3,714 research outputs found
Experimental results of underwater cooperative source localization using a single acoustic vector sensor
This paper aims at estimating the azimuth, range and depth of a cooperative broadband acoustic source with a single vector sensor in a multipath underwater environment, where the received signal is assumed to be a linear combination of echoes of the source emitted waveform. A vector sensor is a device that measures the scalar acoustic pressure field and the vectorial acoustic particle velocity field at a single location in space. The amplitudes of the echoes in the vector sensor components allow one to determine their azimuth and elevation. Assuming that the environmental conditions of the channel are known, source range and depth are obtained from the estimates of elevation and relative time delays of the different echoes using a ray-based backpropagation algorithm. The proposed method is tested using simulated data and is further applied to experimental data from the
Makai’05 experiment, where 8–14 kHz chirp signals were acquired by a vector sensor array.
It is shown that for short ranges, the position of the source is estimated in agreement with the geometry of the experiment. The method is low computational demanding, thus well-suited to be used in mobile and light platforms, where space and power requirements are limited
Online Localization and Tracking of Multiple Moving Speakers in Reverberant Environments
We address the problem of online localization and tracking of multiple moving
speakers in reverberant environments. The paper has the following
contributions. We use the direct-path relative transfer function (DP-RTF), an
inter-channel feature that encodes acoustic information robust against
reverberation, and we propose an online algorithm well suited for estimating
DP-RTFs associated with moving audio sources. Another crucial ingredient of the
proposed method is its ability to properly assign DP-RTFs to audio-source
directions. Towards this goal, we adopt a maximum-likelihood formulation and we
propose to use an exponentiated gradient (EG) to efficiently update
source-direction estimates starting from their currently available values. The
problem of multiple speaker tracking is computationally intractable because the
number of possible associations between observed source directions and physical
speakers grows exponentially with time. We adopt a Bayesian framework and we
propose a variational approximation of the posterior filtering distribution
associated with multiple speaker tracking, as well as an efficient variational
expectation-maximization (VEM) solver. The proposed online localization and
tracking method is thoroughly evaluated using two datasets that contain
recordings performed in real environments.Comment: IEEE Journal of Selected Topics in Signal Processing, 201
Hybrid Radio-map for Noise Tolerant Wireless Indoor Localization
In wireless networks, radio-map based locating techniques are commonly used
to cope the complex fading feature of radio signal, in which a radio-map is
built by calibrating received signal strength (RSS) signatures at training
locations in the offline phase. However, in severe hostile environments, such
as in ship cabins where severe shadowing, blocking and multi-path fading
effects are posed by ubiquitous metallic architecture, even radio-map cannot
capture the dynamics of RSS. In this paper, we introduced multiple feature
radio-map location method for severely noisy environments. We proposed to add
low variance signature into radio map. Since the low variance signatures are
generally expensive to obtain, we focus on the scenario when the low variance
signatures are sparse. We studied efficient construction of multi-feature
radio-map in offline phase, and proposed feasible region narrowing down and
particle based algorithm for online tracking. Simulation results show the
remarkably performance improvement in terms of positioning accuracy and
robustness against RSS noises than the traditional radio-map method.Comment: 6 pages, 11th IEEE International Conference on Networking, Sensing
and Control, April 7-9, 2014, Miami, FL, US
Development and testing of a dual accelerometer vector sensor for AUV acoustic surveys
This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of theWiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS has the potential to contribute to this aim in various ways, for example, owing to its spatial filtering capability, it may reduce the amount of post processing by discriminating the bottom from the surface reflections. Additionally, its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The present paper is focused on results related to acoustic wave azimuth estimation as an example of its spatial filtering capabilities. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. Sensitivity and directionality of these three sensors were measured in a tank, whilst the direction estimation capabilities of the accelerometers paired with the hydrophone, forming a vector sensor, were evaluated on a Medusa Class AUV, which was sailing around a deployed sound source. Results of these measurements are presented in this paper.European Union [645141]info:eu-repo/semantics/publishedVersio
Vector sensors for underwater : acoustic communications
Acoustic vector sensors measure acoustic pressure and directional components separately.
A claimed advantage of vector sensors over pressure-only arrays is the directional information
in a collocated device, making it an attractive option for size-restricted applications.
The employment of vector sensors as a receiver for underwater communications is relatively
new, where the inherent directionality, usually related to particle velocity, is used
for signal-to-noise gain and intersymbol interference mitigation. The fundamental question
is how to use vector sensor directional components to bene t communications, which
this work seeks to answer and to which it contributes by performing: analysis of acoustic
pressure and particle velocity components; comparison of vector sensor receiver structures
exploring beamforming and diversity; quanti cation of adapted receiver structures in distinct
acoustic scenarios and using di erent types of vector sensors. Analytic expressions
are shown for pressure and particle velocity channels, revealing extreme cases of correlation
between vector sensors' components. Based on the correlation hypothesis, receiver
structures are tested with simulated and experimental data. In a rst approach, called
vector sensor passive time-reversal, we take advantage of the channel diversity provided
by the inherent directivity of vector sensors' components. In a second approach named
vector sensor beam steering, pressure and particle velocity components are combined, resulting
in a steered beam for a speci c direction. At last, a joint beam steering and
passive time-reversal is proposed, adapted for vector sensors. Tested with two distinct
experimental datasets, where vector sensors are either positioned on the bottom or tied
to a vessel, a broad performance comparison shows the potential of each receiver structure.
Analysis of results suggests that the beam steering structure is preferable for shorter
source-receiver ranges, whereas the passive time-reversal is preferable for longer ranges.
Results show that the joint beam steering and passive time-reversal is the best option to
reduce communication error with robustness along the range.Sensores vetoriais acústicos (em inglês, acoustic vector sensors) são dispositivos que
medem, alem da pressão acústica, a velocidade de partÃcula. Esta ultima, é uma medida que
se refere a um eixo, portando, esta associada a uma direção. Ao combinar pressão acústica
com componentes de velocidade de partÃcula pode-se estimar a direção de uma fonte sonora
utilizando apenas um sensor vetorial. Na realidade, \um" sensor vetorial é composto de um
sensor de pressão (hidrofone) e um ou mais sensores que medem componentes da velocidade
de partÃcula. Como podemos notar, o aspecto inovador está na medição da velocidade de
partÃcula, dado que os hidrofones já são conhecidos.(...)This PhD thesis was supported by the Brazilian Navy Postgraduate Study Abroad
Program Port. 227/MB-14/08/2019
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