276 research outputs found
Distributed detection, localization, and estimation in time-critical wireless sensor networks
In this thesis the problem of distributed detection, localization, and estimation
(DDLE) of a stationary target in a fusion center (FC) based wireless sensor network
(WSN) is considered. The communication process is subject to time-critical
operation, restricted power and bandwidth (BW) resources operating over a shared
communication channel Buffering from Rayleigh fading and phase noise. A novel algorithm
is proposed to solve the DDLE problem consisting of two dependent stages:
distributed detection and distributed estimation. The WSN performs distributed
detection first and based on the global detection decision the distributed estimation
stage is performed. The communication between the SNs and the FC occurs over a
shared channel via a slotted Aloha MAC protocol to conserve BW.
In distributed detection, hard decision fusion is adopted, using the counting
rule (CR), and sensor censoring in order to save power and BW. The effect of
Rayleigh fading on distributed detection is also considered and accounted for by
using distributed diversity combining techniques where the diversity combining is
among the sensor nodes (SNs) in lieu of having the processing done at the FC.
Two distributed techniques are proposed: the distributed maximum ratio combining
(dMRC) and the distributed Equal Gain Combining (dEGC). Both techniques show
superior detection performance when compared to conventional diversity combining
procedures that take place at the FC.
In distributed estimation, the segmented distributed localization and estimation
(SDLE) framework is proposed. The SDLE enables efficient power and BW
processing. The SOLE hinges on the idea of introducing intermediate parameters
that are estimated locally by the SNs and transmitted to the FC instead of the
actual measurements. This concept decouples the main problem into a simpler set
of local estimation problems solved at the SNs and a global estimation problem
solved at the FC. Two algorithms are proposed for solving the local problem: a
nonlinear least squares (NLS) algorithm using the variable projection (VP) method
and a simpler gird search (GS) method. Also, Four algorithms are proposed to solve
the global problem: NLS, GS, hyperspherical intersection method (HSI), and robust
hyperspherical intersection (RHSI) method. Thus, the SDLE can be solved through
local and global algorithm combinations. Five combinations are tied: NLS2 (NLS-NLS),
NLS-HSI, NLS-RHSI, GS2, and GS-N LS. It turns out that the last algorithm
combination delivers the best localization and estimation performance. In fact , the
target can be localized with less than one meter error.
The SNs send their local estimates to the FC over a shared channel using the
slotted-Aloha MAC protocol, which suits WSNs since it requires only one channel.
However, Aloha is known for its relatively high medium access or contention delay
given the medium access probability is poorly chosen. This fact significantly
hinders the time-critical operation of the system. Hence, multi-packet reception
(MPR) is used with slotted Aloha protocol, in which several channels are used for
contention. The contention delay is analyzed for slotted Aloha with and without
MPR. More specifically, the mean and variance have been analytically computed
and the contention delay distribution is approximated. Having theoretical expressions
for the contention delay statistics enables optimizing both the medium access
probability and the number of MPR channels in order to strike a trade-off between
delay performance and complexity
Design and optimization of wireless sensor networks for localization and tracking
Knowledge of the position of nodes in a WSN is crucial in most wireless
sensor network (WSN) applications. The gathered information needs to be
associated with a particular location in a specific time instant in order to
appropiately control de surveillance area. Moreover, WSNs may be used for
tracking certain objects in monitoring applications, which also requires the
incorporation of location information of the sensor nodes into the tracking
algorithms. These requisites make localizacion and tracking two of the most
important tasks of WSN.
Despite of the large research efforts that have been made in this field,
considerable technical challenges continue existing in subjects areas like data
processing or communications. This thesis is mainly concerned with some
of these technical problems. Specifically, we study three different challenges:
sensor deployment, model independent localization and sensor selection.
The first part of the work is focused on the task of sensor deployement.
This is considered critical since it affects cost, detection, and localization accuracy
of a WSN. There have been significant research efforts on deploying
sensors from different points of view, e.g. connectivity or target detection.
However, in the context of target localization, we believe it is more convenient
to deploy the sensors in views of obtaining the best estimation possible
on the target positioning. Therefore, in this work we suggest an analysis of
the deployment from the standpoint of the error in the position estimation.
