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1

Direction Estimation and Tracking of Coherent Sources Using a Single Acoustic Vector Sensor

Wajid Mohd, Kumar Arun, Bahl Rajendar

Archives of Acoustics

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2020

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Vol. 45, No. 2

209--219

EN

A single acoustic vector sensor (AVS) cannot be used to find the direction-of-arrival (DOA) of two or more coherent (fully correlated) sources. We have proposed a technique for estimating DOAs (in 2D geometry) of two simultaneous coherent sources using single AVS under the assumption that acoustic sources enter in the field sequentially. The DOA estimation has been investigated with two different configurations of AVS, each consisting of three microphones in a plane. The technique has been also applied in tracking (a) an acoustic source in the presence of stationary interfering coherent source and (b) two coherent sources when the sources are changing their locations alternatively. The experimental environment has been generated using the Finite-Element Method tool viz. COMSOL to corroborate the proposed scheme.

2

Lorentzian Operator for Angular Source Localization with Large Array

Khmou Y., Safi S., Frikel M.

Journal of Telecommunications and Information Technology

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2015

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nr 4

98--105

EN

Source localization problem consists of an ensemble of techniques that are used to obtain spatial information of present radiation in given medium of propagation, with a constraint of the antenna geometry and the characteristics of radiating sources. This condition gives multitude of cases to study, hence several methods were proposed in the literature. In this paper, a new algorithm for estimating the Direction of Arrival (DoA) of narrowband and far eld punctual sources is introduced. By exploiting the spectrum of covariance matrix of received data, the Lorentzian function on spectral matrix to lter the eigenvalues is applied. This ltering process eliminates the eigenvalues belonging to signal subspace. Parameters of Lorentz function are adjusted using rst and second statistics of eigenvalues. The algorithm requires the knowledge of minimum eigenvalue and is performing when the dimension of antenna is relatively large which is conrmed by several Monte Carlo simulations.

3

Performing acoustic localization in a network of embedded smart sensors

Astapov S., Ehala J., Preden J.-S.

International Journal of Microelectronics and Computer Science

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2015

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Vol. 6, nr 3

86--95

EN

Situation awareness is an important aspect of ubiquitous computer systems, as these systems of systems are highly integrated with the physical world and for successful operation they must maintain high awareness of the environment. Acoustic information is one of the most popular modalities, by which the environment states are estimated. Multi-sensor approaches also provide the possibility for acoustic source localization. This paper considers an acoustic localization system of dual channel smart sensors interconnected through a Wireless Sensor Network (WSN). The low computational power of smart sensor devices requires distribution of localization tasks among WSN nodes. The Initial Search Region Reduction (ISRR) method is used in the WSN to meet this requirement. ISRR, as opposed to conventional localization methods, performs significantly less complex computations and does not require exchange of raw signal between nodes. The system is implemented on smart dust motes utilizing Atmel ATmega128RFA1 processors with integrated 2.4GHz IEEE 802.15.4 compliant radio transceivers. The paper discusses complications introduced by low power hardware and ad-hoc networking, and also reviews conditions of real-time operation.

4

Comparative Study between Several Direction of Arrival Estimation Methods

Khmou Y., Safi S., Frikel M.

Journal of Telecommunications and Information Technology

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2014

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nr 1

41--48

EN

In this paper a comparative study, restricted to one-dimensional stationary case, between several Direction of Arrival (DOA) estimation algorithms of narrowband signals is presented. The informative signals are corrupted by an Additive White Gaussian Noise (AWGN), to show the performance of each method by applying directly the algorithms without pre-processing techniques such as forward-backward averaging or spatial smoothing.