Acoustic Source Localization With Distributed Asynchronous Microphone Networks

Canclini, Antonio; Antonacci, Fabio; Sarti, Augusto; Tubaro, Stefano

doi:10.1109/tasl.2012.2215601

Cited by 94 publications

(54 citation statements)

References 15 publications

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“…The method presented in [20] also considers acoustically determined orientation estimate of the device, which contains a microphone array. This method has been used in localisation of an asynchronous source in [24].…”

Section: Related Workmentioning

confidence: 99%

Real-time sound source localisation for target tracking applications using an asynchronous microphone array

Miró

Vidal-Calleja

2015

2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)

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Abstract-This paper presents a strategy for sound source localisation using an asynchronous microphone array. The proposed method is suitable for target tracking applications, in which the sound source with a known frequency is attached to the target. Conventional microphone array technologies require a multichannel A/D converter for inter-microphone synchronization making the technology relatively expensive. In this work, the requirement of synchronization between channels is relaxed by adding an external reference audio signal. The only assumption is that the frequencies of the reference signal and the sound source attached to the target are fixed and known beforehand. By exploiting the information provided by the known reference signal, the Direction Of Arrival (DOA) of target sound source can be calculated in real-time. The key idea of the algorithm is to use the reference source to "pseudo-align" the audio signals from different channels. Once the channels are "pseudoaligned", a dedicated DOA estimation method based on Time Difference Of Arrival (TDOA) can be employed to find the relative bearing information between the target sound source and microphone array. Due to the narrow band of frequency of target sound source, the proposed approach is proven to be robust to low signals-to-noise ratios. Comprehensive simulations and experimental results are presented to show the validity of the algorithm.

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Section: Related Workmentioning

confidence: 99%

Real-time sound source localisation for target tracking applications using an asynchronous microphone array

Miró

Vidal-Calleja

2015

2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)

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“…Examples of such applications include indoor navigation [1], locationbased services [2], patient monitoring [3], and many others involving ad hoc microphone arrays [4][5][6][7][8][9][10][11]. These applications have one thing in common: they require the estimation of the mobile device position.…”

Section: Introductionmentioning

confidence: 99%

Acoustic Sensor Self-Localization: Models and Recent Results

Haddad

Lima

Martins

et al. 2017

Wireless Communications and Mobile Computing

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The wide availability of mobile devices with embedded microphones opens up opportunities for new applications based on acoustic sensor localization (ASL). Among them, this paper highlights mobile device self-localization relying exclusively on acoustic signals, but with previous knowledge of reference signals and source positions. The problem of finding the sensor position is stated as a function of estimated times-of-flight (TOFs) or time-differences-of-flight (TDOFs) from the sound sources to the target microphone, and the main practical issues involved in TOF estimation are discussed. Least-squares ASL solutions are introduced, followed by other strategies inspired by sound source localization solutions: steered-response power, which improves localization accuracy, and a new region-based search, which alleviates complexity. A set of complementary techniques for further improvement of TOF/TDOF estimates are reviewed: sliding windows, matching pursuit, and TOF selection. The paper proceeds with proposing a novel ASL method that combines most of the previous material, whose performance is assessed in a real-world example: in a typical lecture room, the method achieves accuracy better than 20 cm.

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“…Since distributed microphone arrays have larger array aperture than traditional microphone arrays [7,8], it can provide better performance of sound source localization, and therefore it becomes a hot research area.…”

Section: Introductionmentioning

confidence: 99%

Compressing Sensing Based Source Localization for Controlled Acoustic Signals Using Distributed Microphone Arrays

Zhang

Yuan

et al. 2017

Mathematical Problems in Engineering

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In order to enhance the accuracy of sound source localization in noisy and reverberant environments, this paper proposes an adaptive sound source localization method based on distributed microphone arrays. Since sound sources lie at a few points in the discrete spatial domain, our method can exploit this inherent sparsity to convert the localization problem into a sparse recovery problem based on the compressive sensing (CS) theory. In this method, a two-step discrete cosine transform-(DCT-) based feature extraction approach is utilized to cover both short-time and long-time properties of acoustic signals and reduce the dimensions of the sparse model. In addition, an online dictionary learning (DL) method is used to adjust the dictionary for matching the changes of audio signals, and then the sparse solution could better represent location estimations. Moreover, we propose an improved block-sparse reconstruction algorithm using approximate 0 norm minimization to enhance reconstruction performance for sparse signals in low signal-noise ratio (SNR) conditions. The effectiveness of the proposed scheme is demonstrated by simulation results and experimental results where substantial improvement for localization performance can be obtained in the noisy and reverberant conditions.

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Acoustic Source Localization With Distributed Asynchronous Microphone Networks

Cited by 94 publications

References 15 publications

Real-time sound source localisation for target tracking applications using an asynchronous microphone array

Real-time sound source localisation for target tracking applications using an asynchronous microphone array

Acoustic Sensor Self-Localization: Models and Recent Results

Compressing Sensing Based Source Localization for Controlled Acoustic Signals Using Distributed Microphone Arrays

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