1,079 research outputs found
EM Algorithm for Multiple Wideband Source Localization
A computationally efficient algorithm using the expectation-maximization (EM) algorithm for multiple wideband source localization in the near field of a sensor array/area is addressed in this thesis. Our idea is to decompose the observed sensor data, which is a superimposition of multiple sources, into the individual components in the frequency domain and then estimate the corresponding location parameters associated with each component separately. Instead of the conventional alternating projection (AP) method, we propose to adopt the EM algorithm in this work; our new method involves two steps, namely Expectation (E-step) and Maximization (M-step). In the E-step, the individual incident source waveforms are estimated. Then, in the M-step, the maximum likelihood estimates of the source location parameters are obtained. These two steps are executed iteratively and alternatively until the pre-defined convergence is reached. The computational complexity comparison between our proposed EM algorithm and the existing AP scheme is investigated. It is shown through Monte Carlo simulations that the computational complexity of the proposed EM algorithm is significantly lower than that of the existing AP algorithm
Signal Processing and Propagation for Aeroacoustic Sensor Networking,” Ch
Passive sensing of acoustic sources is attractive in many respects, including the relatively low signal bandwidth of sound waves, the loudness of most sources of interest, and the inherent difficulty of disguising or concealing emitted acoustic signals. The availability of inexpensive, low-power sensing and signal-processing hardware enables application of sophisticated real-time signal processing. Among th
Emitter Location Finding using Particle Swarm Optimization
Using several spatially separated receivers, nowadays positioning techniques, which are implemented to determine the location of the transmitter, are often required for several important disciplines such as military, security, medical, and commercial applications. In this study, localization is carried out by particle swarm optimization using time difference of arrival. In order to increase the positioning accuracy, time difference of arrival averaging based two new methods are proposed. Results are compared with classical algorithms and Cramer-Rao lower bound which is the theoretical limit of the estimation error
Technology Implications of UWB on Wireless Sensor Network-A detailed Survey
In today’s high tech “SMART” world sensor based networks are widely used. The main challenge with wireless-based sensor networks is the underneath physical layer. In this survey, we have identified core obstacles of wireless sensor network when UWB is used at PHY layer. This research was done using a systematic approach to assess UWB’s effectiveness (for WSN) based on information taken from various research papers, books, technical surveys and articles. Our aim is to measure the UWB’s effectiveness for WSN and analyze the different obstacles allied with its implementation. Starting from existing solutions to proposed theories. Here we have focused only on the core concerns, e.g. spectrum, interference, synchronization etc.Our research concludes that despite all the bottlenecks and challenges, UWB’s efficient capabilities makes it an attractive PHY layer scheme for the WSN, provided we can control interference and energy problems. This survey gives a fresh start to the researchers and prototype designers to understand the technological concerns associated with UWB’s implementatio
Wireless sensor network’s localization based on multiple signal classification algorithm
Wireless sensor networks (WSNs) are a number of sensitive nodes senses a physical phenomenon at the position of their deployment then sends information to the base station to take appropriate operation. (WSNs) are used in many applications such track military targets, discover fires, study natural phenomena such as earthquakes, humidity, heat, etc. The nodes are spread in large areas and it is difficult to locate them manually because they are published randomly by planes or any other method and since the information received from sensitive nodes is useless without knowing their location in this case a problem resulted in the positioning of the nodes. So it unacceptable to equip each sensor node with global position system (GPS) due to various problems such as raises cost and energy consumption. In this paper explained a non-GPS technique to self-positioning of nodes in (WSNs) by using the multiple signal classification (MUSIC) algorithm to determine the position of the active sensor through estimated the direction of arrival (DOA) of the node signal. Then modified MUSIC algorithm (M-MUSIC) to solve the problem of coherent signal. MATLAB program successfully used to simulate the proposed algorithm
Algorithms for propagation-aware underwater ranging and localization
Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of
the crucial research problems of modern time. Underwater localization stands among the
key issues on the way to the proper inspection and monitoring of this significant part of our
world. In this thesis, we investigate and tackle different challenges related to underwater
ranging and localization. In particular, we focus on algorithms that consider underwater
acoustic channel properties. This group of algorithms utilizes additional information
about the environment and its impact on acoustic signal propagation, in order to improve
the accuracy of location estimates, or to achieve a reduced complexity, or a reduced
amount of resources (e.g., anchor nodes) compared to traditional algorithms.
First, we tackle the problem of passive range estimation using the differences in the
times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand
energy- effective algorithm that can be used for the localization of autonomous
underwater vehicles (AUVs), and utilizes information about signal propagation. We study
the accuracy of this method in the simplified case of constant sound speed profile (SSP)
and compare it to a more realistic case with various non-constant SSP. We also propose
an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic
propagation via ray models, takes into account the difference between rectilinear and
non-rectilinear sound ray paths. According to our evaluation, this offers improved range
estimation results with respect to standard algorithms that consider the actual value of
the speed of sound.
We then propose an algorithm suitable for the non-invasive tracking of AUVs or
vocalizing marine animals, using only a single receiver. This algorithm evaluates the
underwater acoustic channel impulse response differences induced by a diverse sea
bottom profile, and proposes a computationally- and energy-efficient solution for passive
localization.
Finally, we propose another algorithm to solve the issue of 3D acoustic localization
and tracking of marine fauna. To reach the expected degree of accuracy, more sensors
are often required than are available in typical commercial off-the-shelf (COTS) phased
arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple
COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of
state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We
propose a solution for passive 3D localization and tracking using a wideband acoustic
array of arbitrary shape, and validate the algorithm in multiple experiments, involving
both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under
project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell
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