2,188 research outputs found
The finite harmonic oscillator and its associated sequences
A system of functions (signals) on the finite line, called the oscillator
system, is described and studied. Applications of this system for discrete
radar and digital communication theory are explained.
Keywords: Weil representation, commutative subgroups, eigenfunctions, random
behavior, deterministic constructionComment: Published in the Proceedings of the National Academy of Sciences of
the United States of America (Communicated by Joseph Bernstein, Tel Aviv
University, Tel Aviv, Israel
Accurate detection of moving targets via random sensor arrays and Kerdock codes
The detection and parameter estimation of moving targets is one of the most
important tasks in radar. Arrays of randomly distributed antennas have been
popular for this purpose for about half a century. Yet, surprisingly little
rigorous mathematical theory exists for random arrays that addresses
fundamental question such as how many targets can be recovered, at what
resolution, at which noise level, and with which algorithm. In a different line
of research in radar, mathematicians and engineers have invested significant
effort into the design of radar transmission waveforms which satisfy various
desirable properties. In this paper we bring these two seemingly unrelated
areas together. Using tools from compressive sensing we derive a theoretical
framework for the recovery of targets in the azimuth-range-Doppler domain via
random antennas arrays. In one manifestation of our theory we use Kerdock codes
as transmission waveforms and exploit some of their peculiar properties in our
analysis. Our paper provides two main contributions: (i) We derive the first
rigorous mathematical theory for the detection of moving targets using random
sensor arrays. (ii) The transmitted waveforms satisfy a variety of properties
that are very desirable and important from a practical viewpoint. Thus our
approach does not just lead to useful theoretical insights, but is also of
practical importance. Various extensions of our results are derived and
numerical simulations confirming our theory are presented
Incoherent dictionaries and the statistical restricted isometry property
In this article we present a statistical version of the Candes-Tao restricted
isometry property (SRIP for short) which holds in general for any incoherent
dictionary which is a disjoint union of orthonormal bases. In addition, under
appropriate normalization, the eigenvalues of the associated Gram matrix
fluctuate around 1 according to the Wigner semicircle distribution. The result
is then applied to various dictionaries that arise naturally in the setting of
finite harmonic analysis, giving, in particular, a better understanding on a
remark of Applebaum-Howard-Searle-Calderbank concerning RIP for the Heisenberg
dictionary of chirp like functions.Comment: Key words: Incoherent dictionaries, statistical version of Candes -
Tao RIP, Semi-Circle law, deterministic constructions, Heisenberg-Weil
representatio
Delay-Doppler Channel Estimation with Almost Linear Complexity
A fundamental task in wireless communication is Channel Estimation: Compute
the channel parameters a signal undergoes while traveling from a transmitter to
a receiver. In the case of delay-Doppler channel, a widely used method is the
Matched Filter algorithm. It uses a pseudo-random sequence of length N, and, in
case of non-trivial relative velocity between transmitter and receiver, its
computational complexity is O(N^{2}log(N)). In this paper we introduce a novel
approach of designing sequences that allow faster channel estimation. Using
group representation techniques we construct sequences, which enable us to
introduce a new algorithm, called the flag method, that significantly improves
the matched filter algorithm. The flag method finds the channel parameters in
O(mNlog(N)) operations, for channel of sparsity m. We discuss applications of
the flag method to GPS, radar system, and mobile communication as well.Comment: 11 page
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
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