Investigation of sampling frequency requirements for acoustic source localisation using wireless sensor networks

Bouzid, Omar Mabrok; Tian, Gui Yun; Neasham, Jeffrey; Sharif, B.S.

doi:10.1016/j.apacoust.2010.12.013

Cited by 22 publications

(20 citation statements)

References 18 publications

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“…The membership matrix is updated at each iteration of the algorithm; denotes the membership matrix at the tth iteration and expresses the membership degree of the point at the cluster h. The center of the cluster h at the tth iteration is calculated by (9), where m is the fuzziness coefficient. The value of the objective function at the iteration tth is given by (10), where is the Euclidean norm.…”

Section: The Novel Strategy For the 3-d Reconstructionmentioning

confidence: 99%

“…Numerous research works have been proposed in literature relating to the sonic output data interpretation and they mostly concern with the time of flight (TOF) estimation: e.g., in [2] the first tests to differentiate the reflection from a plane and from a corner are expounded; in [3] some echo parameters (energy, duration and range) are used to characterize the roughness and the orientation of the reflecting surfaces, in [4] a digital signal-processing technique is proposed to automatically compensate the speed variations of sound that are due to temperature or other atmospheric conditions; in [5] four methods of TOF estimation are compared in a statistical way; in [6] neural networks improve the accuracy in target differentiation; in [7] some classification and fusion techniques for indoor differentiation and localization are compared; in [8] a new approach for profile extraction by processing ultrasonic arc maps is proposed; in [9] an analisys for acoustic source localization is presented to investigate the sampling frequency influence on the accuracy of the estimation of the delay time between received acoustic signals of three microphones.…”

Section: Introductionmentioning

confidence: 99%

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A New Strategy for Spatial Reconstruction of Orthogonal Planes Using a Rotating Array of Ultrasonic Sensors

2012

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In this paper, the authors present a new strategy for accurately reconstructing an L-shaped obstacle such as some wooden panels opportunely connected so as to form a right angle. The mechatronics scanning system consists of four inexpensive ultrasonic sensors moved in three-dimensional (3-D) space by means of a digital motor. The motor rotation is controlled in order to point the sensor array at the target and to obtain distance measurements for each shaft position. Ultrasonic distance sensors propagate large beams and feel the significant effect of multiple reflections. For the sake of excluding all misrepresented distance values at the intersection of the planes, the proposed approach uses powerful mathematical tools together with a physical indicator based on the reflected signal energy. The Fuzzy C-Means (FCM) classification allows partitioning a data set, and the introduced physical indicator is able to select the specific cluster corresponding to the spurious distances. Each remaining cluster permits to calculate the equation of a plane because it is referred to the distance values deriving from a direct reflection. These distances are then transformed considering the sensors directivity and the direction of reflection so as to obtain two sets of 3-D points. Finally, the reconstruction of each plane is achieved by the RANdom SAmple Consensus (RANSAC) in such a way as to better fit these points. The details of this strategy and the experimental tests are shown, demonstrating the applicability and the good results.

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Section: The Novel Strategy For the 3-d Reconstructionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Strategy for Spatial Reconstruction of Orthogonal Planes Using a Rotating Array of Ultrasonic Sensors

2012

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“…2 Each cluster is then searched intelligently for the support of RIR and the structure of Ψ i helps in reducing the complexity involved in it [7]. …”

Section: Time Delay Estimationmentioning

confidence: 99%

“…In addition, these TDE methods suffer from poor time resolution at low sampling frequencies caused by the missing time information which results in large uncertainty in the times of arrival. The effect of under-sampling on the performance of these algorithms is discussed in [2]. The high sampling frequency requirement of these algorithms makes the TDE process not only computationally intensive but also puts a strain on the hardware requirements.…”

Section: Introductionmentioning

confidence: 99%

Time delay estimation in a reverberant environment by low rate sampling of impulsive acoustic sources

Omer

Quadeer

Sharawi

et al. 2012

2012 11th International Conference on Information Science, Signal Processing and Their Applications (ISSPA)

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This paper presents a new method of time delay estimation (TDE) using low sample rates of an impulsive acoustic source in a room environment. The proposed method finds the time delay from the room impulse response (RIR) which makes it robust against room reverberations. The RIR is considered a sparse phenomenon and a recently proposed sparse signal reconstruction technique called orthogonal clustering (OC) is utilized for its estimation from the low rate sampled received signal. The arrival time of the direct path signal at a pair of microphones is identified from the estimated RIR and their difference yields the desired time delay. Low sampling rates reduce the hardware and computational complexity and decrease the communication between the microphones and the centralized location. The performance of the proposed technique is demonstrated by numerical simulations and experimental results.

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“…The effect of under-sampling on the performance of these algorithms is discussed in [17]. The high sampling frequency requirement makes the localization process not only computationally intensive but also demands sophisticated hardware.…”

Section: Introductionmentioning

confidence: 99%

Sub-sampling-based 2D localization of an impulsive acoustic source in reverberant environments

Omer

Quadeer

Sharawi

et al. 2014

EURASIP J. Adv. Signal Process.

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This paper presents a robust method for two-dimensional (2D) impulsive acoustic source localization in a room environment using low sampling rates. The proposed method finds the time delay from the room impulse response (RIR) which makes it robust against room reverberations. We consider the RIR as a sparse phenomenon and apply a recently proposed sparse signal reconstruction technique called orthogonal clustering (OC) for its estimation from the sub-sampled received signal. The arrival time of the direct path signal at a pair of microphones is identified from the estimated RIR, and their difference yields the desired time delay estimate (TDE). Low sampling rates reduces the hardware and computational complexity and decreases the communication between the microphones and the centralized location. Simulation and experimental results of an actual hardware setup are presented to demonstrate the performance of the proposed technique.

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Investigation of sampling frequency requirements for acoustic source localisation using wireless sensor networks

Cited by 22 publications

References 18 publications

A New Strategy for Spatial Reconstruction of Orthogonal Planes Using a Rotating Array of Ultrasonic Sensors

A New Strategy for Spatial Reconstruction of Orthogonal Planes Using a Rotating Array of Ultrasonic Sensors

Time delay estimation in a reverberant environment by low rate sampling of impulsive acoustic sources

Sub-sampling-based 2D localization of an impulsive acoustic source in reverberant environments

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