Broadband variations of the MUSIC high-resolution method for Sound Source Localization in Robotics

Argentieri, Sylvain; Danès, Patrick

doi:10.1109/iros.2007.4399422

Cited by 66 publications

(43 citation statements)

References 9 publications

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“…Moreover, they can tolerate unsynchronized input given that the sources are static or that they move at a rather slow rate relative to the analysis frame. DOA measurements describe the direction from which sound is propagating with respect to a sensor in each time instant and are an attractive approach to location estimation also due to the ease in which such estimates can be obtained: a variety of broadband DOA estimation methods for acoustic sources are available in the literature, such as the broadband MUSIC algorithm, [51] the ESPRIT algorithm [52], Independent Component Analysis (ICA) methods [53], or Sparse Component Analysis (SCA) methods [54]. When the microphones at the nodes follow a specific geometry, for example, circular, methods such as Circular Harmonics Beamforming (CHB) [55] can also be applied.…”

Section: Doa-based Localizationmentioning

confidence: 99%

A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks

Cobos

Antonacci

Alexandridis

et al. 2017

Wireless Communications and Mobile Computing

117

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Wireless acoustic sensor networks (WASNs) are formed by a distributed group of acoustic-sensing devices featuring audio playing and recording capabilities. Current mobile computing platforms offer great possibilities for the design of audio-related applications involving acoustic-sensing nodes. In this context, acoustic source localization is one of the application domains that have attracted the most attention of the research community along the last decades. In general terms, the localization of acoustic sources can be achieved by studying energy and temporal and/or directional features from the incoming sound at different microphones and using a suitable model that relates those features with the spatial location of the source (or sources) of interest. This paper reviews common approaches for source localization in WASNs that are focused on different types of acoustic features, namely, the energy of the incoming signals, their time of arrival (TOA) or time difference of arrival (TDOA), the direction of arrival (DOA), and the steered response power (SRP) resulting from combining multiple microphone signals. Additionally, we discuss methods not only aimed at localizing acoustic sources but also designed to locate the nodes themselves in the network. Finally, we discuss current challenges and frontiers in this field.

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Section: Doa-based Localizationmentioning

confidence: 99%

A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks

Cobos

Antonacci

Alexandridis

et al. 2017

Wireless Communications and Mobile Computing

117

View full text Add to dashboard Cite

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“…Indeed, for far sources, only the direction of arrival (DOA) can be accurately estimated, while the range estimate is generally unreliable [1]. On the other hand, distributed arrays envision the presence of multiple sensors, each equipped with one or more microphones, located around the volume of interest [5][6][7][8][9][10]. With this configuration, the source is observed from different angles, with benefits in terms of localization accuracy.…”

Section: Introductionmentioning

confidence: 99%

Distributed 3D Source Localization from 2D DOA Measurements Using Multiple Linear Arrays

Canclini

Antonacci

Sarti

et al. 2017

Wireless Communications and Mobile Computing

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This manuscript addresses the problem of 3D source localization from direction of arrivals (DOAs) in wireless acoustic sensor networks. In this context, multiple sensors measure the DOA of the source, and a central node combines the measurements to yield the source location estimate. Traditional approaches require 3D DOA measurements; that is, each sensor estimates the azimuth and elevation of the source by means of a microphone array, typically in a planar or spherical configuration. The proposed methodology aims at reducing the hardware and computational costs by combining measurements related to 2D DOAs estimated from linear arrays arbitrarily displaced in the 3D space. Each sensor measures the DOA in the plane containing the array and the source. Measurements are then translated into an equivalent planar geometry, in which a set of coplanar equivalent arrays observe the source preserving the original DOAs. This formulation is exploited to define a cost function, whose minimization leads to the source location estimation. An extensive simulation campaign validates the proposed approach and compares its accuracy with state-of-the-art methodologies.

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“…Many approaches were based on beamforming [22]. Argentieri and Danes proposed an online beamspace MUSIC method with a beamforming scheme to localize sound sources in robotics [25]. Sun et al proposed several steered beamformerbased and subspace-based localization techniques in the spherical EB domain [26].…”

Section: Introductionmentioning

confidence: 99%

Acoustic source localization in mixed field using spherical microphone arrays

Huang

Wang

2014

EURASIP J. Adv. Signal Process.

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Spherical microphone arrays have been used for source localization in three-dimensional space recently. In this paper, a two-stage algorithm is developed to localize mixed far-field and near-field acoustic sources in free-field environment. In the first stage, an array signal model is constructed in the spherical harmonics domain. The recurrent relation of spherical harmonics is independent of far-field and near-field mode strengths. Therefore, it is used to develop spherical estimating signal parameter via rotational invariance technique (ESPRIT)-like approach to estimate directions of arrival (DOAs) for both far-field and near-field sources. In the second stage, based on the estimated DOAs, simple one-dimensional MUSIC spectrum is exploited to distinguish far-field and near-field sources and estimate the ranges of near-field sources. The proposed algorithm can avoid multidimensional search and parameter pairing. Simulation results demonstrate the good performance for localizing far-field sources, or near-field ones, or mixed field sources.

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Broadband variations of the MUSIC high-resolution method for Sound Source Localization in Robotics

Cited by 66 publications

References 9 publications

A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks

A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks

Distributed 3D Source Localization from 2D DOA Measurements Using Multiple Linear Arrays

Acoustic source localization in mixed field using spherical microphone arrays

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