6,585 research outputs found
Distributed Cooperative Localization in Wireless Sensor Networks without NLOS Identification
In this paper, a 2-stage robust distributed algorithm is proposed for
cooperative sensor network localization using time of arrival (TOA) data
without identification of non-line of sight (NLOS) links. In the first stage,
to overcome the effect of outliers, a convex relaxation of the Huber loss
function is applied so that by using iterative optimization techniques, good
estimates of the true sensor locations can be obtained. In the second stage,
the original (non-relaxed) Huber cost function is further optimized to obtain
refined location estimates based on those obtained in the first stage. In both
stages, a simple gradient descent technique is used to carry out the
optimization. Through simulations and real data analysis, it is shown that the
proposed convex relaxation generally achieves a lower root mean squared error
(RMSE) compared to other convex relaxation techniques in the literature. Also
by doing the second stage, the position estimates are improved and we can
achieve an RMSE close to that of the other distributed algorithms which know
\textit{a priori} which links are in NLOS.Comment: Accepted in WPNC 201
Non-line-of-sight Node Localization based on Semi-Definite Programming in Wireless Sensor Networks
An unknown-position sensor can be localized if there are three or more
anchors making time-of-arrival (TOA) measurements of a signal from it. However,
the location errors can be very large due to the fact that some of the
measurements are from non-line-of-sight (NLOS) paths. In this paper, we propose
a semi-definite programming (SDP) based node localization algorithm in NLOS
environment for ultra-wideband (UWB) wireless sensor networks. The positions of
sensors can be estimated using the distance estimates from location-aware
anchors as well as other sensors. However, in the absence of LOS paths, e.g.,
in indoor networks, the NLOS range estimates can be significantly biased. As a
result, the NLOS error can remarkably decrease the location accuracy.
And it is not easy to efficiently distinguish LOS from NLOS measurements. In
this paper, an algorithm is proposed that achieves high location accuracy
without the need of identifying NLOS and LOS measurement.Comment: submitted to IEEE ICC'1
Target Tracking in Confined Environments with Uncertain Sensor Positions
To ensure safety in confined environments such as mines or subway tunnels, a
(wireless) sensor network can be deployed to monitor various environmental
conditions. One of its most important applications is to track personnel,
mobile equipment and vehicles. However, the state-of-the-art algorithms assume
that the positions of the sensors are perfectly known, which is not necessarily
true due to imprecise placement and/or dropping of sensors. Therefore, we
propose an automatic approach for simultaneous refinement of sensors' positions
and target tracking. We divide the considered area in a finite number of cells,
define dynamic and measurement models, and apply a discrete variant of belief
propagation which can efficiently solve this high-dimensional problem, and
handle all non-Gaussian uncertainties expected in this kind of environments.
Finally, we use ray-tracing simulation to generate an artificial mine-like
environment and generate synthetic measurement data. According to our extensive
simulation study, the proposed approach performs significantly better than
standard Bayesian target tracking and localization algorithms, and provides
robustness against outliers.Comment: IEEE Transactions on Vehicular Technology, 201
A survey of localization in wireless sensor network
Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network
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