33,074 research outputs found
The estimation of geoacoustic properties from broadband acoustic data, focusing on instantaneous frequency techniques
The compressional wave velocity and attenuation of marine sediments are fundamental to marine science. In order to obtain reliable estimates of these parameters it is necessary to examine in situ acoustic data, which is generally broadband. A variety of techniques for estimating the compressional wave velocity and attenuation from broadband acoustic data are reviewed. The application of Instantaneous Frequency (IF) techniques to data collected from a normal-incidence chirp profiler is examined. For the datasets examined the best estimates of IF are obtained by dividing the chirp profile into a series of sections, estimating the IF of each trace in the section using the first moments of the Wigner Ville distribution, and stacking the resulting IF to obtain a composite IF for the section. As the datasets examined cover both gassy and saturated sediments, this is likely to be the optimum technique for chirp datasets collected from all sediment environments
Multipath Parameter Estimation from OFDM Signals in Mobile Channels
We study multipath parameter estimation from orthogonal frequency division
multiplex signals transmitted over doubly dispersive mobile radio channels. We
are interested in cases where the transmission is long enough to suffer time
selectivity, but short enough such that the time variation can be accurately
modeled as depending only on per-tap linear phase variations due to Doppler
effects. We therefore concentrate on the estimation of the complex gain, delay
and Doppler offset of each tap of the multipath channel impulse response. We
show that the frequency domain channel coefficients for an entire packet can be
expressed as the superimposition of two-dimensional complex sinusoids. The
maximum likelihood estimate requires solution of a multidimensional non-linear
least squares problem, which is computationally infeasible in practice. We
therefore propose a low complexity suboptimal solution based on iterative
successive and parallel cancellation. First, initial delay/Doppler estimates
are obtained via successive cancellation. These estimates are then refined
using an iterative parallel cancellation procedure. We demonstrate via Monte
Carlo simulations that the root mean squared error statistics of our estimator
are very close to the Cramer-Rao lower bound of a single two-dimensional
sinusoid in Gaussian noise.Comment: Submitted to IEEE Transactions on Wireless Communications (26 pages,
9 figures and 3 tables
Measuring test mass acceleration noise in space-based gravitational wave astronomy
The basic constituent of interferometric gravitational wave detectors -- the
test mass to test mass interferometric link -- behaves as a differential
dynamometer measuring effective differential forces, comprising an integrated
measure of gravity curvature, inertial effects, as well as non-gravitational
spurious forces. This last contribution is going to be characterised by the
LISA Pathfinder mission, a technology precursor of future space-borne detectors
like eLISA. Changing the perspective from displacement to acceleration can
benefit the data analysis of LISA Pathfinder and future detectors. The response
in differential acceleration to gravitational waves is derived for a
space-based detector's interferometric link. The acceleration formalism can
also be integrated into time delay interferometry by building up the
unequal-arm Michelson differential acceleration combination. The differential
acceleration is nominally insensitive to the system free evolution dominating
the slow displacement dynamics of low-frequency detectors. Working with
acceleration also provides an effective way to subtract measured signals acting
as systematics, including the actuation forces. Because of the strong
similarity with the equations of motion, the optimal subtraction of systematic
signals, known within some amplitude and time shift, with the focus on
measuring the noise provides an effective way to solve the problem and
marginalise over nuisance parameters. The -statistic, in
widespread use throughout the gravitation waves community, is included in the
method and suitably generalised to marginalise over linear parameters and noise
at the same time. The method is applied to LPF simulator data and, thanks to
its generality, can also be applied to the data reduction and analysis of
future gravitational wave detectors.Comment: 10 pages, 3 figures, 1 tabl
Calibration Challenges for Future Radio Telescopes
Instruments for radio astronomical observations have come a long way. While
the first telescopes were based on very large dishes and 2-antenna
interferometers, current instruments consist of dozens of steerable dishes,
whereas future instruments will be even larger distributed sensor arrays with a
hierarchy of phased array elements. For such arrays to provide meaningful
output (images), accurate calibration is of critical importance. Calibration
must solve for the unknown antenna gains and phases, as well as the unknown
atmospheric and ionospheric disturbances. Future telescopes will have a large
number of elements and a large field of view. In this case the parameters are
strongly direction dependent, resulting in a large number of unknown parameters
even if appropriately constrained physical or phenomenological descriptions are
used. This makes calibration a daunting parameter estimation task, that is
reviewed from a signal processing perspective in this article.Comment: 12 pages, 7 figures, 20 subfigures The title quoted in the meta-data
is the title after release / final editing
Joint Transmit and Receive Filter Optimization for Sub-Nyquist Delay-Doppler Estimation
In this article, a framework is presented for the joint optimization of the
analog transmit and receive filter with respect to a parameter estimation
problem. At the receiver, conventional signal processing systems restrict the
two-sided bandwidth of the analog pre-filter to the rate of the
analog-to-digital converter to comply with the well-known Nyquist-Shannon
sampling theorem. In contrast, here we consider a transceiver that by design
violates the common paradigm . To this end, at the receiver, we
allow for a higher pre-filter bandwidth and study the achievable
parameter estimation accuracy under a fixed sampling rate when the transmit and
receive filter are jointly optimized with respect to the Bayesian
Cram\'{e}r-Rao lower bound. For the case of delay-Doppler estimation, we
propose to approximate the required Fisher information matrix and solve the
transceiver design problem by an alternating optimization algorithm. The
presented approach allows us to explore the Pareto-optimal region spanned by
transmit and receive filters which are favorable under a weighted mean squared
error criterion. We also discuss the computational complexity of the obtained
transceiver design by visualizing the resulting ambiguity function. Finally, we
verify the performance of the optimized designs by Monte-Carlo simulations of a
likelihood-based estimator.Comment: 15 pages, 16 figure
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