12,106 research outputs found
Sub-Nyquist Sampling: Bridging Theory and Practice
Sampling theory encompasses all aspects related to the conversion of
continuous-time signals to discrete streams of numbers. The famous
Shannon-Nyquist theorem has become a landmark in the development of digital
signal processing. In modern applications, an increasingly number of functions
is being pushed forward to sophisticated software algorithms, leaving only
those delicate finely-tuned tasks for the circuit level.
In this paper, we review sampling strategies which target reduction of the
ADC rate below Nyquist. Our survey covers classic works from the early 50's of
the previous century through recent publications from the past several years.
The prime focus is bridging theory and practice, that is to pinpoint the
potential of sub-Nyquist strategies to emerge from the math to the hardware. In
that spirit, we integrate contemporary theoretical viewpoints, which study
signal modeling in a union of subspaces, together with a taste of practical
aspects, namely how the avant-garde modalities boil down to concrete signal
processing systems. Our hope is that this presentation style will attract the
interest of both researchers and engineers in the hope of promoting the
sub-Nyquist premise into practical applications, and encouraging further
research into this exciting new frontier.Comment: 48 pages, 18 figures, to appear in IEEE Signal Processing Magazin
Multichannel Sampling of Pulse Streams at the Rate of Innovation
We consider minimal-rate sampling schemes for infinite streams of delayed and
weighted versions of a known pulse shape. The minimal sampling rate for these
parametric signals is referred to as the rate of innovation and is equal to the
number of degrees of freedom per unit time. Although sampling of infinite pulse
streams was treated in previous works, either the rate of innovation was not
achieved, or the pulse shape was limited to Diracs. In this paper we propose a
multichannel architecture for sampling pulse streams with arbitrary shape,
operating at the rate of innovation. Our approach is based on modulating the
input signal with a set of properly chosen waveforms, followed by a bank of
integrators. This architecture is motivated by recent work on sub-Nyquist
sampling of multiband signals. We show that the pulse stream can be recovered
from the proposed minimal-rate samples using standard tools taken from spectral
estimation in a stable way even at high rates of innovation. In addition, we
address practical implementation issues, such as reduction of hardware
complexity and immunity to failure in the sampling channels. The resulting
scheme is flexible and exhibits better noise robustness than previous
approaches
Simultaneous Amplitude and Phase Measurement for Periodic Optical Signals Using Time-Resolved Optical Filtering
Time-resolved optical filtering (TROF) measures the spectrogram or sonogram
by a fast photodiode followed a tunable narrowband optical filter. For periodic
signal and to match the sonogram, numerical TROF algorithm is used to find the
original complex electric field or equivalently both the amplitude and phase.
For phase-modulated optical signals, the TROF algorithm is initiated using the
craters and ridges of the sonogram.Comment: 10 pages, 5 figure
Demodulation of intensity and shot noise in the optical heterodyne detection of laser interferometers for gravitational waves
Demodulation of intensity noise in the optical heterodyne detector is analyzed for application in interferometric gravitational-wave detectors. The correlation function and the power spectral density of the demodulated intensity noise are derived, taking into account the effect of bandpass filtering at the photodiode and an arbitrary demodulation waveform. The analysis includes demodulation of the rf-modulated shot noise as a special case of the intensity noise. For shot-noise-limited detection, the signal-to-noise ratio is found as a function of the modulation parameters, and the optimization of the signal-to-noise ratio with respect to the demodulation phase is described
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