@article{
 title = {Indoor localization with audible sound — towards practical implementation},
 type = {article},
 year = {2015},
 identifiers = {[object Object]},
 keywords = {audio,localization,location,mobile,sound,ubicomp},
 websites = {http://dx.doi.org/10.1016/j.pmcj.2015.10.016},
 month = {10},
 id = {b9074a93-81e7-3138-9d90-017eee1866de},
 created = {2018-07-12T21:31:55.499Z},
 file_attached = {false},
 profile_id = {f954d000-ce94-3da6-bd26-b983145a920f},
 group_id = {b0b145a3-980e-3ad7-a16f-c93918c606ed},
 last_modified = {2018-07-12T21:31:55.499Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {moutinho:audio},
 source_type = {article},
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 abstract = {This paper presents an innovative evaluation and comparison of several methods and techniques necessary to implement an indoor localization system based on audible sound. Experiments were conducted in a room with conditions very close to possible practical application demonstrating that time delay estimation using generalized cross-correlation phase transform provides the best estimate to the distance to fixed anchors, and highlight the benefits of a new localization method entitled circle shrinking based on an optimization methodology. Of the three optimization methods tested, Gauss-Newton proves to be the most adequate, and among the three medium access methods evaluated, code division multiple access acoustic transmission provided the best results. A localization system combining these components and using only off-the-shelf hardware reached an average accuracy of 1.3 cm in the central area of the test room with an excitation signal-to-noise ratio as low as 7.2 dB, an almost unperceivable noise like audio signal. These results represent an advance of the state-of-the-art in indoor localization systems, pointing towards the possibility of widespread practical implementation with everyday use components.},
 bibtype = {article},
 author = {Moutinho, J N and Araujo, R E and Freitas, D},
 journal = {Pervasive and Mobile Computing}
}

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