To this end, we suggest the application of the modified Cram´er-Rao
bound (MCRB) in a sensor network to perform a prior analysis of the system
operation in the localization task. This analysis provides knowledge
about the system behavior without a complete deployment. It also provides
essential information to select fundamental parameters properly, like
the number of sensors. To do so, a complete formulation of the modified
information matrix (MFIM) and MCRB is developed for the most common
measurement models, such as received signal strength (RSS), time-of-arrival
(ToA) and angle-of-arrival (AoA). In addition, this formulation is extended
for heterogeneous models that combine different measurement models. Simulation
results demonstrate the utility of the proposed analysis and point
out the similarity between MCRB and CRB.
Secondly, we address the problem of target localization which encompasses
many of the challenging issues which commonly arise in WSN. Consequently,
many localization algorithms have been proposed in the literature each one oriented towards solving these issues. Nevertheless, it have seen
tahta the localization performance of above methods usually relies heavily
on the availability of accurate knowledge regarding the observation model.
When errors in the measurement model are present, their target localization
accuracy is degraded significantly.
To overcome this problem, we proposed a novel localization algorithm
to be used in applications where the measurement model is not accurate or
incomplete. The independence of the algorithm from the model provides
robustness and versatility. In order to do so, we apply radial basis functions
(RBFs) interpolation to evaluate the measurement function in the entire
surveillance area, and estimate the target position. In addition, we also
propose the application of LASSO regression to compute the weigths of the
RBFs and improve the generalization of the interpolated function. Simulation
results have demonstrated the good performance of the proposed
algorithm in the localization of single or multiples targets.
Finally, we study the sensor selection problem. In order to prolong the
network lifetime, sensors alternate their state between active and idle. The
decision of which sensor should be activated is based on a variety of factors
depending on the algorithm or the sensor application. Therefore, here we
investigate the centralized selection of sensors in target-tracking applications
over huge networks where a large number of randomly placed sensors are
available for taking measurements.
Specifically, we focus on the application of optimization algorithms for
the selection of sensors using a variant of the CRB, the Posterior CRB
(PCRB), as the performance-based optimization criteria. This bound provides
the performance limit on the mean square error (MSE) for any unbiased
estimator of a random parameter, and is iteratively computed by
a particle filter (in our case, by a Rao-Blackwellized Particle Filter). In
this work we analyze, and compare, three optimization algorithms: a genetic
algorithm (GA), the particle swarm optimization (PSO), and a new
discrete-variant of the cuckoo search (CS) algorithm. In addition, we propose
a local-search versions of the previous optimization algorithms that
provide a significant reduction of the computation time. Lastly, simulation
results demonstrate the utility of these optmization algorithm to solve a
sensor selection problem and point out the reduction of the computation
time when local search is applied. ---------------------------------------------------Las redes de sensores se presentan como una tecnologÃa muy interesante
que ha atraÃdo considerable interés por parte de los investigadores en la
actualidad [1, 109]. Recientes avances en electrónica y en comunicaciones
inalámbricas han permitido de desarrollo de sensores de bajo coste, baja
potencia y multiples funciones, de reducido tamaño y con capacidades de comunicación a cortas distancias. Estos sensores, desplegados en gran número
y unidos a través de comunicaciones inalámbricas, proporcionan grandes
oportunidades en aplicaciones como la monitorización y el control de casas,
ciudades o el medio ambiente.
Un nodo sensor es un dispositivo de baja potencia capaz de interactuar
con el medio a través de sus sensores, procesar información localmente y
comunicar dicha información a tus vecinos más próximos. En el mercado
existe una gran variedad de sensores (magnéticos, acústicos, térmicos, etc),
lo que permite monitorizar muy diversas condiciones ambientales (temperatura,
humedad, etc.) [25]. En consecuencia, las redes de sensores presentan
un amplio rango de aplicaciones: seguridad en el hogar, monitorización del
medio, análisis y predicción de condiciones climáticas, biomedicina [79], etc.
