10,402 research outputs found
Source localization and denoising: a perspective from the TDOA space
In this manuscript, we formulate the problem of denoising Time Differences of
Arrival (TDOAs) in the TDOA space, i.e. the Euclidean space spanned by TDOA
measurements. The method consists of pre-processing the TDOAs with the purpose
of reducing the measurement noise. The complete set of TDOAs (i.e., TDOAs
computed at all microphone pairs) is known to form a redundant set, which lies
on a linear subspace in the TDOA space. Noise, however, prevents TDOAs from
lying exactly on this subspace. We therefore show that TDOA denoising can be
seen as a projection operation that suppresses the component of the noise that
is orthogonal to that linear subspace. We then generalize the projection
operator also to the cases where the set of TDOAs is incomplete. We
analytically show that this operator improves the localization accuracy, and we
further confirm that via simulation.Comment: 25 pages, 9 figure
Gravitational Wave Burst Source Direction Estimation using Time and Amplitude Information
In this article we study two problems that arise when using timing and
amplitude estimates from a network of interferometers (IFOs) to evaluate the
direction of an incident gravitational wave burst (GWB). First, we discuss an
angular bias in the least squares timing-based approach that becomes
increasingly relevant for moderate to low signal-to-noise ratios. We show how
estimates of the arrival time uncertainties in each detector can be used to
correct this bias. We also introduce a stand alone parameter estimation
algorithm that can improve the arrival time estimation and provide
root-sum-squared strain amplitude (hrss) values for each site. In the second
part of the paper we discuss how to resolve the directional ambiguity that
arises from observations in three non co-located interferometers between the
true source location and its mirror image across the plane containing the
detectors. We introduce a new, exact relationship among the hrss values at the
three sites that, for sufficiently large signal amplitudes, determines the true
source direction regardless of whether or not the signal is linearly polarized.
Both the algorithm estimating arrival times, arrival time uncertainties, and
hrss values and the directional follow-up can be applied to any set of
gravitational wave candidates observed in a network of three non co-located
interferometers. As a case study we test the methods on simulated waveforms
embedded in simulations of the noise of the LIGO and Virgo detectors at design
sensitivity.Comment: 10 pages, 14 figures, submitted to PR
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The influences of environmental conditions on source localisation using a single vertical array and their exploitation through ground effect inversion
The performance of microphone arrays outdoors is influenced by the environmental conditions. Numerical simulations indicate that, while horizontal arrays are hardly affected, direction-of-arrival (DOA) estimation with vertical arrays becomes biased in presence of ground reflections and sound speed gradients. Turbulence leads to a huge variability in the estimates by reducing the ground effect. Ground effect can be exploited by combining classical source localization with an appropriate propagation model (ground effect inversion). Not only does this allow the source elevation and range to be determined with a single vertical array but also it allows separation of sources which can no longer be distinguished by far field localization methods. Furthermore, simulations provide detail of the achievable spatial resolution depending on frequency range, array size and localization algorithm and show a clear advantage of broadband processing. Outdoor measurements with one or two sources confirm the results of the numerical simulations
Quantification of the performance of iterative and non-iterative computational methods of locating partial discharges using RF measurement techniques
Partial discharge (PD) is an electrical discharge phenomenon that occurs when the insulation materialof high voltage equipment is subjected to high electric field stress. Its occurrence can be an indication ofincipient failure within power equipment such as power transformers, underground transmission cableor switchgear. Radio frequency measurement methods can be used to detect and locate discharge sourcesby measuring the propagated electromagnetic wave arising as a result of ionic charge acceleration. Anarray of at least four receiving antennas may be employed to detect any radiated discharge signals, thenthe three dimensional position of the discharge source can be calculated using different algorithms. These algorithms fall into two categories; iterative or non-iterative. This paper evaluates, through simulation, the location performance of an iterative method (the standardleast squares method) and a non-iterative method (the Bancroft algorithm). Simulations were carried outusing (i) a "Y" shaped antenna array and (ii) a square shaped antenna array, each consisting of a four-antennas. The results show that PD location accuracy is influenced by the algorithm's error bound, thenumber of iterations and the initial values for the iterative algorithms, as well as the antenna arrangement for both the non-iterative and iterative algorithms. Furthermore, this research proposes a novel approachfor selecting adequate error bounds and number of iterations using results of the non-iterative method, thus solving some of the iterative method dependencies
Low cost underwater acoustic localization
Over the course of the last decade, the cost of marine robotic platforms has
significantly decreased. In part this has lowered the barriers to entry of
exploring and monitoring larger areas of the earth's oceans. However, these
advances have been mostly focused on autonomous surface vehicles (ASVs) or
shallow water autonomous underwater vehicles (AUVs). One of the main drivers
for high cost in the deep water domain is the challenge of localizing such
vehicles using acoustics. A low cost one-way travel time underwater ranging
system is proposed to assist in localizing deep water submersibles. The system
consists of location aware anchor buoys at the surface and underwater nodes.
This paper presents a comparison of methods together with details on the
physical implementation to allow its integration into a deep sea micro AUV
currently in development. Additional simulation results show error reductions
by a factor of three.Comment: 73rd Meeting of the Acoustical Society of Americ
Optimal source localization problem based on TOA measurements
Determining an optimal emitting source location based on the time of arrival (TOA) measurements is one of the important problems in Wireless Sensor Networks (WSNs). The nonlinear least-squares (NLS) estimation technique is employed to obtain the location of an emitting source. This optimization problem has been formulated by the minimization of the sum of squared residuals between estimated and measured data as the objective function. This paper presents a hybridization of Genetic Algorithm (GA) for the determination of the global optimum solution with the local search Newton-Raphson (NR) method. The corresponding Cramer-Rao lower bound (CRLB) on the localization errors is derived, which gives a lower bound on the variance of any unbiased estimator. Simulation results under different signal-to-noise-ratio (SNR) conditions show that the proposed hybrid Genetic Algorithm-Newton-Raphson (GA-NR) improves the accuracy and efficiency of the optimal solution compared to the regular GA
Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey
Growing progress in sensor technology has constantly expanded the number and
range of low-cost, small, and portable sensors on the market, increasing the
number and type of physical phenomena that can be measured with wirelessly
connected sensors. Large-scale deployments of wireless sensor networks (WSN)
involving hundreds or thousands of devices and limited budgets often constrain
the choice of sensing hardware, which generally has reduced accuracy,
precision, and reliability. Therefore, it is challenging to achieve good data
quality and maintain error-free measurements during the whole system lifetime.
Self-calibration or recalibration in ad hoc sensor networks to preserve data
quality is essential, yet challenging, for several reasons, such as the
existence of random noise and the absence of suitable general models.
Calibration performed in the field, without accurate and controlled
instrumentation, is said to be in an uncontrolled environment. This paper
provides current and fundamental self-calibration approaches and models for
wireless sensor networks in uncontrolled environments
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