7,398 research outputs found
Matrix Design for Optimal Sensing
We design optimal () matrices, with unit columns, so that
the maximum condition number of all the submatrices comprising 3 columns is
minimized. The problem has two applications. When estimating a 2-dimensional
signal by using only three of observations at a given time, this minimizes
the worst-case achievable estimation error. It also captures the problem of
optimum sensor placement for monitoring a source located in a plane, when only
a minimum number of required sensors are active at any given time. For
arbitrary , we derive the optimal matrices which minimize the maximum
condition number of all the submatrices of three columns. Surprisingly, a
uniform distribution of the columns is \emph{not} the optimal design for odd
.Comment: conferenc
A General Bayesian Framework for Ellipse-based and Hyperbola-based Damage Localisation in Anisotropic Composite Plates
This paper focuses on Bayesian Lamb wave-based damage localization in structural health monitoring of anisotropic composite materials. A Bayesian framework is applied to take account for uncertainties from experimental time-of-flight measurements and angular dependent group velocity within the composite material. An original parametric analytical expression of the direction dependence of group velocity is proposed and validated numerically and experimentally for anisotropic composite and sandwich plates. This expression is incorporated into time-of-arrival (ToA: ellipse-based) and time-difference-of-arrival (TDoA: hyperbola-based) Bayesian damage localization algorithms. This way, the damage location as well as the group velocity profile are estimated jointly and a priori information taken into consideration. The proposed algorithm is general as it allows to take into account for uncertainties within a Bayesian framework, and to model effects of anisotropy on group velocity. Numerical and experimental results obtained with different damage sizes or locations and for different degrees of anisotropy validate the ability of the proposed algorithm to estimate both the damage location and the group velocity profile as well as the associated confidence intervals. Results highlight the need to consider for anisotropy in order to increase localization accuracy, and to use Bayesian analysis to quantify uncertainties in damage localization.Projet CORALI
Performance Limits and Geometric Properties of Array Localization
Location-aware networks are of great importance and interest in both civil
and military applications. This paper determines the localization accuracy of
an agent, which is equipped with an antenna array and localizes itself using
wireless measurements with anchor nodes, in a far-field environment. In view of
the Cram\'er-Rao bound, we first derive the localization information for static
scenarios and demonstrate that such information is a weighed sum of Fisher
information matrices from each anchor-antenna measurement pair. Each matrix can
be further decomposed into two parts: a distance part with intensity
proportional to the squared baseband effective bandwidth of the transmitted
signal and a direction part with intensity associated with the normalized
anchor-antenna visual angle. Moreover, in dynamic scenarios, we show that the
Doppler shift contributes additional direction information, with intensity
determined by the agent velocity and the root mean squared time duration of the
transmitted signal. In addition, two measures are proposed to evaluate the
localization performance of wireless networks with different anchor-agent and
array-antenna geometries, and both formulae and simulations are provided for
typical anchor deployments and antenna arrays.Comment: to appear in IEEE Transactions on Information Theor
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