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Identifier 000416964
Title Multiple sound source location estimation and counting in wireless acoustic sensor networks
Alternative Title Εκτίμηση θέσης και αριθμού πολλαπλών ηχητικών πηγών σε δίκτυα ακουστικών αισθητήρων
Author Αλεξανδρίδης, Αναστάσιος Ι
Thesis advisor Μούχταρης, Αθανάσιος
Reviewer Τσακαλίδης, Παναγιώτης
Moonen, Marc
Abstract Wireless acoustic sensor networks (WASNs) represent a new paradigm for acoustic signal acquisition. Multiple acoustic nodes that feature processing and communication capabilities are distributed in the environment where typically multiple sound sources are active. In such a setup, inference of location information has always been an attractive research problem. Enabling machines to estimate the locations of the multiple simultaneously active sound sources from their acoustic emissions is crucial in many applications, such as wildlife monitoring and speech enhancement for robust signal acquisition. Throughout the years, different localization methods have been proposed with the everlasting goal to achieve the lowest possible localization error. Although significant steps have been made towards this direction, another unexplored field concerns the practical limitations posed by the sensor network that restrict the application of such methods to real-life WASNs. Such limitations include the limited processing power and battery life of the nodes, the communication bandwidth that has to be attained at low levels, the real-time requirements and synchronization issues. In this thesis, we consider the problem of multiple source localization and we investigate the development of methods that not only achieve high accuracy in realistic scenarios but also attain low communication bandwidth, tolerate unsynchronized input and are computationally efficient to facilitate their application in real-life WASNs. We consider a WASN where each node is a microphone array that estimates and transmits information related to the directions of arrival (DOAs) of the active sound sources. Such a scheme attains very low communication bandwidth, as only the DOAs need to be transmitted. Moreover, DOA-based localization methods can tolerate unsynchronized input, thus the acoustic signals need not be perfectly synchronized. We first focus on the single source case and propose a computationally efficient nonlinear least squares estimator that can accurately estimate the source's location using an iterative grid-based approach. We then proceed to the multiple sources case, assuming that the number of sources is known. In this case, a core problem for DOAbased approaches is that the fusion center that receives the multiple DOA estimates from the nodes cannot know to which source each DOA belongs. This is known as the data-association problem. To address this problem we propose two solutions: the first concerns the extension of our grid-based approach to multiple sources and the second utilizes additional information, apart from the DOA estimates, in order to find the correct association of DOAs from the nodes to the sources. We then relax the assumption of known number of sources and propose another method that can jointly perform source counting and location estimation. Our method is based on clustering narrowband per-frequency location estimates which are inferred using narrowband per-frequency DOA estimates from the nodes. Since a determinant factor that affects localization performance is the accuracy in which the DOA estimates are obtained, we also investigate how we can improve DOA estimation performance and we propose a methodology to infer more accurate and reliable DOA estimates. Finally, we investigate the potential use of location information to audio processing applications. We provide two examples of how location information can be used for spatial audio capturing and for the design of beamformers that leverage location information in order to estimate the steering vector of the target source. Our preliminary results reveal the potential of locationbased approaches to provide improved performance.
Language English
Subject Direction-of-arrival estimates
Localization
Location information
Microphone arrays
Εκτιμήσεις κατεύθυνσης άφιξης
Εύρεση θέσης
Πληροφορία θέσης
Συστοιχίες μικροφώνων
Issue date 2018-03-23
Collection   Faculty/Department--Faculty of Sciences and Engineering--Department of Computer Science--Doctoral theses
  Type of Work--Doctoral theses
Permanent Link https://elocus.lib.uoc.gr//dlib/a/3/c/metadata-dlib-1530864967-475045-5324.tkl Bookmark and Share
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