of the analog front-end to enable correct signal reconstruction in the digital domain. In practice, hardware devices such as filters deviate from their desired design behavior due to component variations. Existing reconstruction algorithms are sensitive to such deviations, which fall into the more general category of measurement matrix perturbations. This paper proposes a model-based technique that aims to calibrate filter model mismatches to facilitate improved signal reconstruction quality. The mismatch is considered to be an additive error in the discretized impulse response. We identify the error by sampling a known calibrating signal, enabling least-squares estimation of the impulse response error. The error estimate and the known system model are used to calibrate the measurement matrix. Numerical analysis demonstrates the effectiveness of the calibration method even for highly deviating low-pass filter responses. The proposed method performance is also compared to a state of the art method based on discrete Fourier transform trigonometric interpolation.
Year
Venue
Field
2013
CoRR
Discretization,Impulse response,Demodulation,Mathematical optimization,Algorithm,Discrete Fourier transform,Numerical analysis,Statistics,Compressed sensing,Signal reconstruction,Mathematics,Trigonometric interpolation
DocType
Volume
Citations 
Journal
abs/1303.6135
2
PageRank 
References 
Authors
0.40
14
3
Name
Order
Citations
PageRank
Pawel Jerzy Pankiewicz120.40
Thomas Arildsen2288.21
Torben Larsen322.09