Sound Source and Microphone Localization From Acoustic Impulse Responses

Salvati, Daniele; Drioli, Carlo; Foresti, Gian Luca

doi:10.1109/lsp.2016.2601878

Cited by 18 publications

(10 citation statements)

References 36 publications

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“…Earlier works (e.g. [14]) assumed that multiple static sources where located in a polygonal room and that a moving receiver was collecting data. [15] addressed the problem of a moving emitter-receiver device to reconstruct a room shape using a geometric solution.…”

Section: Related Workmentioning

confidence: 99%

On-plate localization and mapping for an inspection robot using ultrasonic guided waves: a proof of concept

Pradalier

Ouabi

Pomarède

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper presents a proof-of-concept for a localization and mapping system for magnetic crawlers performing inspection tasks on structures made of large metal plates. By relying on ultrasonic guided waves reflected from the plate edges, we demonstrate that it is possible to recover the plate geometry and robot trajectory to a precision comparable to the signal wavelength. The approach is tested using real acoustic signals acquired on test metal plates using lawnmower paths and random-walks. To the contrary of related works, this paper focuses on the practical details of the localization and mapping algorithm.

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Section: Related Workmentioning

confidence: 99%

On-plate localization and mapping for an inspection robot using ultrasonic guided waves: a proof of concept

Pradalier

Ouabi

Pomarède

et al. 2020

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…Recently, several approaches, suitable for the static scenario, were presented. The joint estimation problem is solved by applying various mathematical methods [66,67].…”

Section: Array Calibrationmentioning

confidence: 99%

Joint speaker localization and array calibration using expectation-maximization

Dorfan

Schwartz

Gannot

2020

J AUDIO SPEECH MUSIC PROC.

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Ad hoc acoustic networks comprising multiple nodes, each of which consists of several microphones, are addressed. From the ad hoc nature of the node constellation, microphone positions are unknown. Hence, typical tasks, such as localization, tracking, and beamforming, cannot be directly applied. To tackle this challenging joint multiple speaker localization and array calibration task, we propose a novel variant of the expectation-maximization (EM) algorithm. The coordinates of multiple arrays relative to an anchor array are blindly estimated using naturally uttered speech signals of multiple concurrent speakers. The speakers' locations, relative to the anchor array, are also estimated. The inter-distances of the microphones in each array, as well their orientations, are assumed known, which is a reasonable assumption for many modern mobile devices (in outdoor and in a several indoor scenarios). The well-known initialization problem of the batch EM algorithm is circumvented by an incremental procedure, also derived here. The proposed algorithm is tested by an extensive simulation study.

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“…Hence, the transformed matrix Φ DU (k, f ) contains only the noise eigenvectors and it is negative semidefinite. Substituting (7) in (3), we have…”

Section: B Optimal Du Beamformer In Single-source Case With Spatially...mentioning

confidence: 99%

Power Method for Robust Diagonal Unloading Localization Beamforming

Salvati

Drioli

Foresti

2019

IEEE Signal Process. Lett.

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We propose a robust version of the diagonal unloading (DU) beamforming for the acoustic source localization problem in high noise conditions. The DU beamformer exploits the subspace orthogonality property by the removal or the attenuation of the signal subspaces, obtained through the subtraction of an opportune diagonal matrix from the covariance matrix. As a result, it provides high resolution directional response with low computational complexity. We show that a robust DU beamformer can be implemented by subtracting the largest eigenvalue of the estimated covariance matrix from the diagonal elements, and that this implementation is valid in general (i.e., for both the single-source and the multiplesource case). We propose the use of the power method for the estimation of the largest eigenvalue in the DU procedure. We show with numerical simulations that the proposed method improves the localization performance in high noise conditions without substantial increment of the computational cost. Applications for this method include a number of scenarios involving multirotor aerial systems due to its robustness to the noise and its low computational complexity.

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Sound Source and Microphone Localization From Acoustic Impulse Responses

Cited by 18 publications

References 36 publications

On-plate localization and mapping for an inspection robot using ultrasonic guided waves: a proof of concept

On-plate localization and mapping for an inspection robot using ultrasonic guided waves: a proof of concept

Joint speaker localization and array calibration using expectation-maximization

Power Method for Robust Diagonal Unloading Localization Beamforming

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