Underwater channel estimation and multiple object tracking using embedded computing

Edwin Anaya; David Marquez; Neysha Matos; Genesis Nieves; Juan Valera; Cesar Aceros; Domingo Rodriguez

doi:10.1109/MWSCAS.2017.8052892

Underwater channel estimation and multiple object tracking using embedded computing

Edwin Anaya
, David Marquez
, Neysha Matos
, Genesis Nieves
, Juan Valera
, Cesar Aceros
, Domingo Rodriguez

Research output: Chapter in Book/Report/Conference proceeding › Conference and proceedings › peer-review

1 Scopus citations

Abstract

This work presents an embedded computing framework for the analysis and design of large scale algorithms utilized in the estimation of acoustic doubly dispersive, randomly time-variant, underwater communication channels. Channel estimation results are used, in turn, in the proposed framework for the development of efficient high performance algorithms, based on fast Fourier transformations, for the search, detection, estimation, and tracking (SDET) of underwater moving objects through acoustic wavefront signal analysis techniques associated with real-time electronic surveillance and acoustic monitoring (eSAM) operations. Particular importance is given in this work to the estimation of the range and speed of deep underwater moving objects modeled as point targets. The work demonstrates how to use Kronecker products signal algebra (KSA), a branch of finite-dimensional tensor signal algebra, is used as a mathematical language to assist in the development and implementation of the embedded computing algorithms.

Original language	English
Title of host publication	2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	188-191
Number of pages	4
ISBN (Electronic)	9781509063895
DOIs	https://doi.org/10.1109/MWSCAS.2017.8052892
State	Published - 27 Sep 2017
Event	60th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2017 - Boston, United States Duration: 6 Aug 2017 → 9 Aug 2017

Publication series

Name	Midwest Symposium on Circuits and Systems
Volume	2017-August
ISSN (Print)	1548-3746

Conference

Conference	60th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2017
Country/Territory	United States
City	Boston
Period	6/08/17 → 9/08/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Access to Document

10.1109/MWSCAS.2017.8052892

Cite this

Anaya, E., Marquez, D., Matos, N., Nieves, G., Valera, J., Aceros, C., & Rodriguez, D. (2017). Underwater channel estimation and multiple object tracking using embedded computing. In 2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017 (pp. 188-191). Article 8052892 (Midwest Symposium on Circuits and Systems; Vol. 2017-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MWSCAS.2017.8052892

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title = "Underwater channel estimation and multiple object tracking using embedded computing",

abstract = "This work presents an embedded computing framework for the analysis and design of large scale algorithms utilized in the estimation of acoustic doubly dispersive, randomly time-variant, underwater communication channels. Channel estimation results are used, in turn, in the proposed framework for the development of efficient high performance algorithms, based on fast Fourier transformations, for the search, detection, estimation, and tracking (SDET) of underwater moving objects through acoustic wavefront signal analysis techniques associated with real-time electronic surveillance and acoustic monitoring (eSAM) operations. Particular importance is given in this work to the estimation of the range and speed of deep underwater moving objects modeled as point targets. The work demonstrates how to use Kronecker products signal algebra (KSA), a branch of finite-dimensional tensor signal algebra, is used as a mathematical language to assist in the development and implementation of the embedded computing algorithms.",

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Anaya, E, Marquez, D, Matos, N, Nieves, G, Valera, J, Aceros, C & Rodriguez, D 2017, Underwater channel estimation and multiple object tracking using embedded computing. in 2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017., 8052892, Midwest Symposium on Circuits and Systems, vol. 2017-August, Institute of Electrical and Electronics Engineers Inc., pp. 188-191, 60th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2017, Boston, United States, 6/08/17. https://doi.org/10.1109/MWSCAS.2017.8052892

Underwater channel estimation and multiple object tracking using embedded computing. / Anaya, Edwin; Marquez, David; Matos, Neysha et al.
2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 188-191 8052892 (Midwest Symposium on Circuits and Systems; Vol. 2017-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference and proceedings › peer-review

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AU - Rodriguez, Domingo

PY - 2017/9/27

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AB - This work presents an embedded computing framework for the analysis and design of large scale algorithms utilized in the estimation of acoustic doubly dispersive, randomly time-variant, underwater communication channels. Channel estimation results are used, in turn, in the proposed framework for the development of efficient high performance algorithms, based on fast Fourier transformations, for the search, detection, estimation, and tracking (SDET) of underwater moving objects through acoustic wavefront signal analysis techniques associated with real-time electronic surveillance and acoustic monitoring (eSAM) operations. Particular importance is given in this work to the estimation of the range and speed of deep underwater moving objects modeled as point targets. The work demonstrates how to use Kronecker products signal algebra (KSA), a branch of finite-dimensional tensor signal algebra, is used as a mathematical language to assist in the development and implementation of the embedded computing algorithms.

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Anaya E, Marquez D, Matos N, Nieves G, Valera J, Aceros C et al. Underwater channel estimation and multiple object tracking using embedded computing. In 2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 188-191. 8052892. (Midwest Symposium on Circuits and Systems). doi: 10.1109/MWSCAS.2017.8052892

Underwater channel estimation and multiple object tracking using embedded computing

Abstract

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