A Turbo Approach to Distributed Acoustic Detection and Estimation

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dc.contributor.authorEgger, Sean Roberten
dc.contributor.committeechairRoan, Michael J.en
dc.contributor.committeememberHong, Dennis W.en
dc.contributor.committeememberJohnson, Martin E.en
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2014-03-14T20:48:33Zen
dc.date.adate2009-12-18en
dc.date.available2014-03-14T20:48:33Zen
dc.date.issued2009-11-17en
dc.date.rdate2009-12-18en
dc.date.sdate2009-11-30en
dc.description.abstractNetworked, multi-sensor array systems have proven to be advantageous in the sensor world. A large amount of research has been conducted with these systems, with a main interest in data fusion. Intelligently processing the large amounts of data collected by these systems is required in order to fully utilize the benefits of a multi-sensor array system. A robust but flexible simulation environment would provide a platform for accurately comparing current and future data fusion theories. This thesis proposes a simulator model for testing fusion theories for these acoustic multi-sensor networks. An iterative, lossless data fusion algorithm was presented as the model for simulation development. The arrangement and orientation of objects in the simulation environment, as well as most other system parameters are defined by the user before the simulation runs. The sensor data, including noise, is generated at the appropriate time delay and propagation loss before being processed by a delay and sum beamformer and a matched filter. The resulting range-Doppler maps are modified to probability density functions, and translated to a single point of reference. The data is then combined into a single world model. An iterative process is used to filter out false targets and amplify true target detections. Data is fused from each multi-sensor array and from each simulation run. Target amplitudes are gained if they are present in all combined world models, and are otherwise reduced. This thesis presents the results of the fusion algorithm used, including multiple iterations, to prove the algorithms effectiveness.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-11302009-123833en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-11302009-123833/en
dc.identifier.urihttp://hdl.handle.net/10919/35866en
dc.publisherVirginia Techen
dc.relation.haspartEgger_SR_T_2009.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectlossless information fusionen
dc.subjectmulti-sensor arrayen
dc.subjectacoustic simulationen
dc.titleA Turbo Approach to Distributed Acoustic Detection and Estimationen
dc.typeThesisen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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