A diferencia de las redes convencionales, las redes de sensores sus propias
limitaciones, como la cantidad de energÃa disponible, el corto alcance de sus
comunicaciones, su bajo ancho de band y sus limitaciones en el procesado
de información y el almacenamiento de la misma. Por otro parte, existen
limitaciones en el diseño que dependerán directamente de la aplicación que
se le quiera dar a la red, como por ejemplo el tamaño de la red, el esquema
de despliegue o la topologÃa de la red..........Presidente: Jesús Cid Sueiro; Vocal: Mónica F. Bugallo; Secretario: Sancho Salcedo San
Modelling Nuclear Body Dynamics in Living Cells by 4-D Microscopy, Image Analysis and Simulation
The work presented here demonstrates rules of and validates models for nuclear body (NB) dynamics. Simulation tools developed in the course of this work can be used in future work to generate hypotheses about related aspects of nuclear architecture. Initially I examined the mobility of vimentin nuclear bodies bodies (VNB) in interphase by single particle tracking and analysis of fluorescence images from 4-D confocal laser scanning microscopy (CLSM). These synthetic nuclear bodies are observed in cells transfected with labelled nuclear-targeted Xenopus laevis vimentin. Analysis shows that VNBs undergo anomalous diffusion in the nuclei, independent of metabolic energy. Individual bodies display either one of the three modes of diffusion -- directed, restricted or simple. The consistency of modes and magnitudes of diffusion constants between VNBs and bona fide nuclear bodies points to a generic mechanism that mediates and regulates the mobility of nuclear bodies. Since the results of diffusion analysis of VNBs did not agree with a simple diffusion model, I tested the alternative interchromosomal domain (ICD) compartment model. The ICD model predicts that in interphase cell nuclei, individual decompacted chromosomes do not intermingle, but are separated by a significant interchromatin space forming a network of channels. These networks could affect the mobility of nuclear bodies. Monte Carlo simulations that predict the effects of channels and other obstructions on NB diffusion were tested, but they could not explain deviation from ideal behaviour. Fitting an empirical model of `critical diffusion' produced similar results. Therefore the ICD model as a purely obstructing network of channels needs modification, to possibly include binding. To examine the role of chromatin density in intra-nuclear diffusion, I employed multidimensional fluorescence recovery after photobleaching (FRAP) in living cells. The influence of chromatin density on diffusive mobility of the nuclear yellow fluorescent protein (YFP) appears marginal. A 2-D diffusion simulation to better characterize the experiment provides a tool to produce `diffusion maps' of the nucleus. The related aspect of nuclear body integrity and dynamics was examined for the distribution of topoisomerase II beta (TopoIIb), which localizes preferentially in the nucleolus. The experimentally observed diffusion and binding dynamics were formulated as a compartment model and fitted to the experiments. The model topology, flux constants and residence times estimates could be validated, providing a predictive model of TopoIIb dynamics By demonstrating that VNB diffusion is anomalous and consistent with other bona fide NBs, I have revealed a mechanism that regulates NB mobility. The diffusion of these bodies deviates however from ideal diffusion, and can be explained by neither the effect of chromatin density on molecular diffusion, nor the different models of NB diffusion. I have shown that binding rather than diffusion appears to determine nuclear body localization and dynamics, as in the case of TopoIIb. Nuclear bodies and nuclear architecture has been recently hypothesized as emerging from simple local interactions. The predictive model for TopoIIb distribution dynamics provides evidence for this. The models presented here, are in keeping with the increasing trend to abstract nuclear dynamics as mathematical models. It is hoped that the work presented here will contribute to the effort of arriving at an integrated model for nuclear bodies and therefore better understanding nuclear architecture
1992 NASA/ASEE Summer Faculty Fellowship Program
For the 28th consecutive year, a NASA/ASEE Summer Faculty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The program was conducted by the University of Alabama and MSFC during the period June 1, 1992 through August 7, 1992. Operated under the auspices of the American Society for Engineering Education, the MSFC program, was well as those at other centers, was sponsored by the Office of Educational Affairs, NASA Headquarters, Washington, DC. The basic objectives of the programs, which are the 29th year of operation nationally, are (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate and exchange ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA centers
A Survey of 3D Indoor Localization Systems and Technologies
Indoor localization has recently and significantly attracted the interest of the research community mainly due to the fact that Global Navigation Satellite Systems (GNSSs) typically fail in indoor environments. In the last couple of decades, there have been several works reported in the literature that attempt to tackle the indoor localization problem. However, most of this work is focused solely on two-dimensional (2D) localization, while very few papers consider three dimensions (3D). There is also a noticeable lack of survey papers focusing on 3D indoor localization; hence, in this paper, we aim to carry out a survey and provide a detailed critical review of the current state of the art concerning 3D indoor localization including geometric approaches such as angle of arrival (AoA), time of arrival (ToA), time difference of arrival (TDoA), fingerprinting approaches based on Received Signal Strength (RSS), Channel State Information (CSI), Magnetic Field (MF) and Fine Time Measurement (FTM), as well as fusion-based and hybrid-positioning techniques. We provide a variety of technologies, with a focus on wireless technologies that may be utilized for 3D indoor localization such as WiFi, Bluetooth, UWB, mmWave, visible light and sound-based technologies. We critically analyze the advantages and disadvantages of each approach/technology in 3D localization
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