71,807 research outputs found
An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters
A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values
The COST IRACON Geometry-based Stochastic Channel Model for Vehicle-to-Vehicle Communication in Intersections
Vehicle-to-vehicle (V2V) wireless communications can improve traffic safety
at road intersections and enable congestion avoidance. However, detailed
knowledge about the wireless propagation channel is needed for the development
and realistic assessment of V2V communication systems. We present a novel
geometry-based stochastic MIMO channel model with support for frequencies in
the band of 5.2-6.2 GHz. The model is based on extensive high-resolution
measurements at different road intersections in the city of Berlin, Germany. We
extend existing models, by including the effects of various obstructions,
higher order interactions, and by introducing an angular gain function for the
scatterers. Scatterer locations have been identified and mapped to measured
multi-path trajectories using a measurement-based ray tracing method and a
subsequent RANSAC algorithm. The developed model is parameterized, and using
the measured propagation paths that have been mapped to scatterer locations,
model parameters are estimated. The time variant power fading of individual
multi-path components is found to be best modeled by a Gamma process with an
exponential autocorrelation. The path coherence distance is estimated to be in
the range of 0-2 m. The model is also validated against measurement data,
showing that the developed model accurately captures the behavior of the
measured channel gain, Doppler spread, and delay spread. This is also the case
for intersections that have not been used when estimating model parameters.Comment: Submitted to IEEE Transactions on Vehicular Technolog
Indoor wireless communications and applications
Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter
AROMA: Automatic Generation of Radio Maps for Localization Systems
WLAN localization has become an active research field recently. Due to the
wide WLAN deployment, WLAN localization provides ubiquitous coverage and adds
to the value of the wireless network by providing the location of its users
without using any additional hardware. However, WLAN localization systems
usually require constructing a radio map, which is a major barrier of WLAN
localization systems' deployment. The radio map stores information about the
signal strength from different signal strength streams at selected locations in
the site of interest. Typical construction of a radio map involves measurements
and calibrations making it a tedious and time-consuming operation. In this
paper, we present the AROMA system that automatically constructs accurate
active and passive radio maps for both device-based and device-free WLAN
localization systems. AROMA has three main goals: high accuracy, low
computational requirements, and minimum user overhead. To achieve high
accuracy, AROMA uses 3D ray tracing enhanced with the uniform theory of
diffraction (UTD) to model the electric field behavior and the human shadowing
effect. AROMA also automates a number of routine tasks, such as importing
building models and automatic sampling of the area of interest, to reduce the
user's overhead. Finally, AROMA uses a number of optimization techniques to
reduce the computational requirements. We present our system architecture and
describe the details of its different components that allow AROMA to achieve
its goals. We evaluate AROMA in two different testbeds. Our experiments show
that the predicted signal strength differs from the measurements by a maximum
average absolute error of 3.18 dBm achieving a maximum localization error of
2.44m for both the device-based and device-free cases.Comment: 14 pages, 17 figure
Effects of virtual acoustics on dynamic auditory distance perception
Sound propagation encompasses various acoustic phenomena including
reverberation. Current virtual acoustic methods, ranging from parametric
filters to physically-accurate solvers, can simulate reverberation with varying
degrees of fidelity. We investigate the effects of reverberant sounds generated
using different propagation algorithms on acoustic distance perception, i.e.,
how faraway humans perceive a sound source. In particular, we evaluate two
classes of methods for real-time sound propagation in dynamic scenes based on
parametric filters and ray tracing. Our study shows that the more accurate
method shows less distance compression as compared to the approximate,
filter-based method. This suggests that accurate reverberation in VR results in
a better reproduction of acoustic distances. We also quantify the levels of
distance compression introduced by different propagation methods in a virtual
environment.Comment: 8 Pages, 7 figure
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
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