34,985 research outputs found
Direction of Arrival with One Microphone, a few LEGOs, and Non-Negative Matrix Factorization
Conventional approaches to sound source localization require at least two
microphones. It is known, however, that people with unilateral hearing loss can
also localize sounds. Monaural localization is possible thanks to the
scattering by the head, though it hinges on learning the spectra of the various
sources. We take inspiration from this human ability to propose algorithms for
accurate sound source localization using a single microphone embedded in an
arbitrary scattering structure. The structure modifies the frequency response
of the microphone in a direction-dependent way giving each direction a
signature. While knowing those signatures is sufficient to localize sources of
white noise, localizing speech is much more challenging: it is an ill-posed
inverse problem which we regularize by prior knowledge in the form of learned
non-negative dictionaries. We demonstrate a monaural speech localization
algorithm based on non-negative matrix factorization that does not depend on
sophisticated, designed scatterers. In fact, we show experimental results with
ad hoc scatterers made of LEGO bricks. Even with these rudimentary structures
we can accurately localize arbitrary speakers; that is, we do not need to learn
the dictionary for the particular speaker to be localized. Finally, we discuss
multi-source localization and the related limitations of our approach.Comment: This article has been accepted for publication in IEEE/ACM
Transactions on Audio, Speech, and Language processing (TASLP
Accurate angle-of-arrival measurement using particle swarm optimization
As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates
Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices
Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments;
where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range
estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in
delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both
ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient
signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution,
tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on
TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate
an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally,
we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible
acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance
Sensor array signal processing : two decades later
Caption title.Includes bibliographical references (p. 55-65).Supported by Army Research Office. DAAL03-92-G-115 Supported by the Air Force Office of Scientific Research. F49620-92-J-2002 Supported by the National Science Foundation. MIP-9015281 Supported by the ONR. N00014-91-J-1967 Supported by the AFOSR. F49620-93-1-0102Hamid Krim, Mats Viberg
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Development and Demonstration of a TDOA-Based GNSS Interference Signal Localization System
Background theory, a reference design, and demonstration
results are given for a Global Navigation Satellite
System (GNSS) interference localization system comprising a
distributed radio-frequency sensor network that simultaneously
locates multiple interference sources by measuring their signals’
time difference of arrival (TDOA) between pairs of nodes in
the network. The end-to-end solution offered here draws from
previous work in single-emitter group delay estimation, very long
baseline interferometry, subspace-based estimation, radar, and
passive geolocation. Synchronization and automatic localization
of sensor nodes is achieved through a tightly-coupled receiver
architecture that enables phase-coherent and synchronous sampling
of the interference signals and so-called reference signals
which carry timing and positioning information. Signal and crosscorrelation
models are developed and implemented in a simulator.
Multiple-emitter subspace-based TDOA estimation techniques
are developed as well as emitter identification and localization
algorithms. Simulator performance is compared to the CramérRao
lower bound for single-emitter TDOA precision. Results are
given for a test exercise in which the system accurately locates
emitters broadcasting in the amateur radio band in Austin, TX.Aerospace Engineering and Engineering Mechanic
Parametric high resolution techniques for radio astronomical imaging
The increased sensitivity of future radio telescopes will result in
requirements for higher dynamic range within the image as well as better
resolution and immunity to interference. In this paper we propose a new matrix
formulation of the imaging equation in the cases of non co-planar arrays and
polarimetric measurements. Then we improve our parametric imaging techniques in
terms of resolution and estimation accuracy. This is done by enhancing both the
MVDR parametric imaging, introducing alternative dirty images and by
introducing better power estimates based on least squares, with positive
semi-definite constraints. We also discuss the use of robust Capon beamforming
and semi-definite programming for solving the self-calibration problem.
Additionally we provide statistical analysis of the bias of the MVDR beamformer
for the case of moving array, which serves as a first step in analyzing
iterative approaches such as CLEAN and the techniques proposed in this paper.
Finally we demonstrate a full deconvolution process based on the parametric
imaging techniques and show its improved resolution and sensitivity compared to
the CLEAN method.Comment: To appear in IEEE Journal of Selected Topics in Signal Processing,
Special issue on Signal Processing for Astronomy and space research. 30 page
Effects of the ISM on Detection of Low-frequency Gravitational Waves
Time variable delays due to radio wave propagation in the ionized
interstellar medium are a substantial source of error in pulsar timing array
efforts. We describe the physical origin of these effects, discussing
dispersive and scattering effects separately. Where possible, we give estimates
of the magnitude of timing errors produced by these effects and their scaling
with radio frequency. Although there is general understanding of the
interstellar medium propagation errors to be expected with pulsar timing array
observations, detailed comparison between theory and practice is still in its
infancy, particularly with regard to scattering effects.Comment: 18 pages, 9 figures. Accepted by Classical and Quantum Gravity for
Focus Issue on Pulsar Timing Array
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